Review
Green & Sustainable Science & Technology
Shuai Zhang, Kai Huang, Yufei Yuan
Summary: The importance of spare parts inventory management is gaining attention, particularly in the pursuit of sustainability. Research in this area is mainly divided into two categories, focusing on spare parts characteristics and research methodologies, and emphasizing supply chain structures and analytical techniques.
Article
Engineering, Industrial
Fabio Sgarbossa, Mirco Peron, Francesco Lolli, Elia Balugani
Summary: This study aims to contribute to the field of AM spare parts inventory management by developing decision trees that consider various parameters and sourcing alternatives, with an interdisciplinary approach to evaluate economic and technical performance.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Review
Engineering, Industrial
Alessandra Cantini, Mirco Peron, Filippo De Carlo, Fabio Sgarbossa
Summary: Configuring supply chains is crucial for the success of spare parts retailers. This paper introduces a new methodology called SP-LACE, which reviews the configuration of spare parts supply chains and evaluates their economic benefits. The results indicate that SP-LACE provides economic benefits and ensures high service levels, overcoming the limitations of existing literature methodology.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Management
Leandro Reis Muniz, Samuel Vieira Conceicao, Lasara Fabricia Rodrigues, Joao Flavio de Freitas Almeida, Tassia Bolotari Affonso
Summary: This paper presents a new hybrid approach based on criticality analysis and optimization for spare parts inventory management in the mining industry. The study combines qualitative and quantitative methods to obtain the spare parts to be stocked, achieving an increase in criticality and number of items stocked compared to historical data. The proposed approach provides systematic tools for analyzing the trade-off between spare parts criticality and total inventory value.
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT
(2021)
Review
Management
Cerag Pince, Laura Turrini, Joern Meissner
Summary: Forecasting spare parts demand has been a challenging issue for many companies, and has received considerable attention over the past fifty years. This paper provides a critical review and quantitative analysis of current literature on spare parts demand forecasting methods, offering detailed insights into when and why particular forecasting methods should be preferred.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Goncalo Cardeal, Marco Leite, Ines Ribeiro
Summary: This paper aims to contribute to the large-scale adoption of additive manufacturing by proposing and demonstrating a decision-support model that identifies spare parts suitable for AM and supports the definition of optimized warehouse management strategies. The application of the model in the paper and pulp industry demonstrates significant economic gains from properly identifying spare parts and optimizing management strategies. However, there are still environmental difficulties to be overcome for large-scale adoption.
COMPUTERS IN INDUSTRY
(2023)
Article
Management
Yue Zhang, Bram Westerweel, Rob Basten, Jing-Sheng Song
Summary: This study examines how an original equipment manufacturer (OEM) can digitize the spare parts supply chain using 3D printing and intellectual property (IP) licensing. The results show that IP licensing can drive production decentralization in the supply chain, leading to increased profits for the OEM.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Engineering, Industrial
Hulya Gucdemir, Gokcecicek Tasoglu
Summary: The timely and cost-effective supply of spare parts is crucial for the high-tech industries. This paper presents a novel spare parts inventory control model that considers part transformation-based substitution, and determines near-optimal inventory levels through simulated annealing based simulation optimization. Computational analyses demonstrate the usefulness of transforming spare parts for companies facing long production lead times and high penalty costs.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yan Zhao, Qianwang Deng, Like Zhang, Weifeng Han, Fengyuan Li
Summary: Integrated scheduling of production and distribution is important for cost saving and customer satisfaction. This paper proposes an optimal spare parts production scheduling model in a flowshop environment, with the objective of maximizing equipment operational utility on the customer side and introducing a speed adjustment strategy to guide equipment operation and maintenance.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics
Ernesto Armando Pacheco-Velazquez, Manuel Robles-Cardenas, Saul Juarez Ordonez, Abelardo Ernesto Damy Solis, Leopoldo Eduardo Cardenas-Barron
Summary: This article presents a heuristic method to determine the optimal inventory level for spare parts, aiming to minimize total costs. The research offers a valuable decision-making framework based on two parameters, providing a quick and reliable estimation for practitioners.
