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CRANFIELD UNIVERSITY
Marco Pugi
Development of a model for the integration of the factor “human” in factory planning
Cranfield University RWTH Aachen University
Università di Pisa Engineering and Management of Manufacturing Systems
MSc Academic Year: 2015 - 2016
Supervisors: Dr Konstantinos Salonitis Mr Matthias Dannapfel
Dr Gino Dini
CRANFIELD UNIVERSITY
Cranfield University Università di Pisa
MSc Engineering and Management of Manufacturing Systems Engineering Management
MSc Double Degree Programme
Academic Year 2015 - 2016
Marco Pugi
Development of a model for the integration of the factor “human” in factory planning
Supervisor: Dr Konstantinos Salonitis Mr Matthias Dannapfel
Dr Gino Dini
This thesis is submitted in partial fulfilment of the requirements for the degree of MSc Engineering and Management of Manufacturing Systems © Cranfield University 2015/2016. All rights reserved. No part of this publication may be reproduced without the written permission of the
copyright owner.
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To my mom and dad, landmark of my life.
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ABSTRACT
Nowadays factory planning has to face a turbulent environment due to changes in
customer demand and rules of competition. Thus, there is a growing need for
responsiveness, rapidity and predictability of the outcome in the planning stage. This
can be obtained only if the planner is fully integrated with the system and is able to
“turn the route “ promptly.
The aim of this work is supporting manufacturing industry to facilitate the full
integration of the planning team with factory planning processes in order to minimise
the variability of the expected output of the project, which is introduced by the
involvement of the human factor. This variability can affect the desired outcome
because it induces uncertainty.
“Factory planning project is not a black box as well as human factor is not a
machine”.
The trigger of the study is an evident lack of a holistic approach in the planning stage
due to a widespread “watertight compartments view” which avoids the integration of
each factory planning area with the system and mainly with the brain, the planner.
Accordingly, The innovation of this study is contained in the ability of providing a
comprehensive approach to avoid local optimisations and detachment of planning
decision points within compartments. Another key aspect is the analysis that derives
from the awareness that it’s impossible to achieve synergy between planner and
system just considering technical aspects and neglecting the human and
psychological ones.
The outcome of the research is a set of structured methodologies and a qualitative
model with the aim of avoiding local optimisations and supporting the planner in the
decision making process. Human issue cannot be ignored without huge benefits
reduction in the production system.
Keywords: Team Selection, Conflict Management, Virtual Production Planning,
System Integration, Collaborative Based Factory Planning, Motivation strategy,
Competency development programme, Project Management.
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ACKNOWLEDGEMENTS
The SATM Department of Cranfield University, the factory planning department
of WZL RWTH Aachen University and the DICI department of Università di
Pisa, support this work.
I would like to reach with this section all the people around me that have made
this achievement possible, unfortunately I cannot list everybody here.
I want to express my deepest thankfulness to Borgo de’ Medici srl, Borgo de’ Medici USA Srl, Gucci spa and Amazon Italia for their valuable help and
information. The availability and cordiality of their teams have brought great
value to the research during the model development and the validation stages.
My special gratitude is for my supervisor Dr Konstantinos Salonitis for the
valuable and constant direction that have driven successfully this work, Mr Matthias Dannapfel for the introduction in this field of study and for the
continuous feedback, Dr Gino Dini for the support and availability.
Finally, I would like to thank Matteo Pugi, Borgo de’ Medici’s finance and
planning manager for the help in the validation phase of the model.
Apart from all the people already listed, I want to acknowledge my colleague
and friend Gael Masullo for his invaluable collaboration and help in the
development of the literature review database.
Last but not least, I would like to express my gratitude to my father Mauro for
his invisible support during my projects and challenges.
Cranfield, September 2016
Marco Pugi
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TABLE OF CONTENTS
ABSTRACT ................................................................................................................................ III
ACKNOWLEDGEMENTS ............................................................................................................ IV
LIST OF ABBREVIATIONS .......................................................................................................... VII
1 INTRODUCTION .................................................................................................................... 10
1.1 RESEARCH BACKGROUND ................................................................................................................ 10
1.2 VISION, RESEARCH OBJECTIVES AND QUESTIONS .................................................................................. 12
1.3 GAP ANALYSIS ............................................................................................................................... 15
2 RESEARCH METHODOLOGY .................................................................................................. 16
2.1 SCIENTIFIC APPROACH .................................................................................................................... 16
2.2 RESEARCH METHOD ....................................................................................................................... 16
3 FACTORY PLANNING AND HHFI MODEL ................................................................................ 19
3.1 MODEL OVERVIEW ......................................................................................................................... 19
3.2 ADAPTABILITY ............................................................................................................................... 22
3.2.1 Team Selection And Management ......................................................................................... 23
3.2.2 Factory Planning Methodology Selection .............................................................................. 36
3.2.3 Technology Support ............................................................................................................... 38
3.3 REPEATABILITY .............................................................................................................................. 43
3.3.1 Motivation Strategy ............................................................................................................... 44
3.4 RESPONSIVENESS ........................................................................................................................... 53
3.4.1 System Integration ................................................................................................................. 54
3.5 PREDICTABILITY & CONTROLLABILITY ................................................................................................. 56
4 VALIDATION & FUTURE IMPROVEMENTS ............................................................................. 57
4.1 VALIDATION .................................................................................................................................. 57
4.2 FUTURE IMPROVEMENTS ................................................................................................................. 60
5 CONCLUSION ........................................................................................................................ 62
6 APPENDIX ............................................................................................................................ 64
6.1 A1-‐BELBIN’S REPORT ..................................................................................................................... 64
6.2 A2 – VOICEPRINT REPORT ............................................................................................................... 70
6.3 A3 – PROJECT MANAGEMENT: PMP AND PRINCE2 ............................................................................. 79
7 BIBLIOGRAPHY ..................................................................................................................... 82
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LIST OF FIGURES
FIGURE 1 INTERNAL AND EXTERNAL CHANGE DRIVERS ................................................... 11
FIGURE 2 RESEARCH FRAMEWORKS ................................................................................. 17
FIGURE 3 RESEARCH METHOD’S SUB-‐TASKS .................................................................... 18
FIGURE 4 PLANNING PROJECT .......................................................................................... 19
FIGURE 5 HHFI MODEL ..................................................................................................... 21
FIGURE 6 TEAM SELECTION AND MANAGEMENT PROCESS ............................................. 23
FIGURE 7 FACTORY PLANNING KEY ROLES INVOLVED ...................................................... 24
FIGURE 8 BELBIN'S TEAM ROLES ...................................................................................... 26
FIGURE 9 BELBIN'S MODEL CATEGORIES .......................................................................... 27
FIGURE 10 BELBIN'S REPORT EXTRACT ............................................................................. 28
FIGURE 11 THE 9 VOICEPRINT'S VOICES ........................................................................... 29
FIGURE 12 VOICEPRINT OVERALL SHAPE .......................................................................... 30
FIGURE 13 VOICEPRINT PREFERENCES ............................................................................. 31
FIGURE 14 INTERNATIONAL MANAGEMENT’S TRAPS ...................................................... 32
