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, Industrial
Jiewu Leng, Weinan Sha, Baicun Wang, Pai Zheng, Cunbo Zhuang, Qiang Liu, Thorsten Wuest, Dimitris Mourtzis, Lihui Wang
Summary: Industry 5.0 aims to prioritize human well-being in manufacturing systems, achieving social goals beyond employment and growth for the sustainable development of humanity. However, research on Industry 5.0 is still in its early stages and lacks systematic exploration. This paper reviews the evolution and characteristics of Industry 5.0, discusses its connotation system and diversified essence, and proposes a tri-dimensional system architecture for its implementation. It also examines key enablers, future implementation paths, potential applications, and challenges. The limitations of current research are discussed, and potential future research directions are highlighted.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Management
Marcos Dieste, Guido Orzes, Giovanna Culot, Marco Sartor, Guido Nassimbeni
Summary: This study challenges the assumption of a sustainable Fourth Industrial Revolution by identifying the possible unintended negative impacts of Industry 4.0 (I4.0) technologies on sustainability, highlighting the motivations and actions to mitigate such impacts, and evaluating alternative assumptions. The results reveal various unintended negative effects on environmental and social aspects, providing insights into the reasons, severity, and corrective actions for these impacts.
INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT
(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)
Review
Chemistry, Multidisciplinary
Anbesh Jamwal, Rajeev Agrawal, Monica Sharma, Antonio Giallanza
Summary: Industry 4.0, as a new industrial revolution, encompasses data management, manufacturing competitiveness, production processes, and efficiency. Sustainability plays a crucial role in business strategy and is highlighted in achieving manufacturing sustainability. The study findings suggest that Industry 4.0 technologies are instrumental in achieving manufacturing sustainability.
APPLIED SCIENCES-BASEL
(2021)
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
Computer Science, Artificial Intelligence
Jung-Chun Liu, Ching-Hsien Hsu, Jia-Hao Zhang, Endah Kristiani, Chao-Tung Yang
Summary: Smart manufacturing is a major trend in the manufacturing industry, enabled by the Internet of Things and Big Data technology. This paper uses Apache Kafka to process and store real-time production data in a big data system. The performance of Kafka in terms of throughput and data transfer rate is analyzed, and it is found to be efficient and scalable.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Alberto Martinez-Gutierrez, Javier Diez-Gonzalez, Paula Verde, Ruben Ferrero-Guillen, Hilde Perez
Summary: Smart Manufacturing is characterized by digitization and massive communication of Cyber-Physical Systems under the Industrial Internet of Things paradigm. However, the lack of interoperability due to communication protocol heterogeneity hinders asset connectivity. The implementation of interoperability is crucial for decision-making in decentralized self-organized production hierarchies. To address this technological challenge, the authors propose a hyperconnected demonstrator, connecting heterogeneous assets in an inspection process automation case study.
Article
Automation & Control Systems
Jiewu Leng, Shide Ye, Man Zhou, J. Leon Zhao, Qiang Liu, Wei Guo, Wei Cao, Leijie Fu
Summary: Blockchain technology is driving business and industrial innovation as a new generation secure information technology, but its applications in Industry 4.0 are facing challenges such as scalability, flexibility, and cybersecurity issues. This study discusses cybersecurity issues in manufacturing systems and proposes metrics for implementing blockchain applications, providing insights for future research directions in blockchain-secured smart manufacturing.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Review
Computer Science, Interdisciplinary Applications
Yue Yin, Pai Zheng, Chengxi Li, Lihui Wang
Summary: The combination of AR and DT has attracted growing research interest in academia and industry, especially in the context of the human-centric trend. AR has the potential to integrate operators into the new generation of HCPS, with DT as a pillar component.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Energy & Fuels
Fernando Matsunaga, Vitor Zytkowski, Pablo Valle, Fernando Deschamps
Summary: This paper discusses the sustainability issue of improving energy consumption efficiency through technology and methods. The research includes systematic review, experiments, and result discussion.
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME
(2022)
Article
Chemistry, Analytical
Petr Ilgner, Petr Cika, Martin Stusek
Summary: Recent developments in mMTC scenarios have led to unprecedented requirements, triggering the Industry 4.0 revolution. The focus is on ensuring reliability, communication security, and flawless functionality of critical infrastructure. This paper discusses network grid architecture, communication strategies, and methods for building scalable and high-speed data processing and storage platforms, with a specific focus on data transmissions using the IEC 60870-6 (ICCP/TASE.2) standards.
Review
Engineering, Chemical
Hossein Abedsoltan
Summary: This paper reviews the applications and trends of plastics in the automotive industry, explores the potential of plastics in automotive innovation and sustainable practices.
POLYMER ENGINEERING AND SCIENCE
(2023)
Review
Computer Science, Interdisciplinary Applications
Hector Canas, Josefa Mula, Manuel Diaz-Madronero, Francisco Campuzano-Bolarin
Summary: This article focuses on the advances, advantages, limitations, requirements, and methodologies in implementing the strategic Industry 4.0 (I4.0) initiative, particularly in the field of production planning. It proposes a taxonomy of I4.0 design terms and presents models, algorithms, and components used in an I4.0 setting.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Goncalo Roque Rolo, Andre Dionisio Rocha, Joao Tripa, Jose Barata
Summary: Research explores the use of Digital Twins to predict and understand the execution of distributed manufacturing control systems. However, due to the early stage of Digital Twins technology, existing implementations are far from standardized, requiring analysis and solution development based on individual cases.
