AI as an enabler for long-term resilience in manufacturing

Abstract

Artificial Intelligence (AI) will increase the level of intelligence in the manufacturing industry by promoting, inter alia, the matching of production and demand, improving quality inspection, increasing product yield, reducing product failure rates, and improving production efficiency. While the last decade of Industry 4.0 was determined by technology-driven innovation, the coming years will focus on data- and intelligence-driven innovation. In this perspective, AI is an enabler for the transition from smart factories towards intelligent factories with self-optimising and self-healing characteristics. While smart factories are capable of applying previously acquired knowledge, intelligent factories will be able to autonomously acquire new knowledge and apply it for self-optimisation purposes. The 2020 World Manufacturing Report: Manufacturing in the Age of Artificial Intelligence has already reported on the potential of AI in manufacturing. AI applications impact the resilience, efficiency, and scalability of manufacturing operations and have become increasingly significant during recent disrupting events like the current COVID-19 pandemic or the blockage of the Suez Canal . Resilience is defined as the ability of a system to withstand potentially high-impact disruptions and is characterised by the ability of a system to proactively mitigate or absorb the impact of disruptions, and quickly recover to normal conditions. According to several scholars, Industry 4.0 and AI play a major role in achieving more resilient factories and circular value chains. The aim of this whitepaper is to develop recommendations for the adoption of AI in factories based on identified challenges, for long-term resilience in cognitive manufacturing.