FIGURE 15 FOSTERING THE ABILITY OF WORKING TOGETHER ......................................... 34
FIGURE 16 SCENARIO TECHNIQUE .................................................................................... 35
FIGURE 17 PLANNING MODULES ...................................................................................... 36
FIGURE 18 PLANNING TOOLS IN DIGITAL FACTORY ......................................................... 38
FIGURE 19 FP TECHNOLOGIES .......................................................................................... 42
FIGURE 20 PORTER AND LAWLER'S MODEL ..................................................................... 45
FIGURE 21 COMPETENCE FRAMEWORK ........................................................................... 47
FIGURE 22 INCENTIVES OPTIONS ...................................................................................... 51
FIGURE 23 VPI LOGIC ........................................................................................................ 55
FIGURE 24 VALIDATION PROCESS ..................................................................................... 59
FIGURE 25 FUTURE IMPROVEMENTS ............................................................................... 60
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LIST OF ABBREVIATIONS
BdM CAD CBFP DF DICI FP HHFIM IEA IT OLAP PM PMI PMP PRINCE2 PTC RWTH Srl SW UK US USA VDI VPI VR WZL 2D 3D
Borgo de’ Medici Computer-Aided Drafting Collaborative Based Factory Planning Digital Factory Dipartimento di ingegneria civile ed industriale Factory Planning Holistic Human Factor Integration Model International Ergonomics Association Information Technology On-line Analytical Processing Project Management Project Management Institute Project Management Professional Projects IN Controlled Environments 2 Parametric Technology Corporation Rheinisch-Westfälische Technische Hochschule Società a Responsabilità Limitata Software United Kingdom United States United States of America Verein Deutscher Ingenieure Virtual Production Intelligence Virtual Reality Werkzeugmaschinenlabor 2 Dimensions 3 Dimensions
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1 INTRODUCTION
1.1 Research Background
Actually companies are facing various challenges due to a lack of a
systematic and structured way to run factory-planning projects. Moreover,
there is an old-fashion vision of factory planning, which too often considers
it like a black box. This kind of perspective implies to take into account
only required input and desired output and to ignore other types of
relationships and complexities. While the organisation is influenced by
external change factors that raise new challenging requirements, the
planner gropes in the dark because of the lack of a defined set of
procedures, methodologies and tools for facing the change. Furthermore,
most of the areas of interest of Factory Planning research are analysed
individually without identifying links and relations among them. This
obsolete approach is called “watertight compartments view”.
Factory planning is a relatively modern field of study and the effort in the
research has strongly increased over the time in the last two decades but
a holistic point of view is still missing. As shown in Figure 1, Companies
are struggling to satisfy the customer demand because of several change
drivers that have increased the turbulence in the market. This turbulence
asks for the development of factory planning projects with high level of
flexibility, responsiveness, re-configurability and predictability of the
output. It can be achieved only if there is a full integration and compatibility
within the human factor, the systems in place and the planning process.
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Figure 1 Internal and External Change Drivers
The most critical resource in FP is the brain, the planner. Very often the
factor “human” is considered as such a core element. If human aspects
are ignored, the system takes the risk of not achieving the optimal
performance.
The International Ergonomics Association (IEA) has defined human factor research as “understanding of interactions among humans and other
elements of a system in order to optimize human well being and overall
system performance” (IEA Council, 2000). In the recent past, the planner
is ignored or taken into account too late in the FP process, making the
great majority of planning choices difficult to modify. There are critical
challenges in the integration of the human factor in FP because of the
incredible variability in individual competence and skills and the way of
behave in team contexts.
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1.2 Vision, Research Objectives and Questions
This study sets the aim of achieving a structured approach to integrate the
key resource of the plant, the planner, in the factory planning process. The
developed model explores in a systemic way all the core areas for the
planning process in order to minimize the output variability due to
incompatibility between human factor and system. This goal can be
achieved analysing the problem mainly from two different perspectives:
• Methodological point of view: taking into account which tools are
needed, which factory planning methodologies deserve to be chosen on
the basis of the advantages they bring and which support programmes are
needed to keep high standards of human resources’ performances.
• Psychological point of view: considering the variability introduced
inside the system by the planner in terms of individual attitude and skills,
competences and experience and how to avoid conflicts and find
synergies.
The research strives for answering unexplored dilemmas in a structured
way with the ambitious goal of replacing every single and not
comprehensive company approach. The boundary of the research can be
highlighted from the following questions:
1. Can human factor introduce a degree of variability in the factory planning process if not supported with a systemic and comprehensive approach (tools, methodologies…)?
The current perception, which is widespread in industry, is to consider
factory-planning projects like black boxes, so the prime focus deserves to
be on required inputs (as software, labour hours, human resources…) and
the desired outputs (deliverables). Ignoring the level of complexity of
human relationships, conflicts management and individual attitudes,
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organisations take the risks of project delays, budget overruns and
unsatisfying results.
2. How can I ensure the effectiveness of factory-planning projects’ results and increase the predictability of the output?
The variability needs to be managed and mitigated. This study aims to
provide a model that supports the human factor integration in the system
by managing planning critical areas. From this research perspective “Full
integration with the system” means: “complete availability of tools,
methodologies, resources and programmes in a holistic approach which
takes into account requirements and constraints of each area and avoids
local optimisations”. For example, nowadays the planner, because of a
lack of a big picture, makes decisions about planning methodologies
without considering the integrative information model managing all data
which are contained in the project. Furthermore, planning team is built
regardless the resources composition and without a clear programme to
sustain its performance is very common in industry. This kind of “watertight
compartments view” which induces to make decision considering all the
planning areas as isolated and ignoring the interfaces among them
introduces variability.
This research wants to emulate what was made for the Toyota’s House of
Quality in manufacturing industry:
• Identifying the most critical planning areas
• Presenting and discussing the most relevant decision points
• Providing a model and a set of tools/methodologies to achieve satisfying
results in each area.
3. What is the focus of the research in a vast and not so much explored field like factory planning?
The focus of this research is on the psychological and human aspects
rather than technical and “hard” ones. This work aims to produce an
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integrated model to achieve the full involvement of the planner in project
by listing and describing the most important technical areas (like
technology support, planning methodology) but going through the ones
based on a “soft” and “human-based” analysis (like team management,
conflict management, motivation, career expectations) that are neglected
by the current literature.
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1.3 Gap Analysis
The triggers of this research are some gaps easily identifiable in factory
planning literature that we have decided to face in a holistic way.
1. Factory planning main areas are analysed and debated separately like watertight compartments. The lack of a holistic approach may sacrifice global effectiveness for local optimisation.
Literature about Factory Planning spreads across several different areas
of interest like information management, planning methodologies,
technology and planning tools. However, actually no academic study has
elaborated a holistic and interconnected work, which establishes the
relationships and the criticalities derived from those areas. How an event
that affects one area may affect the others. Current literature doesn’t offer
guidelines for finding synergies, for example the planning methodology
(0+5+X, CBFP) is selected regardless the team members, the SW tools
available, the size or the structure rigidity of the organisation. One decision
in a specific area could affect negatively the global efficiency of the system
and generate sub-optimisations. This research wants to add a systemic
perspective of factory planning besides the stand-alone one.
2. The importance of human factor integration and anthropological aspects like conflict management and collaborative interactions are almost completely ignored.
Factory planning literature involves mainly technical aspects regardless
the importance of the variable “Human” in terms of individual attitude,
skills, competence, experience, work approach and what is needed for a
full and natural integration with the system. The innovative aspect of this
research is to consider human resources (the planning team) “pivot” of the
whole factory-planning project.
