Computers & Industrial Engineering最新文献

{"title":"Robotic disassembly of electric vehicle batteries: Technologies and opportunities","authors":"Yue Zang ,&nbsp;Mo Qu ,&nbsp;Duc Truong Pham ,&nbsp;Roger Dixon ,&nbsp;Farzaneh Goli ,&nbsp;Yongquan Zhang ,&nbsp;Yongjing Wang","doi":"10.1016/j.cie.2024.110727","DOIUrl":"10.1016/j.cie.2024.110727","url":null,"abstract":"<div><div>The demand for electric vehicle (EV) battery services, such as repair, remanufacturing, and recycling, is rising as more EVs enter the market. Disassembly is an essential step in these services, but it is usually done manually, which is slow and costly. Therefore, robots have been proposed to disassemble batteries. This work provides an extensive overview of existing technologies in EV battery disassembly and potential robotics. The technologies investigated in this paper focus on how robots can enhance automation and flexibility. This paper summarises the characteristics and applicability of the potential technologies and highlights promising research directions to stimulate further exploration by researchers.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110727"},"PeriodicalIF":6.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662103","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":"A location-sizing and routing model for a biomethane production chain fed by municipal waste","authors":"Anna Livia Croella ,&nbsp;Luca Fraccascia","doi":"10.1016/j.cie.2024.110714","DOIUrl":"10.1016/j.cie.2024.110714","url":null,"abstract":"<div><div>This paper proposes an integrated approach for a biomethane supply chain from Organic Fraction of Municipal Solid Waste (OFMSW), addressing both strategic plant location-sizing and tactical vehicle routing. A two-stage iterative approach following a cluster-first location&amp;sizing&amp;route-second approach is implemented to optimize investment and transportation costs. A novel classification of waste producers into small and large categories allows for a tailored approach, minimizing transportation costs through waste pooling for small producers and allocating vehicles effectively for large producers. Extensive computational experiments on a case study on the Lazio Region demonstrate the cost-effectiveness of the proposed approach, which saves 30% of transportation costs with respect to a location-sizing model. Additionally, the sensitivity analysis highlights the significant impact of including huge-scale plants in the solution.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110714"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662077","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":"A reinforcement learning-driven cooperative scatter search for the knapsack problem with forfeits","authors":"Juntao Zhao ,&nbsp;Mhand Hifi","doi":"10.1016/j.cie.2024.110713","DOIUrl":"10.1016/j.cie.2024.110713","url":null,"abstract":"<div><div>The knapsack problem with forfeits belongs to the NP-hard combinatorial optimization family and arises in various applications like resource allocation, finance, and logistics, where certain item combinations incur penalties. Efficiently solving such a problem is crucial for optimizing resources while minimizing penalties. This paper proposes a novel reinforcement learning-driven cooperative scatter search algorithm to solve it, combining the robust exploration capabilities of scatter search with the adaptive learning strengths of <span><math><mi>Q</mi></math></span>-learning. The algorithm starts by generating a diverse archive set to ensure broad exploration of the solution space. It then iteratively generates and combines subsets using path-relinking, followed by a two-stage improvement process: <span><math><mi>Q</mi></math></span>-learning for dynamic enhancement and a tabu-based local search for refinement. Experimental evaluations on benchmark instances highlight the proposed method’s competitiveness against state-of-the-art approaches. The method establishes new lower bounds on 22 instances and matches existing bounds on others.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110713"},"PeriodicalIF":6.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662104","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":"Ergonomic design of Human-Robot collaborative workstation in the Era of Industry 5.0","authors":"Ali Keshvarparast ,&nbsp;Nicola Berti ,&nbsp;Saahil Chand ,&nbsp;Mattia Guidolin ,&nbsp;Yuqian Lu ,&nbsp;Olga Battaia ,&nbsp;Xun Xu ,&nbsp;Daria Battini","doi":"10.1016/j.cie.2024.110729","DOIUrl":"10.1016/j.cie.2024.110729","url":null,"abstract":"<div><div>The increasing adoption of collaborative robots to support job execution in manufacturing has catalyzed companies’ attention to safety and well-being issues. Sharing the human-centric perspective and harmonious human–machine collaboration concepts emphasized by Industry 5.0, the design phase of a collaborative workstation must integrate both psychological and physical risk evaluations to provide a safe and inclusive work environment suitable for a diversified workforce. Accelerating the pre-deployment phase to quickly reconfigure workstation design and assess its impact on workload balancing and task sequencing during the deployment of assembly lines still represents a challenging task considering the available software tools. This research proposes a new mathematical model to accelerate the design of ergonomic human-robot collaborative workstations based on task alternatives and the combined consideration of postural assessment and fatigue analyses for each of them to design an ergo-friendly collaborative environment. Surface electromyography analysis is jointly adopted with postural risk assessment measured with inertial measurement units and developed by a digital ergonomic platform to determine the optimal workplace configuration for tools, equipment, and resources to promote physical well-being while considering station productivity. Experimental tests are performed to investigate arm muscles and postural risk assessment for different configurations of workstation design and collaborative human-robot job progression. Experimental results demonstrate the feasibility, and the advantages of the proposed approach compared to existing simulation software to quickly generate and assess alternative scenarios and find a trade-off between ergo-quality levels and system performance. The final discussion offers valuable information for decision-makers and practitioners to facilitate the integration of human factors throughout the early stages of ergo-friendly workspace design, while effectively managing the complexity generated by resource allocation and collaborative robots.