Article
Automation & Control Systems
Meifa Huang, Leilei Chen, Yanru Zhong, Yuchu Qin
Summary: This paper proposes a generic method based on fuzzy aggregation operator for multi-criterion decision-making problems in design for additive manufacturing. The method effectively considers interactions of criteria, reduces noise criterion values, and captures the risk attitude of decision-makers, as demonstrated through numerical experiments and examples of additive manufacturing machine and material selection, as well as optimal build direction selection.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Review
Construction & Building Technology
Surayyn Uthaya Selvan, Soultana Tanya Saroglou, Jens Joschinski, Mariasole Calbi, Verena Vogler, Shany Barath, Yasha Jacob Grobman
Summary: Rapid urbanization has negative impacts on the built and biotic environment, requiring interdisciplinary mitigation strategies. Current nature-based solutions integrated into building envelope design have proven beneficial, but they often overlook the potential to support other living organisms. A multi-species approach is envisioned to facilitate more holistic envelope-design solutions.
BUILDING AND ENVIRONMENT
(2023)
Review
Environmental Sciences
Guangdong Tian, Weidong Lu, Xuesong Zhang, Meng Zhan, Maxim A. Dulebenets, Anatoly Aleksandrov, Amir M. Fathollahi-Fard, Mikhail Ivanov
Summary: With the growing severity of environmental problems, low-carbon development has become an inevitable choice. The complexity of low-carbon green sustainable development, influenced by various factors, poses challenges for decision-makers. This paper provides a systematic review and analysis of multi-criteria decision-making (MCDM) techniques in the field of low-carbon transport and green logistics, filling the gap in existing literature. Future directions for MCDM techniques in these areas are also presented.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Roberto Raffaeli, Jacopo Lettori, Juliana Schmidt, Margherita Peruzzini, Marcello Pellicciari
Summary: In the process of design, it is necessary to consider information from multiple fields in order to thoroughly evaluate material properties, compatibility, and reshape design for optimal design results. This paper proposes a structured and algorithmic framework to support designers in evaluating and guiding the adoption of additive manufacturing.
APPLIED SCIENCES-BASEL
(2021)
Article
Automation & Control Systems
Jayakrishnan Jayapal, Senthilkumaran Kumaraguru, Sudhir Varadarajan
Summary: This research aims to establish multiple criteria for evaluating design variations in additive manufacturing and proposes a decision support system based on quantitative metrics. The proposed method demonstrates significant cost reductions by evaluating topologically optimized design variants.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Review
Engineering, Chemical
Yuchu Qin, Qunfen Qi, Peizhi Shi, Shan Lou, Paul J. Scott, Xiangqian Jiang
Summary: This paper reviews the application of multi-attribute decision-making (MADM) methods in additive manufacturing (AM). It presents an overview of existing MADM methods, analyzes published articles, applied methods, and solved problems, and discusses the main issues in applying MADM methods to AM. The research findings are then summarized.
Article
Computer Science, Interdisciplinary Applications
Chen Zheng, Yuyang Du, Tengfei Sun, Benoit Eynard, Yicha Zhang, Jing Li, Xinwei Zhang
Summary: Robotic manufacturing systems play a vital role in the post-pandemic world, and designing suitable systems for SMEs is challenging. This study proposes a distributed multiagent collaborative conceptual design method to assist SMEs in implementing robotic manufacturing systems through the collaboration of designers and suppliers.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Prateek Saxena, Emanuele Pagone, Konstantinos Salonitis, Mark R. Jolly
Summary: A decision-making approach for sand mould manufacturing was developed and implemented, comparing traditional sand moulds with 3D printed sand moulds and analyzing the impact of batch size on mould manufacturing.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Mechanical
Diqian Ren, Jun-Ki Choi, Kellie Schneider
Summary: This study proposes a method to solve the complex process selection in 3D printing applications by creating a new multicriteria decision-making tool. The proposed methodology takes into account the decision-maker's preferences and provides a more accurate selection process for 3D printing technologies.
RAPID PROTOTYPING JOURNAL
(2022)
Article
Engineering, Manufacturing
Zhiping Wang, Yicha Zhang, Shujie Tan, Liping Ding, Alain Bernard
Summary: Support structures are crucial for additive manufacturing processes, with the number and position of support points directly impacting the performance and final printing quality. This paper proposes a method to determine support points, optimizing their distribution while ensuring manufacturability, particularly useful for complex structures in medical applications.
