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Technology Report: IIoT Launch TemplateA Smart Industry Technology Report on Starting Your Digital Transformation

It’s common knowledge that in order for your business to thrive in the modern industrial era, you must adopt elements

of the Industrial Internet of Things. But equally common is a lack of understanding about getting started. Opportunities

abound with digital transformation, but figuring out the how and when and where and “Who is going to pay for all of

this?” can be tricky. This Technology Report provides the justification and tactics for launching into the IIoT, enabling you

to look back from the near future with only one question…“Why didn’t we do this sooner?”

TECHNOLOGY REPORT


TECHNOLOGY REPORT

CONTENTS

The future of manufacturing: Only the innovative need apply

Launch your IIoT strategy sooner than later

How to justify your first IIoT trial

Seize the IIoT in just 3 steps

5 steps to getting started with predictive simulation


TECHNOLOGY REPORT: I IOT LAUNCH TEMPLATE

The future of manufacturing: Only the innovative need applyBy Mike Bacidore

“Detroit, we have a problem. The rampant growth the global economy has been experiencing is fading away,” warned Alastair Orchard, vice president, Digital Enterprise, Siemens. “The global economy is growing at the same rate it was in the Dark Ages, the 1300s. For the first time in centuries, we have to tell our children they may not have a better life than their parents.” Orchard was one of several presenters who spoke at the 2017 Manufacturing in America Summit, sponsored by Siemens and Electro-Matic, which more than 2,000 people attended at General Motors’ Renaissance Center in Detroit.

Historically, growth has always been driven by revolutions in manufacturing. First it was by steam. Second was by electricity, and the third indus-trial revolution was by automated mass produc-tion. “Each represented a huge leap forward,” said Orchard. “If you want to grow, you have to produce more. We’ve sent manufacturing off-shore, chasing low-cost labor from country to country. Low-cost labor eventually becomes high-cost labor.” Orchard explained how industry has focused on relocating manufacturing facilities to emerging countries with lower costs of living. Over time, wages rise in those countries, and corporations have to move operations again to find lower-cost labor.The digital enterprise is about proximity to consum-ers, no longer off-shoring or building mega facto-ries, said Orchard.

“We’ve been producing things the same way for 50 years, so now we’ve turned to the tech sector,”

said Orchard. “We’ve failed to increase productivity because we haven’t reinvented manufacturing. Now, the same Moore’s Law that’s put a computer in your child’s Xbox has changed manufacturing. The cost of key technologies has been dropping. Speed has improved, cost has dropped, and production has increased.”

Much of the reason for shorter time to market, higher profitability and more product has been the introduction of digitalization, and more specifically the digital twin. “When we talk about the digital twin, we’re not just talking about the product,” ex-plained Orchard. “Siemens has extended the digital twin throughout the entire value chain. We’ve cre-ated a digital enterprise. You can identify problems in the design and problems in manufacturing. Bottlenecks can be improved without ever commit-ting a physical resource.”

Siemens runs months of production in a digital simulation to look for electrical, software and auto-mation. “We can actually generate the automation code the machine will need,” explained Orchard. “We can revolutionize the way we do commission-ing. We make sure it works. We can train operators in the virtual world. We take that manufacturing blueprint and hand it over to the MES to coordinate all of that to make sure the plant behaves and the product is made right the first time. We can provide native access to the digital twin.”

Siemens already has attempted this in 320 plants. Siemens’ electronics factory in Amberg, Germany,



makes 1 million products per month. “That’s one every second, and products are delivered within 24 hours,” explained Orchard. “Since we’ve digi-tized, we’ve reduced 200 defects/million to just 10. Amberg had 1,200 people working when we started. And we still have 1,200 people working, but pro-duction has increased ninefold.”

