2

Foreword

− Introduction of SME Development Fund (SDF) − Introduction of project : Hong Kong foundation

industry towards “Industry 4.0” Editorial Board and Disclaimer Organizer and support organization

Table of contents

Sector-specific Industry 4.0 Benchmarking Model Section One: Overview

− What is “Industry 4.0” − Reasons and objectives of implementing

"Industry 4.0" − “Industry 4.0” goes beyond automation − Project benefits for Hong Kong SMEs

Section Two: Industry 4.0 Core Principles − Concept of Industry 4.0

− Industry 4.0 framework

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− Building corporate uniqueness (innovative digital business model)

− Smart solutions, smart innovation, smart supply

chain, smart production

− Implementation driven by technology

Section Three: Industry 4.0 Maturity Model

− Analytical level − Enterprise level − Smart level − Industry 2.0 (-1) − Industry 3.0 (-2) − Industry 4.0

Frame condition (0i) Real-time data generation (1i) Real-time data analysis (2i) Information Physics Fusion System (CPS)

(3i) Smart Autonomous System (4i)

Section Four: Questionnaire on Maturity level of Industry 4.0

− The Sample Questions in Questionaire − The Methodology in Evaluation

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− The Meaning of scale Section Five: Insights from the Survey

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Foreword

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Introduction of SME Development Fund (SDF)

The Hong Kong Special Administrative Region Government established the SME Development Support Fund in 2001 to subsidize projects that will enhance the competitiveness of Hong Kong SMEs as a whole or in particular industries. The SME Development Support Fund aims to support non-distributed profit support organizations, business organizations, professional bodies and research institutes to implement projects which will enhance the competitiveness of SMEs in Hong Kong as a whole or their respective industries. SMEs in Hong Kong can apply and be suitable for the following institutions: A) Supporting organizations, business organizations, professional bodies and research institutions that do not distribute profits*; B) The applicant institution shall be a statutory body or an institution registered under the laws of the Hong Kong Special Administrative Region; * "Non-distributed profits" institutions/organizations are organizations/organizations that do not distribute

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bonuses to their directors, shareholders, employees or any person. Applicants may receive up to $5 million in funding or 90% of the project's funding for each approved project (whichever is lower). The balance must be borne by the applicant in cash, in kind, or by other sponsors. The SME Development Fund (SDF) and the Organization Support Programme under the Dedicated Fund on Branding, Upgrading and Domestic Sales (BUD(OSP)) have been merged to form the TSF with effect from 1 October 2018. TSF provides financial support to projects which aim at enhancing the competitiveness of non-listed Hong Kong enterprises in general or in specific sectors, including assisting them in developing any markets. For inquiries, please contact the Trade and Industry Department ("TID") for the Application Form and Guide to Application. Hong Kong Federation of Innovative Technologies and Manufacturing Industries (“FITMI”) has been funded by the "SME Development Support Fund" of the Trade and Industry Department of the Government of the Hong Kong Special Administrative Region. The Hong Kong Productivity Council has implemented the

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project to promote the implementation of Industry 4.0 for SMEs in Hong Kong. In this project, “Short-Mid-Term Strategic Upgrade Mapping,” developing a “Sector-specific Industry 4.0 Benchmarking Model” and a “Sector-specific practical implementation guideline” will be developed to assist HKSMEs of four Industries sectors to migrate their legacy manufacturing operation and production into Industry 4.0 gradually. In order to provide a robust reference protocol to assist them in riding on this new management and manufacturing concept, the information and standard are important to assist them in mastering the know-how of step-by-step realization towards Industry 4.0. Introduction of project: Hong Kong foundation industry towards “Industry 4.0” In the face of the increasing number of overseas customers who are implementing "Industry 4.0", Hong Kong companies as suppliers must also upgrade to "Industry 4.0" in order to remain competitive in the international market. To help Hong Kong SMEs move forward and implement "Industry 4.0", the Hong Kong

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Federation of Creative Technology and Manufacturing Industries (FITMI) has partnered with the HKPC to launch a three-year "Hong Kong Basic Industry into Industry 4.0". "Deployment Plan" to promote the upgrading and transformation of Hong Kong's industrial sector and enhance its competitive edge. The "Plan" is funded by the Industry and Trade Administration's "SME Development Support Fund." The "Industry 4.0" team of the HKPC will work with international experts to conduct an in-depth analysis of the current situation of the Hong Kong industry and deploy new services. The model develops a blueprint for the short- and medium-term strategy upgrade and prepares an industry implementation guide for Industry 4.0 to provide a step-by-step and feasible upgrade for local infrastructure industries. The "Plan" is supported by more than 20 chambers of commerce and will implement "Industry 4.0" through the three significant trilogy industries, plastics, electronics, metals, and machinery. The "Plan" trilogy: Enterprise on-site assessment, preparation of three industry guides of different natures, the publication of research results in various seminars and workshops, and sharing of experience with the industry.

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Three industry guides provide a multi-angle "Industry 4.0" upgrade reference: "Industry 4.0 Benchmarking Guidelines" for objective and systematic assessment criteria and models for Hong Kong companies, covering product development, sales, procurement, production, quality management , logistics and services, and other important operational areas; "Industry 4.0 deployment medium and short-term strategic upgrade blueprint" introduces the analysis of the overall maturity of Hong Kong enterprises; and "Industry 4.0 implementation of industry design and implementation of industry guidelines and case studies" is detailed Introduce the "Industry 4.0 Implementation Plan", including technology, hardware, software, management concepts, procurement solutions, cost budgeting, and business benefits. For HKSMEs, it is necessary to have knowledge and technique to implement industry 4.0 at different levels of adoption and company status. While the proposed upfront knowledge and know-how transfer programmes for four sectors will be the trump card to maintain their qualified suppliers status and act as the catalysis to boost the overall technological and unique

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position of HKSMEs in the global industrial arena, and hence, Hong Kong industry as a whole.

"Hong Kong foundation industry towards "Industry 4.0" deployment project" was officially launched. The guests included (from left): Dr. Lawrence Cheung, Director of Technology Development, HKPC, Li Yuen Fat, Chairman of FITMI, and Toni Drescher, Head of Fraunhofer IPT, Germany. The process of Hong Kong enterprises moving towards "Industry 4.0" has just started. Most of the enterprises are still in the stage of industrial 2.0 to 3.0, that is, labor-intensive production and application of automation equipment for mass production. There is no single method or technology for the implementation of "Industry 4.0".

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The industry must develop appropriate routes and strategies in accordance with the nature of its business and the degree of development. "Industry 4.0". Companies are advised to "listen and see more", understand their capabilities and customer needs firstly, and then develop an "Industry 4.0" development blueprint. The Hong Kong industry is now in need of absorbing more "Industry 4.0" information to tie in with the assistance of the Government, experts and partners, and to formulate an overall development blueprint based on its actual situation.

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Editorial Board and Disclaimer Publication: Hong Kong Productivity Council Productivity Building, 78 Tat Chee Avenue, Kowloon, Hong Kong Copyright: Hong Kong Federation of Innovation, Technology and Manufacturing Federation Hong Kong Productivity Council The project is organized by the Hong Kong Federation of Innovation, Technology and Manufacturing Industries. The Hong Kong Productivity Council is responsible for implementation and is funded by the SME Development Support Fund of the Trade and Industry Department of the Government of the Hong Kong Special Administrative Region. Any opinions, research findings, conclusions or recommendations expressed in this publication / in the event (or members of the project team) do not represent the Hong Kong Special Administrative Region Government, the Trade and Industry Department or the SME Development Support Fund and the development of brands, upgrading and expansion The

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opinion of the special fund (institutional support plan) review committee of the domestic market. The information in this report is for reference only. Although the content has been tried to be precise, neither the publisher nor the organization involved in the project is responsible for the negligence of the information provided or any loss caused thereby. Copyright may not be reproduced All rights reserved. No person may use any electronic or mechanical technology without the consent of the publisher. And other methods of reprinting or using the information in this report, including photocopying, recording, and placing the information into any form of information storage or reading system.

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Organizer and supporting organization

Organizer:

Implementation organization:

Funding for the SME Development Fund:

Any opinions, findings, conclusions or recommendations

expressed in this material/event (or by members of the Project

team) do not reflect the views of the Government of the Hong

Kong Special Administrative Region, Trade and Industry

Department or the Vetting Committee of the SME

Development Fund and the Dedicated Fund on Branding,

Upgrading and Domestic Sales (Organisation Support

Programme).