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2 Research Methodology
2.1 Scientific Approach
Very often in manufacturing engineering it is hard to identify and to adopt
effectively one scientific methodology and rigorously respect it. The main
reason why the partnership between academia and industry is solid:
research has to be profitable and has to develop concrete aspects.
In addition, a second layer of complexity is introduced by the psychological
and anthropological research approach. Factory planning is a process
within a socio-technical system composed by infrastructure, technology,
procedure but also people, expectations, skills and hierarchy. In the end it
is almost impossible to apply a methodology and faithfully follow it.
However, G. Sohlenius has developed the paradigm “Science of
engineering” which takes inspiration from Theodore von Karma and his
statement:
“The scientist explores what is, the engineer creates what has never been”
This paradigm allows researchers to adopt a flexible methodology to
proceed in the study. In the next paragraph there is a brief explanation of
the methodology and how it has been adapted for this research.
2.2 Research Method
The framework for the development of the research is shown in figure 2
and broken down into specific sub-tasks in figure 3. The science of engineering method is the criteria at the base of this research study. A
brief explanation of each step is highlighted below:
• Analyse what is: collecting information, developing a big picture of the
problem, identifying criticalities and areas of improvement, evaluating the
applicability of state-of-art methodologies and industrial best practices,
trying to identify the TO-BE scenario and the vital requirements to arrive
there.
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• Imagine what should be: based on the development of a “vision for a
better future, clear identification and structure of requirements, exploration
of applicability of existing standards, suggestions about areas integration.
• Create what has never been: The development of the model for the
integration of human factor and support methodologies for each specific
area of interest.
• Analyse the result of the creation: Verifying results, validating the
model from industrial experts and identifying gaps and needs for future
improvements.
Figure 2 Research Frameworks
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Figure 3 Research Method’s sub-tasks
During the phase of Information collection and Model validation three
multinational companies of different size have been interviewed and
visited in order to bring value and dependability to the research. The
basement of this research is the joint support of academia with the
opinions of the industrial experts.
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3 Factory Planning and HHFI model
3.1 Model Overview
According to factory planning manual of Michael Schenk, Planning and
innovation of manufacturing plants can be translated in “envisioning”
production process in advance. This perspective of factory planning
involves tools that effectively design the planning process. A systemic,
holistic and structured approach is influenced by situation-driven decisions
and it should support the development of a planning project through the
management of direct and indirect planning activities.
Project Design reflects a creative design activity that uses prepared
technical building blocks/modules (components, assemblies, individual
systems, etc.) and organisational solutions to design, dimension, structure
and configure a user-friendly technical unit (device, machine, plant,
building, manufacturing plant, etc.). The output is a planning project that
involves the development of the building of manufacturing plants and it is
an input for it in the first phases of factory planning. Figure 4 shows
planning project’s features in detail.
Figure 4 Planning project
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Due to the turbulence of the market and the speed at which factors
influence factory change, a plant or even a network can lose
competitiveness and become a stagnant factory. This is the main risk for a
manufacturing organisation and it happens when a complex organisational
body has been structured over the time and relies on tradition and
complacency. Hierarchical levels are numerous and strictly separated with
a precise definition of tasks and roles. Employee contribution in terms of
creativity and participation is not considered as essential and the salary
system relies only on output rather than results. The attention is on the
functional optimization of commercial, design and manufacturing areas. As
a result decision-making process is not responsive and fast. This situation
may highlight a lack of a propensity for long-term goals, for innovation,
systems harmonisation, complacency and mainly for human factor
integration.
The model developed is called Holistic Human Factor Integration Model (HHFI) and it is the first effort in the whole factory planning literature in:
• Identifying and discussing critical areas of interest for the full integration
of the human factor with factory planning processes, procedures, tools in
other words with the system.
• Providing a comprehensive set of methodologies for the decision making
process in “soft” areas like conflict management and team selection.
• Highlighting the importance of fitting the project out with strategic
attributes and showing how to pursue them. The model is based on the
idea that the planner can be integrated in the project only if the project
itself stands on solid pillars:
1. Adaptability & Flexibility 2. Responsiveness 3. Predictability and controllability 4. Repeatability
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Each pillar is broken down into some critical decision areas and the
planner needs a set of structured methodologies to support the decision
making process in each of these areas. Figure 3 shows the HHFIM model.
Figure 5 HHFI Model
The following sections will explain the importance of each attribute (pillar)
and the most critical decision points to take into account. Some areas are
common for every type of project; on the contrary other areas are specific
for factory planning projects. Even if the focus of the planner has to be
constant on all of these areas, this research doesn’t aim to replace
manuals of factory planning, so each area will concern only particular key
aspects not already discussed in literature rather than a generic
explanation.
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3.2 Adaptability
The first area of interest for the full integration of the human factor
concerns the ability of the project itself to change its features and structure
on the basis of the manifestation of external events. Adaptability is defined
as “the ability of exchange, remove, adjust or add parts of the
manufacturing resources after the manifestation of an external event or a
change driver. In other words, adaptability shows the potential of putting in
place reactive or proactive solutions with little expanses at several
hierarchical levels.” The pillars of adaptability are modularity, scalability,
compatibility and integration.
This research validates the vision that a project can achieve adaptability
only if well-manages and takes effective decisions in 3 key areas of
interest:
1. Team Selection and Management: This area relies on the idea
of compatibility. An adaptable project needs the right human resources
with the right skills and attitude and a structured methodology to make the
team integrated with the project.
2. Factory Planning Methodology selection: this area is based on
the ideas of modularity and scalability. The newest factory planning
methodology called Collaborative Based Factory Planning (CBFP) is a
modular framework able to allocate every piece of project to the most
suitable team or person. “The right task to the most suitable partner”.
3. Technology support: in the era of industry 4.0, simulation, virtual
and augmented realities have gained core relevance for factory planning.
This paragraph establishes a link between expectations and output,
planner and tools, human and factory planning. The planner cannot
envision in advance future development and anticipate obstacles without
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the necessary equipment. The ability of turning the route promptly needs
more and more cutting-edge technologies.
3.2.1 Team Selection And Management
The effective management of the planning team involves aspects like
team selection and conflict management. This research wants to proof
that the full human factor integration in the factory planning process is
possible only if the right person operates in the right team and receives the
right and adequate support from the management and the organisation
itself. A theoretical framework has been developed in order to guide the
management in the right direction. As shown in figure 6, each step aims to
recommend also some specific tools in order to make the process the
most effective possible.
Figure 6 Team selection and Management process
Team selection methodology concerns 3 key steps:
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1. (Requirements Definition) Professional profiles & qualifying skills: the first step in the team selection phase is the requirements
definition. The management needs to identify the most desirable
professional profiles for the accomplishment of the project. Figure 7 shows
the most common characters involved in factory planning projects.
Figure 7 Factory Planning key roles involved
On the basis of the project features the management has to select
• Number of teams
• Size of the team
• Hierarchical relationships and organisation of the team
• External support (consultants)
• Points of contact with the rest of the organisation (interfaces)
• Ownership and responsibilities (approvals)
• The key roles involved
• The skills required for the full achievement of the tasks.