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110729"},"PeriodicalIF":6.7,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662078","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":"Train assignment and handling capacity arrangement in multi-yard railway container terminals: An enhanced adaptive large neighborhood search heuristic approach","authors":"Tian Xia ,&nbsp;Li Wang ,&nbsp;Wenqian Liu ,&nbsp;Qin Zhang ,&nbsp;Jing-Xin Dong ,&nbsp;Xiaoning Zhu","doi":"10.1016/j.cie.2024.110733","DOIUrl":"10.1016/j.cie.2024.110733","url":null,"abstract":"<div><div>Expanding terminal scale and constructing multiple railway handling yards have become popular strategies for leading railway container terminals globally to cope with the ever-increasing handling volume. Although such an approach greatly enhances the terminal’s productivity, it also intensifies handling operations and introduces additional inter-yard interactions, complicating terminal management. To address these challenges, this paper investigates an integrated optimization approach for multi-yard railway container terminals, which feature both rail-road and rail-rail container transshipment operations. The train assignment plan for each yard and the handling capacity arrangement for each train are jointly optimized while considering inter-yard container transits, workload allocation for yards, and safety requirements in train shunting. This problem is formulated as a nonlinear programming model, with the objective to minimize operational delay and service time for each incoming train, and to minimize workload differences and container transit volume among yards. To efficiently solve this problem, this research develops an enhanced adaptive large neighborhood search (EALNS) heuristic, which includes several customized operators and feasibility repair methods, and is further enhanced with a local search method and backtracking mechanism compared to the standard ALNS framework. Computational experiments with different data scales and problem settings demonstrate the superiority of the EALNS in terms of solution quality and stability compared with three other solution methods. Additionally, practical insights for terminal operations are drawn through detailed analysis of different infrastructure configurations, transshipment train characteristics, and unit cost settings.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110733"},"PeriodicalIF":6.7,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662076","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":"Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation","authors":"Antonio Padovano ,&nbsp;Chiara Sammarco ,&nbsp;Nasia Balakera ,&nbsp;Fotios Konstantinidis","doi":"10.1016/j.cie.2024.110715","DOIUrl":"10.1016/j.cie.2024.110715","url":null,"abstract":"<div><div>The rapid integration of Cognitive Digital Twins (CDTs) across various industries has revolutionized operational practices, leading to enhanced efficiency and improved decision-making capabilities. However, this technological advancement is accompanied by significant environmental implications, particularly regarding the management of electronic waste (e-waste) and digital waste. While e-waste primarily concerns the disposal of obsolete hardware, digital waste encompasses inefficiencies, redundancies, and unnecessary consumption of computational resources in the digital environment. This paper emphasizes the importance of understanding the lifecycle impacts of CDTs and advocates for the implementation of sustainable practices in their management. To address these challenges, we introduce Digital Twin Portfolio Management (DTPM) as a systematic framework for optimizing the CDT ecosystem. We also present the Digital Twin Triple Bottom Line as a framework for assessing the technical, economic, and environmental impacts of CDT implementations, ensuring that organizations can identify inefficiencies and align their operations with broader sustainability objectives. The findings elucidate the various types of waste generated by CDTs, establishing a critical link between digital asset management and environmental sustainability. Additionally, the study advocates for improved APM practices tailored to the unique challenges posed by CDTs, contributing valuable insights to the evolving discourse on IT portfolio management. Future research directions are also discussed, including the need for expanded case studies and longitudinal investigations to enhance the generalizability and understanding of CDT lifecycle management.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110715"},"PeriodicalIF":6.7,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662071","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":"Multi-objective model for electric vehicle charging station location selection problem for a sustainable transportation infrastructure","authors":"Murat Bilsel ,&nbsp;Huseyin Selcuk Kilic ,&nbsp;Zeynep Tugce Kalender ,&nbsp;Gulfem Tuzkaya","doi":"10.1016/j.cie.2024.110695","DOIUrl":"10.1016/j.cie.2024.110695","url":null,"abstract":"<div><div>The transportation industry mostly depends on conventional vehicles, leading to significant adverse effects on the environment. The widespread usage of electric vehicles can be seen as a relief for this problem. However, the success of electric vehicles largely depends on the availability and proper deployment of charging station infrastructure. It is crucial for cities to strategically select suitable locations for charging stations with adequate capacity levels to promote sustainable and environmentally-friendly transportation options. Hence, in this study, a multi-objective model is proposed for the electric vehicle charging station location selection and capacity allocation problem. The model aims to maximize customer satisfaction, minimize total risk, and minimize costs as key objective functions. To manage the demand effectively, the region of interest is divided into grids. The proposed multi-objective model is applied to the European side of Istanbul and solved by using AUGMECON2 technique. Finally, computational analyses are presented based on scenarios including different demand values. These analyses provide valuable insights into the effectiveness of the proposed model and its implications for achieving sustainable transportation in Istanbul.