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Smart Manufacturing and the Internet of Things

September 14, 2015


“Manufacturing worldwide is on the cusp of a revolution,” writes Kevin O’Marah (@komarah), chief content officer, and Pierfrancesco Manenti (@PierManenti), VP of research at SCM World. “New information technologies are suddenly offering not only to make the management of manufacturing more effective, as we saw with early versions of plant and enterprise software, but the work itself smarter.”[1] McKinsey analysts, Markus Löffler and Andreas Tschiesner, agree. “In manufacturing,” they assert, “the potential for cyber-physical systems to improve productivity in the production process and the supply chain is vast.”[2] O’Marah and Manenti explain that the reason the Internet of Things (IoT) is going to make manufacturing smarter is because it will significantly improve visibility in each and every step of the manufacturing process. “Technologies based on the Internet of Things,” they explain, “have the potential to radically improve visibility in manufacturing to the point where each unit of production can be ‘seen’ at each step in the production process. Batch-level visibility is being replaced by unit-level visibility. This is the dawn of smart manufacturing.”


According to Kylie Jane Wakefield, taking advantage of the IoT is a matter of survival. “In a marketplace where companies increasingly need to do whatever they can to survive,” she observes, “those that don’t take advantage of connectivity are lagging behind.”[3] Despite the imperative to modernize and connect manufacturing processes, John Nesi, Vice President of Market Development at Rockwell Automation, told Wakefield that, a year ago, only 10 percent of industrial operations could be classified as connected enterprises. O’Marah and Manenti agree that the number of connected enterprises is relatively small; but, they insist, that situation is changing. “SCM World’s recent field survey on smart manufacturing and the Internet of Things finds that while one in five today admit their factory operations are offline completely, this will drop to near zero in five years.” PwC analysts have found that the number of connected enterprises in the U.S. is already growing. They report, “35% of US manufacturers are currently collecting and using data generated by smart sensors to enhance manufacturing/operating processes.”[4]


Nesi explained to Wakefield why enterprises are transforming. “Global competitive pressures are challenging industrial and manufacturing companies to drive inefficiencies out of their systems, manage workforce skills gaps and uncover new business opportunities.” The PwC analysts conclude, “The world is hurtling into an era of deep data inter-connectivity.” Clearly, it’s not just connectivity that is going to make such a big difference in manufacturing in the decades ahead; it’s analyzing all of data that is going to be created by that connectivity that will provide the big breakthroughs. OpenText Manufacturing Industry Strategist, Mark Morley (@MarkMorley), has identified four areas where the IoT and associated analytics will shape manufacturing in the years to come.[5] They are:

Incoming Materials – Determining what is coming in a shipment and where that shipment is located helps manufacturers make better decisions. Managers need to be able to dive down into individual suppliers whether they are in China or Europe.

Shop Floor – Manufacturers want to know how machines are performing on the shop floor, specifically with regards to maintenance. When you have an assembly line full of robots, it can be devastating when you have to take one offline or if it stops all by itself. Being able to analyze and predict when issues may occur is very valuable.

Distribution – What good is a product if you can’t put it in the hands of the customer? Being able to monitor the performance of distributors such as DHL or FedEx and making sure a product arrives on time are important for all manufacturers.

Aftermarket – Once a product has shipped, IoT and analytics are keys to making sure the product is maintained and has maximum uptime, notes Morley. Whether it’s a generator or airplane engine, having granular insight into a product’s performance improves customer satisfaction.

In other words, Morley sees the benefits of end-to-end supply chain visibility made possible by the IoT. O’Marah and Manenti agree. They explain:

“Smart manufacturing is about creating an environment where all available information — from within the plant floor and from along the supply chain — is captured in real-time, made visible and turned into actionable insights. Smart manufacturing comprises all aspects of business, blurring the boundaries among plant operations, supply chain, product design and demand management. Enabling virtual tracking of capital assets, processes, resources and products, smart manufacturing gives enterprises full visibility which in turn supports streamlining business processes and optimizing supply and demand.”

Ultimately, I believe that manufacturers will be adopt what I call a Cognitive Value Chain™ that involves corporate digital transformation, the Internet of Things, and cognitive computing. Cognitive computing systems can handle many more of the confounding variables that can affect operations than traditional computer systems. In Accenture’s latest technology vision entitled “From Digitally Disrupted to Digital Disrupter,” analysts state that cognitive computing will provide the “ultimate long-term solution” for many business challenges. Although that might sound like hype, O’Marah and Manenti explain, ‘”In essence, smart manufacturing is a decision-making environment.” And cognitive computing systems excel in such environments. Bain analysts, Michael C. Mankins and Lori Sherer (), note that decision making is one of the most important aspects of any business. “The best way to understand any company’s operations,” they write, “is to view them as a series of decisions.”[6] They explain:

“People in organizations make thousands of decisions every day. The decisions range from big, one-off strategic choices (such as where to locate the next multibillion-dollar plant) to everyday frontline decisions that add up to a lot of value over time (such as whether to suggest another purchase to a customer). In between those extremes are all the decisions that marketers, finance people, operations specialists and so on must make as they carry out their jobs week in and week out. We know from extensive research that decisions matter — a lot. Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.”

Allowing AI to make routine decisions frees human decision makers to concentrate on more important decisions. O’Marah and Manenti agree, they explain, “Smart manufacturing includes proactive and autonomic analytics capabilities, making smart manufacturing an intelligent and self-healing environment. With smart manufacturing, organizations can predictively meet business needs through intelligent and automated actions driven by previously inaccessible insights from the physical world. Smart manufacturing transforms businesses into proactive, autonomic organizations that predict and fix potentially disruptive issues, evolve operations and delight customers, all while increasing the bottom line.”


[1] Kevin O’Marah and Pierfrancesco Manenti, “The Internet of Things Will Make Manufacturing Smarter,” IndustryWeek, 14 August 2015.
[2] Markus Löffler and Andreas Tschiesner, “The Internet of Things and the future of manufacturing,” Insights & Publications, June 2013.
[3] Kylie Jane Wakefield, “How The Internet Of Things Is Transforming Manufacturing,” Forbes, 1 July 2014.
[4] “The Internet of Things: what it means for US manufacturing,” PwC, 2015.
[5] Michael Singer, “4 Areas Where IoT and Analytics Can Shape Manufacturing,” OpenText Analytics, 15 July 2015.
[6] Michael C. Mankins and Lori Sherer, “Creating value through advanced analytics,” Bain Brief, 11 February 2015.

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