Siemens’ success has come from innovation. Complacency is the enemy of innovation, but how does a company learn to innovate? “Innovation is an overwhelming word, and we often think it doesn’t apply to us,” said Josh Linkner, author of Hacking Innovation. “Like so many companies, Ringling Bros. and Barnum & Bailey became intoxicated with their own success, and now they’re out of busi-ness. Cirque du Soleil took a new approach, and now they perform for sold-out crowds throughout the world. Cirque du Soleil is valued at $2 billion and growing.”

Augmented reality, the Internet of Things, 3D printing, robotics, sensors and automation are all converging and creating a storm of change. “We can no longer rely on the rules of the past,” said Linkner. “The rules of the game have fundamentally changed. The one thing that can’t be outsourced or automated is human creativity.”

Linkner offered five big ideas that are obsessions to innovators.

1. Get curious. “The more curious we are, the more creative we become,” explained Linkner. “We’re very good at pattern recognition. Any time you’re about to make a decision instinc-tively, pause and ask, ‘Why not? What if?’”

Linkner told the story of Jessica O. Matthews, a Nigerian woman who is a Harvard graduate. She’s also the CEO of Uncharted Play and the inventor of the Soccket soccer ball, which har-vests energy from the athletes kicking the balls and can use that energy to run a light bulb for up to eight hours.

2. Crave what’s next. “Letting go is harder to do when you’re having success,” warned Linkner. “Too often, we overestimate the risk of try-ing something new, but we underestimate the risk of standing still. What if we apply planned obsolescence to our daily work? When you’re stuck on a problem, look for a borrowed idea. We can get great inspiration by borrowing from a company that’s outside our viewpoint.”

3. Defy tradition. There are many traditions that can and should be upheld, said Linkner. “But traditions in our professional lives can be deadly,” he cautioned. “Let’s look that tradition squarely in the eye and defy it. Don’t change for the sake of change, but challenge it. Make a list and see what would happen if you flipped it upside-down and did the opposite. You might find ones that work.”

4. Get scrappy. “We think of innovation as an equation that’s tied to our balance sheet,” explained Linkner. “The real DNA of innova-tion is grit—drawing on internal resources and doing more with less. Throw your imagination and creativity at those big problems.”

5. Adapt fast. “The myth of innovation is that a single lightning bolt of inspiration followed

For the first time in centuries, we have to tell our children they may not

have a better life than their parents.



by mindless execution is how things happen,” warned Linkner. “Take the weight of the world off of your shoulders. Micro-innovations can turn into great results. It’s more about the speed at which you respond.” Linkner shared the

entrepreneurial story of Tom Lix, founder of Cleveland Whiskey, a premium distillery that has changed the rules of the whiskey industry with its pressurized technology that reduces the aging process from 10 years to a few days.



Launch your IIoT strategy sooner than laterBy Anurag Garg

As you’re aware, the Industrial Internet of Things (IIoT)—a fast track to the future of businesses—has taken off. Although the resulting new products are just beginning to hit the streets, companies like Tesla, Google, GE and Ford have all invested in technologies and automation.

And while change and innovation take time, manu-facturers that haven’t implemented an IIoT strategy are at a severe disadvantage. By the time the first products from these powerhouse companies hit the market, businesses that haven’t invested in, say, artificial intel-ligence will have lost their opportunity to compete because the time gap is too great.

According to Bill Ruh, chief digital officer for GE, “Industrial companies that don’t invest in data [IIoT] now will eventually be like consumer companies that missed the internet.”

CREATING AN IIOT STRATEGY

The next 5-10 years of innovation are set to completely change industry. Now is the time to implement an IIoT strategy, which is critical to a business’ future success. An effective IIoT strategy should include the following:

DEFINED FEATURES AND FUNCTIONALITY

To remain competitive in the next 5-10 years, a company needs to identify and define the features and functionalities that will carry them into the future. Key questions to ask: • What features and functionalities will be most

needed and expected by our current or targeted customer base?

• What features and functionalities is our competi-tion currently developing?

• What strong value multipliers does our company want to add to our products?

