Computers & Industrial Engineering最新文献

{"title":"Bayesian enhanced EWMA scheme for shape parameter surveillance in Inverse Gaussian models","authors":"Tahir Abbas ,&nbsp;Amara Javed ,&nbsp;Nasir Abbas","doi":"10.1016/j.cie.2024.110637","DOIUrl":"10.1016/j.cie.2024.110637","url":null,"abstract":"<div><div>Bayesian control charts (BCC) are increasingly recognized as highly effective statistical schemes to investigate manufacturing processes and effectively control process variability. This technique is mainly adept at handling uncertain parameters in the manufacturing sector. This study sets the surveillance threshold for the Inverse Gaussian Distribution (IGD) shape parameter. It develops several non-informative exponentially-weighted moving averages (EWMA) control charts (CCs) using different loss functions (LFs). The proposal and existing charts are assessed using different individual performance measures. The non-informative Bayesian (NIB) charts developed in this study are evaluated across various sample sizes. The simulation study determines that the proposed non-informative Bayesian EWMA CCs are more effective than conventional classical EWMA charts. These proposed EWMA chart techniques excel in identifying faults in the shape parameter and perform better than their classical counterpart in swiftly identifying shifts. Additionally, the procedure is applied to real data from the manufacturing industry, and the results validate the conclusions drawn from the simulation outcomes.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"197 ","pages":"Article 110637"},"PeriodicalIF":6.7,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Managing platelets supply chain under uncertainty: A two-stage collaborative robust programming approach","authors":"Maryam Izadidoost Sheshkol ,&nbsp;Keyvan Fardi ,&nbsp;Ashkan Hafezalkotob ,&nbsp;Robert Ogie ,&nbsp;Sobhan Arisian","doi":"10.1016/j.cie.2024.110645","DOIUrl":"10.1016/j.cie.2024.110645","url":null,"abstract":"<div><div>This study investigates the role of horizontal collaboration among blood centers in mitigating the negative impacts of fluctuations in blood platelet supply and demand during normal circumstances and after sudden-onset disasters. Specifically, four scenarios are studied: no collaboration, collaboration among blood centers, collaboration among hospitals, and collaboration among blood centers and hospitals. To formulate these scenarios, we propose a two-stage robust programming model that enables decision-makers to monitor the collaborative behavior of blood centers and hospitals before and after changes in supply and demand occur. In the first stage, a robust optimization approach is developed to cope with supply and demand uncertainties, where collaboration is limited to blood centers. In the second stage, the uncertain parameters (supply and demand) are treated as deterministic. The key decision is how to transfer platelets among hospitals located in a collaborative cluster. This research uses benchmark data from previous studies to test and validate the developed model and solution approach. Comparing the results obtained in different scenarios, we systematically select the most favorable scenario in terms of model performance under normal and emergency situations. The final results indicate that the network achieves the highest performance when blood centers and hospitals participate in the grand coalition.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110645"},"PeriodicalIF":6.7,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian calculation of degradation-based burn-in policy for heterogeneous item under two-dimensional warranty","authors":"Yinzhao Wei ,&nbsp;Xiaoliang Ling ,&nbsp;Sanyang Liu","doi":"10.1016/j.cie.2024.110638","DOIUrl":"10.1016/j.cie.2024.110638","url":null,"abstract":"<div><div>Two-dimensional (2D) warranty service has been greatly used in many heavy equipment and consumer durables. The items with 2D warranty are usually highly reliable and their heterogeneity is unavoidable. Degradation-based failure model is often used to characterize failure modes for highly reliable items. This paper proposes a degradation-based burn-in model for heterogeneous items with renewing 2D warranty. We consider that the degradation of item is modeled through the inverse Gaussian process and that the item is replaced by a new one as soon as it fails within warranty period. We screen the items based on the degradation information of the items during burn-in to enhance the reliability of items passed burn-in. The models based on performance and cost are proposed to analyze the burn-in procedures from different perspectives. Firstly, we investigate the properties of the optimal policies for the three burn-in models. Secondly, we further present a Bayesian method to solve the uncertainty of parameters in the model. The Bayesian method allows us to incorporate prior knowledge and update our beliefs based on observed data, providing more accurate and reliable estimates. Finally, we give an example of the gallium arsenide laser devices to illustrate the benefits of proposed model and method.