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Supporting organizations (in no particular order):

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Supporting organizations (in no particular order):

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“Sector-specific Industry 4.0 Benchmarking Model”

Section One:

Overview

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What is “Industry 4.0” The Term Industry 4.0 stands for the fourth industrial revolution. Best understood as a new level of organization and control over the entire value chain of the life cycle of products; it is geared towards increasingly individualized customer requirements. The basis for the fourth industrial revolution is the availability of all relevant information in real time by connecting all instances involved in the value chain. The ability to derive the optimal value-added flow at any time from the data is also vital. The connection of people, things, and systems create dynamic, self-organizing, real-time optimized value-added connections within and across companies (i40, 2019; Thangaraj, 2018) The concept of Industry 4.0 only emerged in 2011 as a future project within the framework of the High-Tech Strategy. Acatech - the German Academy of Engineering Sciences - presented a research agenda and implementation recommendations in 2013 at the Hannover Fair. These recommendations were compiled at the initiative of the German Federal Ministry of Education and Research (BMBF). Over 3

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million euros were invested in pre-analysis, education, and promotion. Industry 4.0 does not only concern manufacturing processes in factories, but the concept applies to all operations, including products and services. Technology enables Industry 4.0; however, the selection of the right applications is essential to deliver value to the company. The goal is different from the past, instead of creating new industrial technologies (predictive industrial revolution), but integrating all industry-related technologies, sales, and product experiences. It is to build a smart factory with adaptability, resource efficiency, and ergonomics, and integrate customers and business partners in business processes and value processes to improve production efficiency and achieve smart production. With the advent of the industrial Internet era, Germany's Industry 4.0 practice provides a new path to explore future production. It connects factories, machines, production materials, and people through network technology, bringing unlimited imagination to industrial intelligence. Enterprises have started to implement Industry 4.0 and gradually expand the concept of Industrie 4.0 not

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only into their supply chain but also in the complete value chain. In particular the automotive industry as well as the consumer goods industry. Additionally, product personalization, small batch sizes, and flexible production, including many different data points, have led to a highly flexible new working model. German manufacturing is one of the most competitive manufacturing industries in the world and has a leading position in the global manufacturing equipment sector. Much of this stems from Germany's focus on the research and development of innovative industrial technology products and the management of complex industrial processes. Germany has a strong equipment and workshop manufacturing industry, a high level of competence in the world of information technology, and expertise in embedded systems and automation engineering. These factors together have established Germany's leading position in the manufacturing engineering industry. (Mingxing, 2019)

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Industry 4.0, proposed by Germany in 2011, aims to help Germany maintaining its leading position in the global industrialized countries (re-industrialization and industrial renaissance in the UK and the US, China from a big country to a strong country) and increase the technological content of the country in the industry to increase industrial added value. With the development and application of a large number of innovative technologies, it is aimed to encourage and assist industrialists in maintaining local production. (Industry Cluster 4.0, 2019) Through the

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implementation of the Industry 4.0 strategy, Germany will become a supplier and leading market for a new generation of industrial production technology (i.e., information physics systems) (Mingxing, 2019), which will enable Germany to enhance its global competitiveness once again while continuing to maintain the development of domestic manufacturing. (Industry Cluster 4.0, 2019) Reasons and objectives of implementing "Industry 4.0" "Industry 4.0" is hailed as the fourth industrial revolution, using digital information to integrate sensors, Internet of Things, big data, the Internet, and other technologies to achieve smart and automated production. There are two reasons for implementing Industry 4.0. The first reason is to launch innovative business models, develop smart products and services, sustainable growth, and revenue. The second reason is to reduce costs, save time, create a safer production environment, and improve production quality and flexibility.

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Although most of the SMEs in Hong Kong are positive about investing in "Industry 4.0", they generally do not know where to start. “Industry 4.0” goes beyond automation Many people think that "Industry 4.0" is automation, but it is not. Everyday automation was already introduced with the third industrial revolution. Data is the essence of "Industry 4.0". "Industry 4.0" connects the entire product cycle through the Internet of Things (IoT), from "single order," purchasing, "ordering", production to shipment, real-time Data analysis, flexible adjustment according to actual conditions. Therefore, "Industry 4.0" is a direction, not an end; companies are doing business, not "Industry 4.0." Providing personalized products and services with high efficiency, high quality, and low cost is the real goal. According to the HKPC's understanding, in the past year or two, many OEMs and ODM factories in Hong Kong have received overseas customers' inquiries about "Industry 4.0". Customers even sent out questionnaires to understand the degree of Hong

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Kong businessmen's understanding of "Industry 4.0". For example, Ask the manufacturer about the smart factory, smart data, Internet of Things, and other concepts, and ask if the manufacturer's production and test equipment has been connected. Finally, even ask the manufacturer's ERP system to connect with the customer's system. It is beyond your choice for manufacturers to implement "Industry 4.0" for more and more overseas customers and upgrade to the "Industry 4.0" smart manufacturing model. Together with smart manufacturing in national policy will promote the provinces and municipalities to subsidize smart manufacturing projects, encourage enterprises to carry out technological and industrial changes, Hong Kong businesspeople should seize the opportunity to transform. The biggest problem in the industry is the lack of awareness of "Industry 4.0", which is doubtful about the benefits of equipment, software and workforce training for "Industry 4.0". Of course, the implementation of "Industry 4.0" is not singular and unilateral. Each industry and each company must

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develop appropriate routes and strategies by its nature of business and development level. The upgrade of the company to "Industry 4.0" is a gradual process. First, companies should be aware of their ability to implement "Industry 4.0" and their customers' needs, and then formulate an "Industry 4.0" development blueprint. The HKPC collaborated with the Fraunhofer IPT Institute in Germany to develop an “Industry 4.0” maturity assessment model from 0 to 4, which can be used as a reference for the implementation of “Industry 4.0”. Enterprises, especially SMEs, are moving towards "Industry 4.0". Although there are many challenges, they are actually "big and big, small and small", but they must do it. Among them, digitalization is the first step. SMEs do not need to invest heavily in new equipment. They can install sensors on existing machines or plug in a "set-top box" to connect to the network. This will enable existing production lines to add networking and collect real-time information. Take the first step towards "Industry 4.0" (Microsoft, 2019)!

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Project benefits for Hong Kong SMEs The proposed project will assist HKSMEs to maintain their international status and ride on the global industrial trend, by contributing a clear and comprehensive roadmap and practical implementation guidance for HKSMEs to transform their production modes from I 2.0, I 3.0 to Industry 4.0 step-by-step. Four sectors i.e. 1) Metal, 2) Plastics, 3) Electronics and 4) Machinery Equipment of Hong Kong Industries will be evaluated and studied. These sectors are the foundation industries, cover most of the HKSME manufacturing process and are characterized by relatively low labor intensivity and mutual inter-correlation. They are expected to have direct and immediate compliance pressure from their overseas buyers. Therefore these sectors will be evaluated and their current operation condition will be studied based on a reliable and practical solution composing of a “Short-Mid-Term Strategic Upgrade Mapping”, development of a “Sector-specific Industry 4.0 Benchmarking Model” and a “Sector-specific practical implementation guideline”. A solution proposal will be developed and compiled by HKPC Industry 4.0

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Implementation Team and overseas experts of Industry 4.0. In particular, the benchmarking model is used to collect the whole picture of the four Industries’ current production conditions. Then the information collected will be used as important reference for compiling the “Short-Mid-Term Strategic Upgrade Mapping” and “Sector-specific Practical Implementation Guideline and Case Analysis”. Upon collecting and reviewing the benchmarking results, the overseas expert and HKPC consultant will conduct on-site detailed analysis for four sectors to identify a series of industry 4.0 project ideas and case studies. Afterwards these ideas and studies will be compiled in the form of a “Sector-specific practical implementation guideline and case anslysis” which will be the valued reference as these guidelines and cases will be derived in accordance with the actual situations of HKSMEs and contains local operation elements. It would be difficult for the overseas experts to straightly compile an implementation guideline composing of different project ideas and cases without having a personal impression of the actual situation of local SMEs. HKSMEs can then use our developed implementation guideline to select appropriate Industry 4.0 project ideas for self-

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implementation based on their own status step-by-step. In the following direct benefits for SMEs of our proposed deliverables are listed:

Catch up with the ideas of the latest digital information management system and management roadmap of Industry 4.0.

Immediately identify their current industry level (Industry 2.0, 3.0 or 4.0) by conducting preliminary self-assessment and find out suitable development methods from the implementation guideline compiled by experts of Industry 4.0.

Minimize the investment amount on hardware and software by referring to the suggested solutions of various levels and complexity in the implementation guideline.

Time-saving as the latest information of Industry 4.0 can be obtained through the Platform.

Obtain hands-on and practical knowledge on how to implement Industry 4.0 effectively and economically.

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Based on our acquired price information on overseas industry 4.0 experts, SMEs have to pay a much higher cost if they implement Industry 4.0 on their own without industry-wide program support. The high cost of manpower and financial resources would be needed to be spent on collecting consolidated information, and the latest development of Industry 4.0 to understand the knowledge and implementation know how. Also, it would bring a tremendous financial burden for HK SMEs if they hire overseas experts to conduct Industrial assessment and project ideas identification based on their operation individually. The SMEs may also suffer significant loss if they invest unsuitable hardware and software, conduct unsuitable implementation methods, or even misunderstand their level of maturity. Overseas experts will provide Industry 4.0 detail theory, definition, standards, best practices, implementation know-how, etc. from overseas institutes and overseas enterprises as innovative and technical inputs. Overseas experts will develop the draft benchmarking model, high-level training, conduct 4 HKSMEs benchmarking studies, draft strategic upgrade mapping, identifying Industry 4.0 project ideas for four HKSMEs, etc.

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Section

Two: Industry 4.0

Core Principles

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Concept of Industry 4.0 The term Industry 4.0 is based on the previous global industrial revolutions throughout the last centuries. The commencement of the 1st Industrial Revolution is closely linked to a small number of innovations. Foremost the power machine became suitable and was introduced into industrial use in the second half of the 18th century.

Figure 1 Effects of the different industrial revolutions

The 2nd Industrial Revolution came with the analysis and optimization of workflows. Applying science to engineering processes, labor was allocated according to specific process steps (a division of labor).

Overhead productivity

compared to 2010

Computer operations

per second per 1$

In dependence on: H.-J. Warnecke (1992) Fraktale Fabrik

19001825

#Op./(s*1$)T€/(c*a)

CollaborationSteam machine Automation

Yearly consumption of

energy in Germany

Medium per capita income

in Germany

%

30

GWh/a

2,5

2,0

1,5

1,0

0,5

3,0

3,5

1. Industrial Revolution 2. Industrial Revolution 3. Ind. Revolution 4. Industrial Revolution

1925 1950 1975 2000 2025 2050

25

20

15

10

5

600

400

200

800

1,E+09

1,E+00

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Productivity increased due to the standardization of best practices and the elimination of waste. The 3rd Industrial Revolution introduced automation technology into industrial use by the developments of electronics and computers. Production lines were automated with industrial robots and Programmable Logic Controllers (PLC). The 4th Industrial Revolution integrates the physical and digital world in production companies creating value by digital-driven business models and further increase in productivity and efficiency. Industry 4.0 is driven by recent trends in both the cyber and physical world. The single source of truth is the practice of structuring information and schemata in a single database. Any possible linkages to the data are established by reference only. The single source of truth is the basis for reliability and consistency in the company data necessary for data analytics and predictions. The digital players in the market drive the cooperation in business and social communities. Information Technology (IT) supports the storage of data in the cloud, provide methods for data mining and high-speed computing. Automation processes by including sensors become highly robust and cost-efficient and provide open IT-Systems. Industry 4.0

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fosters collaboration and productivity by improving human/human, human/machine, and machine/machine interfaces.

