The Genesis
The term Industry 4.0 was first used in 2011 at the Hanover Fair, the world’s biggest industry exhibition where a set of recommendations were presented to the German Federal Government. The notion caught on, and was supplemented by a McKinsey interview between their experts and executives of Robert Bosch. The crux of the ideas is interconnected networks of machines, sensors and products, resulting in intelligent value chains. The phrase 4.0 recognizes and pays tributes to the previous three industrial revolutions, driven by steam & water power, the advent of mass production with Henry Ford and the IT & Electronics Revolution in the 1960~70 era.
The Paradigm
Though the term “Industry” has many connotations, its reference in this particular perspective encompasses the broad enterprise which is required to realize a product, both in the discrete and the process kind of manufacturing. A typical value chain in such an industrial context would involve the flow of both material as well as information. The paradigm shift in Industry 4.0 is the way in which information is generated, shared and analyzed in order to address the typical manufacturing challenges.
The motivation behind Industry 4.0 is to achieve specific objectives. It intends to enhance product innovation through better feedback of the product in its usage scenario. Collaboration is enhanced between different elements of the value chain. The manufacturing process itself is greatly enhanced, due to better measurement, control and analysis mechanisms. And all of these are made possible due to the evolution of cyber physical systems.
Cyber-physical systems enable physical systems to be connected in the cyber world, thus enabling better interaction and control mechanisms. Imagine every device in the world, having its own IP address and being able to communicate with other devices in networks. The advantages are many, and significant! We refer to this as the Internet of Things, which will change the way we interact with physical devices, much as the same way in which the internet has changed information and communication systems.
The marriage of cyber physical systems into the manufacturing enterprise thus gives birth to the “smart factory” or “The Factory of the Future”. There is a significant improvement in the usual parameters by which conventional manufacturing systems are evaluated, like safety, quality, time and cost. There are additional, path breaking benefits like flexibility, self- adaptability, self-learning, adaptive tolerance definition and control, greater visualization and better risk management. Needless to say, automation levels improve drastically and are also more efficient and effective. Complexity levels would also drastically reduce in greatly spread out global operations and supply chains!
The Enablers
The internet, in its various forms has been in widespread use for at least two decades now. However, the single most important enabling factor in its increasing application in smart manufacturing has been the corresponding up gradation of the hardware elements, specially sensors and mechatronics to a level to which the speed, bandwidth and efficiency of the internet can be applied for real time data gathering, process monitoring and control. Listed below is a description of the key enablers to a successful Industry 4.0.
Apart from these enablers, it is imperative to have critical resources like human resources, enabling infrastructure and the right legal and regulatory frameworks in place. Technical standards are also a good measure of the maturity of a technology and its application, and such efforts are underway with initiatives like the International Standard for Metadata Registries. Another interesting debate is the choice of open vs. closed systems. Since manufacturing has traditionally been a closed system, with production systems rarely been discussed about outside the plant, the extent of usage of open source is in question
The Application
At the core of the application of Internet of Things in Manufacturing is the creative ways in which data from sensors can be applied across all activities. With the advent of embedded sensors of all shapes, sizes and sensory capabilities & mechanisms, deeper visibility and control of the whole process is now feasible.
1. Seamless and Connected Operations
The ability of Internet of Things to deliver real-time data is changing the way production systems communicate within themselves. The complexity in these systems inherently stems from the dependencies within each other, and most wastage, delays and mistakes often happen because the material or the information does not reach the right process at the right time. The Internet of things not only solves these problems but also provides a way to proactively reconfigure systems based on the situation.
2. Better Operations Visibility
The Internet of Things, along with the plant network provide better visibility across all the operations of the company. It leads to increased automation and reduces variation due to human involvement. With the help of PLCs, both measurement and control in real time are possible. This would play an important role in sectors like automotive, where traceability of not just the final product but also the components which are assembled into it is required to be implemented and stored for specified periods. The same data can also be shared with suppliers in order to improve their turnovers.
3. Robust and Optimized Shop floor Asset Management
Though most companies have been implementing asset management activities, the ability of machines to now intelligently send and receive information has changed the extent to which proactive plans can be based around them. In many cases, configuration setting as well as troubleshooting is automated, thus reducing the burden of the Engineering and the maintenance departments as well as their need to rely upon the equipment provider to attend to such activities. Upgrades can also be done in situ. These capabilities are in fact, enabling more and more machine makers to move from segregated product and service models into integrated revenue models, which also integrated them tighter into the manufacturing company’s supply chain. A similar example could be derived from the aerospace industry where engine makers directly monitor aircraft engine maintenance and often attend to them directly, in interaction with the end customers, the airlines.
Aniruddha M S 