Managing complexity in manufacturing: highlights from autonomic computing applications

In recent years, manufacturing sector has experienced a deep digital transformation driven by Industry 4.0 paradigms and the adoption of technologies such as the Industrial Internet of Things and service-oriented architectures. This shift led a significant deployment of distributed software components – often referred to as “services” or “agents” – across hierarchical levels of informative systems. While this evolution has enabled and enhanced data interoperability and production flexibility, it has also introduced new challenges related to complexity, coordination, and reliability. This paper explores the concept of autonomic computing, an approach already adopted in computer science to address these challenges, enabling systems to self-configure, self-heal, self-optimize, and self-protect. Through a systematic review of current approaches and technologies, the study identifies the state of the art of autonomic computing adoption in manufacturing highlighting how it serves in making production environments more resilient, adaptive, and efficient.