Figure 2 Drivers for Industrie 4.0

Additionally, the adaption of Industry 4.0 is enabled by

recent changes in sensor technology. Sensors are

becoming smaller, cheaper, and more versatile. They

can measure more data and can interact with each

other.

Furthermore, networks are established ad-hoc and

automatic. The data transfer rate and the number of

network partners significantly increases. Data sources

are linked together from different and heterogeneous

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sources. Thus, diagnostics analytics and predictive

modeling are possible such as pattern recognition.

Apart from the data side, the interaction with the user

becomes the central role. The human-machine-

interface (HMI) is user-specific and suited to the needs

of the customers. Assistance systems help in manual

processes such as maintenance work. Methods from

augmented reality interact link the digital to the

physical world.

"Industry 4.0" promotes industrial applications and

develops innovative technologies while encouraging

smart production, upgrading and transformation,

researching and developing industries suitable for

Hong Kong-based industries, and creating high-quality

and diverse employment opportunities.

The "Industry 4.0" concept encompasses a

fundamental shift from centralized control to

decentralized enhanced control to create a highly

flexible production model for personalized and digital

products and services. In this model, traditional

industry boundaries will disappear, and new forms of

activity and forms of cooperation will emerge. The

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process of creating new value is changing, and the

division of industry chain will be reorganized.

Additionally, the adaption of Industry 4.0 is enabled by

recent changes in sensor technology (Figure 3).

Figure 3 Enablers of Industry 4.0

Sensors are becoming smaller, cheaper, and more

versatile. They can measure more data and can

interact with each other. Furthermore, networks are

established ad-hoc and automatic. The data transfer

rate and the number of network partners significantly

increases. Data sources are linked together from

different and heterogeneous sources. Thus,

diagnostics analytics and predictive modeling are

possible such as pattern recognition. Apart from the

data side, the interaction with the user becomes a

central role. The human-machine-interface (HMI) is

Sensors:§ become smaller, cheaper,

more versatile

§ can measure more data

§ can interact with eachother,

etc.

Ad-hoc networks:§ Automated recognition

and utilization

§ Significant increased data

transfer rates

§ Increasing number ofnetwork partners, etc.

Smart Data:§ Linked data from

heterogeneous sources

§ Diagnostic analytics

(pattern recognition)§ Predictive analytics,

etc.

HMI:§ User-specific Human-

Machine-Interface (HMI)

§ Assistance Systems

§ Augmented Reality,

etc.

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user-specific and suited to the needs of the

customers. Assistance systems help in manual

processes such as maintenance work. Methods from

augmented reality interact link the digital to the

physical world.

“Industry 4.0" will pay special attention to attracting

SMEs to participate, and strive to make SMEs users

and beneficiaries of a new generation of smart

production technology, and also become the creators

and suppliers of advanced industrial production

technology (Mingxing, 2019).

For a structured approach towards understanding the

different aspects of Industry 4.0 one can use the

Smart i4.0 Navigator (Figure 4). The navigator gives a

structured overview over the interaction of a unique

business model (Uniqueness), technology driven

applications that implement the business model

(Application) and the technologies that enable these

applications (Enablers). The central element of the

navigator is value creation. Value from the viewpoint

of a company doing business can be created in the

form of Growth & Revenue or in the form of enhanced

Productivity & Efficiency affecting costs of the

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company. To drive growth & revenue the other

important viewpoint regarding value creation is the

customers ́one. For a successful business it is of

utmost importance which value it creates for the

customer. This value determines how successful a

company will be in gaining and keeping satisfied

customers and ultimately how successful a company

will be in generating growth & revenue. In order to

make Enablers, Applications and Business Model work

successfully together with the ultimate target of value

creation a company needs a coherent strategy and

organizational structure (Strategy and Organization) as

well as a supportive Mindset and Culture. These

aspects form the framework and internal environment

for a prosperous business.

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Figure 4 Smart i4.0 Navigator (Source: KEX AG)

Building corporate uniqueness (Innovative Digital Business model) The business model is the foundation of a company and

determines whether it will be successful and grow in the middle

and long run. The best business idea will fail if there is no

functioning business model beneath it. Furthermore the

business model can differentiate a company from its

competitors leading to a unique position in a market and

thereby significant competitive advantage.

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Figure 5 Smart i4.0 Navigator – New Digital Business Models (Source KEX

AG)

The business models evolving from Industry 4.0, will go beyond traditional business methods. Due to the possibility to add sensors to the products and machinery, a new quality of data will be available. Enabling the analysis of user data along the whole product life cycle, which will result in data-driven business models and new add on services which can additionally be offered, such as predictive maintenance on demand. When companies aim to develop such new business models and services, it is necessary to develop upfront a digital vision for the company and a holistic strategy

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which will be introduced with the support of a defined roadmap. The establishment of a digital roadmap to enhance the common understanding and vision of Industry 4.0 at all levels across the organization is a first step in changing the mindset of the company towards a more digital one. Business model innovation has changed the face of all walks of life and redistributed billions of dollars in value. Retailers like Amazon are entering the market in a groundbreaking business model.

But it's not uncommon to write a business model of innovation in business models like Apple Computer

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("Apple"). The analysis of the major innovations of the old companies over the past decade has nothing to do with the business model.

In 1975 • Weight: 81⁄2 US-Pound (about 3.9 kg) • Size: 83⁄4 x 6 x 9 inches (approx. 22 x 15 x 23 cm) • Image quality: 100 x 100 primitives (0.01 million pixels), black and white • Save pictures to tape: Each photo takes 23 seconds. • Pictures are sent to TV: Each photo takes 30 seconds. New business models often cause an industry to disappear. Kodak has a long history but finally went bankrupt in 2012. Texas Instruments published the first patented digital camera in 1972. Kodak is aware of the potential of this new technology. Later, in the

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1990s, a new technology of digital images related to Microsoft was launched.

Figure 6 Stephen Shasen and the first digital camera

When the first digital camera entered the market in 1999, Kodak predicted that digital cameras accounted for only 5% of the market in ten years, and analog cameras remained 95% strong. In 2009, the reality was different, and the analog camera had only 5% of the market, but it was too late. Between 2008 and 2008, Kodak reduced the number of employees by more than 80%. In 2012 Kodak filed for bankruptcy protection.

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It has been found that the average profit margin of the innovative business model has increased by 6%. Therefore, managers believe that the advantages of innovative business models are more important than product or service innovation.

The methodology of the St. Gallen business Model Navigator supports the development of new business models. The Navigator focuses on four main aspects and questions which should be answered when developing a new Business Model. The four main questions are:

- What do you offer to the customer? - Who is your target market?

Figure 7 St. Gallen Business Model Navigator (Gassmann, 2013)

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- How is the value proposition created? - How is the revenue created? (Gassmann, 2013)

The main areas of the Business Model Navigator are further described in the following. The “who question” targets the customer – asking the following question is mandatory: Who are our target customers? For any successful business model, a company must understand exactly which are the relevant customer segments to address and which are not. The customer is, therefore, at the center of the business model.(Prof. Oliver Gassmann, 2019) “What” focuses on the benefit of the customer. It

describes what is offered to customers in order to satisfy their needs or solve problems. In other words, the customer value proposition has to be defined upfront. (Gassmann, 2013) In order to achieve the value proposition, a company has to perform various processes and activities. These processes and activities - together with the resources, skills, and partners involved - form the 3rd dimension in the design of a business model. (Prof. Oliver

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Gassmann, 2019) The value chain focuses on how the service or product is produced within the company. The 4th dimension explains why a business model is financially sustainable. It includes aspects such as cost structure and revenue mechanics. The revenue mechanism dimensions answer the central question of any company: How do you make a profit Focusing on the income model of the new business model. (Prof. Oliver Gassmann, 2019) In the process of innovation, the power of imitation and reorganization is emphasized. The phrase “no need to reinvent the wheel” describes the fact that, with careful observation, only a few phenomena are new. Often, innovation is a small change in something that exists elsewhere. Over hundreds of business model innovators, it is found that about 90% of the innovations are recombined with previously existing concepts. (Gassmann, 2013)

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It is important to understand the 55 business models that make up many new business models. The Business Model Innovation Map by Prof. Dr. Oliver Gassmann depicts the 20 most popular models and companies that apply them to new business models. (Gassmann, 2013) For example, the RAZOR AND BLADE model can be traced back to Gillette's 1904 move to sell primary products (razors) at low prices and make money from more expensive consumables (blades). This model defines the value proposition and revenue logic of the business model and has since expanded to many industries. Examples include inkjet printers and ink

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cartridges, blood glucose meters and test strips, or Nespresso coffee machines and capsules. In the business world, there are not many new business models. However, you can find many powerful application backgrounds and industries. When considering an innovative business model, existing business models can be used as inspiration. The Business Model Innovation Map is one of the tools to help with innovation. If they can be used elsewhere, why not apply them? This method brings external stimuli. (Gassmann, 2013) Another well known example for a business model innovation is “Power-by-the-hour” of British jet engine manufacturer Rolls-Royce. The company shifted its business model from selling turbines and aftermarket services towards a wholistic service offering charging its customers by the time of turbine usage. The engine will remain the property of Rolls-Royce and the company will also be responsible for the maintenance and repair of the engines. In the context of the 55 business models by Prof Gassmann this is an example for “Servitization”.