BRIDGING THE GAP

Comparing where your company is with where it needs to go is the first step to making critical decisions. Es-sentially, you need to evaluate what it will take to meet your goals. Key questions to ask: • How big is the gap we need to bridge between

where we are and where we want to be? • What technologies do we need to integrate to

meet our goals? • What is standing in our way from getting our

products to where we want them to be?

CREATE AN IMPLEMENTATION PLAN

Identify and prioritize the necessary steps to meet your product goals. The implementation plan may be revised, but having a roadmap in place is critical to ensuring that your company is always moving forward. Key questions to ask: • What small or easy-to-implement changes can be

made to quickly improve features and functional-ity and add more value to the market?

• What areas do we need to further explore or research to meet future goals?

• What are the most important features and func-tionalities that need to be implemented in a timely manner?

SMART MACHINES AREN’T BUILT IN A DAY

An ideal example of a successfully-implemented IIoT strategy is Google’s AI-driven cars. Their product won’t be available for purchase for several years, but



the time they have invested in this product has placed them well at the front of the race to produce smart vehicles. At this point, other car manufacturers that are just getting started on this future technology may as well drop out of the race. Don’t let this happen to you with your products.

While your company likely isn’t producing smart

cars, there is a growing list of expectations for utilizing smarter machines in manufacturing. Data from IIoT, AI and automation opens the door to new possibili-ties for refining and innovating products. The sooner you implement an IIoT strategy, the more poised your company will be to remain competitive and maintain your customer base.

Now is the time to implement an IIoT strategy, which is critical to a business’ future success.



How to justify your first IIoT trialBy Steve Diogo

From 10,000 feet up, the Industrial Internet of Things (IIoT) dazzles: it’s a gleaming vista of connect-ed machines that do the jobs they were designed to do while providing the data that can tell their owners how to drive continual improvements in efficiency, safety, productivity and profitability. But come down to earth—to the executive suite, the IT department and the plant floor—and you will mostly find questions that leave different business units struggling to chart a clear path forward or even to decide whether to take the first step at all.

Where do you start if you’re the guy charged with developing your company’s first IIoT initiative? It’s an important question. According to Dave Petrucci, analytics, engineering and IoT VP at the industrial consulting company Genpact, it’s the most important question there is, and it can be summed up in three letters: ROI.

“We’ve heard the McKinseys, GEs and Ciscos of the world talk about the high-level story, but people on the floor still have questions, starting with, ‘where’s my IIoT box?,’” Petrucci said. “This is the challenge when you start talking to the different business units. There is an expectation that this is magic. Engineers don’t like magic. CFOs like it even less.”

Beyond the magic, real barriers remain, ranging from business units locked in silos to the belief that, in the end, the IIoT is just another IT investment or, worse, another dose of hype that just won’t pay off. Moving past these obstacles requires vision and practi-cality, Petrucci said. Vision to create new marketplaces and leapfrog competition, and practicality to drive the step change that can result in real business outcomes.

IS YOUR BUSINESS READY?

For those who are ready to begin an IIoT trial, Petrucci lists five areas of readiness that need to be identified before a successful IIoT initiative can get underway.Mission readiness refers to clearly identifying the problem you’re trying to solve. And it needs to be spe-cific and concrete in order to gain buy-in and maintain momentum. “If you’re just doing this to throw analyt-ics and technology at a general problem, that’s prob-ably not the right reason to do it,” Petrucci said. “But if you’re trying to drive out costs or create a new revenue stream or fundamentally change the way you do busi-ness, that’s a good reason to do it; and it’s a reason that has a measurable ROI.”

Asset-readiness means understanding what needs to be connected to achieve the desired goal, then deter-mining the optimal way to make those connections. “It’s not about throwing a sensor on everything,” Pe-trucci said. Instead, it’s about identifying the necessary variables to run your process and determining the best way to capture the information required to analyze and optimize them. “Everyone keeps telling you that data is cheap,” Petrucci said. “And data is cheap. But data management is probably one of the most expen-sive things in your organization. So how do you define what data you really need and what you don’t?”

