The Intelligent Factory

"Industry 4.0: Smart Factories" comes after our first book "Industry 4.0: Navigating the Manufacturing Revolution in ASEAN" (2019), and takes us through the key technologies as the pillars to build up a Smart Factory to transform the current manufacturing operations into a brand new model driven by the innovation based on the real-time data collection, processing and analysis. We also present our understanding of the principles of building a real smart factory. As a surging region, ASEAN is on its way to gain a lot of value from this round of revolution and catch up with the leading economies and find our place in the global value chain.

Collected here are 112 papers concerned with new directions in manufacturing systems, given at the 41st CIRP Conference on Manufacturing Systems. The high-quality material includes reports of work from both scientific and engineering standpoints.

Research efforts in the past ten years have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Concepts and Methods puts these advances in perspective, showing how process industries can benefit from these new techniques. The book consolidates results developed by leading academic and industrial groups in the area, providing a systematic, comprehensive coverage of conceptual and methodological advances made to date. Written by leaders in the field from around the world, Smart Manufacturing: Concepts and Methods is essential reading for graduate students, researchers, process engineers, and managers. It is complemented by a companion book titled Smart Manufacturing: Applications and Case Studies, which covers the applications of smart manufacturing concepts and methods in process industries and beyond. Takes a process-systems engineering approach to design, monitoring, and control of smart manufacturing systems Brings together the key concepts and methods of smart manufacturing, including the advances made in the past decade Includes coverage of computation methods for process optimization, control, and safety, as well as advanced modelling techniques

Disruptions in global supply chains have rarely ever caused more headlines than at the moment. The nature of internationally connected supply chains has been to take advantage of globalization strategies for sourcing, production and distribution of products and materials. Consequently, there is hardly any industry that is not highly globalized and vulnerable to disruption. Now, while these disruptions have varying impacts on industries and individual companies, the hypothesis discussed in this book is that executing a strict digitalization strategy based on Industry 4.0 principles helps manufacturing companies master these disruptions and even turn them into opportunities. Implementing Indus- try 4.0 strategies increases productivity and agility for manufacturing operations and provides much higher visibility. Consequently, the resiliency against supply chain disruptions is significantly increased. This book covers: - Introduction to Industry 4.0 principles - How to execute an Industry 4.0 strategy - Insights into SAP’s strategy Industry 4.Now - Case study examples

Research efforts in the past decade have led to considerable advances in the concepts and methods of smart manufacturing. Smart Manufacturing: Applications and Case Studies includes information about the key applications of these new methods, as well as practitioners’ accounts of real-life applications and case studies. Written by thought leaders in the field from around the world, Smart Manufacturing: Applications and Case Studies is essential reading for graduate students, researchers, process engineers and managers. It is complemented by a companion book titled Smart Manufacturing: Concepts and Methods, which describes smart manufacturing methods in detail. Includes examples of applications of smart manufacturing in process industries Provides a thorough overview of the subject and practical examples of applications through well researched case studies Offers insights and accounts of first-hand experiences to motivate further implementations of the key concepts of smart manufacturing

Condition modelling and control is a technique used to enable decision-making in manufacturing processes of interest to researchers and practising engineering. Condition Monitoring and Control for Intelligent Manufacturing will be bought by researchers and graduate students in manufacturing and control and engineering, as well as practising engineers in industries such as automotive and packaging manufacturing.

This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.

Artificial Intelligence (AI) technologies enable manufacturing systems to sense the environment, adapt to external needs, and extract process knowledge, including business models such as intelligent production, networked collaboration, and extended service models. This book therefore focuses on the implementation of AI in customized manufacturing (CM). The main topics include edge intelligence in manufacturing, heterogeneous networks, intelligent fault diagnosis and maintenance, dynamic resource scheduling in manufacturing, and the construction mode of the smart factory. Based on the insights of CM and AI, the authors demonstrate the implementation of AI in the smart factory for CM, including architecture, information fusion, data analysis, dynamic scheduling, flexible production line construction, and smart manufacturing services. This book will provide important research content for scholars in artificial intelligence, smart manufacturing, machine learning, multi-agent systems, and industrial Internet of Things.