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Figure 8 Power-by-the-hour – Servitization

With regard to the St Gallen Business Model Navigator Rolls Royce has fundamentally changed its revenue model (Value), its value chain (How) as well as its value proposition (What) while the target customers (Who) remained the same. As shown in Figure 6 sensors, network connectivity and data analytics are the enabling technologies working together in smart product as application in an innovative business model. Smart Factory and applications (smart solutions, smart innovation, smart supply chain, smart production)

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The smart factory is a significant theme of Industry 4.0, and it is also the specific basic scene that reflects Industry 4.0. The "smart factory" is not just a physical factory, but also a virtual factory that supports decentralized network manufacturing. Smart factories are considered to be a key component of smart infrastructure, with a core focus on smart production systems, processes, and the implementation of networked branch production facilities. In the future, the business will establish a network that uses information physics systems as a carrier, including mechanical equipment, storage systems, and

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production equipment. Regarding the manufacturing sector, cyber-physical systems will include smart machines, warehouse systems, and production facilities that automatically exchange information, trigger actions, and coordinate control. Thereby, the quality of production, design, material resources, supply chain, life cycle management, etc. are improved. Smart factories have been using new production methods, and the products are uniquely tagged to trace their footprint throughout the life cycle, showing the current status and future processing methods. The embedded production system will form a horizontal network with the vertical network of the factory or enterprise business process and the dispersed value chain and form immediate management from the procurement of raw materials. To achieve the above vision, Industry 4.0 needs to include the following elements: Cyber-Physical System (CPS), Internet of Things (IoT), Service Networking (IOS), Cloud Computing, Big Data and Smart Factory. The realization of these elements depends on the application of advanced equipment. The technology is based on the Cyber-Physical System (CPS) and the Internet of Things (IoT). In the rapid development of

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the Internet, more and more powerful and independent micro-computers (embedded systems) have realized factories that cooperate with other microcomputers and the Internet, the physical world and the virtual world (cyberspace) with information physics systems. The implementation of CPS modernizes production methods. Industry 4.0 depicts a blueprint for a smart factory: in a smart factory, people, machines, and resources naturally collaborate and collaborate as if they were in a social network. Smart products know the details of how they are made and how they will be used. They will assist the production process by answering such questions as "When was I made" or "The set of parameters on the machine should be used to handle me" through RFID or other embedded systems? "My next stop will be sent there. Moreover, other issues". Smart factories are connected to smart mobility, smart logistics, and smart system networks. Smart factories are characterized by end-to-end engineering manufacturing. This end-to-end engineering manufacturing not only covers manufacturing processes but also includes manufactured products and product research. Develop processes to integrate both digital and physical systems seamlessly. Smart

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factories will make increasingly complex manufacturing processes for workers more manageable while making the manufacturing process attractive while making the manufactured products environmentally sustainable. Critical indicators of production system performance are yield, quality, cost, and component accuracy. Industry 4.0 proposes to use data to analyze and understand the factors that affect the above-mentioned key indicators of the production system and to predict and monitor the risks that may occur — the key to predictive manufacturing. Today's production systems in most factories use commercial management software to assist plant managers in obtaining information such as overall equipment efficiency (OEE), to timely grasp and respond to the influencing factors and results produced in the production system. However, more in the production system is the influence of invisible factors, such as the degradation of equipment performance, the lack of precision, and the waste of resources. The accumulation of invisible factors often causes visible influencing factors to a certain extent. For example, the decline of equipment eventually leads to downtime, and the lack of precision eventually leads

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to quality deviation. Therefore, predicting and managing these invisible factors is the key to avoiding the influence of visible factors. In Industry 4.0's factory, Self-Prediction functions become new features in monitoring and control systems that help users understand machine performance degradation, remaining available time, lack of precision, and various factors. Quality and cost impact. Also, the machine can be predicted by the fusion of the performance of the components and the peer-to-peer. This predictive capability allows the plant to take timely maintenance measures to improve management efficiency and thereby optimize machine uptime. Finally, the health information of the machine can also be fed back to the machine design department to form a closed cycle lifecycle update design that ultimately achieves worry-free production. This predictive analytics approach enables both product and manufacturing systems to be self-aware and self-maintaining. Product Prediction Service and System Forecasting combine information from manufacturing systems and supply chain systems to enable products to generate proactive service requests and further predict/prevent potential failures.

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Smart Solution:

Figure 9 Smart i4.0 Navigator – Smart Products / Solutions (Source KEX AG)

The smart solution includes products or services.

Products/services are aware of customer behavior and

generate user data connections to the operating

platform. Provides value-added services to customers

by observing and analyzing user behavior through

sensors. For example, connecting and sensing infusion

pumps can promote safety, safety, and timely

personal assistance while reducing logistics costs. It is

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expected to increase the annual growth rate of the

market by > 30%.

A new generation of smart products, such as mobile

phones, automobiles, and home appliances, has

innovative features that adapt to the specific needs of

the user and the specific environment, and this

adaptability is one-way, and the smart product will

contain different components and embedded

software. Moreover, smart products can interact with

users in a smart way, such as the following four major

interactive projects:

Four characteristics of smart products:

I. Background and awareness Perceived

environment Interactive and

nearby equipment Interaction and

background

II. Safety and security Check user

permissions Provide

remote use function

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The main functions of smart products:

Because the new generation of smart products is a

relatively advanced product, the design and

manufacturing are very complicated, usually contain

thousands of components and need to achieve the

overall operation, so the system-level engineering

design has become a pivotal position.

As with traditional methods, companies need to

design each subsystem separately and then spend

billions of dollars on physical testing later in the

product design process, and if design changes are

needed, the cost will be very high and time-

consuming, traditional The actual test method may

not provide all the information needed to eliminate

product risk and ensure product success. So in the

III. External information About obtaining

external data/services

Integrate social networks

IV. User profiles Distinguish

product users

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new era of Industry 4.0, a part of smart products

emphasizes product lifecycle management,

engineering simulation and simulation software

applications to provide these data and manage and

quickly and finely adjust the entire product system in a

virtual environment. The entire product development

process to production can be easily mastered.

Smart flower pots: Smart pots do not require soil. As

long as the lighting and irrigation systems are set up,

they can provide enough nutrients for the three

important stages of seed germination, seedling

growth and harvesting. It can grow almost all types of

plants with an acceptable maximum height of 2

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meters. The pots are equipped with 18 LED lights,

which adjust the light intensity according to the

growth of the plants. The built-in irrigation system

also has this capability.

Smart luggage: The smart luggage incorporates many

useful functions. The built-in digital scale can indicate

the weight of the items carried by the user; and the

application software can check whether the luggage is

overweight; the built-in battery can charge the

electronic device. In addition, it also configures a

digital control lock that users need to use to turn on

their smartphone. If the suitcase is unfortunately lost,

the suitcase will be automatically locked. When your

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suitcase is lost somewhere, it will send a reminder

notification to your phone and help you find it through

a close-range map navigation.

Smart Trash Can: An US company has developed a

solar-powered trash can that automatically

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compresses in 41 seconds after the trash is full and

notifies the cleaners via the wireless network. This

smart trash can is especially suitable for areas with

high traffic, such as shopping centers, amusement

parks or sightseeing areas. The device is 128 cm high

and weighs about 136 kg. The normal capacity of a

trash can is 120 liters, but it can accommodate up to

five times the volume of waste by compression

technology.

On the other hand, the smart service referred to in the

era of Industry 4.0 is no longer a model of remote

artificial online response and after-sales product

service in the traditional sense, but rather focuses on

the use of big data formed by the entire industry chain

for comprehensive data analysis and the mining of

valuable data provides users with customized

information for their specific activities and needs to

assist their specific activities in decision-making.

This part is the core content of smart production. It

can collect the original information of customers and

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accumulate into a powerful database to provide the

basis for building the structure model of demand. It

can further explore the hidden needs related to

identity, work and life status. In order to provide

customers with accurate and efficient services.

Information and network-based electronic services are

infiltrating into various industries and fields of the

social economy, supporting the transformation of

modern society from a manufacturing economy to a

service economy. In the Internet environment,

collaboration between enterprises is closer, and the

organization and operation mechanism of enterprises

are becoming more service-oriented. This is a new

enterprise organization model that implements the

flattening of organizations in the form of business

components, improves the operational efficiency of

enterprises, and realizes the need for business

collaboration across enterprises.

"Context-awareness" applied to smart products is that

service systems and service networking provide

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efficient and reasonable services to customers based

on the time, place, and activities of customer

information and services. The system architecture of

context-aware services includes sensor layers and

scenarios. Perception engine, repository and business

service layer and execution process, including

situation information collection, situational reasoning,

business service invocation, and analysis of the

theoretical and technical issues involved.

Cloud computing is the key technology for computing

resource service, and how cloud resources and service

applications are actually utilized is an important issue

of concern. Linking the common network resource

sharing and application integration requirements of

various industries with the core ideas of cloud

computing, emphasizing the important role of virtual

resource centers and domain services in applying

cloud computing concepts.

Smart services involve service computing and service

management. Modern service management is paying

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more and more attention to the role of customers in

the process of creating service value together,

establishing a network of communication with

customers, further presenting production information,

increasing production transparency and meeting

customer-defined requirements.

The four major categories of the main functions of smart services:

I. Optimize use Forecast user

needs Collect location

related services Optimize services

through collected usage data

II. Ecosystem Provide an ecosystem

platform Personalized user

experience Selling collected usage

data

III. Resources Arranging the use

of resources and infrastructure

IV. Community Integrate community

services Users can use their

personal electronic devices to query

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resource details through the network

Provide remote user support

Smart innovation:

Figure 10 Smart i4.0 Navigator – Smart Processes (Source KEX AG)

Smart innovation provides an early user experience

for the fuzzy front end and agile development teams.

As a result, data-driven engineering and open

innovation have improved customer personalization

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and exploration of unknown areas, while the company

has a positive attitude toward future innovations.