IT/OT convergence readiness. “Like it or not, the information technology and operational technology roles are colliding, and if you look at the resources that are in those roles today, they’re not the skills or even the people that are going to be in those roles two or three years from now,” Petrucci said. “There needs



to be an evolution of skill sets and people who have a broader view of how these two areas interact.

Organizational readiness means having the people and skills in place to handle the challenges of IIoT design and operations. “People have been telling you for the past few years that you need data scientists and PhDs in machine learning. But real operational companies don’t have these skills,” Petrucci said. “You really need to assess if you have what’s needed to move ahead.”

Execution readiness refers to one simple question: Can this be run in a daily operation? “There’s a differ-ence between science projects and programs that can gain the trust of upper management to run the real operations of the business,” Petrucci said. “You need to have sufficient organizational alignment and clarity of mission to move a project from a science project to an investment that be leveraged to improve the business.”

If these f ive areas of readiness are less than ready, then fundamental work needs to happen before any IIoT initiative can be put into motion, Petrucci warned. But if an enterprise can confi-dently check off these f ive boxes, then it’s time to move to a pilot program.

STARTING ON THE WRONG FOOT

The traditional—and wrong—way to implement new technology is pick a cool technology, figure out how to implement it, then hope it will solve a business problem down the road. “If this what you’re doing, stop,” Petrucci said. The first step is to define the busi-ness problem you want to solve. “It’s as simple as going to your corporate metrics and asking, what are the three things that are going to make the CTO or CFO or CEO successful? Dig into those and define how you’re going to support those through all of this new technology.” Once these metrics have been identified, there are four steps to designing your pilot: Define the business issue you want to affect; identify the data you need to affect it; determine how you are going to col-lect, store and analyze that data; determine what you need to sensor.

Remember, there is no magic IIoT box. And there is no magic path to the promise of IIoT functionality. Successful pilot programs require alignment of goals and people and multiple levels of readiness. Without these, Petrucci says no IIoT program can succeed. But with them, the promise of business transformation can be made real. ”

Successful pilot programs require alignment of goals and people and multiple levels of readiness.



Today it’s pretty hard to pick up an industry trade publication or Google anything related to manufac-turing and not find an article on the promise of the Industrial Internet of Things (IIoT). Combine the IIoT with advancements in cloud computing and cyber-physical systems (autonomous smart physical assets), and the experts say the stage is set for new manufacturing realities to evolve. Gartner’s Emerg-ing Technology Hype Cycle put the IIoT firmly at the “peak of inflated expectations.” Despite the hype, we will be—or are—bearing witness to the begin-ning of what many are calling Industry 4.0, the next industrial revolution.

Those old enough to remember carbon paper, over-head transparencies, fax machines, and phone booths as critically important business tools will no doubt be optimistic. The IIoT promises to redefine or add to the capabilities that organizations must master to be competitive, and it promises to do so sooner rather than later. Rest assured that it will have considerable impact. Accenture estimates it could add $14.2 tril-lion to the global economy by 2030. Is your organiza-tion ready?

That said, no one can actually deliver on the com-plete IIoT vision today. This is the stuff of tomorrow’s competitive landscape. Although vendors have been working for more than two decades to develop and perfect smarter instruments, realizing the full prom-ise across a much broader set of assets will require significant collaboration, development work, and the establishment of a great many new standards.

However, organizations should not use this as an excuse to wait to get started on better leveraging data from connected assets. There is a great deal you can

do to ensure that your organization doesn’t go the way of the dodo bird. While industry players negotiate the standards required to enable the promise of the IIoT, and Industry 4.0 and IT teams work on organizations’ information “plumbing,” maintenance and operations teams have an opportunity to do some very important foundation work.

