INDUSTRIAL INTERNET OF THINGS:A Data-Driven Future for Manufacturing

5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

Despite the rapid growth of sensors and the buzz around the Internet of Things, adoption in manufacturing has lagged behind the hype. Based on a recent IDG Research survey of 100 executives in the manufacturing industry, this white paper explores the various challenges standing in the way of adoption, the security implications of an Industrial Internet of Things (IIoT) strategy for businesses, and what manufacturing organizations should do to optimize their IIoT implementation while mitigating risk.

“For a while, companies have been doing certain things to connect machine-to-machine without necessarily referring to it as the IIoT…The demarcation is in the IIoT’s ability to integrate data that previously resided in silos and transform the way we process that information in order to inform decision making.”

Jay Monahan, Global SAP shop floor lead for Dell Services

Learn more about Smart Manufacturing and IIoT.

The IIoT has generated substantial buzz, driven by three main trends: the explosion of sensors in everyday items, the arrival of inexpensive storage options, and better chipsets for connectivity. Today, sensors that record, transmit, and share information are interwoven into the fabric of everyday items, from the watches and clothes we wear to the thermostats that regulate our home temperatures. But, while the biggest buzz is around consumer IoT, the Industrial

IoT in businesses such as manufacturing is where the biggest strides are being made.

Even though manufacturers have used statistical process control and data analysis to help optimize their systems for years, the term “IIoT” is relatively new. With IIoT, new integrated sensor data, combined with advancements in connectivity, security, interoperability, and analytics, creates immense potential for organizations.

Challenges Impeding Adoption 5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

The consumer market was quick to adopt the IoT. But companies with a business-to-business focus have been slower to invest.

According to a recent study by Dell and IDG Research Services on emerging technologies, only 29% of enterprise respondents in manufacturing are investing heavily in the IIoT, while a quarter say they’re doing little in this area.

And when asked at what stage of investment in the IIoT they expect to be in 24 months, respondents predicted little progress beyond researching and piloting solutions toward the goal of generating a network of connected devices integrated with enterprise applications.

“Particularly in manufacturing, those companies that collect, merge, and analyze the various data sets recorded on the factory floor—from unit production and equipment operation data to process and human operator data—will stand out from their competition through better, informed decision making,”

Prasoon Saxena, Managing Executive, Global Manufacturing Services at Dell.

Of manufacturers utilizing IIoT:

have improved in business innovation.

53%

have increased their competitive edge.

50%

have reduced total cost of ownership.

50%

Factors Driving Adoption Challenges Impeding Adoption 5 Steps to Optimize & Mitigate Risk

Factors Driving Adoption

“The tools available today are capable of ad hoc recording, enabling end users to move though processes faster. Inquiries that traditionally take hours, days, or even weeks can be performed on-demand.”

Jay Monahan

Equipment across the factory floor can generate thousands of data types and petabytes of data in only a few days. The real value is not the data itself, but the ability to improve the decision making by providing end users the power to view multiple business scenarios instantaneously and react in real time.

In manufacturing, process variability stems from numerous factors that can often be monitored via sensors. That data is strongly correlated to yield, quality, and output. When integrated, that sensor data provides insights that show when processes are getting out of whack.

Through data analytics and visualization tools, organizations can interpret those results and make informed decisions about emerging quality issues and predictive maintenance. This limits hardware failure and downtime, which ultimately reduces cost and improves productivity.

Given myriad types of parametric, product, and equipment data available, these benefits are the tip of the iceberg. With additional data mining and advanced analytics, new business value and efficiency gains emerge, fueling a competitive advantage.

Factors Driving Adoption Challenges Impeding Adoption 5 Steps to Optimize & Mitigate Risk

In addition to improved component uptime, increased yield and throughput, predictive maintenance and reduced component failure, data analytics and IIoT enable organizations to gain insights into factory floor processes that improve their decision making, business innovation and position in the market.

Real results: In fact, the top benefit linked to the IIoT is improved business innovation, cited by 53% of respondent organizations in IDG’s study, followed by reduced cost of ownership, cited by 50%.

