Soft Computing in Smart Manufacturing
This book aims at addressing the challenges of contemporary manufacturing in the Industry 4.0 environment as well as in future manufacturing (aka Industry 5.0) by implementing soft computing -one of the major subfields of artificial intelligence (AI). Learning and predicting capabilities of soft computing techniques (e.g. machine learning) as well as optimization capabilities (e.g. evolutionary algorithms) and other features of AI should be exploited to respond to issues of smart manufacturing.
... The demand for product personalization introduces a high level of uncertainty and requires highly adaptive, agile processes and systems. Increased efficiency and predictive quality are expected from manufacturing processes and systems to accomplish the "first time right" production in a business environment characterized by a dynamic nature, individualization, and mass customization. Therefore, robust and resilient solutions are needed to integrate state-of-the-art soft computing techniques and develop new ones to tackle the above challenges. These solutions should rely on learning, prognostic, and optimization features to successfully address unforeseen events and take into account the availability and status of manufacturing system resources and the need for real-time feedback and (re)action, as well as address specific concerns of security and effective human-system collaboration. This volume is intended as a text book for students at the postgraduate level (doctoral and master studies) interested in the applications of soft computing in manufacturing and industrial engineering, and as a reference for academicians and researchers in universities and developers in research institutes, working both in soft computing and manufacturing and industrial engineering fields, as well as for professionals in the industry. This book contributes to the development and application of soft computing systems, including links to hardware, software, and enterprise systems, in resolving modern manufacturing issues in complex, dynamic, and globalized industrial scenarios. It addresses the heterogeneous complementary aspects such as control, monitoring, and modeling of different manufacturing tasks, including intelligent robotic systems and processes, modeling and parametric optimization of advanced conventional and nonconventional manufacturing processes, cybersecurity framework for Internet of Things-based systems, addressing trustworthiness and resilience in machine-to-machine and human-machine collaboration, in static and dynamic digital twins integration in a smart manufacturing, in Standard for Exchange of Product compliant Numerical Control (STEP-NC) technology for a smart machine vision system, and in integration of Open Computer Numerical Control (CNC) with Service-Oriented Architecture (SOA) for STEP-NC monitoring system. The opening chapter offers a comprehensive review of the various aspects of contemporary manufacturing such as machining technology, computerized numerical control, automation, robotics, integrated manufacturing systems, and computer integrated (flexible) manufacturing. This is followed by application of the major soft