I’LL HAVE MY DATA BIG, MY FACTORIES SMART,

AND MY MACHINES CURIOUS AND CHATTY

Forget synergy, rightsizing, future-proofing, and a host of other terms. The new buzzword bingo cards sport terms such as big data, machine learning, and virtual twin. After unprecedented IT spending in the late 1990s, by 2005, many senior executives were tak-ing a hard look at IT spend and demanding better re-turns. Despite this, the risks of chasing new and shiny IT things—to your organization’s detriment—are as real as they were back then. The organization’s focus should be balanced between new IT capabilities and leveraging legacy investments, not just IT investments.

Your plants do not have the benefit of the same kind of trade-up offered by cell phone providers that allow customers to upgrade their phones every two years. IIoT solutions must enable the previous century of capital investment if they hope to see timely adoption, so while your data is big and getting bigger, don’t let that consume all of your focus and attention.

Organizations have significant historical and real-time data that, with advanced analytical tools or machine-learning capabilities, can lead to improved but often incomplete understanding of your assets. You can close some information gaps, but one must also ask, “What am I missing?”

Seize the IIoT in just 3 stepsBy Bruce Hawkins and Scott Bruni



Pervasive sensing (think connected sensors almost everywhere, embedded or otherwise) is one of the keys to realizing the promise of the IIoT. Connected devices are critical and are growing in use, but accord-ing to a 2015 PricewaterhouseCoopers report, only one-third of U.S. manufacturers use smart devices in manufacturing and operations. This leaves a large gap in what’s needed to optimize reliability, safety, effi-ciency, and ultimately financial return. For companies that are limited to legacy sensing investments, most of which were made decades ago to meet minimum automation requirements rather than lifecycle value optimization objectives, the benefits of the IIoT will be significantly limited and challenged in many cases to pay for themselves.

The good news is you aren’t starting from scratch. Your organization has already made investments in sensing that will support realization of the IIoT’s promise. Our experience setting up equipment-health-monitoring solutions would suggest that roughly 60% of the instrumentation needed for critical assets already exists. So we can start there.

STEP 1: KNOW WHAT YOU HAVE

Or, stated more accurately, find out what you have. Do not underestimate the importance of knowing what you have when it comes to developing a win-nable proposal. A solid inventory will give you a head start with prioritizing new needs and identifying where legacy instrumentation investment supports the future vision.

That sounds simple enough, but in practice it is generally far from simple. Most plants’ master equip-

ment lists were developed over many years by multiple contributors. Those contributions were not frequently focused on developing an accurate inventory. Rather, much of the equipment hierarchy was probably created just to facilitate ordering parts, capture costs, or fulfill some other workflow-driven requirement. As a result, the CMMS is generally not the repository for an ac-curate inventory of the organization’s assets. But even if your organization has recently completed a major master-data cleanup, there’s value in confirming the quality of what you have documented against what’s in the plant.

Piping and instrumentation diagrams (P&IDs) can be equally suspect. If your plant has any age on it, chances are that the P&IDs do not accurately reflect the scope of the organization’s assets. A rigorous and disciplined management-of-change process might mean you have a better start than most, but in many cases, P&IDs and CMMS master equipment lists con-tain an incomplete and potentially flawed inventory.

Your people can be a treasure trove of information. Many of your mechanics and operators likely are car-rying around in their heads a considerable inventory of the plant’s assets just from being around the equipment for the past 30-plus years. (If a large number of your experienced, knowledgeable mechanics and operators have recently taken up residency in central Florida to work on their bocce and golf skills, however, you may have already missed that opportunity.)

If your master equipment list is in rough shape, you’ll want to start working on remedying that situa-tion. For some plants, this will be a significant under-taking. It may well require physically walking down

There is a great deal you can do to ensure that your organization doesn’t go

the way of the dodo bird.



the complete asset base to document what you have. The good news is that there is a pretty strong business case (even without the IIoT benefits) for doing this work. According to our research and Doc Palmer, av-erage wrench time in industrial settings falls between 25% and 35%. Effective planning and scheduling facilitated by quality asset master data can increase this to as high as 65%. Effectively doubling the capacity of organization to do work or cutting the labor content of your maintenance work in half will justify a consider-able amount of data cleanup work.