However, to realize the efficiencies and innovations that can be garnered through instrumenting the physical world, successful companies indicate that careful planning and a clearly defined roadmap is critical. These benefits, among others, should drive investment in the IIoT beyond what the survey respondents’ expect.

Improved business innovation

Reduced cost of ownership

Competitive edge

Improved process performance

Better decision making

Improved service response time

Improved personnel productivity

Faster time to market

Reduced machine/asset downtime

Improved asset utilization

Better working with/serving our suppliers/customers

53%

50%

50%

49%

44%

41%

37%

37%

36%

33%

26%

Source: IDG Research Services, September 2015

Benefits of IoT

Factors Driving Adoption Challenges Impeding Adoption 5 Steps to Optimize & Mitigate Risk

Real-world example: Predicting equipment failure in a production environment.

IIoT technology is capable of detecting defective Test Interface Units (TIUs) that wrongly categorize good units as bad. Prior to the IIoT, if a faulty TIU categorized a unit as bad, the unit would be scrapped and replaced with a spare part during regular preventative maintenance, even if it was operating properly.

In a recent pilot conducted in one of its manufacturing facilities, one Fortune 500 company found that data analytics, applied to factory equipment and sensors, were able to predict up to 90% of potential TIU failures before being triggered by the existing factory’s online process control system, helping to save inventory that would have been categorized as faulty and reducing yield losses by up to 25%.

Challenges Impeding Adoption 5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

Challenges Impeding AdoptionWhile the business benefits of the IIoT are attainable, various hurdles continue to slow adoption of IIoT strategies and solutions. For enterprises to invest in the IIoT, they will need to overcome organizational resistance, security concerns, the added demand that the IIoT places on infrastructure, and the inherent ambiguity that surrounds new technologies.

Since the IIoT is a relatively new term, its definition lacks consistency across industries. As with many emerging technologies, this ambiguity muddies the value proposition and obscures a clear path to profitability.

27%

say unclear financial benefit is a barrier.

48%

say budget constraints are a barrier.

Challenges Impeding Adoption 5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

Return on investment matters, and with budgetary constraints inhibiting technology investment, an inability to demonstrate immediate value has kept proponents from making a strong business case for the IIoT.

Security, cited by 34% of IDG respondents, poses another challenge. The scale of the IIoT creates an unprecedented attack surface for hackers as the proliferation of sensors on factory equipment expose the organization to risk that must be mitigated.

Moreover, in order for companies to analyze information on process variability holistically rather than in isolation, they must integrate the data generated by these sensors. This includes data pertaining to material, process recipes and methods, and equipment differences. Thus, in addition to shoring up the network and extended attack surface, the various platforms and protocols of the sensors cataloguing data must be managed.

Concern over the demand the IIoT would place on existing IT infrastructure has further slowed adoption.

Today, imagination is the only limit to what can be monitored and measured. However, the more data that IT collects, the more it must store, process, and analyze and concerns over insufficient resources and the need to purchase expensive hardware has had an impact on IIoT investment.

Finally, organizations have struggled to develop a clear roadmap for the IIoT. Industry use cases or best practices are still emerging. Accordingly, many organizations are unsure of where to begin, or even whether their infrastructure and business processes are equipped to handle an IIoT implementation.

Challenges Impeding Adoption 5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

“With all of the information we’re able to track today, organizations often have the tendency to want to start too big and end up getting lost in a snowstorm of data points… You cannot launch an IIoT initiative with the attitude that you have to collect everything. Rather, start small with a pilot program focused on a known bottleneck and define key, manageable KPIs.”

