Review
Engineering, Industrial
Jeff Morgan, Mark Halton, Yuansong Qiao, John G. Breslin
Summary: This paper provides a fundamental research review of Reconfigurable Manufacturing Systems (RMS) and explores the state-of-the-art in distributed and decentralized machine control and machine intelligence. Key areas reviewed include RMS fundamentals, machine control technologies, and machine intelligence paradigms. The paper establishes a vision for next-generation Industry 4.0 manufacturing machines with Smart and Reconfigurable (SR*) capabilities.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Manufacturing
Aaron D. Neal, Richard G. Sharpe, Katherine van Lopik, James Tribe, Paul Goodall, Heinz Lugo, Diana Segura-Velandia, Paul Conway, Lisa M. Jackson, Thomas W. Jackson, Andrew A. West
Summary: The research aims to demonstrate the implementation of a Cyber-Physical System for monitoring and controlling Returnable Transit Items in the Automotive Industry. It utilizes RFID tags for identification and has developed a real-time model to support decision-making. The study provides practical insights and challenges in asset monitoring and traceability within the automotive sector.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2021)
Review
Chemistry, Multidisciplinary
Prasoon Kumar, Khalid Baig Mirza, Kaushik Choudhury, Magali Cucchiarini, Henning Madry, Pratyoosh Shukla
Summary: Tissue engineering involves assembling cells onto a 3D scaffold to form functional tissue with the guidance of scaffolding systems. Proper understanding of cellular communication in a reactor is crucial for appropriate positioning of cells in a 3D environment during tissue formation. Sensors and actuators integrated with cyber-physical systems can enhance cell communication and tissue morphogenesis.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Business
Manjot Singh Bhatia, Saurabh Kumar
Summary: This article empirically examines the critical success factors (CSF) for implementing I4 technologies in the Indian automotive manufacturing industry. The study finds that data governance is the most critical factor, followed by legal aspects and collaboration and teamwork. These findings provide guidance for automotive manufacturing firms in adopting I4 technologies successfully.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Review
Engineering, Industrial
Fotios K. Konstantinidis, Nikolaos Myrillas, Konstantinos A. Tsintotas, Spyridon G. Mouroutsos, Antonios Gasteratos
Summary: This study evaluates the application of machine vision technology in intelligent factories through a systematic literature review strategy and proposes an assessment framework. The findings indicate that machine vision is widely used in various technological areas of Industry 4.0, such as autonomous robots and augmented reality. By analyzing vision-based applications in the automotive manufacturing process, the study clusters the components and processing techniques of machine vision systems and presents the I5.0 technology maturity assessment framework, guiding the integration of machine vision into intelligent factories.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Huitaek Yun, Martin B. G. Jun
Summary: Smart manufacturing drives the need for new interfaces to facilitate communication between autonomies such as big data analysis, digital twin, and self-decisive control. This study proposes a human interface framework based on virtual reality (VR) for cyber-physical systems, enabling collaboration between humans and autonomies, and its effectiveness has been demonstrated.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Elisa Reboredo, Pedro Espadinha-Cruz
Summary: This paper proposes a maturity model for additive manufacturing (AM) to help organizations in the manufacturing sector determine their level of maturity and presents a case study on an automaker to validate the model.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Ozan Emre Demir, Marcello Colledani, Roberto Paoletti, Giulia Pippione
Summary: Recent advances in smart manufacturing technologies have highlighted the importance of defect mitigation strategies in low-volume production systems, especially in high-tech, high-variety products. This paper proposes a dynamic function-oriented selective and adaptive assembly based on CyberPhysical System (CPS) capabilities to meet changing product quality standards and enhance flexibility. A real-case study in the optoelectronics industry is used to validate the method, emphasizing its benefits in terms of final product quality.
COMPUTERS IN INDUSTRY
(2023)
Article
Automation & Control Systems
Ayoub Chakroun, Yasmina Hani, Abderrahmane Elmhamedi, Faouzi Masmoudi
Summary: Industry 4.0 is a crucial step in the digital transformation of manufacturing companies, enabling increased flexibility, customization, quality, and productivity. This study focuses on implementing a smart manufacturing process for a brass accessories company, utilizing a simulation platform controlled by a dedicated cyber-physical production system and a master production program. The findings demonstrate the successful optimization of Industry 4.0 application, leading to improved production efficiency.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Mathematics
Varun Tripathi, Somnath Chattopadhyaya, Alok Kumar Mukhopadhyay, Shubham Sharma, Changhe Li, Gianpaolo Di Bona
Summary: The present study aims to develop a methodology for cleaner production management using lean and smart manufacturing in Industry 4.0. The results of two case studies show that the developed methodology can achieve a sustainable production system and problem-solving, while enhancing productivity within limited constraints.
Review
Engineering, Industrial
Jiewu Leng, Dewen Wang, Weiming Shen, Xinyu Li, Qiang Liu, Xin Chen
Summary: Digital twins technology can assist designers in effectively simulating various interactions and behaviors of manufacturing processes, thereby reducing the time and cost of physical commissioning and reconfiguration.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Hong-Long Chen
Summary: This study evaluates the impact of Industry 4.0 maturity on corporate financial performance, with a focus on the mediating effects of internal business process performance (IBPP), supply chain performance (SCP), and customer performance. The results show that Industry 4.0 maturity significantly affects IBPP, SCP, and customer performance, which in turn influence financial performance. Industry 4.0 magnifies potential returns mainly through IBPP, SCP, and customer performance.
Review
Engineering, Manufacturing
Till Bottjer, Daniella Tola, Fatemeh Kakavandi, Christian R. Wewer, Devarajan Ramanujan, Claudio Gomes, Peter G. Larsen, Alexandros Iosifidis
Summary: In recent years, there has been a growing hype around Digital Twins (DTs) in both industry and academia. DTs have the potential to increase automation and advance towards Smart Manufacturing. This literature review focuses on DTs at the unit level in manufacturing, specifically in terms of real-time control. The review summarizes the current implementation and operation of DTs, and highlights their potential benefits in four categories: generic reference models, services, DT content (models and data), and DT deployment (hardware and software).
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2023)
Article
Automation & Control Systems
Yoo Ho Son, Kyu Tae Park, Donggun Lee, Seung Woo Jeon, Sang Do Noh
Summary: The study proposes a digital twin-based cyber-physical system for predicting the feasibility of production plans in automotive body production lines, which was experimentally verified to achieve an average prediction performance of 94.02% for actual production plans. This system provides an advanced solution for predicting production feasibility in automotive manufacturing.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Manufacturing
Tianyue Wang, Bingtao Hu, Yixiong Feng, Xiaoxie Gao, Chen Yang, Jianrong Tan
Summary: This paper proposes a data augmentation-based manufacturing quality prediction approach in human cyber-physical systems. A DA-GBDT model is developed to improve the accuracy of quality prediction under the HCPS context. Experimental results show that this method can enhance existing quality prediction methods and provide guidance for product optimization decisions in smart manufacturing systems.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2023)