In addition to evaluating the quality of your master data, you’ll want to look at your historical data—both process and transactional data. If a core tenet of the IIoT is deriving more insights from your data, then data quality will impact the value and frequency of those light-bulb moments. Data quality is a bit of a circular logic problem. We tend to not use data that we know is inaccurate, but then its poor quality exists be-cause we don’t use it. Understanding where your data quality issues are will help you understand where your processes and performance management system might need some improvement or discipline.

STEP 2: UNDERSTAND HOW EACH ASSET DRIVES

(OR FAILS TO DRIVE) VALUE

The digital transformation of plants and factories promises many benefits. Most are associated with op-timizing availability and reliability. Filling the gap in sensing to support this transformation requires knowl-edge of the risks to equipment availability and reliabil-ity. It requires knowledge of how and why assets fail and ultimately what’s critical to drive enterprise value.

However, measuring or even defining value for your operations is not always as straightforward as one might think. Often, the easy part is understand-ing an asset’s potential impact on cash flow (costs and revenue). Operational risk and uncertainty can have a significant impact on shareholder value as well. One need look only at the shareholder impact of the

Deepwater Horizon incident on shareholder value for affected companies. Likewise, there’s a host of dotcom enterprises that demonstrate a history of negative cash flow but enviable valuations, so clearly there is more to value than just reducing spend or expanding revenue.

The good news is you don’t need to prepare a valua-tion. Also, there are proven approaches, based on reli-ability best practices, to help you develop the needed appreciation of how your assets impact value. These are criticality analysis and development, reliability-centered maintenance analysis (RCMA), failure modes and effects analysis (FMEA), and root cause failure analysis (RCFA).

Criticality analysis is an often underappreciated activity. Too often, gut feelings are considered as effec-tive as employing a disciplined, quantitative approach. But if you ask five people, you’ll likely get five different answers on asset rankings. Alternatively, with all the retirements that have happened in the past couple of years, you might get two different answers and, from your recent hires, three puzzled looks. There are sev-eral reasons why an organization should do a critical-ity analysis. As this relates to setting a foundation for IIoT, it’s worth focusing on a few points.

To paraphrase Winston Churchill, the value of the plan is in the planning. Criticality development can be similar. While the end product has tremendous value, the process of reviewing the asset base and identify-ing how systems and equipment contribute to or affect safety, environmental quality, product quality, produc-tion, and ultimately plant economics will provide valu-able insights on the business drivers for improvement and investment. Why is this important? If you are going to grow, you’ll need to justify some investment.

The other important contribution that critical-ity makes to building a solid foundation is that it will serve as something of a road map. A criticality analysis provides priority and informs the level of rigor required in the next part of Step 2, reliability engineering. RCMA, FMEA, and RCFA are proven



approaches that will help you identify new sensing requirements to detect or prevent these failures. As a positive side effect, you’ll also eliminate non-value-adding activities and improve your return on mainte-nance in the process.

STEP 3 (OR IS IT 0?): BUILD YOUR PLAN AND

BUSINESS CASE

It wasn’t so long ago that quality was all the rage in manufacturing industries. Phil Crosby’s “Qual-ity is Free” was required reading, among other books mandated by many employers. While it’s easy to ap-preciate the many lessons Crosby’s book had to offer, the most powerful contribution may have been the title. In many ways, it’s equally true with reliability. But as with many free things, you still have to show up to be able to claim your prize. Showing up in this case means implementing what you’ve learned from the previous steps.