Jay Monahan

Budgetary constraints

Security/compliance concerns

Unclear financial benefit/difficulty calculating ROI

Lack of interest from executives/stakeholders

Lack of in-house skills

Organization doesn’t recognize business value

Diversity of niche providers and solutions

Data Volume and complexity

No barriers

Lack of data protocol standards

48%

34%

27%

25%

23%

20%

17%

17%

15%

13%

Source: IDG Research Services, September 2015

Barriers to investment in IoT

Challenges Impeding AdoptionFactors Driving Adoption 5 Steps to Optimize & Mitigate Risk

Steps to Optimize Benefits and Mitigate Risks Associated with IIoT 5

5 Steps to Optimize & Mitigate RiskChallenges Impeding AdoptionFactors Driving Adoption

1Join forces.IIoT is the intersection of Operations Technology (OT) and Information Technology (IT) to achieve business outcomes, and collaboration between OT, IT and business management is essential. No single department has the knowledge and experience to address all essential functions, yet differences in departmental culture, operating methods and KPIs can derail integration and data sharing. Build strong partnerships to overcome differences and leverage organization-wide expertise.

2Clarify business outcomes and ROI.There is hype and confusion about what is possible with IIoT, and the risks associated with it, which can result in inertia in the face of growing competitive pressure. Getting help from a trusted partner to identify IIoT opportunities and use cases, supported by concrete return-on-investment analysis, can pave the way forward.

Look for a holistic, objective methodology, rather than one-size fits all approach to determine the right combination of IIoT devices, applications, communications and data management tools for your organization’s specific use cases.

5 Steps to Optimize & Mitigate RiskChallenges Impeding AdoptionFactors Driving Adoption

3Start small with what you have.Beginning with small IIoT projects that use the equipment and data you already have allows you to prove ROI and establish best practices before full-scale implementation. With data growing exponentially, it is tempting to want to analyze it all. Don’t. Everything is more manageable when you begin small, pilot a concise program with well-defined KPIs, establish a new flow of data, develop policy, and expand it once it’s refined. That said, prepare a solution that can scale.

Realize new value from legacy assets

Good news: Even if your assets and systems weren’t originally designed to connect to the

Internet and share data, they still can. By attaching intelligent gateways to existing assets, you can collect

data from these previously untapped resources. So getting the benefits of an IIoT solution doesn’t mean

starting from scratch.

5 Steps to Optimize & Mitigate RiskChallenges Impeding AdoptionFactors Driving Adoption

4Think security first.Security can be an afterthought when it comes to implementing IIoT, which puts critical organizational operations and data at risk. Secure sensors, smart devices and software are available, so be sure to understand the in-built security posture of solutions you are considering before buying.

The key to IIoT security is this: be cautious but not paralyzed. Prior to embarking on an IIoT deployment, be sure to modernize your applications to ensure security requirements are met and proper protocols are installed and aligned. Review and strengthen your current IT security, identity, privacy and management practices to prepare for potential additional risk exposure. 5

Architect for analytics.Data itself is not valuable; the value comes from the insights you can glean from the data. The power of data analytics stems from the ability to integrate and correlate the vast amount of data that goes unused throughout today’s plant and extract meaningful insights from it. Integrate data currently stored in silos and you will unlock insights buried in the data you already have.

ConclusionChallenges Impeding Adoption 5 Steps to Optimize & Mitigate RiskFactors Driving Adoption

ConclusionAlthough current IIoT adoption has largely lagged behind hype in the B2B space, pioneering manufacturers are taking the necessary steps to capitalize on its potential by investing in enabling technologies and mitigating their risk factors. Many first movers have already begun extending successful pilot programs more broadly to augment productivity and efficiency gains.

The cost savings and added throughput recognized by these organizations have in turn improved gross margins and bottom-line results creating new opportunities for reinvestment. In order for manufacturing companies to remain competitive, they need to continue to differentiate themselves through the efficiency optimization afforded by the IIoT.

At Dell, we know manufacturing and supply chain operations firsthand. Being a manufacturer ourselves, we understand your business challenges. As a technology leader, we know how technology can turn those challenges into competitive advantage. We speak your language to help IT, Operations and Engineering collaborate to make better technology decisions and get the most value from every dollar spent.

Dell takes a pragmatic approach to the IIoT, starting small with the equipment and data you already have, we architect for analytics and think security first. With the industry’s broadest portfolio of IIoT enabling technologies and rich partner ecosystem, Dell reduces the complexity of deploying IIoT solutions and enables you to make the promise of IIoT a reality today.

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