Example: The user experience has been incorporated

into the product testing phase and a disruptive

network is used to create products and technologies

with open and innovative user data drives.

Smart innovation combines all of these concepts,

including system-level quality, attributes, features,

functionality, behavior and performance. Through the

integration and integration of advanced

manufacturing, information processing, artificial

intelligence and other technologies, smart equipment

can form an smart production system with self-

organization and self-adjustment functions such as

perception, analysis, decision-making, execution, and

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independent learning, as well as network and synergy.

Production facilities.

In the era of Industry 4.0, devices with IoT concepts

such as computers, smart phones, smart TVs, smart

robots, smart wearable devices, etc., have been

network terminals since their birth; traditional air

conditioners, refrigerators, automobiles, machine

tools, wind turbines, etc. will be new members of the

future Internet of Things, they will connect to the

network world, forming a variety of smart networks.

The process of smart equipment can be carried out in

two dimensions: stand-alone intelligence, and smart

homes, smart production lines, smart workshops, and

even smart factories formed by the interconnection of

devices. This process will continue to deepen and

progress with the evolution of ICT innovation

applications.

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Smart supply chain:

Figure 11 Smart i4.0 Navigator – Smart Networks (Source KEX AG)

Based on a transparent visualization supply chain,

transportation logistics, business operations, and

production engineering are distributed to different

units in the supply chain. Example: Electronic kanban,

instant notification to suppliers that pallets and boxes

need to be refilled.

The smart supply chain utilizes a new generation of

information technology to enable the logistics system

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to have the ability to sense, process, self-learn,

analyze and make decisions and solve some of the

problems in logistics. The smart supply chain is

connected with smart production and other networks.

End-to-end connectivity for customer-centric logistics

services. Leverage integrated intelligence technology

and support with cloud computing, big data, Internet

of Things, mobile Internet and CPS, as well as technical

support such as Global Positioning System (GPS) and

Earth Information System (GIS).

The future development of the smart supply chain will

reflect four characteristics: intelligence, integration

and layering, flexibility and socialization. In the

process of logistics operation, a large number of smart

operations and decision-making are involved; with

logistics management as the core, the integration of

transportation, storage, packaging and loading and

unloading in the logistics process and the hierarchy of

smart logistics systems are realized; the development

of smart supply chain.

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The concept of “customer-centered” will be more

prominent, and production will be flexibly adjusted

according to changes in consumer demand, and

flexible to meet market demand. Development will

promote the development of the regional economy

and the optimal allocation of world resources to

achieve the goal of socialization.

The smart supply chain can be applied to the internal

decision-making of the enterprise. Through the

analysis of a large amount of logistics materials, the

decision of the logistics customer's demand,

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commodity inventory, logistics smart simulation, etc.

is made.

Automate logistics management (acquisition of data,

automatic classification and automatic access, etc.) to

make logistics operations more efficient and agile.

Smart supply chains can also reduce the cost of

logistics warehousing. Actively acquire information in

the logistics process, and actively monitor the

transportation process and cargo status, as well as

proactive analysis of logistics information, so that

logistics operations are tracked and managed from the

source to achieve faster information flow.

Within the logistics enterprise, the external logistics

data transmission function is also realized

simultaneously, and the information is exchanged

with the service unit, thereby improving service

quality, accelerating response time, and promoting

customer satisfaction, and the integration of the

overall logistics supply chain will be closer.

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The logistics field is one of the most practical

application areas of IoT related technologies. The

construction of the Internet of Things will further

enhance the intelligence, information and automation

of logistics. Promote the integration of logistics

functions. It will have a positive impact on the

operation of all aspects of logistics services.

The logistics system based on the Internet of Things

can realize the whole process of identification and

tracking of raw materials, parts, semi-finished

products and finished products on the entire

production line. Reduce manual identification costs

and error rates by using Electronic Product Code (EPC)

technology, you can quickly identify the required raw

materials and components from a wide variety of

inventory by identifying electronic tags. Automatic re-

formation of detailed replenishment information to

achieve balanced production and steady production.

The Internet of Things can make the management of

articles more transparent and visualized during

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transportation. By attaching EPC tags to goods and

vehicles transported in transit, RFID check-receiving

devices are installed at some checkpoints of the

transport lines, so that enterprises can understand in

real time. The current location and status of the cargo.

Realize the visual tracking management of

transportation goods, lines and time. In addition, it

can help achieve smart scheduling, such as predicting

and scheduling the best driving routes in advance,

shortening transportation time and improving

transportation efficiency.

In warehousing management, IoT technologies (such

as EPC technology) can automate the inventory

management, and pick-up processes of warehouses,

thereby improving operational efficiency and reducing

operating costs. The goods stored in the warehouse

can be freely placed, which improves the space

utilization of the warehouse. Through real-time

inventory, the inventory can be quickly and accurately

grasped, the replenishment can be carried out in time,

the inventory management capability can be

improved, and the inventory level can be lowered. At

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the same time, accurate and efficient extraction of

different goods according to instructions, reducing the

outbound operation time.

The use of EPC technology in the delivery process can

accurately understand the storage location of the

goods, which can greatly shorten the extraction time,

improve efficiency and speed up the transportation.

By reading the EPC label and checking with the order

form, the accuracy of delivery is improved. In addition,

you can also know exactly how many goods are

currently in transit, the origin and destination of the

shipment, and the estimated time of arrival. When the

EPC-labeled goods are picked up by the customer, the

smart shelves will automatically identify and report to

the system through the network. The logistics

enterprises can realize the agile reaction operation

and predict the logistics demand and service timing

through the historical records, so that the logistics

enterprises can better carry out the logistics

enterprises. Active marketing and proactive services.

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A German company in the logistics center of

Humboldt is a very representative example for

Industry 4.0. Inside the Humboldt Logistics Center, you

will see a box of car engine parts piled up, as the green

light lights up, the stairway sends out a box of parts,

with the conveyor belt reaching the terminal; the

worker puts the box part at the terminal on the

luggage rack. There, it will be shipped with more parts

to the assembly point of the assembly plant, waiting

for assembly.

All parts of the Humboldt Logistics Center production

line have a unique RFID code that automatically

exchanges messages with the checkpoints along the

way, increasing overall productivity. Here, each time a

worker takes out a box of parts, he clips the "watch

strip" that records the product information into a

rectangular plastic clip. The clip is attached to the box

with a radio frequency identification code at the

bottom of the clip - the ID of the box. After each

production step, the card reader automatically reads

the relevant information and then feeds it back to the

control center for processing.

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For example, when the shipping truck carries the box

parts out of the logistics center, the assembly plant

5000 meters away can get dynamic information.

Before the assembly workers bring it to the

production line, the logistics center and the supplier

can make a decision on whether to replenish the

goods based on the real-time information received.

At the Humboldt Logistics Center, there is a fuel

injector for assembling diesel engines. The main

injector body and the internal ejector are provided by

different suppliers, but one of the two parts is printed

on the sample QR code. This is done to speed up visual

management. When labeling a single product, it is

more convenient to use a two-dimensional code than

a radio frequency code. When labeling each box of

parts, a radio frequency identification code is used.

There are several ways to attach a smart tag to a

product: barcode, QR code, RF code or sensor. When

the Humboldt Logistics Center introduced the RF code

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system, it cost hundreds of thousands of euros, but it

turns out that such investment is quite worthwhile.

When the new system is put into use, the factory

inventory is reduced by 30%, the production efficiency

is increased by 10%, and the savings can reach tens of

millions of euros.

The smart factory example of Humboldt Logistics

Center embodies this smart production process and is

highly compatible with the concept of lean

production, which not only avoids waste in the

production process, but also makes the entire

production process more accurate and efficient. In

addition, smart factories in the industrial 4.0 era can

achieve more advanced features. For example, the

production equipment can identify the maintenance

requirements and send relevant information to the

management personnel, and the management

personnel can remotely monitor the production status

and operation flow through the system. Thereby

optimizing the resource configuration and the like.

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Smart production:

Figure 12 Smart i4.0 Navigator – Smart Production (Source KEX AG)

Smart production is an ideal production system. It

smartly edits product features, cost, logistics

management, security, production time and more to

achieve optimal product manufacturing for different

customers.

The smart production proposed by Germany refers to

the use of information physics systems, relying on

different sensors, industrial software, network

communication systems, new human-computer

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interaction, etc. to realize mutual recognition and

interconnection among people, devices and products.

Effective communication, which promotes the close

integration of R&D, production, management, service

and Internet, promotes the development of

customized, flexible, green and networked production

methods, and continuously enriches and enhances the

global competitive advantages of Germany's own

manufacturing industry.

Production technologies such as sensors, data

analysis, etc. must be properly applied to the

production line, and production performance can also

be analyzed in real time to their key performance

indicators (KPIs). Examples: Effectively reduce

inventory, quickly configure machine mode changes,

production performance, better predictive

production, and fault prevention.

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Based on the digital chemical plant, smart factories

use the Internet of Things and equipment monitoring

technology to not only effectively strengthen

information management and services, but also

clearly grasp the entire product sales process, and also

improve the controllability of the production process

and reduce the production line. Human intervention,

timely and accurate collection of production line data.

Through the emerging technologies such as smart

systems and smart networks, it rationally arranges

production plans and production schedules, and builds

a humanized chemical plant with high efficiency,

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energy saving, environmental protection and

comfortable environment.

Real-time sensing, dynamic control and control of

large engineering systems through the integration and

deep collaboration of 3C: Computation,

Communication and Control technologies through the

Super Industrial Internet-Information Physics

Integration System (CPS) information service.

Products manufactured in smart factories have a

unique label in the production process that traces

their history throughout the life cycle, viewing current

conditions and future processing methods.

