International Journal of Industrial Engineering: Theory, Applications and Practice
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Modeling Logistics of Maintenance Services in Large Facility Portfolios: Modeling Logistics of Maintenance Services
No full textWe study maintenance service operations in large facilities portfolios with a focus on modeling logistics of associated spare parts and their storage locations serviced by personnel from several trades who move around the buildings in their vehicles. The key challenge is to reduce the cost of spare parts inventory, storage, and vehicles while providing responsive customer service. To address these challenges, we propose (i) inventory models to determine stock levels and (ii) storage space in personnel vehicles to allocate the mix and location of spare parts by trade. The two models can be readily integrated, and conceptually, technician vehicles serve as “forward-reserve storage” that improves service responsiveness. The proposed model is applied to a large facility of a non-profit organization with 330 buildings, 17,000 spare parts, and 254 vehicles. Compared to prevailing practice, the proposed model can potentially reduce $1.27 million worth of inventory costs, a reduction of ~77%
OPTIMIZATION MODEL OF COLD CHAIN LOGISTICS DELIVERY PATH BASED ON GENETIC ALGORITHM
No full textThis study is for optimizing the distribution path problem of cold chain logistics. This study proposes an improved genetic algorithm that introduces natural number coding, elite preservation strategy and adaptive cross-mutation strategy. A cold chain logistics distribution path optimization model is constructed, taking into account various costs, including customer demand, time window requirements, maximum mileage of refrigerated trucks, payload, and other constraints. To address the cold chain logistics distribution path, an improved genetic algorithm is utilized. This study designs experiments to test the performance of improved genetic algorithms and applies the model to an example for experimental analysis. The results show that the improved genetic algorithm has better performance in convergence and convergence speed. From the perspective of distribution cost, the optimization model based on the improved algorithm significantly reduces the total distribution cost compared with that before optimization. The above results show that this study effectively optimizes the cold chain logistics distribution route by improving the genetic algorithm and significantly reducing the total distribution cost. This study not only proves the effectiveness of elite preservation strategy and adaptive cross-variation strategy but also shows the importance of considering various costs and constraints comprehensively. This provides a valuable optimization tool for the cold chain logistics industry, helps to improve efficiency and reduce costs, and has important practical significance
SYSTEM DYNAMICS ANALYSIS FOR IMPACT OF CLOUD-BASED INFORMATION-SHARING ON SUPPLY CHAIN PERFORMANCE
No full textCloud computing has emerged as a vital tool for facilitating information-sharing and collaboration in supply chain operations. However, how the information is shared in the cloud-based supply chain has not been thoroughly investigated. Thus, adopting a system dynamics approach, this research deepens the understanding of information transmission within the supply chain by proposing a general stock and flow model and endorsing the model in an equipment manufacturing setting in China. Building upon the general model, this paper establishes a conceptual framework for cloud-based information-sharing mechanisms both within and across supply chains. The impact of cloud-based information-sharing on supply chain performance is evaluated by inventory level and customer satisfaction. The findings indicate a positive influence of information-sharing on supply chain performance. Notably, sharing information across supply chains enhances customer satisfaction to a greater extent than within the supply chain. However, it does not lead to a significant increase in inventory levels. This research expounds on the impact of information-sharing on the supply chain in quantitative forms, which is of theoretical and practical significance to the field of supply chain management
A NEW BI-OBJECTIVE MODEL TO OPTIMIZE SOLID TRANSPORTATION UNDER UNCERTAINTY TO FACILITATE CATASTROPHE VICTIMS: A CASE STUDY
No full textThis study addresses the crucial challenge of efficient resource allocation during emergencies, aiming to minimize loss of life and property. We analyzed a case study for the 2015 floods in Tamil Nadu, India, where local emergency centers in Chennai and surrounding cities distributed relief materials. Additionally, employing a Bi-objective Solid Transportation Problem (BOSTP) model, minimizes both cost and time of delivery. Further, the traditional methods like Row Maximum, Least Cost, and Vogel's Approximation are compared to BOSTP, which shows that Column Maximum yields an optimal result based on cost and time constraints. However, introduced a novel algorithm for BOSTP using trapezoidal neutrosophic numbers(TNN) to account for inherent uncertainties in logistics, specifically shipment cost and time. Lastly, performance analysis of the BOSTP model and sensitivity analysis under various scenarios demonstrate its effectiveness in enhancing rapid humanitarian assistance during emergencies. This case study contributes to developing efficient bi-objective models for future disaster response efforts
PROJECT SELECTION REVISITED: CUSTOMIZED TYPE-2 FUZZY ORESTE APPROACH FOR PROJECT PRIORITIZATION
