Why We Need Automation Models: Handling Complexity in Industry 4.0 and the Internet of Things

The Fourth Industrial Revolution is a common buzzword these days. Even though it is somewhat artificial and marketing -inspired, it correctly reflects that the evolution of automation happened in waves driven by technological advances and inventions such as the steam engine, assembly line production, and the introduction of computers and the Internet. A less obvious driver of automation is the separation of power from information, which marked the step from individually crafting workpieces to more efficient, labor-saving series production. With the availability of computers, collecting and processing information in automation systems became the predominant challenge. At the same time, the technology push also provided the basis for making automation systems more complex in many different respects, such as plant size, number of devices and data points, device interaction, real-time and security requirements, and system integration. Handling this complexity required a structured approach, which is why model architectures to break the automation system down into individual structural levels, functions, processes, resources, and organizational aspects had to be devised. This architecture allows automation systems to be described from different viewpoints that address various aspects of such systems. Flexibility, as requested by the manufacturing of individualized products at lot size one, is especially important for distinguishing between the functional and the implementation or deployment views. However, the different models must be integrated along different dimensions to olve application -specific requirements and to optimally map functions to networked computing resources. Of course, providing communication among the resources is an essential topic for this integration and communication solutions that address these requirements have been developed. Over the years, many different models have evolved, in line with progressing technology foundations, and for some time it looked like Internet technology might help reduce the complexity. However, the recent introduction of new concepts like the Internet of Things (IoT) and cloud computing, which paved the way for massively distributed systems and their adoption in novel automation paradigms such as Industry 4.0 or Industrial Internet, lead to a completely new view on automation models and architectures and make them surprisingly more complex again.