Unlike traditional products, smart products integrate

sensors, processors, memory, communication

modules, and transmission systems into products that

enable dynamic storage, sensing, and communication

capabilities to enable traceability and identifiability of

products. They will "know" how they are produced

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and where they will be sent. This means that in the

huge information system of the smart factory,

production information can be quickly communicated

and integrated. Not only that, but in this production

process, "dialogue" and "communication" can be

carried out between raw materials, production

equipment, production lines and various related

management systems.

When there is wisdom between different people and

things, connections and information are everywhere,

the connection between equipment and equipment,

between people, between things and things, and

between people and things will become more and

more close.

Eventually, a system will be connected to another

system, a small system will form a large system, and a

large system will constitute a larger system, forming a

smart network.

Taking a smart phone as an example, each smart

phone is a system, and the interconnection between

smart phones will form a larger system. The

production link of smart phones is a system

integrating R&D, production, logistics, sales and

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service. Of course, the production line of each smart

production equipment, the supplier of mobile phones,

and the enterprises that host mobile phone

manufacturing are also a system. And every customer

who uses a smartphone in our unit stores all the

information in the enterprise's customer management

system. It instantly senses, captures, evaluates,

selects, and transforms customers' needs.

These are just a few of the many complex systems

associated with smartphones, and smart production

can be imagined to be made up of these different

systems.

In Germany and around the world, a huge system of

super-complexity is taking shape. Machines in the

workshop (such as a smart phone), through the

update of the operating system to achieve functional

upgrades, through the industrial applications to

achieve a variety of functions Plug-and-play (Plug-and-

play), through the application design development

interface (API) to expand manufacturing ecosystem.

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Smart machines are a complex group that can include

different production equipment: lathes, milling

machines, complete automated production lines,

industrial robots, precision instruments and test

equipment, 3D printing equipment, etc to automate

production processes through smart machines.

Intelligence, precision and environmental-friendly are

the basic elements of becoming a smart factory.

Industry 4.0 is not just automation

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Implementation driven by technology

Figure 13 Smart i4.0 Navigator – Enablers (Source KEX AG)

Industry 4.0 is driven by recent trends in both the cyber

and physical world. The single source of truth is the

practice of structuring information and schemata only

in one database. Any possible linkages to the data are

established by reference only.

The digital players in the market drive the cooperation

in business and social communities. Information

Technology (IT) support the storage of data in the cloud,

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provide methods for data mining and high speed

computing. Automation progresses by including

sensors, become highly robust and cost-efficient and

provide open IT-Systems.

In fact, SMEs do not have to have the resources of

large enterprises to achieve the "Industry 4.0"

standard. For Hong Kong SMEs to move towards the

level of "Industry 4.0", please refer to the following

five pragmatic methods:

1. Identify key IT applications

To play the role and value of "Industry 4.0", there is no

need to rush to add all IT applications in one go. First,

determine the areas that require IT support, such as

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digital shop management, regular maintenance,

optimization of energy efficiency, advanced

automation and digital quality management. Focus on

installing the corresponding IT application.

2. Build a good foundation for IT

"Industry 4.0" is dominated by IT applications.

Therefore, enterprises that want to implement

"Industry 4.0" must first lay the foundation for IT. For

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example, they must have a more complete

management system and database to prepare for the

future smart factory solution.

3. Understand the services of different technology

vendors

In the installation of IT applications, technology

vendors will generally provide assistance, but

"Industry 4.0" involves a variety of different

applications and it is difficult for a single supplier to be

responsible.

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According to the experience of the HKPC, companies

start to look for different suppliers to provide

integrated solutions. Each supplier has its technology

strengths. As a user, you should understand the

services of different technology suppliers and find the

one that suits you best.

4. Build a strong and agile internal team

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The team consists of colleagues from different

departments to plan and implement the development

blueprint for "Industry 4.0", discuss the progress of

related projects and provide necessary support. The

interaction of the entire cross-sectoral team can

condense the company's culture of innovation.

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5. Piloting with a new business model

"Industry 4.0" integrates data from the supply chain,

allowing companies to develop new business models,

such as personalized, customized products and

services. Enterprises can use these new business

models as a pilot to grasp the concepts, then broaden

the application level and grasp the business

opportunities in the future.

At present, about 60% to 70% of Hong Kong

enterprises are still between "Industry 2.0" and

"Industry 3.0". Although they are widely used in mass

production, they are not fully automated. As more and

more overseas customers implement "Industry 4.0"

and individual elements of "Industry 4.0" are included

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in the procurement requirements, Hong Kong

manufacturers must speed up the upgrade to

"Industry 4.0" in order to maintain their

competitiveness in the international market.

Therefore, "Industry 4.0" is not only a matter of big

international companies but also a topic of concern

for SMEs in Hong Kong.

Hong Kong has a world-class manufacturing base in

the Pearl River Delta. With the global business

network, sound IT infrastructure, and mature service

industry, Hong Kong has sufficient conditions to move

into the development of "Industry 4.0".

Also, the countries have already proposed "Smart

Manufacturing." With the development of this policy,

Hong Kong people in business are exceptionally

qualified to develop in this direction.

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SECTION 3:

Industry 4.0

Maturity

Model

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PRINCIPLE MATURITY MODEL

Maturity models are widely used for the assessment of

companies, technological systems, and engineering

processes. The first concept of maturity was used by

the National Aeronautics and Space Administration

(NASA) for assessing the readiness of components and

modules of flight/space products. Apart from a

technology-oriented point of view, maturity levels can

assess engineering/production processes, such as

Capability Maturity Model Integration (CMMI) or

Software Process Improvement and Capability

Determination (SPICE) models for quality evaluation.

The Fraunhofer-Institute for Production Technology IPT

and the Hong Kong Productivity Council (HKPC),

together with INC Invention Center, a cooperation of

Fraunhofer and RWTH Aachen Campus, have started

introducing Industry 4.0 concepts in Hong Kong since

2016. These approaches fit with the Re-

Industrialization strategy of the HKSAR Government.

The Hong Kong Productivity Council (HKPC) and the

Fraunhofer (IPT) developed a maturity model for

Industry 4.0. On the basis of the suggestions of the

German VDMA and the Acatach, the i4.0 Maturity

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Model Integrated (i4.0 MMI) follows an operational

and hands-on approach fitting to the Market and

Environment in Asia. Furthermore, the i4.0 MMI has

been conducted with various companies and, thus,

outlines a practical view on Industry 4.0.

The Industry 4.0 maturity model for Hong Kong

Industry has had three levels preparing the

implementation of Industry 4.0 (-2 to 0), and four

progressive levels on reaching different Industry 4.0

maturities (1i to 4i). Preparatory levels are essential to

have the infrastructure to implement Industry 4.0, and

the following maturity levels of Industry 4.0 are

essential as each level provides the data and

knowledge needed to start building towards the next

levels.

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Figure 14 Maturity levels of Industry 4.0 (Günther Schuh, 2017)

The application of the Industry 4.0 Maturity Index

within a company, helps to develop tailor-made

digitalization roadmaps for the introduction of Industry

4.0 to transform the company into a learning, agile

organization.

Impact on

development

process

Ind

us

try 4

.0 d

eg

ree

of

ma

turi

ty

Valu

e f

or

the

org

an

izati

on

Transparency Predictability Adaptability

Industry 3.0

What

happens?

Why does it

happen?

What will

happen?

How can an autonomous

reaction succeed?

“See”

“Understand”

“Be prepared”

“Self-optimization”

Visibility

Industry 4.0

Path of development

Enhancement of

data availability

Enhancing

interpretability of

big data

Improvement of

Predictability through

established patterns and

realistic models

Decisions based

on Smart Data

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Agility provides a company with the ability to adapt

rapidly to changing environmental circumstances, and

in the more far-reaching sense even to fundamental

systemic changes, for example regarding the

company's business model. (Günther Schuh, 2017)

Through the introduction and development of Industry

4.0, manufacturing companies are capable to

significantly reduce the period between an event and

an appropriate action. (Günther Schuh, 2017)

The road to Industry 4.0 is individual for each company.

First of all, the individual starting situation must be

identified, analyzed and objectives must be defined.

The introduction of Industry 4.0 represents a significant

expansion of the digital skills and abilities to

manufacture companies and is embracing change in

many parts of the organization. Therefore, a step-by-

step approach has been developed to support the

transformation process within the company by not

radically changing the whole company but slowly

focusing on the most critical aspects. (Günther Schuh,

2017)

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Therefore, in the first step, an analysis of the already

applicable levels is needed, and afterward, a stepwise

approach can be used to reach higher and more

efficient levels of Industry 4.0

In general, there are four questions that support the

identification of the right industry 4.0 level. Starting

with the visibility level that focuses on the question:

“What happens?” It is about seeing the actual data and

enhancing the data availability.

When the next level of industry 4.0 is reached the

following question can be answered “Why does it

happen?” – based on the available data one can

analyse and understand why a specific event occurred.

The next level is already more advanced and includes

the ability to predict. Asking the question “What will

happen?” – if a company is able to answer this question

based on a data set and can prepare themselves for

specific events the level of predictability is reached

which is marked by the improvement of predictability

through established patterns and realistic models.

The so far highest level which can be reached is

adaptability – focusing on self-optimization of

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processes and applications. The leading question of this

level is “How can an autonomous reaction succeed?” –

whereby the decision which is made bases on smart

available data.

In many companies today it is still often the case that

in some areas not even the first question "What

happens?" can really be answered with the help of

collected data or that different levels are reached in

different business areas.

Before proceeding to the next chapter, we will first

describe and subdivide the individual levels in more

detail.

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Not Ready (-2):

The level represents processes from Industry 2.0 and

3.0 predominantly. This means the company uses the

division of labor by an assembly-line work environment.

Eventually, first programmable controllers/logic are

introduced in order to control and automate process

steps.

Computerization (-1):

The first level describes the starting point for the

development path to a real industry 4.0 company and

assesses the basis for digitization, which is the

company's computerization. This Level describes the

isolated use of information technologies. It is already

well advanced in most companies and is primarily used

to perform repetitive activities more efficient. The

computerization represents a considerable benefit: It

enables a low-cost, low-error production and allows for

a precision that allows the manufacturer to produce

many new products.