ADDITIVE MANUFACTURING
(2021)
Article
Engineering, Manufacturing
Benjamin C. Stump, Brian T. Gibson, Jay T. Reynolds, Charles C. Wade, Michael C. Borish, Peter L. Wang
Summary: As powder bed fusion (PBF) additive manufacturing (AM) progresses, system configurations are shifting towards unconventional configurations to increase throughput. The inclusion of multiple heat sources increases the complexity of control schemes and load balancing becomes crucial. This paper introduces high-performing load balancing methods for multi-beam systems of any complexity, enabling on-the-fly load balancing in case of beam failures and improving system robustness.
ADDITIVE MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Meysam Rabiee, Babak Aslani, Jafar Rezaei
Summary: This paper proposes an anti-biased statistical approach for group decision-making, including extreme, moderate, and soft versions. By eliminating biased decision-makers and assigning different weights to DMs, the approach effectively addresses biased decision-making in various scenarios.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Review
Green & Sustainable Science & Technology
Hussein Mohammed Ridha, Chandima Gomes, Hashim Hizam, Masoud Ahmadipour, Ali Asghar Heidari, Huiling Chen
Summary: Standalone photovoltaic systems are considered promising and rapidly developing renewable energy sources due to their noise-free, easily available, and low-cost nature, particularly for remote areas. However, these systems have drawbacks of low energy conversion efficiency and high capital costs. This paper aims to review recent developments in designing SAPV systems using multi-objective optimization and multi-criteria decision-making methodologies, including mathematical models for estimating the output power of PV modules and storage batteries. Additionally, the techno-economic criteria for evaluating SAPV system performance are discussed to assist designers and customers in selecting the most suitable design before installation.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Computer Science, Information Systems
Honggang Peng, Zhi Xiao, Xiaokang Wang, Jianqiang Wang, Jian Li
Summary: This paper aims to explore Z-number outranking theories and the corresponding MCDM method based on the idea of ELECTRE III. The concordance and discordance indices of Z-numbers are defined by processing their bimodal uncertainty fully. Three types of novel outranking relations for Z-numbers are presented by comparing these indices systematically. An extended MCDM method with the distillation and flow ranking rules is proposed to detect outranking relations among alternatives under multiple criteria.
INFORMATION SCIENCES
(2023)
Article
Construction & Building Technology
Zhen Han, Xiaoqian Li, Jiaqi Sun, Mo Wang, Gang Liu
Summary: Building performance design is crucial for sustainable urban development, involving conflicting performance criteria such as energy consumption and daylighting. This study proposes a multi-criteria decision-making method based on sensitivity analysis and analytic hierarchy process, enabling real-time interactive optimization of building performance. Application of the method to a case study in China demonstrates improved performance and increased design efficiency for architects. This method enhances decision-making in building sustainable design and supports the improvement of building performance and urban sustainability.
ENERGY AND BUILDINGS
(2023)
Review
Engineering, Industrial
Chao Liu, Pai Zheng, Xun Xu
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Qiunan Meng, Xun Xu
Summary: In this paper, an incomplete covering rough set method based on object similarity is proposed to derive a cover for attribute reduction. Experimental results show that it outperforms compared rough set in factor selection accuracy and quote prediction with various proportions of missing data.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Yu Zhang, Xian Yu, Jian Sun, Yongsheng Zhang, Xun Xu, Yadong Gong
Summary: This paper introduces an intelligent STEP-NC-compliant setup planning method that combines rules, AHP, and IBPNN, to automatically and reasonably optimize the machining sequence and datum decision of manufacturing feature groups. The proposed method is verified to be effective and feasible through a case study.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Yuqian Lu, Hao Zheng, Saahil Chand, Wanqing Xia, Zengkun Liu, Xun Xu, Lihui Wang, Zhaojun Qin, Jinsong Bao
Summary: This position paper discusses the concept, needs, reference model, enabling technologies, and system frameworks of human-centric manufacturing. It provides a relatable vision and research agenda for future work in human-centric manufacturing systems. Human-centric manufacturing should address human needs and the human-machine relationships will evolve.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Industrial
Jie Bai, Shuiliang Fang, Xun Xu, Renzhong Tang
Summary: Cloud manufacturing aims to transform the manufacturing industry into a cloud-based service with efficient service standard expression, publication, collaboration, and sharing being a major challenge. To address this, the authors propose the concept of Bill Of Standard manufacturing Service (BOSS) and a synthesized algorithm called LMPF for quickly building a product-oriented BOSS tree.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Editorial Material
Engineering, Industrial
Jie Zhang, Junliang Wang, Ray Zhong, Weidong Li, Xun Xu, Bhaskaran Gopalakrishnan
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Chao Liu, Ziwei Su, Xun Xu, Yuqian Lu
Summary: Cloud manufacturing is a service-oriented manufacturing paradigm that provides ubiquitous and on-demand access to customizable manufacturing services, but the link between field-level manufacturing data and the cloud manufacturing platform has not been well established. Efficient integration of IIoT technologies in cloud manufacturing systems can help overcome this challenge and improve connectivity between field-level manufacturing equipment and the cloud platform.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Artificial Intelligence
Yuanbin Wang, Tao Peng, Wenhu Wang, Ming Luo
Summary: This paper proposes a high-efficient view planning method based on deep reinforcement learning to solve the problem of complex product surface defect detection. The proposed method effectively reduces the viewpoints while ensuring coverage, and its effectiveness and efficiency are verified through experiments.