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As well as the first 7 choices rely mostly on management’s experience; the
last decision point “The skills required for the full achievement of the tasks”
needs a deeper way of exploration. The first step is the identification of the
skills classis.
• Worker skills include communication skills, leadership skills, listening
skills, management skills, planning skills, problem-solving skills, teamwork
skills, and technical work skills.
• Personal attributes include worker calm, clear thoughts, constructive,
creative, dynamic, educated, efficient, energetic, focused, healthy,
intelligent, integrity, knowledgeable, organized, previous success in work,
relationship with others, responsible, seek improvement, and strong.
In order to assess the level of the skills, a special self-questionnaire needs
to be structured and validated. Each questionnaire will be matched with a
checklist developed before the selection phase.
2. (Assessment) Individual attitude: The second step starts from
the idea behind the Belbin’s model that a competitive team needs to be
well balanced differentiating the roles within the members. The individual
role is defined on the basis of the natural and instinctive way of behaving
of a person, in other words a team role is defined as “a tendency to
behave, contribute and interrelate with others in a particular way”. Every
team needs to be formed by the highest number of different roles. The
differentiation of the roles mitigates the outcome variation due to the
introduction of the human factor in the planning process. Every extremist
or one-direction behaviours are limited by the different points of view of the
other team partners. According to the Belbin’s model each human being is
characterized by a different way of behave in team working. As shown in
figure 8, Belbin has identified and described 9 characters that comprehend
the great majority of people behaviours during teamwork.
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Figure 8 Belbin's Team Roles
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As shown in figure 8 and 9 each team roles belongs to a specific category
of behaviour:
Task oriented roles: they are prone to accomplish the task the better and
the faster regardless to people feelings and creativity
People oriented roles: the focus is mainly on coordination and support of
the team members. The achievement of the task needs to take care of
people’s feelings. Ideas Oriented Roles: Creativity is the key concept. Who belongs to this
category shows to be innovation oriented and idea-generators. Sometimes
they lack of judgement about practicality of their ideas.
Figure 9 Belbin's Model Categories
The issue that needs to be addressed is how to link every potential team
member with his related Belbin’s character. Belbin website provides an
online questionnaire that needs to be filled by each potential team member
and in the end generates a report with an extensive description of your
individual attitude and tendencies. This material can bring huge benefits
during the team structure also called “Phase 0”.
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Figure 10 shows an extract of the final output contained in the report with
a bar diagram that highlights the roles in order of preference for the user.
This analysis is based on self-perception only. In appendix A-1 is shown
an example of the report.
Figure 10 Belbin's report extract
This type of analysis is suitable for every type of organisation because of
its high level of scalability. It provides an effective approach to set well
balanced teams and it can be considered the first proactive intervention to
avoid conflicts and delays.
3. (Configuration) Communication and integration
The last step in the team selection involves the potentiality of the
integration within the team. This section concerns mainly 2 areas:
v Completeness of communication repertoire
According to Voiceprint’s point of view, Talk is action. How we
communicate to partners – the content and the manner – implies instant
and long-lasting consequences. It may strongly affect people’s thought,
feelings and behaviour. The focus on this aspect becomes vital in team
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management roles or in team relationships. The core criticality is the lack
of attention in the communication. Speech can often be unintended,
undesirable and unproductive. Voiceprint investigates the way people
adopt 9 distinctive modes of expression or “voices” (shown in figure 11).
Sooner or later all of these voices need to be adopted for an effective
development of the job, primarily in team contexts.
Again the team needs to be well balanced in terms of proficiency of the 9
voices. High level of expertise in the use of the whole repertoire is an
additional effort in avoiding conflicts within the members.
Figure 11 The 9 Voiceprint's voices
The VoicePrint questionnaire defines the self-perceptive portrait of how
individuals use the 9 voices, in other words the way people see
themselves adopting the 9 voices. This self-perception report is an
indication of the shape and completeness of the repertoire, whether
people rely on some voices more than others and whether the approach
changes under pressure. The report is designed to give a structure for
some initial self-reflection, but is certainly not intended to be a substitute
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for an interpretive conversation with a trained and accredited Voiceprint
consultant. The results and the trends are just a starting point for an
introspective analysis and for the understanding the importance in practice
of the repertoire completeness in teamwork. Facilitated exploration is
therefore the best way to explore and contextualise the patterns in
individual distinctive VoicePrint, achieving the awareness of the effects
and consequences of the way you adopt the voices, and concentrating the
efforts in the improvement of the proficiency in the management of this
important collaborative competence. Appendix A-2 provides an example
of the Voiceprint questionnaire report.
The output of the questionnaire is composed by 2 analyses:
This first diagram shown in figure 12 highlights the overall shape of your
VoicePrint. It provides a qualitative representation of the level of the voices
to which the person relies on or use to adopt more frequently.
Figure 12 Voiceprint overall shape
This second diagram, shown in figure 13, ranks your (self-reported) use of
the modes from most to least. The team members can gain benefits
thinking about and reflecting on the patterns. The figure can even give a
brief overview of the individual way of approaching conversations, since
most of the times people start with the most proficient voice and then shift
to other voices of the repertoire. This way of interpreting the individual
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portrait could even provide to the team member insights into his internal
dialogue and the thinking process features.
Figure 13 Voiceprint preferences
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v Cultural factors & Conflict management
Since very often partners of the same team are not trained to perform
outside their cultural boundaries, they need to concentrate their attention
on cultural factors (values, behaviours and beliefs). Neglecting these
aspects may affect integration of the planning team and the achievement
of the optimal result. Furthermore, this challenge can be converted into
benefit taking advantage from diversity intelligently. Figure 14 highlights
the process that can bring the team partner to fall into the similarity or
suspicion traps.
Figure 14 International Management’s Traps
Cultural impact can be broken down mainly into 3 key aspects:
• Political: involves the influence of the educational and legal systems on
culture.
• Sociological: includes religion and people’s belief
• Psychological: highlights the influencing process of our minds when
operating in the political and sociological surroundings.
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Logically, one culture can be defined as the collective programming of the
mind. According to current researches, we can identify seven dichotomies,
which are like decision points. The way of finding a solution for these
dichotomies differentiates the cultures:
• The universal truth versus the particular instance.
• Individualism versus collectivism.
• Affective versus neutral relationships.
• Specific versus diffuse cultures.
• Achievement versus ascription.
• Past, present or future orientation.
• External versus internal control (nature orientation).
Collaboration within international teams is likely to be influences by the
way of facing these dichotomies.
The greatest majority of differences in FP project rise mainly at 2 levels:
• The method of work: The work approach gap can be identified in the
planning and coordination stages. The cultural impact is caused by the
different solutions of the dichotomies of individualism versus collectivism
and neutral versus affective relationships.
• The Preferences in design: Very often, can be identified a limited
consensus within team partners of different cultures
The failure in fostering a collaboration spirit can be partially mitigated
adopting a very common strategy: Dividing the task in multiple sections
and split each of them to every single team member. This makes every
member responsible for his part and avoids conflicts. Clearly, in this case
the quality of the output it is likely to be lower because the result achieved
taking advantage of the diversity is greater that the sum of the single parts.