APPLIED SCIENCES-BASEL
(2021)
Review
Agronomy
Sara Oleiro Araujo, Ricardo Silva Peres, Jose Barata, Fernando Lidon, Jose Cochicho Ramalho
Summary: Investing in technological research is crucial for the development of sustainable solutions in agriculture, leading to the transition to Agriculture 4.0. This article reviews emerging trends from the past decade, focusing on their real-world applications, discussing challenges and future research opportunities, and presenting a cloud-based IoT architecture as a foundation for designing smart agricultural systems.
Review
Computer Science, Information Systems
Luis A. Estrada-Jimenez, Terrin Pulikottil, Sanaz Nikghadam-Hojjati, Jose Barata
Summary: The concept of smart manufacturing has gained significant attention in recent years due to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces autonomous and self-organized elements that can self-manage and make decisions in context-aware and intelligent infrastructures. These solutions contribute to social impact and sustainability by developing adaptable, reusable, and shareable task-specific resources.
Article
Engineering, Chemical
Bruno Silva, Ruben Marques, Dinis Faustino, Paulo Ilheu, Tiago Santos, Joao Sousa, Andre Dionisio Rocha
Summary: This paper presents the process of introducing Artificial Intelligence in plastic injection molding processes in a company in Portugal. The implementation includes data collection, real-time classification, and prediction alert to reduce the production of non-compliant parts, increase productivity, and decrease costs and environmental impact.
Article
Engineering, Chemical
Nelson Freitas, Sara Oleiro Araujo, Duarte Alemao, Joao Ramos, Magno Guedes, Jose Goncalves, Ricardo Silva Peres, Andre Dionisio Rocha, Jose Barata
Summary: This work develops a system that extracts and evaluates useful data to predict energy consumption in automotive spot welding using machine learning models. The method is validated in robotic cells that meet Volkswagen and Ford standards.
Article
Chemistry, Analytical
Joao Pinelo, Andre Dionisio Rocha, Miguel Arvana, Joao Goncalves, Nuno Cota, Pedro Silva
Summary: This study explores the viability of a low-power, cost-effective wireless communication solution for maritime sensing data. Through measurements of RSSI, SNR, and LOS, we showcase the potential of LoRaWAN transmissions to achieve communication distances exceeding 130 km in a LOS-free scenario over the ocean. These findings highlight the promising capabilities of LoRaWAN for reliable and long-range maritime communication of sensing data.
Article
Computer Science, Information Systems
Ricardo Silva Peres, Alexandre Manta-Costa, Jose Barata
Summary: Despite data scarcity being a significant challenge for industrial AI adoption, federated learning can serve as a potential catalyst for collaborative industrial AI. However, there are still unresolved issues regarding its application in smart manufacturing scenarios. This research aims to provide a common framework for collaborative industrial AI in smart manufacturing, addressing collaboration, data privacy, ownership, and security challenges.
Review
Computer Science, Information Systems
Terrin Pulikottil, Luis A. Estrada-Jimenez, Jose Joaquin Peralta Abadia, Angela Carrera-Rivera, Agajan Torayev, Hamood Ur Rehman, Fan Mo, Sanaz Nikghadam-Hojjati, Jose Barata
Summary: Big data in manufacturing shop-floor includes structured and unstructured data collected at every stage of the production process. The utilization of tools, techniques, and best practices is necessary for leveraging the advantages of data-driven performance improvement and optimization. Understanding the approaches and techniques at various stages of the data life cycle is also important. This study provides a narrative literature review of trends and challenges in the field, supported by n-grams analysis, and offers a detailed examination of current trends and existing challenges in different data life cycle stages.
Article
Computer Science, Information Systems
Sara Oleiro Araujo, Ricardo Silva Peres, Leandro Filipe, Alexandre Manta-Costa, Fernando Lidon, Jose Cochicho Ramalho, Jose Barata
Summary: The agricultural sector faces water scarcity and needs innovative management methods. The ID3SAS methodology integrates various technologies to support decision-making, resulting in reduced water consumption and increased crop production.
Proceedings Paper
Automation & Control Systems
Terrin Pulikottil, Luis A. Estrada-Jimenez, Jose Barata
Summary: This paper presents a smart maintenance framework for shop-floor, based on distributed intelligence with two major blocks - innate and adaptive intelligence.
Article
Computer Science, Information Systems
Duarte Alemao, Andre Dionisio Rocha, Sanaz Nikghadam-Hojjati, Jose Barata
Summary: Scheduling in manufacturing presents a significant opportunity for companies to excel in a rapidly changing world. This work proposes a set of requirements and design principles based on the concept of axiomatic design to standardize the design and development of manufacturing scheduling solutions. By providing a generic framework for smart manufacturing scheduling and evaluating it in a practical use case, this paper contributes to the field of Industry 4.0.