Nevertheless, companies still have a large number of

machines without a digital interface. These often have

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long lifetimes or are equipped with manual operation.

(Günther Schuh, 2017)

Connectivity (0):

The level represents the basic formation of a company

towards Industry 4.0. The company provides well-

functioning processes in all departments. Engineering

and Production Processes are optimized based on lean

management/production approaches. Manufacturing

processes are simple and can be measured (i. e. less

inventory). A mindset for continuous improvement is

embraced on all levels of the company hierarchy.

Mostly, there is no troubleshooting, and the process

goal can be reached in time with it is according to

quality requirements. The company embraces Industry

4.0 approaches and has a willingness to integrate and

adapt towards best-practices from Industry and

Research.

Real-time information generation (1i):

Sensors can capture processes from beginning to end

with a variety of data points. Processes and states can

no longer only be recorded in individual areas, such as

a production cell, but throughout the entire company

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in real time. The data in the value chain of the company

can be automatically measured by sensor equipment

and provided to a standard and company-wide

database. The data is available in real-time and

acquired without manual labor. The data within the

company is consistent and provides a single source of

truth. The IT-Systems are integrated, vertically, and

horizontally along with the automation pyramid.

A digital shadow of the data already exists

In many cases, the data collected is only made available

to a small group of people who are directly involved in

the process. Further use of the data beyond the specific

process often fails due to system limitations. (Günther

Schuh, 2017)

Real-time information processing and integration (2i):

The following level focuses on the data, which is

aggregated in a company-wide database. The

integration of IT enables data fusion and a common

data set for analytics and forecasts (i. e. predictive

maintenance). In order to recognize and interpret

cause-effect relationships in the digital shadow, it is

necessary to analyze the collected data in the

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respective context and to apply engineering knowledge.

The semantic linking and aggregation of data to

information as well as the associated contextual

classification represent the process knowledge

required to support more complex decisions.

Additional knowledge can be compiled due to

predictions and modeling.

Transparency is generated about specific operational

processes and sequences. (Günther Schuh, 2017)

Integration of cyber-physical systems (3i):

The 3i level enables the forecasting capability to

simulate different future scenarios and identify the

most likely ones. The company uses mobile assistance

systems for making decentralized decisions. The

human-machine interfaces (HMI) are matured in all

processes leading to efficiency and quick response

times for the operators (i. e. in case of emergencies).

Machines and robots are cooperating in order to work

on a standard process step (and goal).

This stage enables companies to anticipate future

events, make timely decisions, and initiate appropriate

response measures.

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Intelligent, autonomous, and self-organized processes

(4i):

For the last level, the forecasting capability is the

prerequisite for automatic action and self-optimization.

Traditional manufacturing transforms towards an

intelligent and autonomous production environment.

Cyber-Physical Systems (CPS) automatically control and

act autonomously. The production has a high degree of

automation, is self-learning and continuously

optimized its processes and products.

The final level is reached when the respective company

can use the data of the digital shadow in such a way

that decisions with the greatest positive effects can be

made autonomously and without human intervention

in the shortest possible time and the resulting

measures implemented.(Günther Schuh, 2017)

For operations, simplified descriptions of these levels

are:

-2 Not ready: Certain fundamentals are not ready, no transparent processes defined

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-1 Computerization: First steps towards digitalization have been done, but the IT landscape is not ready due to lack of basic connectivity

0 Connectivity: Fundamentals to start Industry 4.0 implementation are ready

1i Visibility: Data on all relevant processes is collected in real time throughout the operations

2i Transparency: Data is aggregated and analyzed in real time in such a way that reasons for situations and changes can automatically be found

3i Predictability: The basis of data and knowledge on the cause-and-effect relationships throughout the operations enables predicting relevant situations (maintenance need, order fulfillment times, …)

4i Adaptability: Strong, controlled models for

the behavior of the operations allow

automatic suggestions of decision options

with clear explanations of the implications

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of each option and underlying scenario

analysis

Table 1: Maturity levels (summary description for

testing operations)

In order to provide a valid model and measurement,

the corporate structure is also analyzed and derived

four capability fields: resources, information systems,

culture and organizational structure. Combined, these

design fields represent the structure of the

organization.

Industry 4.0 Capabilities

Each design field is structured by two principles that

guide further development. Each principle bundles

capabilities that - depending on the benefit-oriented

development stages - must be built up successively.

The degree to which the skills are implemented

determines the degree of maturity of the principle.

These Capabilities are the following:

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- Information Systems

- Culture

- Organizational Structure

- Resources

Figure 15 i4.0MC – Industrie 4.0 Maturity Center Analysis

Whereby Information Systems is divided up into the

principles information processing and integration of IT

Systems. The capability culture focuses on the

willingness to change of an organization and the social

collaboration within a company. The next capability

considers the organizational structure of a business

analyzing the dynamic collaboration in value networks

as well as the organic internal organization. Finally

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resources will be analyzed as well considering the

structured communication and the digital capability of

an organization.

The following paragraphs will explore the individual

capabilities in more detail and analyze them.

Information Systems:

First of all, information systems are socio-technical

within which people and information and

communication technologies provide, process, store

and transmit information in accordance with economic

criteria. The design of information systems in

companies is crucial in order to make effective

decisions based on available data and information.

(Günther Schuh, 2017)

The evolvement of the digitalization enables

manufacturers to be able to take real-time data-based

decisions.

The software systems are vertically and horizontally

integrated into the IT-landscape. The digital tools are

interoperable with automatic file transfer/exchange.

The information systems capability is divided by two

principles, the first one concentrates on how the

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information systems process and prepare the data for

decision support. The other principle focuses on the

integration of information systems for improved data

utilization and increased agility.

Figure 16 Overview of information systems capabilities (Günther Schuh,

2017)

As already described by the two principles the

information system capability is divided in two further

aspects.

Information System - Self-learning information

processing

The design of information systems in companies is key

to making effective decisions based on available data

and information. Aggregating different data sources to

build information and provide material to support

decision-making is a main aspect of the decision-

making processes for industry 4.0.

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Only if these aggregated insights are available for the

employees and if these insights are adding value to the

company the full power of the principle can be

achieved. (Günther Schuh, 2017)

Information System integration

The aim of an integrated information system is to

guarantee the usage of universal data along the whole

value chain. This goal must be achieved through

incorporating the different already existing IT Systems

and enabling the combined usage of data. (Günther

Schuh, 2017)(Günther Schuh, 2017)

Figure 17 Optimum characteristics of a company’s information system

(Günther Schuh, 2017)

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An early example for one of the first stages could be the

introduction of Product-Lifecycle-Management (PLM)

software which links data sources from different

discipline-specific systems together.

Organizational Structure:

Enabling a successful technical transformation and

implementation of new technologies strongly depends

on the organizational structure.

The capability consists of the internal organization of a

company in the form of organizational structure and

process organization as well as the positioning of a

company in the value-added network. The

organizational structure defines the necessary rules

and structures to enable collaboration within a

company and externally. The two leading principles are

therefore the organic internal organization and

dynamic collaboration within the value network.

(Günther Schuh, 2017)

Organic internal organization

The organic organization represents the opposite pole

to the mechanistic organization. It is characterized by

minimal control and a high degree of personal

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responsibility on the part of employees. This makes it

particularly suitable for organizations in a dynamic

environment with well-qualified employees. (Günther

Schuh, 2017)

Figure 18 Overview of organizational structure capabilities (Günther

Schuh, 2017)

Dynamic collaboration within the value network

The smooth and automated exchange of information

between companies empowers more dynamic

collaboration and greater market transparency.

Hurdles for flexibility are aspects such as manual

enquiry, ordering and order processing. The

transparency of operational processes can be

significantly extended using current IoT technologies,

for example to the current production status of the

supplier or his quality level. The result is a more

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effective exchange of information, goods and services.

(Günther Schuh, 2017)

Shaping already existing externa cooperation and

networks more effectively is a first step in reaching the

highest level of adaptability.

Figure 19 Optimum characteristics of an organizational structure (Günther

Schuh, 2017)

Resources:

The capability resources are defined as physical,

tangible resources. This includes on one hand the

employees of a company and on the other hand the

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machines and plants, tools, the used material as well as

semi-finished goods and products.

When the workforce is considered a special set of

competences is necessary to generate the maximum

value of all the collected data points. The latency of

data and implementation can be reduced by

appropriate design of the technical resources. These

two described aspects lead to the principles of the

resource capability which are one, the digital capability

and two, the structured communication. (Günther

Schuh, 2017)

Figure 20 Overview of resource capabilities (Günther Schuh, 2017)

Digital capability

The competence digital capability is defined as the

basic requirements for information-based work and

learning – which enable the generation and analysis of

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data. In order to build up this competence, both the

employees must be trained, and the necessary

technical equipment must be adapted.

Structured Communication

The basic prerequisite is the use of communication

technologies to create temporary networks that enable

interaction between resources. Especially in a world

where centralized management resources become

more and more complicated due to the increased size

and complexity of business processes. The creation of

control loops can have a positive effect on the reaction

speed and robustness of business processes. In order

to achieve these goals, it is necessary to bring together

all the actors involved in order to compare the target

systems.

Digital talents are available to drive the transition

towards Industry 4.0. The companies invest in

developing digital skills. The digital strategy and

training are aligned with each other. Product

companies launch employee exchange programs with

digital players.

