Pub Date : 2021-10-08DOI: 10.1108/ijqrm-09-2020-0316
C. Bhargava, P. Sharma
PurposeAlthough Multi-Layer Ceramic Capacitors (MLCC) are known for its better frequency performance and voltage handling capacity, but under various environmental conditions, its reliability becomes a challenging issue. In modern era of integration, the failure of one component can degrade or shutdown the whole electronic device. The lifetime estimation of MLCC can enhance the reuse capability and furthermore, reduces the e-waste, which is a global issue.Design/methodology/approachThe residual lifetime of MLCC is estimated using empirical method i.e. Military handbook MILHDBK2017F, statistical method i.e. regression analysis using Minitab18.1 as well as intelligent technique i.e. artificial neural networks (ANN) using MATLAB2017b. ANN Feed-Forward Back-Propagation learning with sigmoid transfer function [3–10–1–1] is considered using 73% of available data for training and 27% for testing and validation. The design of experiments is framed using Taguchi’s approach L16 orthogonal array.FindingsAfter exploring the lifetime of MLCC, using empirical, statistical and intelligent techniques, an error analysis is conducted, which shows that regression analysis has 97.05% accuracy and ANN has 94.07% accuracy.Originality/valueAn intelligent method is presented for condition monitoring and health prognostics of MLCC, which warns the user about its residual lifetime so that faulty component can be replaced in time.
{"title":"Statistical and intelligent reliability analysis of multi-layer ceramic capacitor for ground mobile applications using Taguchi’s approach","authors":"C. Bhargava, P. Sharma","doi":"10.1108/ijqrm-09-2020-0316","DOIUrl":"https://doi.org/10.1108/ijqrm-09-2020-0316","url":null,"abstract":"PurposeAlthough Multi-Layer Ceramic Capacitors (MLCC) are known for its better frequency performance and voltage handling capacity, but under various environmental conditions, its reliability becomes a challenging issue. In modern era of integration, the failure of one component can degrade or shutdown the whole electronic device. The lifetime estimation of MLCC can enhance the reuse capability and furthermore, reduces the e-waste, which is a global issue.Design/methodology/approachThe residual lifetime of MLCC is estimated using empirical method i.e. Military handbook MILHDBK2017F, statistical method i.e. regression analysis using Minitab18.1 as well as intelligent technique i.e. artificial neural networks (ANN) using MATLAB2017b. ANN Feed-Forward Back-Propagation learning with sigmoid transfer function [3–10–1–1] is considered using 73% of available data for training and 27% for testing and validation. The design of experiments is framed using Taguchi’s approach L16 orthogonal array.FindingsAfter exploring the lifetime of MLCC, using empirical, statistical and intelligent techniques, an error analysis is conducted, which shows that regression analysis has 97.05% accuracy and ANN has 94.07% accuracy.Originality/valueAn intelligent method is presented for condition monitoring and health prognostics of MLCC, which warns the user about its residual lifetime so that faulty component can be replaced in time.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48783526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-07DOI: 10.1108/ijqrm-03-2021-0062
Sandra García-Bustos, Nadia Cárdenas-Escobar, A. Debón, César Pincay
PurposeThe study aims to design a control chart based on an exponentially weighted moving average (EWMA) chart of Pearson's residuals of a model of negative binomial regression in order to detect possible anomalies in mortality data.Design/methodology/approachIn order to evaluate the performance of the proposed chart, the authors have considered official historical records of death of children of Ecuador. A negative binomial regression model was fitted to the data, and a chart of the Pearson residuals was designed. The parameters of the chart were obtained by simulation, as well as the performances of the charts related to changes in the mean of death.FindingsWhen the chart was plotted, outliers were detected in the deaths of children in the years 1990–1995, 2001–2006, 2013–2015, which could show that there are underreporting or an excessive growth in mortality. In the analysis of performances, the value of λ = 0.05 presented the fastest detection of changes in the mean death.Originality/valueThe proposed charts present better performances in relation to EWMA charts for deviance residuals, with a remarkable advantage of the Pearson residuals, which are much easier to interpret and calculate. Finally, the authors would like to point out that although this paper only applies control charts to Ecuadorian infant mortality, the methodology can be used to calculate mortality in any geographical area or to detect outbreaks of infectious diseases.
