ABSTRACT
Industrial AI (IAI) can be defined as a systematic discipline focusing on the development, validation, deployment, and maintenance of AI solutions (in their varied forms) for industrial applications with sustainable performance.
This chapter discusses the key enablers of this transformative technology and its significant advantages. As Industry 4.0 emerges, manufacturing environments are becoming not only more dynamic and connected but also inherently more complex, with additional inter-dependencies, uncertainties, and large volumes of data generated.
Recent advances in IAI have showcased the potential of this technology to assist manufacturers through its data-driven predictive analytics and capacity to assist decision-making in highly complex, non-linear, and often multistage environments. However, the industrial adoption of the technology is not yet widespread. Essentially, it remains in the experimental pilot stage. Real environments provide unique and difficult challenges, and the technology is not ready to tackle these.
The aim of this chapter is thus twofold. First, it presents a systematic review of current IAI, focusing on its application in real manufacturing environments to identify the main enabling technologies and core design principles. Second, it formulates a set of key challenges and opportunities to be addressed by future research, along with a conceptual framework to bridge the gap between research in this field and the manufacturing industry, with the goal of promoting industrial adoption through a successful transition towards a digitised and data-driven companywide culture. In other words, this chapter provides a clear definition and holistic view of IAI in the Industry 4.0 landscape, identifying and analysing its fundamental building blocks and ongoing trends.
This chapter also gives a brief overview of the effects of the new technologies. It explains how they are changing the manufacturing process and how machines are getting smarter thanks to AI. The Industry 4.0 concept has revolutionised manufacturing and promises a better, more efficient future. This analysis focuses on how AI is integrated, what benefits it brings, and how it improves basic programming.