For those who feel stuck in an endless “do loop,” it’s worth noting the chicken-and-egg nature of this busi-ness case. Sometimes you just need the funds to do the work to justify the funds. Many of you, after reviewing the first two steps discussed above, have come to the realization that your situation will require some level of upfront investment and therefore justification. If you find yourself needing to front-load the business case development step, rest easy. The returns for investment in reliability best practices are generous and well-doc-umented (see “Turning Enterprise Asset Management into Real Earnings Per Share” by Robert DiStefano and Scott McWilliams).

The aggressiveness and success of your plan will

depend on how well you develop your business case and connect the recommendations to risk reduction and improved cash flow. This isn’t necessarily just an exercise in math. A business case is a decision-support tool. In some organizations, it’s more about the math. In others, it’s as much an exercise in social engineering as it is a mathematical exercise. Building organization-al momentum and support for investment is frequently more effective than investing in iterative math exer-cises. Executives are more likely to buy into a positive NPV (net present value) if there are a host of people standing up to say they’ll deliver the benefits.

Existing leadership support will also impact the size and scope of the initial business case. If your execs are already pointing to IIoT as a part of their corporate strategy, it may be time to go for broke and budget big. On the other hand, if you expect significant pushback, then a more targeted pilot or proof of concept may make more sense. Support the process in whatever way it makes sense in your organization, but don’t under-estimate the importance of building organizational support and alliances.

As you do this, it’s probably worth broadening your approach to include influencers outside the usual maintenance and operations suspects. Many of your IT organizations already have money to spend and are making investments in the IIoT. It’s not a bad idea to brush up on your IT language skills and make some new friends. It’ll be worth your time and attention to know and influence how IT believes sensing will impact realization of their IIoT visions. If IT is too busy chasing shiny or cloudy things to appreciate the importance of collaboration and the role of sensing in

Executives are more likely to buy into a positive NPV...if there are a host of people

standing up to say they’ll deliver the benefits.



enabling the IIoT, then perhaps a diet of fallen fruit, crabs, and shellfish (favorites of the dodo) would be appropriate.

As for the plan itself, there are too many variables to address here. But there is one key point of guidance worth covering. Engineers tend to focus exclusively on technology, and they ignore the balance of the holy trinity of consulting (people, process, and technol-ogy) at their peril. If you hear Shoeless Joe Jackson whispering through the cornfield outside the plant, then by all means, charge ahead. The rest of us will have to close the loop. To ensure that you realize the business case, you will need to redesign your processes, skill requirements, and potentially the organization to leverage the addition of new information.

Whether you believe the hype of IIoT or not, you can count on significant change in the not-too-distant

future. Some would have you believe that the IIoT will render obsolete what we’ve known for the past quarter-century about driving reliability improvement. On the contrary, the IIoT will not only enable those best prac-tices, but also will make them mandatory to compete. Regardless of whether you believe in silver-bullet solu-tions, remember one thing: Even the Lone Ranger had sights on his guns and didn’t aim with his eyes closed.

Organizations that have strong reliability programs in place will be better positioned to take advantage of what the IIoT has to offer. Their superior knowledge of their assets will ensure that they aim their sensing investments where they’ll have the greatest impact on value. Those that don’t will find themselves on the losing end of a widening gap between top- and bottom-quartile performers—if they don’t suffer the dodo’s fate.



5 steps to getting started with predictive simulationBy John Beadsmoore

The first challenge faced by many businesses new to predictive simulation is how to leverage the maxi-mum value from a predictive-simulation model. Then comes choosing how best to implement the compre-hensive suite of technology and techniques that are part of the most effective simulation solutions. While I suggest seeking advice from internal resources and experienced external-simulation specialists, here see five broad tips that should help you at the onset of any predictive-simulation initiative.

1. KNOW WHAT YOU WANT

While predictive simulation is a powerful tool, to optimize results you need to know which business issues you’re trying to address. Simulation definitely isn’t a panacea for all business ills, but it does provide a means of demonstrating both the immediate and long-term impacts of decisions, replicating dynamically how certain operations, processes, spaces, equipment and resources are going to behave. It gives everyone the op-portunity to see how potential changes might pan out, not just for them as individuals or departments, but for the organization as a whole. As such, the scope of a sim-ulation model is potentially huge, which is why having a clear objective based on business priorities is essential.