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110638"},"PeriodicalIF":6.7,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling and optimization of a distributed flow shop group scheduling problem with heterogeneous factories","authors":"Jingwen Zhou,&nbsp;Tao Meng,&nbsp;Yangli Jia","doi":"10.1016/j.cie.2024.110635","DOIUrl":"10.1016/j.cie.2024.110635","url":null,"abstract":"<div><div>In this paper, we solve a distributed flow shop group scheduling problem with heterogeneous factories, which we call the distributed heterogeneous flow shop group scheduling problem (DHFGSP). The objective is to minimize the energy consumption cost of the critical factory (the factory with the highest energy consumption cost among all factories). Although the DHFGSP is very meaningful for today’s production situation, it has not captured attention so far. Firstly, in this paper, a mixed integer linear model is developed. Secondly, four heuristic methods are presented based on specific scheduling rules and energy consumption cost criteria features. Thirdly, an effective iterative greedy algorithm based on Q-learning (Q_PIG) is proposed. In the Q_PIG, a family ordering rule is proposed to exchange with families in other factories to explore better quality solutions during the local search. Moreover, a Q-learning algorithm is embedded to select operations (family operations or job operations) for the current solution. The embedding of Q-learning enables the current solution to execute high-quality operations. Comprehensive experiments show that the Q_PIG is very effective for the problem solved.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110635"},"PeriodicalIF":6.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Selecting facility location of Gendarmerie Search and Rescue (GSR) Units; An analysis of efficiency in disaster response","authors":"Adnan Abdulvahitoğlu ,&nbsp;Danişment Vural ,&nbsp;İrfan Macit","doi":"10.1016/j.cie.2024.110639","DOIUrl":"10.1016/j.cie.2024.110639","url":null,"abstract":"<div><div>Disasters, referred to as events that result in physical, economic, and social losses for individuals and disrupt the daily activities of human communities, necessitate ongoing preparedness due to their unpredictable nature. Swift response during and after a disaster is crucial for preserving human life. Hence, it is imperative to initiate planning immediately following a disaster to ensure readiness for various tasks. Given these factors, search and rescue units must carefully select a base location that enables them to promptly reach affected areas.</div><div>Disasters exhibit unique characteristics across different regions of Türkiye. While some regions are prone to earthquakes, others face the risks of landslides, avalanches, or floods. Consequently, the required measures for disaster management vary from region to region. Nevertheless, when the term “disaster” is mentioned in Türkiye, earthquakes often come to mind due to their frequent occurrence and significant impact. The Gendarmerie Search and Rescue (GSR) units have been actively responding to these earthquakes, renowned for their exemplary institutional discipline and working methods. This study aims to examine the operations and deployment locations of GSR units, which play a crucial role in mitigating the impact of frequent earthquakes in Türkiye, utilizing a SWOT analysis. Additionally, a Multi-Criteria Decision Making-based mathematical model will be employed to optimize task activities and to select the most suitable facility locations for GSR units. The use of mathematical modeling in this context ensures that GSR units are strategically positioned to maximize their operational effectiveness and minimize response times. The results will be evaluated through sensitivity analysis.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"197 ","pages":"Article 110639"},"PeriodicalIF":6.