Article
Engineering, Industrial
Andrea Bikfalvi, Esperanza Villar Hoz, Gerusa Gimenez Leal, Monica Gonzalez-Carrasco, Nuria Mancebo
Summary: This paper proposes a solution for integrating occupational safety and health (OSH) into education, combining theoretical foundations and empirical evidence. The findings include analysis of teachers as stakeholders, barriers and facilitators of OSH integration, and the development of an ICT tool for interaction and sharing in this field. The main contribution lies in envisioning, orchestrating, and validating a solution to integrate OSH into schools and ultimately contribute to sustainable development goals.
Review
Engineering, Industrial
Leonardo Leoni, Ahmad Bahootoroody, Mohammad Mahdi Abaei, Alessandra Cantini, Farshad Bahootoroody, Filippo De Carlo
Summary: This paper presents a systematic bibliometric analysis (SBA) on the research of machine learning and deep learning in the field of safety. The main research areas, application fields, relevant authors and studies, and temporal evolution are investigated. It is found that rotating equipment, structural health monitoring, batteries, aeroengines, and turbines are popular fields, and there is an increase in popularity of deep learning and new approaches such as deep reinforcement learning.
Article
Computer Science, Interdisciplinary Applications
Ramon Piedra-de-la-Cuadra, Francisco A. Ortega
Summary: This study proposes a procedure to select candidate sites optimally for ensuring energy autonomy and reinforced service coverage for electric vehicles, while considering demand and budget restrictions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Engineering, Industrial
John Kang, Stephanie C. Payne, Farzan Sasangohar, Ranjana K. Mehta
Summary: This exploratory longitudinal field study aimed to examine the changes in subjective, performance-based, and physiological fatigue measures over time across different shift types in offshore environments. The findings revealed that workers' performances on the psychomotor vigilance test deteriorated over time across all shift types. The study also found correlations between different multimodal fatigue measures.
APPLIED ERGONOMICS
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Computer Science, Interdisciplinary Applications
Yin Yuan, Shukai Li, Lixing Yang, Ziyou Gao
Summary: This paper investigates the design of real-time train regulation strategies for urban rail networks to reduce train deviations and passenger waiting times. A mixed-integer nonlinear programming (MINLP) model is used and an efficient iterative optimization (IO) approach is proposed to address the complexity. The generalized Benders decomposition (GBD) technique is also incorporated. Numerical experiments show the effectiveness and computational efficiency of the proposed method.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Engineering, Industrial
S. Thuillard, L. Audergon, T. Kotalova, A. Sonderegger, J. Sauer
Summary: This study compared the effects of human-induced and machine-induced social stress on task performance and subjective state. The results showed that social stress did not directly affect performance, affect, or self-esteem, but human-induced social stress impaired perceived justice.
APPLIED ERGONOMICS
(2024)
Article
Engineering, Industrial
Yu Du, Jun-qing Li
Summary: This study investigates the group scheduling of a distributed flexible job shop problem using the concrete precast process. The proposed solution utilizes three coordinated double deep Q-networks (DQN) as a learn-to-improve reinforcement learning approach. The algorithm shows superiority in minimizing costs and energy consumption.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Dawei Gao, Kai Huang, Yongsheng Zhu, Linbo Zhu, Ke Yan, Zhijun Ren, C. Guedes Soares
Summary: This paper proposes a semi-supervised fault diagnosis method through feature perturbation and decision fusion. To improve the generalization capability of the model, a dual correlation model is constructed, and the structural parameters are adjusted. The final fusion diagnosis is achieved by analyzing high-confidence samples.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Imanol Nunez, Maite Prieto
Summary: This paper analyzes the effect of worker under-skilling on occupational safety. The results show that under-skilled workers are more prone to accidents and longer periods of sick leave. On-the-job training, safety information, and teamwork weaken the relationship between under-skilling and accidents, with only teamwork reducing the duration of sick leave. Certain organizational and regulatory practices need to be modified to address the health effects of a lack of skills, and the article proposes some recommendations in this regard.
Article
Engineering, Industrial
Kai Huang, Guozhu Jia, Qun Wang, Yingjie Cai, Zhenyu Zhong, Zeyu Jiao
Summary: In the era of Industry 5.0, human-centered smart manufacturing (HSM) has emphasized the role of humans in collaboration with machines. This study proposes a method that combines deep learning-based 3D pose reconstruction with rapid entire body assessment (REBA) to assess the risk of work-related musculoskeletal disorders (WMSDs) in HSM. The proposed method improves the accuracy of risk assessment by introducing weights between different risk levels, leading to a precision rate of 99.31% in experiments conducted on an automobile production line.
APPLIED ERGONOMICS
(2024)
Article
Engineering, Industrial
Changcheng Ji, Fei Gao, Wenjiang Liu
Summary: In this paper, a novel dependence assessment method based on cloud model and best-worst method (BWM) is proposed. Two numerical examples are presented to show that the proposed method can effectively provide reliable assessment results under uncertainty.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jule Bessler-Etten, Leendert Schaake, Jaap H. Buurke, Gerdienke B. Prange-Lasonder
Summary: This article investigates the development of discomfort caused by repetitive and prolonged forces exerted through a rigid cuff. The study found that repetitive force application triggers discomfort but generally does not result in pain and there are no significant differences between different repetitive loading patterns. The design and use of exoskeletons should consider comfort thresholds specific to prolonged repetitive loading.
APPLIED ERGONOMICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Anqi Li, Congying Han, Tiande Guo, Bonan Li
Summary: This study proposes a general framework for designing linear programming instances based on the preset optimal solution, and validates the effectiveness of the framework through experiments.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xubo Yue, Raed Al Kontar, Ana Maria Estrada Gomez
Summary: This article presents a federated data analytics approach for linear regression models, utilizing hierarchical modeling and information sharing to handle data distributed across different devices. It provides uncertainty quantification, variable selection, hypothesis testing, and fast adaptation to new data.
Article
Engineering, Industrial
Zhi Zheng, Aonan Tian, Xiaolan Pan, Duofa Ji, Yong Wang
Summary: A new approach for probabilistic safety assessment of prestressed concrete containment vessels under internal pressure is proposed. The approach uses the continuous damage state of the containment vessel and damage-based fragility to characterize the safety performance of the vessel. The use of damage-based fragility provides a more realistic assessment of component performance compared to traditional pressure-based fragility.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
