Data is the raw material from which we make decisions. With the proper context, data becomes information, and when faced with a problem, we use this information to make the best decision we can to solve it. As we adopted more computer- and PLC-based controls for Industry 3.0, there was a movement to automate the collection of data to make it faster, more accurate, and more comprehensive than what manual collection methods could support. For Industry 3.0, data has been used for control systems, production reporting, and compliance records. As we move to Industry 4.0, our dependence on data increases exponentially to maximize the efficiency of existing production systems and solve manufacturing challenges that were thought to be impossible.
Industry 4.0 describes how manufacturing is evolving to leverage modern and future advances in computer power and connectivity, and data is the lens through which these computer systems interpret the physical world and communicate with each other. Any Industry 4.0 technology is directly reliant on data. An augmented reality application might combine data from cameras, maintenance records, and real-time and historic machine performance data to guide a technician to solve a problem. The digital twin is a fit-for-purpose virtual representation of a physical product or process achieved by synchronizing real-time data in the physical world with its digital model in the virtual world. Advanced analytics and machine learning can automatically identify and contextualize trends in machine data to predict failures for major equipment. Each of these Industry 4.0 applications relies on verbose and accurate data to deliver its value.
Industry 4.0 needs data the same way the brain needs its senses: it is how they connect intelligence with the outside world.
It means you are going to collect and keep more data than ever before. It will also lead to the integration of more disparate data sets from new sources and systems, including product lifecycle management (PLM), enterprise resource planning (ERP), supply chain management (SCM), warehouse management (WMS), and computerized maintenance management (CMMS). As we see more data being used in more applications, the accuracy and integrity of that data becomes critically important; decisions and actions that are based on poor data can be catastrophic.
While the effort needed to collect, coordinate, and contextualize the data required of Industry 4.0 may be significant, the returns can optimize and transform a business. From optimizing supply chains and minimizing disruptions, to reducing new product introduction times, to connecting directly with customers and delivering personalized products, Industry 4.0 can give you a competitive edge today—but it will be an expectation and a requirement tomorrow.
Industry 4.0 is changing the way we manufacture products. It enables us to be more efficient, more sustainable, and more responsive to changing market conditions. Realizing that vision and value requires us to connect intelligent computing and processing systems to the real world, data is the interface that allows the virtual world to connect and communicate to the physical one, and the most fundamental building block that enables Industry 4.0.
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