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Figure 21 Optimum characteristics of resources (Günther Schuh, 2017)

Overall it is important to supplemented existing

competence profiles of employees by extended IT

competence. Technical resources are supplemented

by a data processing layer to extend it to include

connected sensors and actuators and to generate

confirmation data. This are transformed into a digital

system by interaction between resources. There is

communication and interaction between humans and

technical resources as well as among each other in

such a way that both data and information can be

exchanged in real time and all stakeholder groups can

be integrated in the communication. (Günther Schuh,

2017)

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Culture:

The internal culture is an important part of the

introduction of Industry 4.0, because without it the

company will not get the agility it needs. Instead, the

first questions to be clarified are how tomorrow's

internal behaviors should be designed and what skill set

of the employees need. It is only based on these

aspects that technologies can be identified and

introduced that support the desired way of working.

The willingness of employees to continuously change is

one major aspect of the capability of culture. Especially

to adapt and evaluate their own behavior to match the

constant change of the company. Agility is only able to

evolve with the first principle willingness to change of

the employees.

The second principle of culture focuses on the social

collaboration which accelerates the exchange of

knowledge within a company. The target state within a

company is that the workforce actions are led by data

and fact-based knowledge. (Günther Schuh, 2017)

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Figure 22 Overview of culture capabilities (Günther Schuh, 2017)

Willingness to change

Five skills define the principle that employees of

learning, agile companies should master. These skills

should not be viewed in isolation but result from the

interplay of the willingness to change.

These five skills are namely: (Günther Schuh, 2017)

1. Recognize the value of mistakes

2. Openness to innovation

3. Data-based learning and decision-making

4. Continuous professional development

5. Shaping change

Social collaboration

The principle of social collaboration is created by three

skills and these skills accelerate the exchange of

knowledge in the company.

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These three skills are:

1. Democratic leadership style

2. Open communication

3. Confidence in processes and information

systems

Social collaboration occurs in between coworkers with

partners and customers.

Figure 23 Optimum characteristics of culture (Günther Schuh, 2017)

Overall inhabits the company an open mindset towards

IT. The culture empowers digital leaders, rewards

through recognition and compensation, creates a

digital culture, and establishes a digital image for

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recruiting. A digital culture code enables a common

understanding of digitalization for all employees of the

company.

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Section Four

Questionnaire

on Maturity

level of

Industry 4.0

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Questionnaire on Maturity Level of Industry 4.0

On the overall approach, what companies should do to

achieve industry 4.0 and to the benefit of it entirely.

The questionnaire with its assessment is the second

stage as described in Figure 24 Overview what

companies should do? The assessment aims to support

companies in evaluating their situation at first and then

to follow the third step identifying possible solutions

and planning company-specific industry 4.0

development paths. This is done to prepare the step-

by-step transformation to an agile company with an

actual business case behind it.

Figure 24 Overview what companies should do?

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The questionnaire enables a gap analysis to figure out

which processes and departments the company is how

far and in which areas they need the most support and

development to achieve Industry 4.0.

This gap analysis will be achieved through the

evaluation of department and process. The four

different capabilities which were described in section

three of the book will be considered for each

department and analyzed and assessed by the maturity

levels, which were also described in section three. The

usage of the different maturity levels enables a full

assessment of the individual skills and readiness within

a company and more precise within different processes

and departments. The characteristics of individual skills

can vary significantly between individual departments.

Methodology in evaluation

Different industrial sectors differ very strongly in their

process flows, especially discrete manufacturing and

process manufacturing differ strongly. For this reason,

the assessment and, the questionnaire are individually

adapted.

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In the first step, the departments and processes to be

evaluated are first recorded and the general

questionnaire and assessment areas will be adjusted to

the specific needs of the company.

Figure 25 Exemplary Process and Department Overview

Figure 25 is an overview of the different departments

and production processes which will be evaluated and

adapted. Only if a high level of industry 4.0 capabilities

is achieved within every area of the company, it is

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possible to gain the full benefit of the Industry 4. 0

implementations.

After the actual processes and departments for each

company are aligned the questionnaire will be adapted.

Thereby questions for each department, are adapted to

the individual capabilities.

In the following, the questions are assessed by experts

and/or consultants from the area of Industry 4.0 on-site

at the company’s production facilities. Due to their

experience within different industries and countries,

they have a broad understanding of Industrie 4.0 levels

an maturity.

On-site at the different production facilities of the

company, it is necessary to conduct workshops with all

departments. This workshop will enable the experts to

get an understanding of the individual maturity level

within each capability of each department.

The workshop follows a standard, proven procedure

and includes following stated agenda topics:

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Current Situation: Please outline the current

situation in the department and elaborate on

your expectations.

Challenges: Please explain current problems and

difficulties in your department.

Wish List: Please state wishes or improvements

for your department.

Industry 4.0: Please outline your strategic

perspective on Industry 4.0 (i. e. business plan,

human resources)

Questionnaire: The questions for each of the

capabilities within the different processes and

departments are assessed by the

consultant/expert.

Additional interviews and guided tours with the

relevant key contacts and stakeholders of each

department need to be scheduled.

The questionnaires questions focus on the maturity

level of each of the four different capabilities and

principles. The capabilities will be evaluated within

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each department, and in the end, there will also be an

overall score given for the whole company.

Sample Questions

In total, the questionnaire contains 160 questions for

characterizing the readiness of the company for

Industry 4.0. 10-20 leading questions support each

capability. The degree of implementation is equivalent

to the level of maturity in the I4.0 MMI.

In the following, an overview of some of the questions

for different departments at different levels is given:

Considering the supply chain process, one question for

the capability information systems with the principle

information processing could be:

- Within the supply chain management, are there

any data analysis methods being used?

Based on the answer to this question and the extent to

which the data is used, the ability is then assessed and

classified using the maturity level. The question arises:

Are the data only visible (level i1)- or will the data even

be used for prediction (level i3).

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Another exemplary questions in the area of supply

chain management related to the capability

information system could be:

- Do the employees have an overview of the

process interdependence of the whole company

and consider these influences?

This question focuses on the second principle of the

information system capability –digital capability. Due

to the answers given by the interviewed people, the

examinations and consultants will be able to rank the

particular maturity level.

Considering the next capability – resources whit its two

principles, there are also different questions for each

department. The two following ones are exemplary

questions for production assembly.

- How do the employees communicate with each

other? Do they use special supporting tools?

- Is the production process vertically and

horizontally integrated into the company?

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The first question aims to get a better understanding of

the communication structure and how advanced the

communication processes are – focusing on the

principle of structured communication.

The second question seeks to get a better knowledge

of the maturity of the IT systems and their integration

– concentrating on the principle of integration of IT

systems.

In order to give an example of quality control issues, we

evaluated the competence of the department in the

area of organizational structure.

The first question which focuses on the organic internal

organization – whereby the maturity can be defined

asks.

- How does the cooperation between the

coworkers look like? Are there any defining rules

and regulations for it?

Another representative question focuses on the

dynamic collaboration in value networks – especially

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considering the impact in external networks or

cooperation.

- Are the core competencies of the company

known and understood?

After all, also model questions for the capability culture

will be given for the production planning department.

The first questions consider especially the willingness

to change of the employees.

- How are mistakes dealt with in the department,

is there such a thing as a culture of mistakes?

The second question targets the social collaboration

within the department of production planning by

asking for the willingness to use already existing IT

systems.

In summary the examiner will be asking questions for

each of the described capacities and principles in each

department.

The aim of all the different interviews is getting

detailed overview about challenges, mindset,

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capabilities and collaboration mode of each

department.

Figure 4 Summary of possible questions asked per department

The themes and topics which are covered in Figure 4

give an additional overview of questions asked during

the assessment at each department.

Meaning of the scale

When the questionnaire is completed, and the

assessment finished an overall score and scale can be

developed, based on the answers given as well as the

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observed actions and interactions an i4.0 level will be

submitted for each question.

Afterwards individual scores for the capabilities within

the department will be given, followed by the

generation of an overall score for the department –

using the average score of all the question for one

capacity. This will lead then to the possibility to also

rate the average level of a complete company.

The scale which is used for the assessment bases on the

maturity levels which were described in section three.

An overview of the different level which are used for

the scale can be found in Figure 6.

In order to realize great improvements and profits, the

goal must be to achieve predictability and adaptability

in most areas.

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Figure 5 Overview of the industry 4.0 maturity scale

As in Figure 6 shown the scale of maturity assessment

show on the one hand the targeted level of industry 4.0

maturity of a company – indicated by a green dot and

on the other side the actual achieved level of maturity

– indicated by a red dot. In-between the two dots a grey

area can be found which indicated the maturity gap

which has so be minimized through to initiative and

actions to actually reach the targeted Industry 4.0 Level

in each department.

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Figure 6 Exemplary result and scale overview

Assessment result overview

The overall assessment result will be presented with

the overall maturity assessment and gap analysis

versus the target maturity.

The overview information includes:

Detailed assessment results for main processes

(production, products/services, etc.)

The overall maturity in different areas versus the

target maturity is detailed with specific

improvement recommendations

Frameworkconditions

Smart Solutions

Smart Innovation

SmartNetworks

SmartProduction

Business model

Smart products

Focus areas

Smart services

Agile innovation

Digitalized processes

Agile collaboration

Connected supply chains

Decentral production

Data driven excellence

New digital business models

Category

Resources

Strategy

Culture

IT

Framework

0i

Visibility

1i

Transparency

2i

Predictability

3i

Adaptability

4i

Maturity LevelIndustrie 4.0

Goal Current Gap

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Figure 26 Exemplary Overall Industry 4.0 Maturity

These results can be used to focus resources on most

important challenges and are a tool for department

heads and the overall Industry 4.0 team to improve

challenges and use opportunities.

These results help to focus attention on challenges in

individual departments and often include digitalizing

information collected manually and using already

available data for improvements.

Approaches to the next steps after the assessment

usually include:

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A roadmap to start the implementation of

necessary infrastructure as well as processes for

Industry 4.0 implementation

A suggested organizational structure and basic

strategic framework to enable integrating the

Industry 4.0 transformation into the organization

and ensure that the process is understood and

supported by all departments

A list of pilot projects clustered by improvement

areas to start the implementation of Industry 4.0

across the organization