Article
Engineering, Industrial
Yilan Shen, Xi Zhang, Leyuan Shi
Summary: In this study, the interaction between production scheduling and maintenance in a hybrid production system is considered. A model is formulated by introducing stochastic and workload ratio degradation, and the actual job completion time and maintenance costs can be determined based on the degradation status of each machine. An opportunistic maintenance strategy and an adaptive random-key genetic algorithm are proposed and validated through numerical studies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Chemical
Wei Feng, Yiping Feng, Qi Zhang
Summary: In chemical manufacturing processes, equipment degradation can have a significant impact and maintenance planning is crucial. Distributionally robust optimization can address the uncertainty in predictive equipment health models effectively.
Article
Engineering, Industrial
Yaping Li, Tangbin Xia, Zhen Chen, Ershun Pan
Summary: This paper proposes a multiple degradation-driven preventive maintenance (MDPM) policy for serial-parallel multi-station manufacturing systems (SMMS), considering the impact of production rate degradation and machine reliability degradation on system capacity. By maximizing capacity efficiency and minimizing cost rate, a station-level preventive maintenance optimization model is proposed. The scheduling process of MDPM is formulated with three suggested rules for system-level decision making.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Industrial
Mixin Zhu, Xiaojun Zhou
Summary: This paper focuses on the joint optimization of spare part and maintenance scheduling for Serial-Parallel Multi-station Manufacturing Systems (SPMMS). The study investigates the overlap of spare part connections in SPMMS, where spare parts are shared among multiple stations. A multi-layer hypergraph is introduced to describe the connections in SPMMS and a hybrid Opportunistic Maintenance (OM) policy is proposed to incorporate these connections in the maintenance scheduling. The results show that the hybrid OM policy is more cost-effective than other OM policies and different connections have an impact on the cost effectiveness of the OM policy.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Construction & Building Technology
Wenli Liu, Xingyu Tao, Chao Mao, Wenjian He
Summary: Scheduling optimization of manufacturing prefabricated components is critical for enhancing efficiency and productivity in construction. A new optimization method is proposed, which establishes a Prefabricated Components Production Scheduling (PCPS) model considering the parallel work of serial machines and designs a genetic algorithm-based method to seek potential optimal scheduling schemes.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Automation & Control Systems
Yunyi Kang, Logan Mathesen, Giulia Pedrielli, Feng Ju, Loo Hay Lee
Summary: Recent advancements in sensing, data analytics, and manufacturing technologies have enabled the production of highly customized products. However, this also increases the complexity of controlling such systems, leading to the need for fast exploration of alternative operation strategies. The simultaneous use of simulation and stochastic models can help achieve better control and optimization of production systems by balancing accuracy and computational efficiency.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Engineering, Industrial
Shuyuan Gan, Nan Shen
Summary: In this paper, an innovative maintenance strategy is proposed for a system operating exposed to shock environments. The proposed strategy involves a hybrid method that combines a modified human decision-making method (MHDM), Monte Carlo simulation, and genetic algorithm (GA). MHDM is used to select effective maintenance activities based on relevant system information, while Monte Carlo simulation and GA are used to optimize the policy and minimize the expected cost rate. Numerical examples are provided to demonstrate the effectiveness of the proposed method.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Software Engineering
Thuy Anh Ta, Tien Mai, Fabian Bastin, Pierre L'Ecuyer
Summary: The study focuses on a sample average approximation (SAA) approach for multistage stochastic discrete programs, where constraints are approximated by simulation. Consistency of the SAA method is established, showing convergence of optimal values and solutions as sample sizes increase to infinity. Exponential convergence of large deviations for optimal values and solutions is also proven, extending these results to a multistage setting.
MATHEMATICAL PROGRAMMING
(2021)
Article
Engineering, Industrial
Mixin Zhu, Xiaojun Zhou
Summary: This paper studies the joint modeling of spare part provision and maintenance scheduling for Serial-Parallel Multi-station Manufacturing Systems (SPMMS) and introduces a hypergraph-based model to describe the spare part connections. A Combination-Spread Opportunistic Maintenance (CSOM) policy is proposed and a hierarchical optimization method is developed. The case study and comparisons show that the proposed strategy is more cost-effective than traditional maintenance policies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Nan Zhang, Kaiquan Cai, Yingjun Deng, Jun Zhang
Summary: In this paper, the integrated production-maintenance optimization problem of a multi-component deteriorating machine is studied. The deterioration of each component is described by a discrete-time Markov chain with finite state space. Production planning is scheduled based on the system deterioration and the inventory level to meet a constant demand. The mutual dependence between the production and the system deterioration is considered. The problem is formulated into a Markov decision process framework, and the optimal policy with respect to the machine condition and the inventory level is analyzed.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Aerospace
Pedro Orgeira-Crespo, Guillermo Rey, Carlos Ulloa, Uxia Garcia-Luis, Pablo Rouco, Fernando Aguado-Agelet
Summary: The design of a vehicle launch involves optimizing the climb path and mass distribution. This research proposes a software for separately optimizing the trajectory of a launch rocket, maximizing payload weight and global design while varying the power plant selection. The optimization algorithm is compared to real rockets and other modeling algorithms, with differences of up to 9%.
Article
Energy & Fuels
Xiangxin An, Guojin Si, Tangbin Xia, Dong Wang, Ershun Pan, Lifeng Xi
Summary: In this research, a complex maintenance planning and production scheduling problem for serial-parallel manufacturing systems under time-of-use tariffs is studied. An energy-efficient two-stage maintenance strategy is developed, which aims to minimize the total electricity cost and tardiness cost. The strategy includes preventive maintenance planning in the first stage and a mixed-integer programming model for scheduling with maintenance actions in the second stage. The results demonstrate the effectiveness of this strategy in reducing electricity costs and ensuring system productivity, providing guidance for industrial enterprises.
Article
Automation & Control Systems
Hadi Gholizadeh, Maedeh Chaleshigar, Hamed Fazlollahtabar
Summary: This paper discusses the importance of preventive maintenance plans in industrial production systems and how effective maintenance operations can improve production efficiency and reduce costs. An optimization model is proposed considering uncertainties in the production system, and the problem is solved using robust optimization methods.
Article
Chemistry, Multidisciplinary
Zhenhua Gao, Hongjun Wang, Chunliu Zhou, Hongliang Zhang
Summary: This paper proposes a joint optimization model that considers the relationship between production units and the influence of unit state on demand. The objective is to minimize the expected cost rate by analyzing the composition of cost and time and using renewal reward theory. The application of the model is illustrated through a case study, and sensitivity analysis is used to analyze the impact of different parameters on decision-making results.
APPLIED SCIENCES-BASEL
(2022)
Article
Operations Research & Management Science
Jie Jiang, Hailin Sun
Summary: This paper studies multistage stochastic variational inequalities (MSVIs). The multistage stochastic programming and multistage multi-player noncooperative game problems are considered as source problems. The monotonicity properties of MSVIs are derived under less restrictive conditions. The polynomial rate of convergence between the original problem and its sample average approximation counterpart is established.
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
(2023)
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(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
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
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
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
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
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)