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of simulation and machine learning in supply chain management: A synthesis of the literature using the Sim-ML literature classification framework","authors":"Ehsan Badakhshan ,&nbsp;Navonil Mustafee ,&nbsp;Ramin Bahadori","doi":"10.1016/j.cie.2024.110649","DOIUrl":"10.1016/j.cie.2024.110649","url":null,"abstract":"<div><div>Stochastic modeling techniques, such as discrete-event and agent-based simulation, are widely used in supply chain management (SCM) for capturing real-world uncertainties. Over the last decade, data-driven approaches like machine learning (ML) have also gained prominence in SCM, employing methods such as supervised learning (SL), unsupervised learning (UL), and reinforcement learning (RL). As supply chains grow in complexity, hybrid models combining simulation (Sim) and ML are becoming increasingly common, and the field stands to gain from a structured review of this literature. Towards this, we developed the Sim-ML Literature Classification Framework, which includes a hierarchical taxonomy comprising five SC criteria, 22 Sim-ML classes and over 75 Sim-ML subclasses. We applied this framework to synthesize 99 papers, revealing significant diversity in how Sim-ML models are used to address supply chain challenges. Key findings include the recognition of the breadth of study objectives, identifying various forms of model hybridization achieved by combining discrete/continuous simulation techniques with SL, UL, and RL approaches, and the data flow mechanisms such as sequential and feedback methods employed by the simulation and ML elements of the hybrid model. Our findings also identify some gaps in the literature; for example, optimization is rarely incorporated into Sim-ML models. Also, most studies present Sim-ML models for addressing problems in general supply chains, likely due to the lack of access to industrial data. The review also highlights that Industry 4.0 technologies, such as digital twins and blockchain, are underrepresented in current research, as are topics like sustainability and transportation. These gaps suggest significant opportunities for future research. We provide guidelines for practitioners on applying Sim-ML models to manage supply chain drivers, mitigate the impact of disruptions, and integrate emerging technologies. Our review serves as a valuable resource for researchers, practitioners, and students interested in leveraging Sim-ML approaches in SCM.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110649"},"PeriodicalIF":6.7,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probing an LSTM-PPO-Based reinforcement learning algorithm to solve dynamic job shop scheduling problem","authors":"Wei Chen,&nbsp;Zequn Zhang,&nbsp;Dunbing Tang,&nbsp;Changchun Liu,&nbsp;Yong Gui,&nbsp;Qingwei Nie,&nbsp;Zhen Zhao","doi":"10.1016/j.cie.2024.110633","DOIUrl":"10.1016/j.cie.2024.110633","url":null,"abstract":"<div><div>With the growth of personalized demand and the continuous improvement in social productivity, the large-scale and few-variety centralized production model is gradually transitioning towards a personalized model of small batches and multiple varieties, which makes the manufacturing process of the job shop increasingly complex. Furthermore, disruptive events such as machinery failures and rush orders in the job shop increase the uncertainty and variability of the production environment. Traditional scheduling methods are usually based on fixed rules and heuristic algorithms, which are difficult to adapt to constantly changing production environments and demands. This may lead to inaccurate scheduling decisions and hinder the optimal allocation of job shop resources. To solve the dynamic job shop scheduling problem (JSP) more effectively, this paper proposes a Reinforcement Learning (RL) optimization algorithm integrating long short-term memory (LSTM) neural network and proximal policy optimization (PPO). It can dynamically adjust scheduling strategies according to the changing production environment, achieving comprehensive status awareness of the job shop environment to make optimal scheduling decisions. First, a state-aware network framework based on LSTM-PPO is proposed to achieve real-time perception of job shop state changes. Then, the state and action space of the job shop are described within the context of the state-aware network framework. Finally, an experimental environment is established to verify the algorithm’s effectiveness. Training the LSTM-PPO algorithm makes it feasible to achieve better performance than other scheduling methods. By comparing the initial planning time with the actual completion time of the rescheduling decision under different dynamic disturbances, the efficiency of the proposed algorithm is verified for the dynamic JSP.