Industry 4.0 — Facing the Coming Revolution

Stephen DeAngelis

October 12, 2015

“With disruptive forces of change so pervasive around the world,” writes Jeff Dobbs, Global Sector Chair for Industrial Manufacturing at KPMG, “it would be easy to believe that the manufacturing sector is in the midst of a massive transformation. Dig a little deeper, however, and it quickly becomes apparent that — while the enablers of transformation are all around us — few manufacturers are truly transforming. Instead, most are tweaking and adjusting their business models and operating structures in preparation for the battle they know must come.”[1] What KPMG calls an imminent transformation of the manufacturing sector others call a fomenting revolution being fueled by the Internet of Things (IoT), big data, and artificial intelligence. This new industrial revolution is sometimes referred to as Industry 4.0. For example, analysts from Strategy& and PwC write, “The fourth industrial revolution — characterized by the increasing digitization and interconnection of products, value chains and business models — has arrived in the industrial sector.”[2] Whether you believe the revolution “has arrived,” like Strategy& and PwC analysts, or “must come,” like KPMG analysts, Industry 4.0 is going to change the manufacturing sector forever. Simon Jacobson, research vice president at Gartner, has outlined four key aspects of Industry 4.0 that impact the supply chain.[3] They are:

 

1. Smart factories Automated and flexible manufacturing processes that are integrated with customers and business partners in support of product lifecycle changes — will impact current factory layouts.

 

2. The Internet of Services – Connecting production facilities across geographies and company boundaries to create virtual production capabilities will create new business models and disrupt current supply chain designs.

 

3. Advanced Analytics – Capitalizing on big data and predictive analytics — to drive flexibility at the process level, not just production lines or factories — will put more pressure on organizations to use production data to its fullest.

 

Focus on the knowledge worker – The rise of smart machines will not see the demise of the knowledge worker — rather, this increasing complexity demands supply chain professionals expand their problem solving and systems engineering skills.

 

One can’t really discuss big data and predictive analytics without discussing artificial intelligence systems (specifically cognitive computing systems). The Internet of Things will generate so much data that the term “big data” will be deemed inadequate to describe it. Analyzing all of that data for insights and recommendations will be beyond the capability of humans without the assistance of cognitive computing systems. Mark Jaffe, CEO of Prelert, explains, “It’s simply impossible for humans to review and understand all of this data — and doing so with traditional methods, even if you cut down the sample size, simply takes too much time.”[4] The answer, Jaffe says, is employing the power of artificial intelligence (AI), especially machine learning. Cognitive computing systems will also play a vital decision making role in Industry 4.0. Most routine decisions will be made by such systems and human decision makers will only be alerted when an anomaly occurs. This will free them to focus on the most important business decisions — and there will be a lot to focus on. “Industrial manufacturers are facing potential disruptive forces from many directions — new technologies are emerging, their competitors are ramping up their speed of innovation and the technology innovation cycle is shortening,” notes Todd Dubner, a Principal in KPMG’s strategy practice for Industrial Manufacturing. “Given all of this rapid change, it’s not surprising that manufacturers believe they need to be ‘innovation-led’ in order to win in the new environment.”

 

Rob van der Meulen (@bobvdmeulen), Gartner’s public relations manager in the United Kingdom, agrees that business leaders have a lot of things they on which they must focus. [5] He writes, “While the true impacts of Industrie 4.0 are to be seen in the years to come, today chief supply chain officers (CSCOs) need to look beyond existing silos and functions.” He goes on to describe five areas in which a holistic approach is required. They are:

 

1. Supplier management – The dynamic ‘reconfigurability’ of supply networks that Industrie 4.0 promises requires re-examining service-level agreements with upstream and contracted suppliers. Dedicated capacities, enhanced risk profiling, IP protection and the reliability of materials will all need to be included.

 

2. Supply chain visibility – To respond as quickly as possible to planned and unplanned events, the supply chain needs to be as transparent as possible. This will in turn increase productivity and reduce risks.

 

3. Demand Planning – Mass customization requires a connection of production capabilities, with the supply chain based on a clear understanding and translation of fluctuating demand patterns into targeted production units.

 

4. Supply network design – To achieve agility and supply resiliency without compromising time to market, supply networks will need realignment. A 2014 Gartner study showed that this is an area where many companies fall short of expectations. As smarter factories take root, ensuring that alignment is done in a holistic way — not just within manufacturing or logistics — will be critical.

