Special Issue: Leading Information and Communication Technologies for Smart Manufacturing: Facing the New Challenges and Opportunities of the 4th Industrial Revolution
Volume 109, Issue 4
Special Issue Papers
This article provides a wide overview of the latest progress of in situ monitoring and control in powder bed metal additive manufacturing, showcasing solutions from both research and industry.
This article proposes to design, develop, and implement the new DMAIC (define, measure, analyze, improve, and control) methodology for the six-sigma quality management of additive manufacturing.
This article presents the architecture of an AI-driven customized smart factory, showcasing intelligent manufacturing devices, intelligent information interaction, and construction of a flexible manufacturing line.
This article surveys and discusses, with project case studies, the latest software technologies to collect, manage, and elaborate all data generated by Internet of Things (IoT) deployed over a production line.
This article proposes an approach to endowing robots with the capability of autoprogramming of assembly tasks with minimal human assistance that is based on “learning from observation” and “robotic embodiment.”
Based on the analysis of literature approaches and real-world use cases, this article identifies and discusses the main challenges that need to be faced for a tight integration of control and wireless communication in smart manufacturing.
This article discusses the challenges of smart manufacturing based on artificial intelligence and information communication technology from a wireless networking perspective.
This article presents and discusses the cybersecurity risks in the emerging digital manufacturing (DM) context, assesses the impact on manufacturing, and identifies viable approaches to secure DM.
This article deals with the cybersecurity issues posed by the Industry 4.0 era, with specific regard to industrial control systems (ICSs), and presents a unified architectural approach to proactively address these issues.
This article addresses the redeployment of intelligent algorithms and learning for evolving smart cyber–physical production systems (CPPSs) with a comprehensive domain-specific language (DSL), DSL4hDNCS.
This article focuses on the digital twin (DT), one of the key concepts of Industry 4.0, and proposes a methodology for DT design using modeldriven engineering (MDE) that strives toward being both flexible and generic.
This article envisions a connective framework to support the engineering of cyber–physical production systems (CPPSs) in smart manufacturing through the use of a set of digital twins consistent with the real system throughout its lifecycle.
This article revisits the programming paradigm that is currently used for lock-free multicore programming and explains its extension to the system level, exploring its application to two important developments in industrial design.