Artificial Intelligence Applications in Industry 4.0

Abstract

After Industry 1.0 for Mechanization, Industry 2.0 for Electrification, Industry 3.0 for Automation, and Industry 4.0 (I4.0) for Digitalization and networking, we are marching very fast towards Industry 5.0 for Personalization. We shall take a look at the applications and challenges of I4.0 especially in its main scope Artificial Intelligence (AI). I4.0 is mainly powered by the Industrial Internet of Things (IoT) and cyber-physical systems which, by default, are smart, autonomous systems that use algorithms to monitor and control machines, robots and vehicles. I4.0 expects everything in the supply chain to be very smart from manufacturing to warehousing and also logistics. I4.0 also interconnects with back-end systems, like Enterprise Resource Planning, to give companies an uninterrupted level of visibility and monitoring. Truly, I4.0 is a significant part of any organization's transformation towards digitalization. In I4.0, we move digitally from the Internet and client-server technologies to ubiquitous computing, bridging the gap of both logical and physical entities of cyber environments. It merges of Information Technology, Operational Technology which caters technologies like IoT, Big Data, cloud, etc., with additional catalysts like advanced robotics and AI which enable I4.0 with automation and optimization in entirely new ways that lead to opportunities for Innovation and Automation. IT systems are used for data-centric computing; IT systems monitor events, processes, and devices, and make adjustments in enterprise and industrial operations. I4.0 majorly targets Small and Medium Enterprise(SME) which is the economic backbone of any country. I4.0 tries to merge broadly nine digital industrial technologies: IOT, augmented reality, big data, autonomous robots, system integration, cloud computing-digital ubiquity, cyber security, simulation, and additive manufacturing. Hence, the challenges and applications also cater to all these interdependent technologies. When we say challenges, it spreads across these domains individually and also the combinations of these technologies. Hence, it gets complicated as the number of technologies being combined increases, also proportionately with the complexity of each technology. Along with these technological issues, I4.0 also needs to take care of ethical and sustainability issues which are more challenging. The challenges of I4.0 at the basic level spreads from defining the strategy for changing, maximizing results, and interconnections of various sections of the organization. Challenges also include personnel to adapt to the newer working environment, readiness to share the data with the integrated module. In other words, they should be assured of utmost data security and rely on the outcomes. It should mainly work for Circular Economy and Sustainability. Regarding the application of I4.0 especially AI, it covers all the domains, machines, and gadgets that make our thinking and lives better and easier. AI is not meant to replace human beings, but to support and add on to their skills and outcome. It caters to NLP, RPA, AI-optimized hardware to Market Automation. As the main aim is to mimic human thinking and response, it has to draw a conclusion out of hundreds or thousands options while considering ethical, efficiency, environmental, and humanity issues attached to it. Each one is a vast issue by itself. For example, RPA itself caters six more broad categories, i.e., SCM, HR, CRM, accounting, F/S, and healthcare. All these can be further divided. Things become complicated when they are merged for interdependency. AI-optimized hardware has varied applications in agriculture, household appliances, gadgets, teaching and learning, research, etc. Hence, I4.0 has varied applications for both industries and human livelihood. At the same time there are respective challenges which slows down the complete implementation of I4.0.

Topics & Concepts