Putting Industry 4.0 and the Industrial Internet of Things to work in smart factories
Cover story: Industry 4.0 and Industrial Internet of Things (IIoT) are enabled with connectivity to and from devices (from a sensor to a large-scale control system), data, and analytics. Sensors and systems need connectivity with a greater network to share data; analysis allows people to make informed decisions. Industry 4.0 is working for German kitchen manufacturer, Nobilia. Ask three questions on the way to a smarter factory.
Connectivity technology has sparked a significant shift in society where the Internet plays an ever-increasing role in our daily lives as a growing number of devices become Web-enabled, and these concepts can be applied to improve manufacturing efficiencies. The trend of greater connectivity, often referred to as the Internet of Things (IoT), is only a precursor to the avalanche of growth on the horizon, however. The Business Insider news site estimates that by 2017, 82% of companies will have an IoT application implemented into their businesses in some way. [This is part of the June Control Engineering cover story on Industry 4.0 and Industrial Internet of Things to help make smarter factories.]
Let's take a step back and dive deeper into how we define IoT. Breaking it down to its basic components, IoT consists of four basic elements: the actual device, connectivity to and from that device, data, and analytics. The device can be anything from one sensor to a large-scale control system. Sensors and systems need connectivity with a greater network to share the third element—the data generated by the sensor or system. The analysis of this data generates actionable information, allowing people to make informed decisions as a result.
More information, faster
An example of this from the consumer space would be enabling a shoe to track usage info, such as number of days worn per week, how many hours per day, how many hours spent running, or which part of the sole took the most pressure. This information would allow the shoe manufacturer to build a better shoe, perhaps enabling the creation of a more customized product in the future based on individual use of the previous product. This same model is now being applied to cars. By connecting cars to the cloud and monitoring driving habits and car feature usage, auto manufacturers are leveraging this information to improve new car designs.
The evolution of the Internet has enabled instantaneous information delivery to the consumer, changing the behaviors in people's daily lives. In much the same way, connectivity and data analysis will change the operations of the factory, the behaviors of personnel in manufacturing industries, and the way we think about production.
Putting this into practice for industry, often referred to as the Industrial Internet of Things (IIoT), devices or assets connect to the cloud or local information technology (IT) infrastructure to collect and/or transmit data. This data can then be analyzed, providing insight about the device or asset.
For example, sensors monitoring the operating temperature in mechanical components can track any abnormalities or deviations from an established baseline. This allows the company to proactively address undesired behavior as predictive maintenance before crippling system failures can develop, which would otherwise lead to plant downtime and lost production revenue. Information of this magnitude offers incredible value to the enterprise, helping to influence new product designs, streamline system performance, and maximize profitability.
Flexible manufacturing, Industry 4.0
As with IoT, use of connectivity to drive new insights and optimizations can be applied to a manufacturing process and overall supply chain. This is one of the core concepts of Industry 4.0, a technological movement, commonly referred to as the fourth industrial revolution.
Industry 4.0 working group Acatech defines the first industrial revolution as the invention and widespread implementation of the steam engine during the 18th century. The second major revolution in industry was the use of conveyor belts for assembly line manufacturing in the early 1900s (Henry Ford's "Model T" factory). The third industrial revolution was defined by the development of microelectronics, specifically the PC and programmable logic controller (PLC), in the mid-1900s. This leads us to today's fourth revolution, where the connectivity of PCs and machines to the Internet has enabled the creation of cyber-physical systems.
Industry 4.0 will be fully realized with the computerization of traditional industries within manufacturing. Using IoT and this concept of cyber-physical systems will result in the implementation of the "Smart Factory," enabling unparalleled manufacturing flexibility while maintaining exceptionally lean operational efficiency. In the realm of manufacturing, an area of significant focus is not only on the product, but on the process of making that product.
Manufacturers need flexible manufacturing lines that can quickly adapt to rapidly changing customer demands. This calls for flexible machines that are able to run a multitude of product types, with the ultimate goal of profitable production at reduced lot sizes, enabling a complex mixture of products to be run and filled on-demand.
Today, manufacturers also are evaluating how to use big data to get more out of the capital equipment currently in use, while ensuring that new equipment will be built with highly connected control systems. This is where PC-based machine controls solve real connectivity and data challenges. The successful implementation of a Smart Factory really boils down to a convergence of traditional automation technologies (AT) with tools and processes from IT. As such, PC-based control systems are ideally positioned to meet and even exceed the demands of Industry 4.0 concepts.
Industrial PC (IPC) hardware that uses the latest highly efficient and fast processor technology provides flexibility that traditional "black box" controllers cannot provide without adding great expense. While easily processing real-time logic and motion control algorithms, there is plenty of extra processing power within industrial PCs for data collection and communications to higher level systems, such as enterprise-level databases or even the cloud.
Leveraging the power of modern multicore CPUs, the data from the machine or line can be analyzed directly on the controller, with only the results sent back to upstream systems. This is known as "on the fly" analytics or "edge computing." This method greatly reduces the amount of raw data that must be stored on servers, either on premises or in the cloud, and reduces the amount of network traffic being generated. Systems using analytics on the machine controller will run leaner and more efficiently as the results of the analysis can be immediately used to influence the operation. This, in turn, enables manufacturers to implement far greater functionality while minimizing delays in production previously caused by enterprise level "number crunching" and data storage.
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