Get PDFIn this study, a customized version of a less-preferred methodology in decision-making processes, i.e., the interval type-2 fuzzy ORESTE (IT2F-ORESTE), is proposed, and its effectiveness for selecting the most viable projects is demonstrated. The findings are evaluated against those of fuzzy TOPSIS, which is among the most preferred methods, to provide evidence that the proposed method achieves comparable and even superior results. To this end, multicriteria decision-making studies conducted between 2016 and 2021 were examined. Subsequently, 30 automotive manufacturing projects were evaluated over seven criteria using the fuzzy TOPSIS and customized IT2F-ORESTE methods. The results revealed that IT2F-ORESTE assigned the highest ranks to projects with high earning potential, low cost, low number of operations, and high production capacity, whereas fuzzy TOPSIS failed to select the best project. To the best of the authors’ knowledge, this is the first study to utilize this new IT2F-ORESTE method in project evaluation within the automotive industry and demonstrate its superiority over that of conventional methods
A Data-Driven Approach to The City Last-Mile Delivery Problem Towards The Application of Shared Delivery Terminals
No full textThe application of shared delivery terminals is a promising trend in the development of last-mile delivery in city logistics because it can effectively improve the
The application of shared delivery terminals is a promising trend in the development of last-mile delivery in city logistics because it can effectively improve the delivery efficiency of couriers and relax the time-window restrictions for customers to pick up their parcels. In this study, we investigated a vehicle routing problem (VRP) for the application of shared delivery terminals in last-mile delivery. In practical delivery scenarios, the random storage and retrieval behaviors of customers can affect the usage of shared delivery terminals and lead to inevitable uncertainty regarding their available capacity, thereby increasing the complexity of last-mile delivery. To address this issue, we propose a VRP with stochastic terminal capacity (VRPSTC) and design a data-driven predictive optimization approach by collecting first-hand usage data on shared delivery terminals, forecasting the available capacity and optimizing the operational delivery schedule in practice. Numerical experiments show that the proposed data-driven approach can effectively solve the proposed VRPSTC and contribute to an approximately 17%–20% reduction in the total delivery cost compared with traditional stochastic optimization. The proposed VRPSTC is expected to enrich the concept of last-mile delivery in terms of both theoretical research and practical industrial applications.
efficiency of couriers and relax the time-window restrictions for customers to pick up their parcels. In this study, we investigated a vehicle routing problem (VRP) for the application of shared delivery terminals in last-mile delivery. In practical delivery scenarios, the random storage and retrieval behaviors of customers can affect the usage of shared delivery terminals and lead to inevitable uncertainty regarding their available capacity, thereby increasing the complexity of last-mile delivery. To address this issue, we propose a VRP with stochastic terminal capacity (VRPSTC) and design a data-driven predictive optimization approach by collecting first-hand usage data on shared delivery terminals, forecasting the available capacity and optimizing the operational delivery schedule in practice. Numerical experiments show that the proposed data-driven approach can effectively solve the proposed VRPSTC and contribute to an approximately 17%–20% reduction in the total delivery cost compared with traditional stochastic optimization. The proposed VRPSTC is expected to enrich the concept of last-mile delivery in terms of both theoretical research and practical industrial applications
Decision Making Approach for Best Mobile Phone Service Provider Selection Using Laplacian Energy and Cosine Similarity Measures of Hesitancy Fuzzy Graph
No full textTelecommunication is one of the essential necessities of everyday life. In India, the telecommunications sector has seen a significant increase in the day-to-day. Telecommunications service companies hold data about their customers, and crisp graphs are used to depict these records. Examining and selecting the best mobile phone service providers (MPSPs) based on operational restrictions will help determine the best MPSPs. The analysis of MPSPs may be regarded as a difficult decision-making issue. The aim of this article is to provide an outline to examine the performance of MPSPs and the selection of the best MPSP for customers in India. The statistical data were obtained from the Telecom Regulatory Authority of India between April 2019 and March 2021. A novel approach for cosine similarity measures (CSM) among hesitancy fuzzy graphs (HFG) and estimating the certified repute scores of the experts by determining the ambiguous information of hesitancy fuzzy preference relations (HFPRs) and the regular cosine similarity grades from one separable HFPR to some others. And consider “objective” and “subjective” information given by experts. According to CSMs, we define the Laplacian energy of an HFG. This research provides a solution to a decision-making problem by applying the newly developed cosine similarity measure and the Laplacian energy of hesitancy fuzzy graphs. The ranking order of all alternatives and the best one is determined by calculating the cosine similarity between each alternative and the ideal alternative. Finally, an illustrated example is provided to show the applicability of the proposed approach to the decision-making problem as well as its effectiveness
INTEGRATED NEUTROSOPHIC DEMATEL, TOPSIS, AND GRA APPROACH FOR FINANCIAL RATIO PERFORMANCE EVALUATION OF NASDAQ EXCHANGE