Another option is to try to create a joint vision by investing in sustainable reconciliation. In order to reach integration and consensus, a method of
fostering the ability to work together have been developed by creating a
joint vision of the system under design. The collaborative vision supports
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the process of selecting the most suitable methodology, i.e. methods of
work and preferences in design. The logical consequence is that the
factory planning team can take benefit of diversity. Figure 15 shows a
model for developing the competence of working together.
Figure 15 Fostering the ability of working together
Another valuable tools is the Pest analysis. It is commonly used for
investments abroad in order to be able to take into consideration all
external drivers like tributary system, legislation, religion, exchange rates,
government stability and so on that can affect the decision. This tool has
been converted currently to anticipate conflicts in teams. It analyses in
advance all the critical aspects related to a joint collaboration of team
partners with different background and cultures. The outcome of this tool is
a detailed report on the most critical Political, Economic, Social and
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Technological factors that deserve to be managed in order to avoid future
conflicts.
This research recommends also the adoption of a very common tool called
Scenario Technique in order to foster the required joint vision. The
technique is an established tool with clear directives for practice and has
high acceptance in industry. Providing beside quantitative analysis also
assistance in the development of the prediction of every team member of
future events. The final goal is to convert individual knowledge and
perception in a shared strategy. Figure 16 shows the scenario technique’s
phases.
The reconciliation scenario technique gathers the preferences,
expectations and policies of different partners in order to provide a joint
vision of the project. In international factory planning the scenario
technique is not only a tool for systematically developing complex
expectations of the future but is also a method for dealing with group
dynamics in teams.
Figure 16 Scenario Technique
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3.2.2 Factory Planning Methodology Selection
Condition Based Factory Planning (CBFP) is a modular, parallel planning
methodology, which can be reconfigured in response to specific conditions
both of the factory-planning project and of the organisation. This is
considered the most effective methodology for the planning phase of the
project and needs to be adopted from the company, understood from the
team and continuously improved project by project.
A model consisting of 28 basic modules (example shown in Figure 17)
composes the CBFP and eight planning domains, which are defined
based on project experience of the Laboratory for Machine Tools and
Production Engineering (WZL). The modules involve several different
planning tasks like: capacity planning or segmentation.
Figure 17 Planning Modules
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The main concept behind CBFP is to develop the planning duties without
taking into account the temporal sequence but just the contents. In CBFP,
the single planning tasks are encapsulated in different planning modules
with defined input and output information. Due to the resulting
dependencies between the modules, the planning process is determined.
The planning process within the single modules is standardized, which
leads to significant timesaving in factory planning projects. Each module
needs specific information, which are linked to specific dependencies. The
transparency of the project is guaranteed by the identification and study of
those dependencies. The main advantage of this approach is that if
changes occur, the planning teams are able to trace the modifications and
effects derived from the new scenario identifying the dependencies
between input and output in terms of information of the modules. Within
the single modules, the transformation of input into output information
takes place. For single modules, it has also been investigated whether
specific pieces of output information can be generated automatically
without being in need of a human planner using his experience and
intuition to derive and evaluate his planning results. For each module,
software tools have been developed over the time, (as shown in the next
chapter) which are vital and specific for each planning duty. The
criticalities of this approach are mainly 2:
• Data management becomes very complex due to the amount of
dependencies between modules and information.
• CBFP structures a theoretical model to support the information flow but it
doesn’t include an integrative information model managing all data
contained in the project. This can be fixed merging CBFP with Virtual
Intelligence Production (VPI).
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3.2.3 Technology Support “Digital Factory” (DF) consists of the set of tools for the support of the
planner in factory planning and it is considered the planning basement of
the future. The VDI (Verein Deutscher Ingenieure) defines DF as “a
comprehensive network of digital models, methods and tools, including
simulation and 3D/VR visualisation, which are integrated through
continuous data management”. The main goal of DF is a comprehensive
and holistic planning, implementation, control and continuous
improvement of all key processes and resources linked with the finished
product. Digital Factory can be considered formed by 3 elements:
• Modelling and visualisation,
• Simulation and evaluation
• Data management and communication
Figure 18 shows the most common categories of planning tools in the
digital factory. The challenge for the full integration of the planner in the
factory planning process is the selection of the right dimension of
technological planning tools in order to have an effective and efficient
support for the phases of design and simulation. The features of the
company (size, structure rigidity, organisational shape, etc.) influence the
suitability of the tools, for instance a small enterprise with high rigidity in
the structure, which sells commodity products, won’t achieve any type of
benefit from the utilisation of augmented reality tools for product design.
Figure 18 Planning Tools In Digital Factory
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Technological solutions on the market Regarding this huge number of tasks, a vast number of commercial tools
and solutions are available on the market as shown in figure 19
Figure 19 FP technologies
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Challenges for the Planning team in DF
DF is considered the vanguard of factory planning, but "from great power
comes great responsibilities”, so the planner needs to put efforts in the
management of 3 key critical aspects in order to avoid disruption and
inefficiencies:
1. Limited time for the planning process and the complexity of the
organisation’s processes and relations need continuous support from all
areas to ensure up-to-date planning data and avoid silos effect. The whole
planning process in the virtual world influences the concrete production
factory, the logical consequence is that each modifications in the real world have to be converted in the virtual planning data.
2. The tools of the Digital Factory fully rely on the digital database. Errors or defects in digital data may affect the planning process
output and delays in implementation. Re-planning phase could be very
expensive, provoke delays in the launch of production and impede the
achievement of an optimum result.
Theoretically, the DF and the concrete world are identical but,
unfortunately, they differ because there is no a physical link between the
two worlds and In DF the manufacturing plant is virtually built. The hardest challenge is to overlap these two worlds, minimise the divergence and keep DF up-to-date with the real world. Several
problems can be identified during the process of achieving this level of
consistency:
• 3D data is usually not available for all existing plants (Only 2D layout
or production designs).
• Very often there are still planning processes that do not yet use these tools.
• Furthermore, the factory is a dynamic environment. In most cases, changes are not documented and can thus not be transferred back to the virtual planning data of the Digital Factory.
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Focus on Augmented Reality
To find a definition of Augmented Reality (AR), different approaches are
possible. A very general classification is given by Milgram, who used the close
relation of Augmented Reality with Virtual Reality to create a so called Reality-
Virtuality (RV) Continuum. In this continuum, AR finds its place in-between the
Real Environment and the Virtual Environment (see figure 20), in the Mixed
Reality space. In contrast to Augmented Virtuality (AV), Augmented Reality is
situated closer to the real world than to the virtual world. Thus, Augmented
Reality denotes an enhancement of the user’s perception of the real
environment. Another more technical but still technology-independent definition
can be found in the AR survey of Azuma, where the following characteristics for
AR systems are stated:
• It combines real and virtual.
• It is interactive in real-time.
• Real and virtual objects are registered in 3D.
Figura 20 Reality vs Virtuality Continuum
Augmented Reality as a technology requires several system components, which
need to take care of the different functional aspects related to an AR system,
such as tracking the interesting objects in the real world, presenting the
augmented world to the user or controlling interactions between the user and
the system. Reicher conducted a study on software architectures for
Augmented Reality systems to identify a reference architecture built from
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components common to most AR systems. The architecture consists of the
following components:
• Application: containing application specific logic and content,
• Tracking: responsible for determining the users’ and other objects’
poses,
• Control: gathers and processes user input,
• Presentation: uses 3D and other output modalities
• Context: collects different type of context data and makes it available to
other subsystems and
• World Model: stores and provides information about real and virtual
objects around the user.
