Article
Automation & Control Systems
Chunfeng Liu, Jufeng Wang, MengChu Zhou, Tao Zhou
Summary: This study proposes a joint decision model to address the cell formation and product scheduling problems in multifactory cellular manufacturing systems. The research reveals that if a product is processed in a factory with low logistics cost, the cost of delivering the product to the distributor may be high. Additionally, managers' preference for high production rate equipment and workers may result in a higher operational error rate, which in turn affects labor cost, raw material cost, and completion time of products.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Civil
M. A. Hussien, M. Moawad, M. H. Seleem, H. E. M. Sallam, H. M. El-Emam
Summary: In this study, the fracture toughness of fiber-reinforced concrete was experimentally determined using matrix cracked specimens. A comparison was made with traditional through-thickness cracked specimens. The results showed that the matrix cracked specimens provided a more realistic estimation of fracture toughness and the effect of fiber length on toughness was marginal.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING
(2022)
Review
Chemistry, Multidisciplinary
Paolo Renna, Sergio Materi, Michele Ambrico
Summary: This article provides an overview of recent research on design approaches and models for improving the responsiveness and sustainability of cellular manufacturing systems. It highlights the importance of cellular manufacturing systems and discusses the need for redesigning cells to improve responsiveness and address energy costs.
APPLIED SCIENCES-BASEL
(2023)
Article
Green & Sustainable Science & Technology
Jian-guo Duan, Qing-lei Zhang, Ying Zhou, Yan-sen Wang
Summary: This study proposed a new integrated sustainable scheduling approach to reduce carbon emissions and improve efficiency by optimizing energy consumption. The research used genetic algorithm for optimization and validated the effectiveness of the method through comparison.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Chemistry, Multidisciplinary
Thanatat Pasupa, Sadami Suzuki
Summary: This article presents a novel mathematical programming model to address the team formation and worker assignment problem, and evaluates its performance using an adaptive large neighbourhood search method. The results show that the model outperforms other existing methods in both team formation and worker assignment stages.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Environmental
Oliver J. Kershaw, Adam D. Clayton, Jamie A. Manson, Alexandre Barthelme, John Pavey, Philip Peach, Jason Mustakis, Roger M. Howard, Thomas W. Chamberlain, Nicholas J. Warren, Richard A. Bourne
Summary: This paper introduces a new mixed variable multi-objective optimization algorithm that considers discrete variables in self-optimization of chemical reactions. By coupling the algorithm with an automated continuous flow platform, it is possible to determine the optimal values for both continuous and discrete variables simultaneously. This method provides efficient optimization and enhances process understanding.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Computer Science, Software Engineering
S. Sathish, A. R. Lakshmanan, P. Karuppuswamy, C. Bhagyanathan
Summary: The paper introduces a hybrid clustering approach based on Sorensen's similarity coefficient and the Sorensen-SLC algorithm, applied to cell formation issues in cellular engineering. Results show that the Sorensen-SLC technique outperforms existing clustering algorithms, with minimal computation and effective processing.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Christian P. Nielsen, Akshay Avhad, Casper Schou, Elias Ribeiro da Silva
Summary: In recent years, mass customization has required manufacturing companies to be more flexible while maintaining high production throughput. Matrix-Structured Manufacturing Systems (MMS) address this challenge by providing high levels of flexibility, scalability, and redundancy. However, current control system architectures do not fully leverage these advantages, resulting in less efficient manufacturing systems. This paper proposes a control system architecture for MMS that is designed to utilize these benefits and increase manufacturing system performance. A case study with a Danish industrial automation company is presented to validate and verify the proposed control system architecture, demonstrating potential performance improvements and enhanced flexibility.
COMPUTERS IN INDUSTRY
(2023)
Article
Physics, Multidisciplinary
Tiago Ramalho, Stephan Kremser, Hao Wu, Ulrich Gerland
Summary: The study explores schemes for programmable pattern formation within a theoretical framework, assessing systems with different update rules, topologies, and control schemes. The results show that only a fraction of systems allow local organizers to dictate target patterns, while an alternative scheme is insensitive to the timing of organizer inputs.
COMMUNICATIONS PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Qian Sun, Fang Pei, Man Zhang, Bo Zhang, Ying Jin, Zhihe Zhao, Qiang Wei
Summary: This study focuses on understanding the role of the curved structure in the extracellular matrix (ECM) network in regulating stem cell mechanotransduction. The fabrication of a curved nanofiber network promotes cell bridge formation, leading to cell lineage commitment towards osteogenic differentiation.
Article
Computer Science, Artificial Intelligence
Shima Shafiee-Gol, Reza Kia, Mohammad Kazemi, Reza Tavakkoli-Moghaddam, Sobhan Mostafayi Darmian
Summary: The research formulates a mixed-integer nonlinear programming model to design cellular manufacturing systems in dynamic conditions, integrating significant manufacturing characteristics with main production planning and location-allocation strategies. The model includes novel features such as multi-plant location, capacity allocation for multiple markets, and dynamic integration of cell formation, production planning, and location-allocation decisions. Objective function terms aim to optimize revenue and various costs, with the model being NP-hard and meta-heuristics algorithms like grey wolf optimization and genetic algorithm developed for solution. Computational effectiveness of these algorithms is tested against traditional solver using sample problems.
Article
Robotics
Chen Li, Jing Huang, Qing Chang
Summary: Real-time production performance evaluation is crucial for diagnosing manufacturing system health and improving productivity, but studies focusing on systems with variable cycle time machines are often overlooked. With the development of smart manufacturing and increased availability of sensor data, data-driven methodologies can efficiently identify and predict real-time permanent production loss.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Review
Computer Science, Artificial Intelligence
Wenxiang Wang, Kangshun Li, Hassan Jalil, Hui Wang
Summary: This paper proposes a mixed-variable multi-objective evolutionary algorithm based on estimation of distribution algorithm (MVMO-EDA) to address challenges in optimizing mixed-variable multi-objective problems, with improvements in generating offspring, coding for discrete variables, and diversity maintenance strategies leading to competitive performance.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Mathematics, Applied
Pierre-Louis Giscard, Stefano Pozza
Summary: Under certain regularity assumptions, any system of coupled linear differential equations with variable coefficients can be tridiagonalized by a time-dependent Lanczos-like method. The convergence of the so-called *-Lanczos algorithm is formally established, and a full characterization of algorithmic breakdowns is obtained. The solution of the original differential system is available through a finite and treatable number of scalar integral equations, which is crucial for evaluating the elusive ordered exponential function both formally and numerically.
LINEAR ALGEBRA AND ITS APPLICATIONS
(2021)
Article
Remote Sensing
Xingdong Wang, Zhi Guo, Haowei Zhang, Changcheng Wang, Yuhua Wang
Summary: This study introduces an improved ant colony algorithm combined with the XPGR algorithm to automatically detect Antarctic ice sheet surface snowmelt and acquire high-precision snowmelt information. The XPGR algorithm is used to enhance the difference between dry snow and wet snow, and the enhanced ant colony algorithm is employed to adaptively find the optimal threshold for segmenting dry snow and wet snow. The major advancement of the ant colony algorithm is the utilization of a dissimilarity matrix to determine initial clustering centers and the use of Levy flight to dynamically modify the clustering radius. The proposed method is compared to the standard XPGR algorithm and evaluated from October 2017 to February 2018 and from October 2019 to February 2020, showing higher accuracy through further verification with six automatic weather stations (AWS).
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2023)