Article
Management
Melvin Drent, Joachim Arts
Summary: The study explores dual sourcing in a distribution network and proposes optimization solutions using queuing theory and a greedy heuristic method, achieving effective inventory management and reduced stock investments. With dynamic repair policies, expedited repairs can significantly improve the utilization of repairable spare parts and reduce stock investments.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2021)
Article
Engineering, Manufacturing
Christiane B. Haubitz, Ulrich W. Thonemann
Summary: Inventory optimization approaches often focus on steady-state performance and may overlook the transition from an initial state to the optimized state. This study addresses the issue by proposing a phased approach to changing base stock levels in order to avoid undesirable effects. By modeling the inventory transition as a finite-horizon optimization problem and applying specific methods, it is possible to control the transition process effectively and improve fill rates without exceeding the initial inventory budget.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Engineering, Industrial
M. Z. Babai, H. Chen, A. A. Syntetos, D. Lengu
Summary: This paper proposes a new Bayesian method based on compound Poisson distributions, which outperforms the traditional Poisson-based Bayesian method, especially in cases of high demand variability. Additionally, the non-parametric method shows improved performance for longer lead-times and higher demand variability compared to the parametric one.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Computer Science, Interdisciplinary Applications
Mustafa Hekimoglu, A. Gurhan Kok, Mustafa Sahin
Summary: This study develops an advanced stockout risk estimation system for repairable spare parts, using statistical data to estimate future stockout risks, and proposes a repairable inventory control system including repair expediting, inspection, and condemnation processes. The suggested method outperforms heuristic approaches in empirical tests, achieving high accuracy rates and suggesting savings of up to 8%.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Engineering, Industrial
Chaaben Kouki, Christian Larsen
Summary: The study focuses on a spare parts inventory system controlled by a base-stock policy, investigating two rationing policies for critically low inventory levels: reservation policy and threshold policy. Results show that in some cases, the threshold policy outperforms the reservation policy, while in other cases, the difference between the two is minimal.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Maria Iglesias-Mendoza, Akilu Yunusa-Kaltungo, Sara Hadleigh-Dunn, Ashraf Labib
Summary: The paper explores the importance of linking theory with practice in engineering and management education, emphasizing the need to train emergency response teams to cope with rare events and learn from them. By comparing two disaster cases, the relevance of advanced mental modeling approaches for root cause analysis in training is highlighted. Future training should adopt a balanced approach that encompasses dichotomies.
Article
Management
Dylan Jones, Sina Firouzy, Ashraf Labib, Athanasios Argyriou
Summary: This paper presents a methodology for allocating novel robotic devices to potential treatment centers in the South of the UK for enhanced access to prostate cancer diagnosis and treatment technology. A fuzzy logic and goal programming model is used to identify priority locations and optimize allocation decisions, with a comprehensive weight sensitivity analysis generating distinct solutions in a six-dimensional objective space.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Jean Khalil, Ashraf W. Labib
Summary: The purpose of this paper is to construct a fuzzy logic model that acts as a decision support system to minimize inventory-related costs in the field of industrial maintenance. The proposed approach relies on inputs from experts with consideration for incompleteness and inaccuracy, and involves two levels of decision making simultaneously. The results suggest that the fuzzy logic approach is accurate, satisfactory, and practical for this application, with limited sensitivity to data inaccuracies.
INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT
(2022)
Article
Engineering, Industrial
Ahmed Noaman Karar, Ashraf Labib, Dylan Francis Jones
Summary: This paper aims to design a comprehensive framework for an Agile Asset Performance Management system to effectively respond to major crises such as pandemics and fluctuations in demand, improving asset performance. The framework is adaptable to different scenarios and aims to systematize decision support processes to break silo working and promote clear communication among asset stakeholders.
JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING
(2022)
Review
Engineering, Industrial
M. Zied Babai, John E. Boylan, Bahman Rostami-Tabar
Summary: Demand forecasts are crucial for supply chain decision-making, with different levels of decisions requiring different levels of forecast granularity. Aggregating or disaggregating forecast data at different levels, and combining forecasts across levels, can improve accuracy.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Ivan Svetunkov, Huijing Chen, John E. Boylan
Summary: Short-term demand forecasting faces challenges in accurately estimating seasonality due to limited data histories. This study proposes a taxonomy called Parameters, Initial States, and Components (PIC) that leverages the homogenous features of time series. The framework is applied to vector exponential smoothing, and a model selection mechanism is developed to choose the appropriate PIC restrictions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Dylan Jones, Ashraf Labib, Kevin Willis, Joseph. T. Costello, Djamila Ouelhadj, Emmi Susanna Ikonen, Mikel Dominguez Cainzos
Summary: This paper presents a methodology for mapping and prioritizing research and innovation needs in a multi-disciplinary field. The methodology is applied to the field of Arctic maritime safety and security to guide a European Union funded research project. The methodology involves creating a hierarchy of needs through stakeholder workshops, literature review, and questionnaires, and then seeking stakeholder opinion to determine the importance and challenge level of each sub-need. A goal programming knapsack model is used to select priority needs based on overall importance, balance between topics, and balance between long-term research and short-term implementation needs.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Ahmed Noaman Karar, Ashraf Labib, Dylan Jones
Summary: This paper aims to assist asset owners in selecting the equipment maintenance package at the warranty termination time by proposing the shape package process (SPP), which facilitates the choice between multiple packages based on cost and risk considerations. The main novelty lies in introducing two new parameters, the risk reduction factor (RRF) and the value-added indicator (VAI), to compare maintenance packages. Additionally, the suggested process maps the risk profile associated with each package, enabling a cost-cutting process by identifying and eliminating tasks with less value and risk mitigation.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Computer Science, Information Systems
Ashraf Labib, Salem Chakhar, Lorraine Hope, John Shimell, Mark Malinowski
Summary: An intelligence information system (IIS) is a specialized information system for analyzing intelligence relevant to national security. This paper introduces an innovative IIS tool that enhances the effectiveness and efficiency of intelligence analysis for both individual and team analysts.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Soodabeh Amiri Ali Akbar Khani, Siamak Kheybari, Mohammad-Ali Latifi, Negin Salimi, Ashraf Labib
Summary: Traditional industries need innovation to adapt to fast technological advancement, and this research aims to identify and address innovation barriers for better survival and improvement.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2023)
Article
Computer Science, Artificial Intelligence
Fariba Goodarzian, Peiman Ghasemi, Angappa Gunasekaran, Ashraf Labib
Summary: The COVID-19 pandemic has brought pandemic modeling to the forefront of global public policymaking. However, forecasting and modeling the COVID-19 medical waste and its detoxification center remain challenging. This study presents a Fuzzy Inference System for forecasting COVID-19 medical waste and categorizes individuals into different groups based on disease symptoms. A fuzzy sustainable model for COVID-19 medical waste supply chain network is developed for the first time to minimize costs and environmental impact. The study emphasizes the importance of utilizing a detoxification center and controlling social responsibility centers to manage the COVID-19 outbreak and reduce its impact.
FUZZY OPTIMIZATION AND DECISION MAKING
(2023)
Article
Engineering, Industrial
Ahmed Noaman Karar, Ashraf Labib, Dylan Jones
Summary: This research aims to design a resilience-based maintenance optimisation framework that employs the analytical hierarchy process and Knapsack method to select optimum maintenance tasks based on different operating scenarios, in order to improve asset maintenance efficiency and reduce risk.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Computer Science, Interdisciplinary Applications
Lar English, Akilu Yunusa-Kaltungo, Moray Kidd, Ashraf Labib
Summary: A correctly compiled asset register is crucial for a successful asset data solution, but organizations often lack structured asset registers. A case study identified anomalies and provided a comprehensive solution, while also highlighting challenges with software applications. Recommendations for successful deployment of AIMS, focusing on a reliable asset register, were proposed in the study.
ENGINEERING REPORTS
(2022)
Article
Management
Ahmad Ghaith, Huimin Ma, Ashraf W. Labib
Summary: The research aims to explore how High-Reliability Organizations (HROs) achieve high-quality performance in high-risk environments. Through in-depth interviews and literature review, the study found that the organizational framework is a key determinant for achieving high-reliability performance, but it cannot solely explain how HROs manage risk events and operate safely in high-hazard environments.
INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT
(2022)
Article
Engineering, Industrial
Ahmed Noaman Karar, Ashraf Labib
Summary: This paper proposes a framework for an agile criticality assessment process using decision-making grid (DMG), which has shown consistent results and improved asset distribution. The effectiveness of this method in optimizing time and effort has been validated through an industrial case study.
JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING
(2022)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