ADVANCED ENGINEERING INFORMATICS
(2023)
Editorial Material
Engineering, Industrial
Pai Zheng, Xun Xu, Lihui Wang
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Yaoyao Ping, Yongkui Liu, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a manufacturing model that provides on-demand manufacturing services to consumers. Scheduling is a crucial problem for cloud manufacturing, especially when dealing with multiple composite tasks. This research combines sequence generation algorithms with deep reinforcement learning to address cloud manufacturing scheduling problems.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yongkui Liu, Yaoyao Ping, Lin Zhang, Lihui Wang, Xun Xu
Summary: Cloud manufacturing is a service-oriented manufacturing model that provides manufacturing resources as cloud services. This paper explores the use of Deep Reinforcement Learning (DRL) to solve scheduling issues in decentralized robot manufacturing services in cloud manufacturing, proposing DQN and DDQN-based scheduling algorithms. Results indicate that DDQN performs the best in terms of performance and indicators.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Law
Marwan Gharbia, Alice Chang-Richards, Xun Xu, Matilda Hook, Lars Stehn, Rene Jahne, Daniel Hall, Kenneth Park, Jingke Hong, Yingbin Feng
Summary: Through surveys conducted in several countries, this study found that self-certification by manufacturers is the main method of complying with building regulations when using off-site construction techniques. A regulatory compliance system that allocates risks and liabilities fairly is also important. Third-party certification and traceability are necessary for a functional regulatory system. The study recommends policymakers introduce changes in product standards and legislation to improve off-site construction's compliance and performance.
JOURNAL OF LEGAL AFFAIRS AND DISPUTE RESOLUTION IN ENGINEERING AND CONSTRUCTION
(2023)
Article
Engineering, Industrial
Pei Wang, Hai Qu, Qianle Zhang, Xun Xu, Sheng Yang
Summary: In this paper, a production quality prediction framework based on multi-task joint deep learning is proposed to simultaneously evaluate the multitask quality of all stages in a multistage manufacturing system. The proposed method outperforms traditional models in terms of R2, MAE, and RMSE, showing significant improvements in quality prediction accuracy.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Ahmed Z. Naser, Fantahun Defersha, Xun Xu, Sheng Yang
Summary: This paper explores the feasibility of predictive Life Cycle Assessment (LCA) for Additive Manufacturing (AM) by proposing a data-driven framework that combines Machine Learning (ML) and LCA. The framework is demonstrated through a case study on the Fused Filament Fabrication (FFF) process, achieving high prediction accuracy and good generalizability.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Kendrik Yan Hong Lim, Theresia Stefanny Yosal, Chun-Hsien Chen, Pai Zheng, Lihui Wang, Xun Xu
Summary: The increasing complexity of industrial systems requires more effective and intelligent maintenance approaches to address manufacturing defects. This paper introduces a cognitive digital twin system that leverages industrial knowledge graphs to support maintenance planning and operations. The system can manage interconnected systems, facilitate cross-domain analysis, and generate feasible solutions validated through simulation. It can also identify potential disruptions in new product designs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