AR & VR are able to support the full integration of the human factor in factory
planning giving the power of envisioning in advance what some potential
scenarios to the planner. This technology provides to the project the adaptability
and the robustness needed to face the external change drivers and the internal
unexpected requirements simulating in advance what will be.
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3.3 Repeatability
This attribute plays a key role in the integration of the human factor in
factory planning process. It refers to the ability of the organisation to create
a solid basement to make the project sustainable and the ability to
enhance the effectiveness and efficiency of the outcome project by
project. The organisation has to develop solutions for keeping inside:
• Experience and competency developed: the organisation has to
structure a programme in order to support the development of the human
resources’ competences and to preserve them to get out the company.
The human factor cannot be seen as driver of the system if he is not
aware of the competencies he is going to develop. Effective Factory
planning anticipates the future.
• Data and information collected: the information flow needs to be well
structured, precise and accurate (the right information to the right person
at the right level of detail), well timed and efficient. The planner is able to
manage the project effectively only if can promptly collect and find the right
data. The organisation has to defeat the “Silos effect” which is a watertight
compartment view for information. This set of data, information and lesson
learned will constitute the base for the future projects.
A key decision point to make the project sustainable in the long term is
motivation: It’s impossible to preserve experience, competencies and
skilled people inside the company without a clear motivation strategy (in
terms of salary system and career opportunity). The effective approach
aims to push performance to the limit and to preserve talented people from
the migration. The planner and the team cannot be fully integrated in the
project if they don’t see a compensation for their work or the opportunity
for achieving the individual goals beside the company’s ones. Great
expectations demand great opportunities.
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3.3.1 Motivation Strategy
The optimum outcome of the project can be achieved only if there is in
place the right strategy for sustaining and improving employee’s
motivation. The first challenge to be faced is that, of course, motivation
cannot be measured but just indirectly observed as positive delta
performance. The trigger of lack in/good performance can be led back to
two key concepts:
• Intrinsic motivation (i.e. when a job is considered independent,
professionally challenging and as a basis for personal growth)
• Extrinsic motivation (i.e., by payment and threatened punishment).
Literature of motivation stresses mainly two blocks of theories but very
often the structure of the motivation strategy can be derived from both of
them:
• Content theories the concept at the basis of these theories is that the
interpretation of people behaviour is linked to the need of filling some
specific deficiencies. In literature about motivation the main model is
considered the one developed by Abraham Maslow as shown in figure 21.
Figure 21 Maslow's Pyramid
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• Process theories explain actions against the background of complex,
multi-staged decision processes. According to these approaches,
motivation originates in the work process and the mental anticipation of it.
The majority of process theories work with the value which specific
processes and their results have for an employee.
Figure 22 Porter and Lawler's Model
From this last group of theories we have identified the reason why
motivation is related to an important aspect of human motivation deeply
described in literature: there is a lack of motivation where there is no
evidence of future individual improvement. The term individual
improvement can be roughly broken down into 2 main areas:
• Competency development
• Career related aspects (salary system, hierarchical position)
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3.3.1.1 Competence Development
The term “competence” is vaster than qualification; it defines the boundary
of the expertise as a mix of theoretical knowledge and capabilities that
people has command over in determined scenarios.
“Competency refers to the motivation and aptitude of a person to
independently further develop knowledge and ability in an area to a level
that can be characterized as expertise”
From this derives the idea that the learning process should not involve just
instilled and accumulated pre-structured notions because people learn
linking new notions with old knowledge, theoretical contents with practical
experience, suggested solutions with concrete problems. The main
consequence of this concept is that the learning programme has to be
structured to show the real world sense and context of the course content.
Learning programmes, in order to develop competencies, are meaningless
if they are not preceded by a gap determination phase. It’s vital to identify
and distinguish the individual elements of competence. A common model
has defined 4 areas of competency:
• Technical
• Methodological
• Individual
• Social
Figure 23 shows and describes these terms and elucidates the relations
inside the framework.
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Figure 23 Competence Framework
Literature about knowledge distinguishes explicit and implicit knowledge
and agrees that both compose professional competence. The term
explicit knowledge refers to conscious, logically organized knowledge
that can be communicated. Implicit knowledge stems from experience; it
allows tasks to be executed with certainty, however it is not consciously
present and cannot be verbally communicated.
After the identification of the desired competences and the current gap,
the management should design before the project launch and during the
entire course of the project the features of the competence development
programme facing two main aspects:
1. Areas of human resources development: The specific area of
competence that the management wants to improve in the team
(Knowledge & skills oriented, Behaviour oriented)
2. Type of learning: The most suitable way to develop competences
in terms of knowledge and skills. (Formalized learning, Partly formalized
learning, Informal learning)
These two areas are strictly interrelated. After the decision of what
competence area the management wants to improve, it has to decide what
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kind of actions to adopt. The main goal is to align organisation and project
requirements and team competence in the short and long term both. The
initiatives can be divided following mainly 2 main criteria: Level of formalisation and orientation.
According to the level of formalisation we can distinguish:
• Formalized learning is driven by an expert through classes, training and
explanations and is adopted mainly for technical and methodological
competences (more effective for transmitting explicit knowledge)
• Partly formalized learning is most of the times conducted in learning
environments. The experts follow a conscious path but do not pre-
structure the lesson. (effective for implicit and explicit knowledge and for
the transmission of all 4 dimensions of competence). Advantage: very
close to experience and very effective for the development of social and
individual competence. Disadvantage: Lack of exploration of theoretical
elements.
• Informal learning is unstructured and experience oriented. It can be
performed during the project tasks, transmitting informal knowledge to the
partners
In addition on the basis of the orientation we have:
• Knowledge oriented approaches’ goal is the effective alignment of
individual competences with the project’s work task prerequisites. Main
tools:
1. Requirement analysis
2. Scenario building
3. Staff appraisals (provide information about the current capabilities
and employee’s potential. It involves an analysis stage before the structure
of development plans that contain metrics, timeline and the final
evaluation).
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The most up-to-date knowledge oriented approaches take into account
individual learning styles and contain challenging learning purposes based
on work related scenarios.
• Behaviour-oriented measures’ goal is facilitating behaviour
modification in order to align people’s way of acting with the organisation
vision. Main tools:
1. Training measures (group training or outdoor training)
2. Coaching
3. Mentoring
4. Consulting
Change management gains a vital importance to support the change and
avoid delays or failure. The most effective approaches couple training
measures with measures related to design of workplace.
3.3.1.2 Career related aspects
The purpose of career-related area is to structure career development
programme (including the salary system) consistent with the organisation
vision that overlaps the prerequisites of the company with the expectations
of the individuals. Who takes part of a challenging factory-planning project
needs to be aware of the reward for his work. After the conclusion of the
project, on the basis of the employees’ expectations, performance and
willingness, career should move in at least one direction:
• Vertical careers: involve the climb or descent of the hierarchical scale.
For example after the successful completion of the FP project a team
member that has shown leadership and managerial skills should be
selected as team leader for the next project and obtain more commitment.
• Horizontal careers: do not involve hierarchical movements but changes
in department, project or role (if on the same hierarchical level). For
example, at the end of the project the financial responsible of the planning
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team can be moved from the FP project to an ERP introduction one in
order to extend his competences.