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110695"},"PeriodicalIF":6.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662112","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":"Design of a multi-component system-based fixed-wing unmanned aerial vehicle maintenance policy and its case study","authors":"Guangshuai Liu ,&nbsp;Xurui Li ,&nbsp;Si Sun ,&nbsp;Xing Zhao ,&nbsp;Bailin Li","doi":"10.1016/j.cie.2024.110701","DOIUrl":"10.1016/j.cie.2024.110701","url":null,"abstract":"<div><div>At present, flight vehicle structure maintenance is undergoing a paradigm shift from preventive maintenance depending on calendar time and flight cycle to condition-based maintenance (CBM) using structural condition monitoring data. This shift is particularly relevant as unmanned aerial vehicle (UAV) systems increasingly undertake aerial missions. However, unlike CBM for single components, most UAV systems consist of multiple interconnected components. Optimizing pre-flight maintenance and ensuring traceability of inspections from a system-level perspective remains challenging. This study introduces a multi-layered decision-making policy for UAV reliability and stability multi-component evaluation, enhancing service condition monitoring and maintenance evaluation. The system adopts a knowledge-driven approach to develop a comprehensive maintenance framework for multi-component UAVs. It enables detailed damage assessment, effective management, predictive capabilities, and optimization strategies. By integrating and reasoning across knowledge-based, geometric, and decision-making models, the system supports dynamic maintenance and continuous iterative enhancements. To further reduce system complexity, this paper created a risk grating evaluation system. Within the framework of individual components, decision-making rules are established to optimally determine the components needing preventive maintenance when activated by decisions from risk assessments. Additionally, a new soft failure threshold model to determine the optimal maintenance decision variables is defined. This model incorporates general knowledge of the system and subsystems, further optimizing predictive reliability and economic dependency. Finally, the effectiveness and feasibility of this policy are validated through a fixed-wing UAV maintenance case study. The results demonstrate that the proposed framework holds significant promise for maintenance management in aircraft systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110701"},"PeriodicalIF":6.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662051","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":"Product upgrade and advanced quality disclosure in a supply chain","authors":"Yang Liu ,&nbsp;Bin Shen ,&nbsp;Dmitry Ivanov","doi":"10.1016/j.cie.2024.110693","DOIUrl":"10.1016/j.cie.2024.110693","url":null,"abstract":"<div><div>Retailers frequently preannounce the quality of upcoming products, highlighting the importance of information disclosure in supply chains. This study examines the interaction between advanced quality disclosure and product upgrades within a supply chain, where a supplier can release either upgraded products exclusively or alongside regular products in a subsequent period. Using a game-theoretical model, we investigate how the supplier’s upgrade decisions and the retailer’s disclosure strategy affect consumer behaviour, particularly strategic waiting, and product cannibalisation. Our results show that when only upgraded products are offered, the retailer discloses product quality in advance if the innovation level is high. When both regular and upgraded products are available, the retailer chooses advanced disclosure when the innovation level is either high or low. Even when the product improvement is minimal, advanced disclosure reduces cannibalisation and attracts more consumers to the upgraded products, thereby boosting the retailer’s profits. Additionally, the supplier may choose not to upgrade products when the innovation cost is moderate. These insights suggest that advanced disclosure can mitigate both cannibalisation and consumer waiting, particularly in high-tech industries or incremental innovation scenarios, such as electronics and smart home sectors, where the preannouncement of product information is crucial.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110693"},"PeriodicalIF":6.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662073","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 modified adaptive large neighborhood search algorithm for solving the multi-port continuous berth allocation problem with vessel speed optimization","authors":"Bin Ji ,&nbsp;Yalong Song ,&nbsp;Samson S. Yu ,&nbsp;Qian Wei","doi":"10.1016/j.cie.2024.110699","DOIUrl":"10.1016/j.cie.2024.110699","url":null,"abstract":"<div><div>Despite its fast-growing popularity in maritime transportation, container shipping is still fraught with risks and uncertainties with its complex operating environments. This paper studies the multi-port continuous berth allocation problem with speed optimization (MCBAP). In the MCBAP, vessels visit multiple ports sequentially, and the problem aims at minimizing the sum of vessel sailing cost, waiting cost, delay cost and port handling cost, while satisfying various constraints related to vessel sailing and berthing. A mixed integer linear programming (MILP) model for MCBAP is formulated, and a modified adaptive large neighborhood search (MALNS) algorithm is proposed for solving large-scale MCBAPs. In the MALNS, an efficient initial solution generation strategy is developed, and a series of neighborhood solution generation operators are proposed. Finally, the proposed MILP model and MALNS algorithm are tested on a range of MCBAP instances. The numerical results demonstrate that the MILP model can be solved to optimality with CPLEX, and the MALNS can efficiently solve instances at various scales. In addition, sensitivity analyses on fuel prices and vessel design speeds (the planned maximum speeds) are performed, and management insights have been provided.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"198 ","pages":"Article 110699"},"PeriodicalIF":6.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142662072","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}