Artificial intelligence for machining process monitoring

Abstract

Since the early 1980s, implementation of artificial intelligence (AI)-based intelligent machining process monitoring (MPM) has been advancing, parallel to the new AI models and machining technologies. These systems are critical for balancing the tradeoffs among productivity, quality, cost, and sustainability measures of machine tool shops and the broader manufacturing industry. Furthermore, increased demand for high-level process automation, pressure to use less workforce, and data explosion by widely used low-cost sensory equipment have increased the expectation from MPM to become an enabler of the dark factory. This chapter covers a broad range of AI models and techniques used in MPM by providing both algorithmic fundamentals and architectural examples from recent studies. © 2024 Elsevier Inc. All rights reserved.