2. ENGAGE YOUR STAKEHOLDERS

AS SOON AS POSSIBLE

Stakeholders should be involved in the setting of model objectives and scope before any model building starts. If key stakeholders are fully involved in this

phase, they are forced to fully understand their opera-tions, question assumptions and interact in a way that deepens knowledge on the way to clearer insight. Do-ing this earlier rather than later helps develop human thinking and provide access to the best information in enough time to ensure that the resulting model is the best it can possibly be.

Early stakeholder engagement also provides all those involved with the opportunity to understand and ap-preciate how potential benefits outweigh the pain of change. This not only offers reassurance that decisions have been investigated thoroughly and objectively, but instills all stakeholders with the confidence that a project is on the right track. By removing emotion and subjectivity at an early stage, you’re more likely to reach timely decisions by reducing extensive debate, which in turn expedites timescales and potentially saves large sums of money.

3. START WITH SOMETHING IMPORTANT BUT

ACHIEVABLE

For first-time predictive simulators, the best way to start is to pick one specific business problem to solve and develop a model to achieve this. For example, a particular cell within a manufacturing production line that is causing you problems. Any budgetary and time constraints will be best met through this targeted approach and the resulting model will not only serve to address this specific business issue, but will also es-tablish the simulation foundations which will underpin any future predictive simulation activity.



4. MOVE FAST AND MAINTAIN MOMENTUM

Models aren’t set in stone and can always be tuned to solve other business issues as understanding, needs and perspective change, meaning that a phased, iterative approach to simulation is often the most beneficial. The dynamic nature of models means that they can be re-used to support the evolving demands of the busi-ness, with new opportunities or challenges evaluated to accurately predict the impact of proposed changes to ensure the very best decisions are made.

Also, the latest dynamic-simulation solutions grow with your business (in terms of complexity and size), pro-viding the opportunity to analyze new opportunities and threats as soon as they appear on the business horizon.

5. THINK BIG

It’s important to look beyond your initial model. By

taking problems from the real world into the virtual world, dynamically visualizing the various potential outcomes and selecting the best course of action, simulation affords businesses the luxury of exhaustive testing without the associated risks and costs of testing in a live environment. But, to fully optimize results, simulation must ultimately take its rightful place as an integral business process, underpinning all decisions from the board-level down.

This should be the ultimate simulation goal, as it’s only when simulation is embedded into day-to-day operations that organizations can hope to fully under-stand the dynamic and interconnected nature of their business, providing new insights into how the organi-zation is run, highlighting room for improvement and ensuring optimum efficiency, productivity and (per-haps most importantly) profitability.

By taking problems from the real world into the virtual world...simulation affords businesses the

luxury of exhaustive testing without the associated risks and costs of testing in a live environment.

September 18-20 // Swissotel Chicago

DISCOVER TECHNOLOGY’S TRANSFORMATIVE POTENTIAL

At the third-annual Smart Industry conference, you’ll engage with first-mover organizations on the leading edge of digital transformation and explore ways you can:

• Identify opportunities in your market

• Formulate strategies to launch your digital transformation

• Justify investments for your enterprise

• Implement new processes and technologies

• Measure return on investment and expand your commitment

Register before May 26 to take advantage of our Early Registration Perks. You could win Chicago Cubs tickets!

event.smartindustry.com

SpecialOffer!

Key benefits and features include:

Industry briefings Facility tours

Roundtables Business case tracks

Facilitated networking Roundtables

PM full page ad 3.24.17.indd 1 4/19/2017 12:44:46 PM

http://event.smartindustry.com/

technology report: iiot launch template - smart industry · 2017. 10. 13. · report: iiot launch...

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