Evidently, in the development of the career-system, the management
needs to identify, clarify and include the expectations of the employees.
Furthermore, it is important to consider some vital aspects like for example
the readiness of people to move vertically that is commonly stronger than
to move horizontally. This desire of climbing vertically is relies on the wish
for autonomy, power, self-development and higher salary. On the other
hand, the desire of changing horizontally can be justified by more involving
and fascinating tasks or the ambition of enlarging the boundaries of
competence in different fields. Finally, horizontal changes can facilitate
future vertical climbs but sometimes are stopped by the desire of a stable
career development.
Accordingly, the salary system should pursue two main goals
• Developing a payment which is perceived as appropriate
• Controlling employee performance
The challenge for the management is to identify the efficient and effective
combination of incentives between monetary and non-monetary ones in
order to raise the team members’ motivation at the lower cost. Figure 24
shows the most common type of monetary and non-monetary rewards.
The salary systems development process should pursue the fairness
criteria, which is dependent on normative decisions and cultural backgrounds.
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Figure 24 monetary/non monetary incentives
In order to ensure that the salary system developed is expression of the
fairness criteria, the planner should consider several different aspects:
• The relationship between the offer and demand on the job market,
• Acquired qualifications and professional certifications,
• Acquired social privileges, e.g., the length of time someone has belonged
to an organization or their length of service,
• Social needs such as the responsibility for spouses and children,
• The general difficulty of the work task,
• The specific performance of the employee.
Finally, the planner should always follow 3 main guidelines before the
project launch and during the project development:
• The management has to build over the time a goal orientation and clarify
individual targets, which have been agreed upon together and written “on
paper”.
• Management should identify and discuss the conditions under which the
project team can accomplish the task and achieve the required
performance. The new challenge for management is the elimination of
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technological and organisational obstacles beside the design of a
programme for the development of competences.
• The management should be able to vary the management style (from
participative to a performance oriented and vice versa) on the basis of the
features of the planning team (experience, hierarchical rigidity, work
approach, etc.)
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3.4 Responsiveness
The third section describes the key aspects of responsiveness. We can
define it as “the ability of communicating and problem solving in a timely
and efficient manner after the effective analysis of the contextual
conditions”. The potential responsiveness of the project is a key indicator
of the full integration of the human factor because no project is completely
manageable if the planner doesn’t receive promptly the information and
the tools to change the course and bypass in advance obstacles.
Responsiveness of the project can be achieved making effective and
efficient three key elements:
• Communication: A project to be responsive requires a validated and
reliable communication system, cutting-edge technology and a low degree
of hierarchy in the organisational structure. Information flow has to be
precise, timely and structured.
• Problem solving: The organisation needs to stand on solid and
experienced procedures to face challenges. Furthermore, the
organisational structure of the team has to include a body for problem
solving with the responsibilities of crisis management, risk management
and problem solving.
• Compatibility & integration: The organisation has to pursue the full
integration of the systems under the organisation’s umbrella.
Incompatibility among systems or technologies and between planner and
production system can affect the responsiveness of the project to change
route promptly.
The following section will briefly explain the virtual production intelligence,
a vital concept of factory planning, with the aim of increasing the speed
and the quality of the decisions.
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3.4.1 System Integration
Virtual Production Intelligence (VPI) can be defined as an umbrella for
different applications of every description, which supports and makes
easier the access to and the manipulation of information with the final goal
of enhancing the quality of the decisions, overall efficiency and the level of
performance. The key focus of VPI is on the management and analysis of
information produced in digital manufacturing. It is tightly linked to the
concept of “business intelligence system” of Luhn. The VPI strives for
achieving 3 core objectives:
• Holistic: Addressing all sub processes of product development, factory
and production plan etc.
• Integrated: Supporting the adoption and the combination of existent
approaches instead of producing new standards.
• Collaborative: Considering roles, which are part of the planning process,
as well as their communication and delivery processes.
The importance of this section can be identified in the planner’s need of
avoiding the silos effect and the applications incompatibility within the
organisation. The lack of system integration can be disruptive and
obstacle the ability of the planner of managing the project. Effective
decision-making process requires a well-timed, precise and efficient
information flow and this can be achieved only with a full integration of the
system in terms of applications. VPI is the answer to this challenge.
Furthermore, VPI addresses the most critical challenges for the
implementation of Digital Factory like: interoperability, user interaction,
visual analysis and simulation. The IT system that makes the
organisation able to manage all the functionalities and visualisation
capabilities to offer the power to the users to face these critical aspects is
called VPI platform. The core objectives of VPI are the minimisation of planning efforts and the enhancement of planning efficiency giving a
comprehensive analysis and the visualisation in terms of control panel.
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This needs to structure the integrated information model. Using the
adaptive information integration, data can automatically be transferred
between the sources and the data sinks. Furthermore, data can be
consolidated for analysis. Such an information centred approach facilitates
a structured information management that makes an integrated and
efficient data access possible, e.g. by supporting structured query
languages. Methods and tools for data analyses and evaluation, such as
Data Warehousing and OLAP (On-Line Analytical Processing), facilitate
various possibilities to manipulate and to maintain existing data. The
platform serves for planning and support concerns by providing an
integrated and explorative analysis in various fields of application. Figure
25 shows how the platform issued by various user groups in these fields of
application.
Figure 25 VPI logic
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3.5 Predictability & Controllability
The planner and the project team can be seen as foreign bodies of the
system if they have not the power of controlling the process advancement
and the tools to standardise and make predictable the desired outcome.
The clarification of the objectives and the deployment of a shared and
common strategy as well as the ability of project management are vital for
the full control of the project and the avoidance of accidents and delays.
• Strategy and vision deployment guarantees the alignment between
management and planning team, vision and related strategy, stakeholders
and project. This area anticipates every activity of project management like
the project charter or the PM plan development. This area concerns the
ability of the organisation of spreading to several hierarchical levels the
guidelines of his mission. The full integration of the planner can be
achieved only if he is aware and shares the objectives of the company.
The right route can be chosen only if the planner is aware of where the
organisation aims to arrive.
• Project management gives to the planner the ability to control the
project and to avoid budget overruns, delays and stakeholders
dissatisfaction. This area is common to several types of project so it is not
explained in detail here. Appendix A-3 shows a brief discussion about the
differences between two standards: PMP and Prince2. This section is
inserted in order to go beyond the old fashion view of a mutual exclusive
choice between these two standards and to help the organisation to
achieve additional benefits related to PM.
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4 Validation & future improvements
4.1 Validation
Theoretically, there are 3 ways for the model validation and any of them
can be utilised to different sections of the model:
• Judgement of experts (from academia and/or industry)
• Measurements during the on field implementation
• Theoretical results/analysis
The first one has been chosen mainly because of the nature of the model
and of the topic. HFIM is a qualitative and not quantitative model with the
aim of creating an awareness of the decision points that need to be taken
into account in factory planning projects and supporting the decision
making process itself. Furthermore, this model includes some
psychological and “soft” factors that are not easily measurable.
The critique of he model has to be conducted by experts of the system
(and not of the model) and not by the modeller itself. For this research
three companies of different size and sector have been involved. After the
phase of iteration the model has been completed and refined.
