We’re rapidly approaching three centuries since the onset of the original Industrial Revolution, commonly thought to have begun around 1760. The latest incantation of this ongoing process has been dubbed Smart Manufacturing (in the U.S.) or Industry 4.0 (in Europe), and it represents the fourth industrial revolution that has changed production systems:
- Industrial Revolution #1 (circa 1760): occurred through the introduction of mechanical production facilities powered by water and steam.
- Industrial Revolution #2 (circa 1900): happened through the introduction of mass production, based on the division of labor and powered by electrical energy.
- Industrial Revolution #3 (circa 1970): occurred through the introduction of electronics and information technology (IT) for a further automation of production.
- Industrial Revolution #4 (today): based on cyber-physical production systems.
This latter revolution is what we’re in the midst of, no matter what it is called. It is characterized by highly intelligent cyber physical systems that can autonomously perform end-to-end activities along the value chain.
Industry 4.0 is a project in the high-tech strategy of the German government that promotes the computerization of traditional industries such as manufacturing. The goal is the intelligent factory (Smart Factory) that is characterized by adaptability, resource efficiency, and ergonomics, as well as the integration of customers and business partners in business and value processes. Its technological foundation is comprised of cyber-physical systems and the Internet of Things. Experts believe that Industry 4.0 or the fourth industrial revolution could be realized within the decade; it’s certainly well underway.
In the United States, an initiative known as the Smart Manufacturing Leadership Coalition (SMLC) is also working on the future of manufacturing. SMLC is a non-profit organization of manufacturing practitioners, suppliers, and technology companies; manufacturing consortia; universities; government agencies; and laboratories. The aim of this coalition is to enable stakeholders in the manufacturing industry to form collaborative R&D, implementation, and advocacy groups for development of the approaches, standards, platforms, and shared infrastructure that facilitate the broad adoption of manufacturing intelligence.
What do these developments portend? This concept of production will substantially raise the technological complexity of value-adding processes still further in comparison to the situation that exists today. Mastering this degree of complexity calls for suitable software tools to design and construct the relevant plants and systems, and naturally also to operate them. It is urgently necessary that these tools be developed and launched over the coming years. Across the globe, governments, industrial federations, and corporations have recognized the significance of creating their own added value through production.
In Smart Manufacturing, everything is connected with the aid of sensors and RFID chips. For example, products, transport options, and tools will communicate with each other and will be organized with the goal of improving the overall production, even over the boundaries of individual companies. In this production environment, the product itself is an active part of the production process. This seamless integration of the physical and virtual worlds is only possible because every element exists simultaneously, both as a physical and a virtual model.
The Deployment of Cyber Physical Systems
The basis for any significant deployment of cyber physical systems is a seamless data connection across every stage of the value-adding process. For each product, alongside its actual physical depiction, a virtual depiction continues to undergo further development. Consequently, optimum integration of the real and the virtual worlds is the focus of those on the leading edge Smart Manufacturing development and implementation.
A key component of Smart Manufacturing is decentralizing control: Intelligent components operate in each stage of the assembly system through which a part moves. In this type of assembly process, communication occurs at each step to determine what pieces to add or assembly steps to implement. Decentralized control makes it easier to add or change out parts as needed, making it smoother to meet the increasing demand for mass customization.
More than $4 billion has been invested in software companies since 2007, with the aim of enabling digital depiction of the value chain. It is only through complete integration of the individual, value-adding steps that it will be possible to achieve all conceivable advances in productivity.
The Wave of the Future
As this latest industrial revolution moves ahead, there are significant implications for the industrial workforce. Software is driving the advances in today’s manufacturing, and this means that the mouse is replacing the wrench in many places on today’s factory floor.
Having the right people in place is critical to leveraging technological gain, and to realizing the goals of Smart Manufacturing. This has led to much discussion of the shortage of qualified workers in the labor pool, often referred to as the “skills gap.” As baby boomers retire over the next decade, they take critical knowledge and skills that isn’t being replenished by emerging graduates of colleges and technical schools. According to the U.S. Department of Education, “60 percent of the new jobs that will emerge in the 21st century will require skills possessed by only 20 percent of the current workforce.”
Exacerbating the problem is the incorrect notion that manufacturing careers are dirty and poorly compensated. As the Washington Post reported in May 2014, many students are simply not interested in careers offered by industry.According to Raj Batra, president of the Industry Automation Division at Siemens, “it’s critical that we let students, parents and administrators know what these jobs look like and what students need to learn in order to get them. Then we need to provide the training necessary to solve this problem.”
Academia can’t do it alone. “Siemens is taking an active role in building the talent pipeline by driving students into STEM (Science Technology Engineering and Math) fields through a variety of programs starting at the primary school level and continuing through post-secondary institutions,” Batra noted. A great example is the new UI Labs, a public-private partnership to advance digital manufacturing institute in Chicago where Siemens is one of six Key Investors and a Consortium Partner.
No matter what the nature of a manufacturing company, the vision of Smart Manufacturingand consequently the integration of the virtual with the real value chainfrom product development through production and servicing will result in optimizationof the value chain.
From Siemens’ perspective, there are three core elements to this evolution:
- Manufacturing execution. Manufacturing execution will play an even more important role. The degree of connectivity between the automation level and the manufacturing execution system (MES) will increase significantly, also across the borders of companies and locations. The integration of Enterprise Resource Planning (ERP) and MES levels will also advance to achieve complete transparency as well as connectivity to business data. That means that all necessary information is available in real time.
- The merging of the product and production life cycle. The second core element is the merging of product and production life cycle based on a common data model. This will allow manufacturers to meet the challenges that result through ever-shorter product life cycles, both technically and in business.
- Cyber physical systems. Cyber physical systems are a basis for the increase in manufacturing flexibility that results in shorter time to market. These production units can be flexibly integrated into existing production processes. Cyber physical systems combine communications, IT, data, and physical elements using core technologies, including sensor networks; Internet communication infrastructure; intelligent, real-time processing and event management; big data and data provisioning; embedded software for logic; and automated operations and management of systemic activities across enterprises.
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