 

5, Product Innovation Platforms – Products as we know them are changing. New physical devices, such as products, tools or even factory equipment, will have interconnected technology embedded in them. The way things are manufactured will require new thinking, and what new IT calls ‘product innovation platforms’, which aim to define and design products but also to manage product lifecycles.

 

Cognitive computing can help in every one of those areas. By drawing appropriate data from throughout an enterprise, a cognitive computing system can help create corporate alignment by ensuring that all departments are operating using a single version of “the truth.” The Enterra Solutions® offering in this field, the Enterra Enterprise Cognitive System™ (ECS), is a revolutionary approach for coordinating data throughout an organization. The ECS is a fully configurable platform, but we also have pre-configured solutions ready to go for a variety of industries.

 

Conclusions

 

As noted above, Industry 4.0 is being fueled by the IoT, big data, and artificial intelligence. Abigail Phillips (@AbbyPhillips89) indicates that these forces will combine to help “manufacturers think bigger than ever before” in at least three ways.[6] They are:

 

1. Monitoring product quality proactively Cloud computing. Cloud data storage. The Internet of Things. All these factors have collided to create a golden opportunity for manufacturers, who can now use massive data volumes in unexpected new ways. … All this data enables manufacturers to keep a much closer eye — or ear — on product quality. Big data doesn’t just reassure manufacturers that they’re producing high-quality products — it also convinces their customers. Manufacturers now provide an incredible breadth and depth of data on their products’ construction and testing, establishing up front that they’ve delivered something of lasting value. …

 

2. Seeing the future – and changing it Operational analytics are great at telling us what just happened and why. Manufacturers have been doing that kind of analysis for years. But they’re now using the predictive aspects of big data to monitor their operations against their quality standards. That often means predicting when a machine or tool is about to break — before it starts churning out defective products. Predictive analytics tell us what’s about to happen. Prescriptive analytics show us how to make machines do what we want. These disciplines are the crown jewels of business intelligence. Both require vast amounts of data — and the ability to analyze it effectively. That’s what big data delivers for today’s manufacturers. … Predictive analytics isn’t a new discipline. But until recently, its high cost made it practical for only very expensive products or shop equipment. New tools are making predictive analytics a way of life for manufacturers of all sizes. And as the Internet of Things continues to mature, manufacturers are gathering more and more data automatically.

 

3. Getting customers into the data-collection game — The winners in our new data-driven economy will be the companies that can gather vast amounts of data and turn it into actionable processes within their supply chain. For manufacturers, the data gathering doesn’t stop at the boundaries of the organization — it includes information collected at customer sites. Sensors come into play here, too. It’s becoming highly cost-effective for manufacturers to embed sensors into the products they deliver to customers — and the data they’re getting back is well worth the small investment in hardware. By extending the quality control process beyond purchase and throughout the life of their products, manufacturers now gather information that catapults their products to higher levels of performance better design, and longer lifespan.

 

Andrew Dugenske, Director of the Factory Information Systems (FIS) Laboratory, and Alain Louchez (@AlainLouchez), Managing Director of the Center for the Development and Application of Internet of Things Technologies (CDAIT) at Georgia Institute of Technology, write, “Around the globe, intelligent and pervasive industrial automation has been catapulted in recent years to a top national or regional priority. Known by different names, e.g., ‘Advanced Manufacturing’, ‘Smart Manufacturing’, ‘Industry 4.0’ or ‘Factories of the Future’ to highlight a few, these initiatives all bear the same characteristics, i.e., transforming the manufacturing process from a patchwork of isolated silos to a nimble and seamless whole fully integrated with the downstream and upstream production environment.”[7] If your company has yet to make the transformation into an Industry 4.0 digital enterprise, now is the time to start.

 

Footnotes
[1] Global Manufacturing Outlook, KPMG, 2015.
[2] Volkmar Koch, Simon Kuge, Reinhard Geissbauer, and Stefan Schrauf, “Industry 4.0: Opportunities and challenges of the industrial internet,” Strategy&, 2014.
[3] Rob van der Meulen, “A Blueprint for Digitalizing the Value Chain from Factory to Customer,” Gartner, 10 September 2015.
[4] Mark Jaffe, “IoT Won’t Work without Artificial Intelligence,” Wired, November 2014.
[5] Van der Meulen, op. cit.
[6] Abigail Phillips, “3 ways big data is changing the future of manufacturing,” Global Manufacturing, 27 August 2015.
[7] Andrew Dugenske and Alain Louchez, “The Factory of the Future Will Be Shaped by the Internet of Things,” Manufacturing.net, 19 August 2014.