The configuration and refinement of the model were conducted basically
with questionnaires (sent by mail) and interviews (by mail, calls and on-
site visits) to:
• General Manager, finance and planning manager, project manager of
BdM (small size company in the food sector)
• Controller of Gucci (medium size company in the fashion sector)
• Operations Manager, project manager of Amazon Italia (large size
company in the e-commerce sector).
The experts’ selection has been developed on the basis of the current
network of the researcher. The advantage of this choice consists in having
a closer relationship with the interviewees and greater availability in terms
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of time and resources. The trigger of this choice is the unsuitableness of
the questionnaires approach for this psychological/soft topic of human
factor integration. The research gains value only if we are able to include
during the refinement iterations and during the development of the model
also the experience and intuition of the experts. The entire panel has
experience in factory planning projects and has provided valuable
modifications to the model’s structure and contents by the fulfilment of the
questionnaire but mainly with the on-site visits and the interviews. The set
of methodologies containing “team selection”, “conflict management” and
“motivation strategy” has been reviewed, analysed and configured
according to the experts’ perspective. The figure 26 below shows at a high
level the validation process.
In the end, after several iterations the entire panel of experts has agreed
on the value of the model and its innovative ability to fully support the
decision making process in a “fuzzy” and turbulent context as factory
planning. The model has respected the expectations of the user (the
planner) in an innovative way and created a first step for the future
development.
The validation process outcome consists of:
• Experts' approval of the model
• Gap in the research and future improvements
The model has not been tested on field because of the limited timeframe
and the “soft” nature of the topic, which requires incredible efforts in terms
of time for the validation. Accordingly, the next step of the research may
consist of a business case and the physical implementation of the model
inside a real production system and a real factory-planning project in order
to identify more strengths and weaknesses.
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Figure 26 Validation process
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4.2 Future Improvements
After the validation process are emerged some points for future
improvements:
Figure 25 Future Improvements
• Qualitative not quantitative model: because of the nature of the topic,
(which includes human factor) and the nature of the model it is hard to
build a quantitative model. Literature has some techniques to develop
quantitative analysis for the different areas of interest. A methodology to
integrate all of these technics is still missing.
• Specific for Factory Planning: HFIM is specific for factory planning
project and loses relevance when we decide to change the field of
application. Some areas of interest of the model are “commodity”, so they
can be applied to every project (like project management area) but there
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are still some areas specific for factory planning (like methodology
selection).
• Requires a lot of efforts in the planning phase: this model provides a
framework to minimise the output variation due to the introduction of the
human factor but taking into account each single aspect and following the
methodologies in order to make an effective decision is costly in terms of
time. “The optimal decision is a luxury”.
• Other important areas of interest need to be added and discussed: The selection of the areas has been conducted according to the literature
review and the interview with the experts. It is likely that some relevant
areas have been neglected. The future step is to develop a second
iteration of interviews with industry and integrate the residual areas.
• Validation on field: The model needs in the future to be tested on site in
a real project of factory planning and refined accordingly with the result of
the project.
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5 Conclusion
Factory planning is a relatively new field of study, which deserves an
increasing joint research effort from academia and industry. Too often
psychological and human aspects are neglected in literature of FP and too
often the technical areas of study about FP (like simulation technology,
virtual reality, planning methodologies…) are discussed separately. This
research aims to going beyond the old fashion views of “FP as a black
box” and “watertight compartments”. Accordingly, HFIM model is the first
step in the direction of defining the FP boundary and introducing shared
methodologies and practices. The model aims to emulate what the ------‘s
“House of Quality” represents for manufacturing and pursue the objectives
of:
• Identification of the most critical areas
• Development of practices and methodologies to face challenges in each
area.
The research has been conducted developing a “big picture” of the topic,
then defining a generic background of each area but deepening only the
“soft” and “human-based” aspects like Project Management, conflict
management, team selection and management, Motivation and
Competence development.
The judgement and the support of FP experts have brought incredible
value to the model and to the research as a whole. The future steps
consist of the test on field of the model in order to investigate the concrete
applicability and the development of a quantitative model.
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6 Appendix
6.1 A1-Belbin’s Report
Belbin Team RoleReport for
Jo Pink
Colourful Company PLCRainbow HR
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6.2 A2 – Voiceprint Report
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6.3 A3 – Project Management: PMP and Prince2 PM is a vital area of interest not specific for factory planning projects, so
we refer to generic manuals for the basics.
The PRINCE2 and PMP certifications involve two different project
management frameworks that belongs to two different institutions: PMI
and Axelos. Both offer a body of knowledge and a proven approach to
managing projects effectively.
A critical decision point in the planning phase is the selection of the Project
Management Standards. The two main methodologies are Prince2 and
Project Management Professionals. In this section it is interesting to
analyse how the industrial perspectives sometimes relies on erroneous
assumptions like considering these two standards like a mutual exclusive
choice.
The literature of project management and the institutions themselves
recommend a methodology rather than another in function of various
factors, for example, the great majority of literature argues that the optimal
choice should be based on the industry or company you are aiming to
build a career in, the type of project one is leading or directing or the
country the organisation belongs to. Figure 24 shows the current
certification adoption region by region
The nature of these two frameworks is deeply different mainly for three
key aspects:
PMP Prince2 Knowledge book (set of
standards)
Methodology
Descriptive (explains best
practices)
Prescriptive (explains correct
approach)
Answer to “HOW?” Answer to “WHAT, WHEN, WHO?”
80
The first core difference is that PMP is a collection of best practices that
constitute a standard but Prince2 is a “process-based project management
method” that offers a systematic method for delivering a successful project
with clear templates, processes, and steps. The certification is both,
process and project focused. It is a broad, high-level, general framework
of project management principles, which means it is recommended for and
implemented on just about any kind of project. Accordingly PMP is a
descriptive framework, which shows and discusses these best practices
and leaves a certain degree of freedom in the implementation. Prince2 is a
prescriptive model, a set of guidelines that explains in every situation what
to do, when and who.
The result of the interviews to Amazon and Bdm’s project managers
highlights a new perspective of these two frameworks. Because of their
81
nature and application this is no more a mutual exclusive choice, on the
contrary, the joint adoption may bring important benefits to the project.
According to a survey conducted by PMI-NIC (Project Management
Institute – Northern Italy Chapter), the PMI’s certification is achieving more
and more recognition but the integration with Prince2 may bring relevant
benefits:
• Exhaustive Body of Knowledge: provides to the project manager a set
of tools to analyse the project from all angles, ensuring the feasibility
before starting. The probability of failure is minimised clarifying in the
planning stages user requirements and potential risks.
• Well Laid-out Methodology: it avoids waste of time and resources
• Standardization: Confusion in project execution is eliminated since the
same, standard approach is used throughout, with common filing systems,
procedures, and documents.
• Driven by Business Case: PRINCE2 ask for updating the business
case simultaneously to the progress of the project. This can avoid that the
project will not create value for the company and for the customer.
Failure to do so will eliminate the justification for the continuity of the
project.
• Eliminates ambiguity: It divides the master project plan into Project
Plans, Stage Plans, and Team Plans, which simplify the execution of the
project.
82
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8 Sitography
[1] http://www.belbin.com/about/belbin-team-roles/
[2] https://www.pmi.org/certifications/types/project-management-pmp
[3] https://www.prince2.com/eur
[4] https://letstalk.voiceprint.global
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