No full textAccounting and economic-based financial metrics play a crucial role in-stock selection or stock ranking by providing objective and quantifiable measures of a company's financial health and performance. These metrics are used by investors, analysts, and portfolio managers to assess the potential risks and returns associated with investing in a particular stock. This study aims to contribute to stock selection and ranking methodologies by proposing a novel Multi-Criteria Decision-Making (MCDM) model. The model integrates the Decision-Making Trial and Evaluation Laboratory (DEMATEL), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Grey Relational Analysis (GRA) approaches within a neutrosophic environment. Focusing on companies listed on the NASDAQ stock exchange, the research evaluates financial metrics from June 2018 to May 2022, specifically in the Information Technology sector across eight industries. The financial metrics are categorized into two groups: accounting-based financial measures (AFM) and economic value-based financial measures (EFM). Two experts assess the data, and the neutrosophic DEMATEL approach is employed to calculate the weights of the criteria. Subsequently, companies are ranked using neutrosophic TOPSIS and GRA methods. In conclusion, the study conducts a sensitivity analysis using the neutrosophic GRA method to validate the efficiency of the ranking. This research significantly contributes to the field by introducing a comprehensive MCDM model that amalgamates various decision-making techniques within a neutrosophic framework. The results not only provide valuable insights into stock ranking on the NASDAQ stock exchange but also demonstrate the efficacy of the proposed methodology. The integration of DEMATEL, TOPSIS, and GRA in a neutrosophic environment adds originality to the existing literature on financial metrics and MCDM models in stock selection
Development of The Reliability Assessment in Preventive Maintenance of Heat, Ventilation, and Air Conditioning (HVAC) Systems for The Production of Pharmaceutical Product
No full textThe support system of heat, ventilation, and air conditioning (HVAC) in manufacturing plants plays an important role in the optimum efficiency of the production system. Failure to support adequate HVAC on the production floor will cause production defects, stoppage time, unplanned machine downtime, and other related issues. These issues highly affect those products that require dedicated temperature, pressure, and humidity, such as production clean rooms, food industries, and pharmaceutical products. Thus, this study aims to develop and apply the specific reliability assessment in an investigation of HVAC, focusing on the production of pharmaceutical products. In this study, the selected statistical quality tools have been applied in the evaluation and prediction of the HVAC failure and maintenance process. To ensure suitable tools and methods will be applied, a systematic approach has been developed consisting of six steps towards effective maintenance of the HVAC system. The main purpose of the application quality tools such as check sheet, Pareto chart, scatter plot, and probability plot was to evaluate the historical failure data and then to predict the potential future failure through analysis of Mean Time Between Failure (MTBF) in steps 1 to 4. To ensure the developed approach successfully implemented the Failure Mode and Effects Analysis (FMEA) in step 5, the corrective action plan was suggested in step 6. Once the systematic approach of HVAC preventive maintenance had been successfully developed, it was then implemented in the selected production floor of the pharmaceutical industry. The execution of this developed systematic approach to predicting the HVAC resulted in an increase in the total MTBF from 529.50 minutes to 778.23 minutes. It showed an improvement of 47% after the implementation of the developed systematic approach. The obtained results showed that reliability assessment was important for the optimization of production efficiency
Ergonomic Assessment of Embroidery Operators' Working Postures Through Ovako Working posture Assessment System and The Cornell Musculoskeletal Discomfort Questionnaire Methods
No full textRisk factors that threaten body health are likely to be present mostly in every work environment where human power is utilized. An occupational disease is defined as a state of physical disability arising from the way the work is conducted due to the nature of the work done. While employers ensure that their production flows continuously, they should also take various precautions by conducting scientific methods to protect their operators from occupational diseases. This study was carried out among 34 people working in 3 different embroidery facilities. The working postures of the participants were first examined within OWAS (Ovako Working posture Assessment System) as an observatory method. Afterward, to include the operators’ perceptions, the opinions of the operators were also evaluated through the CMDQ (The Cornell Musculoskeletal Discomfort Questionnaire). In this way, a multi-faceted evaluation system was implemented via both external observation and internal evaluation. Based on the study findings, relying on the OWAS method, ergonomic measures should be taken as early as possible, mainly in the preparation and collection stages (40.9% and 43.8%), whereas the embroidery process requires these precautions predominantly (42,6%). According to the CMDQ results, male personnel are more likely to suffer from the back, waist, neck, and hip parts of the body. On the other hand, the female personnel reported loading more on the hips, waist, back, and neck parts of their bodies. Although the same body parts are loaded in male and female operators, the discomfort level of these parts differs among the genders