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"197 ","pages":"Article 110633"},"PeriodicalIF":6.7,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The analysis of evolutionary strategies to facilitate the transformation of traditional buildings into prefabricated buildings","authors":"Dewei Kong ,&nbsp;Yu Zhang ,&nbsp;Zhengshuo Fan ,&nbsp;Yanbo Yang ,&nbsp;Wei Wang ,&nbsp;Ping Liu ,&nbsp;Wei He ,&nbsp;C.J. Wong ,&nbsp;W.M. Edmund Loh","doi":"10.1016/j.cie.2024.110650","DOIUrl":"10.1016/j.cie.2024.110650","url":null,"abstract":"<div><div>This paper establishes a two-party evolutionary game theory model comprising of the governments and prefabricated components suppliers as the players; and uses the replicator dynamic equations to analyze the evolution mechanisms each player’s strategy choices. Results from numerical simulations indicate that the evolution trajectory of the model is significantly influenced by not only the initial strategies of the players, but also by government incentives and regulatory penalties, as well as the costs and benefits resulted from each strategy choice. Also, prefabricated components suppliers exhibit greater responsiveness to variations in cost-related factors. When the subsidy and penalty respectively remain constant at 15% and 5% of the additional cost, the model exhibits both rapid and stable evolutionary trend towards the optimal evolutionarily stable strategy of full cooperation between the two players. This article proposes a suitable threshold for government incentives and penalties, besides serving as a guide for the steady and sustainable growth of the prefabricated buildings sector.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110650"},"PeriodicalIF":6.7,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to enable human-centric collaboration in social product development paradigm: A practical and theoretical exploration","authors":"Yuguang Bao ,&nbsp;Xinguo Ming ,&nbsp;Zhihua Chen ,&nbsp;Tongtong Zhou ,&nbsp;Xianyu Zhang","doi":"10.1016/j.cie.2024.110632","DOIUrl":"10.1016/j.cie.2024.110632","url":null,"abstract":"<div><div>Since 2012, social product development (SPD) has emerged as a potential paradigm for new product development (NPD). However, the emerging SPD practices are difficult to remain and promote after their early success. The lack of sustainable human-centric collaborative settings will hinder the release of crowd-based collective intelligence in NPD. Currently, the core mechanisms of human-centric collaboration (HCC) in SPD are not clear. To narrow the gap between theory and practice, a two-way empirical study is conducted through an in-deep industrial practice investigation and theory-oriented research based on cooperative inquiry. An extreme case of a famous automotive company is sampled as the object of the cooperative inquiry. The proposed theoretical models are verified by two real SPD pilot projects. Inspired by the discipline of Collaborative Engineering, this study explores the HCC issues and it core mechanisms in the context of SPD. Two novel foundation theoretical models are developed to address the focused scientific problem and engineering challenge. A bottom-up model is developed to structurally elicit the HCC requirements and develop reasonable information modules for specific HCC work practices. A top-down model is developed to improve the manageability and reusability of the learnable experience from historical HCC work practices for better business-technology-system alignment. This study put forward novel theoretical models for designing and deploying collaborative work practices for HCC in SPD. A classification-based Descriptive Model of Collaboration (DMoC) is proposed, which is domain-agnostic and customized for SPD requirements. Our model inherits and outperforms in modelling capability than five other proven modelling approaches.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110632"},"PeriodicalIF":6.7,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dynamic electric fence planning framework for dockless bike-sharing systems based on inventory prediction","authors":"Kang Luo ,&nbsp;Yancun Song ,&nbsp;Ziyi Shi ,&nbsp;Qing Yu ,&nbsp;Guanqi Wang ,&nbsp;Yonggang Shen","doi":"10.1016/j.cie.2024.110619","DOIUrl":"10.1016/j.cie.2024.110619","url":null,"abstract":"<div><div>While dockless bike-sharing systems are growing in popularity due to their convenience, indiscriminate parking creates disorder in cities. To address this problem, this paper proposes a novel prediction-based approach for planning dynamic electric fences. These fences can adapt to dynamic usage patterns and efficiently guide parking behavior. First, graded clustering and spatial point integration algorithms are used to determine the locations of electric fence candidates. Second, initial parking and scheduling simulations are developed to calculate the inventory of each candidate. Finally, a spatiotemporal graph neural network is utilized to predict inventory and generate real-time deployment plans for electric fences. Case studies are conducted in two regions in Shanghai, China. Compared to a non-electric fence scenario, extensive experiments show that our framework can satisfy 98.6% of the parking demand and reduce spatial entropy by 15% within a reasonable walking distance. The results contribute to improving urban orderliness and promoting the sustainability of bike-sharing systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110619"},"PeriodicalIF":6.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}