{"title":"A control chart based on Pearson residuals for a negative binomial regression: application to infant mortality data","authors":"Sandra García-Bustos, Nadia Cárdenas-Escobar, A. Debón, César Pincay","doi":"10.1108/ijqrm-03-2021-0062","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0062","url":null,"abstract":"PurposeThe study aims to design a control chart based on an exponentially weighted moving average (EWMA) chart of Pearson's residuals of a model of negative binomial regression in order to detect possible anomalies in mortality data.Design/methodology/approachIn order to evaluate the performance of the proposed chart, the authors have considered official historical records of death of children of Ecuador. A negative binomial regression model was fitted to the data, and a chart of the Pearson residuals was designed. The parameters of the chart were obtained by simulation, as well as the performances of the charts related to changes in the mean of death.FindingsWhen the chart was plotted, outliers were detected in the deaths of children in the years 1990–1995, 2001–2006, 2013–2015, which could show that there are underreporting or an excessive growth in mortality. In the analysis of performances, the value of λ = 0.05 presented the fastest detection of changes in the mean death.Originality/valueThe proposed charts present better performances in relation to EWMA charts for deviance residuals, with a remarkable advantage of the Pearson residuals, which are much easier to interpret and calculate. Finally, the authors would like to point out that although this paper only applies control charts to Ecuadorian infant mortality, the methodology can be used to calculate mortality in any geographical area or to detect outbreaks of infectious diseases.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47320735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-06DOI: 10.1108/ijqrm-03-2021-0085
Sanjeev Yadav, D. Garg, S. Luthra
PurposeThe prime aim of this paper is the identification and prioritization of performance indicators, which motivate the development of an Internet of Things (IoT)-based traceability system for the agriculture supply chain (ASC). Also, this research aims for checking the robustness of obtained results.Design/methodology/approachTen performance indicators have been identified based on the five “criteria in the IoT-based traceable system”. Further, based on five criteria, performance indicators were ranked by using grey-based “Additive Ratio Assessment”.FindingsSustainable practices obtained first rank, and certification of agri-products obtained worst ranking. Further, based on sensitivity analysis, tracking of agri-products and stakeholders' behavior have found high sensitivity. Also, information sharing and global distribution networks have found the least sensitive performance indicators.Research limitations/implicationsThis research has some limitations of taking only a few criteria and alternatives. This study may also contribute as a practical insight to the practitioners and managers in decision-making in the adoption of an IoT-based traceable system within the ASC.Originality/valueThis research may motivate the implementation of an IoT-based efficient traceability mechanism that improved the sustainability and consumer's trust in the ASC during different types of hazardous activities and other outbreaks (COVID-19). Also, this research has provided a theoretical insight based on the dynamic capability theory (DCT).
{"title":"Ranking of performance indicators in an Internet of Things (IoT)-based traceability system for the agriculture supply chain (ASC)","authors":"Sanjeev Yadav, D. Garg, S. Luthra","doi":"10.1108/ijqrm-03-2021-0085","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0085","url":null,"abstract":"PurposeThe prime aim of this paper is the identification and prioritization of performance indicators, which motivate the development of an Internet of Things (IoT)-based traceability system for the agriculture supply chain (ASC). Also, this research aims for checking the robustness of obtained results.Design/methodology/approachTen performance indicators have been identified based on the five “criteria in the IoT-based traceable system”. Further, based on five criteria, performance indicators were ranked by using grey-based “Additive Ratio Assessment”.FindingsSustainable practices obtained first rank, and certification of agri-products obtained worst ranking. Further, based on sensitivity analysis, tracking of agri-products and stakeholders' behavior have found high sensitivity. Also, information sharing and global distribution networks have found the least sensitive performance indicators.Research limitations/implicationsThis research has some limitations of taking only a few criteria and alternatives. This study may also contribute as a practical insight to the practitioners and managers in decision-making in the adoption of an IoT-based traceable system within the ASC.Originality/valueThis research may motivate the implementation of an IoT-based efficient traceability mechanism that improved the sustainability and consumer's trust in the ASC during different types of hazardous activities and other outbreaks (COVID-19). Also, this research has provided a theoretical insight based on the dynamic capability theory (DCT).","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49127033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-04DOI: 10.1108/ijqrm-04-2021-0114
Hemant Sharma, N. Sohani, Ashish Yadav
PurposeIn the recent scenario, there has been an increasing trend toward lean practices and implementation in production systems for the improvement of an organization’s performance as its basic nature is to eliminate the wastes. The increasing interest of customers in customized products and the fulfillment of customers’ demand with good productivity and efficiency within time are the challenges for the manufacturing organization; that is why adopting lean manufacturing concept is very crucial in the current scenario.Design/methodology/approachIn this paper, the authors considered three different methodologies for fulfilling the objective of our research. The analytical hierarchy process, best–worst method and fuzzy step-wise weight assessment ratio analysis are the three methods employed for weighting all the enablers and finding the priority among them and their final rankings.FindingsFurther, the best results among these methodologies could be used to analyze their interrelationships for successful lean supply chain management implementation in an organization. In this paper, 35 key enablers were identified after the rigorous analysis of literature review and the opinion of a group of experts consisting of academicians, practitioners and consultants. Thereafter, the brainstorming sessions were conducted to finalize 28 lean supply chain enablers (LSCEs).Practical implicationsFor lean manufacturing practitioners, the result of this study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process.Originality/valueThis paper is the first of the research papers that considered deep literature review of identified LSCEs as the initial step, followed by finding the best priority weightage and developing the ranking of various lean enablers of supply chain with the help of various methodologies.
{"title":"Comparative analysis of ranking the lean supply chain enablers: An AHP, BWM and fuzzy SWARA based approach","authors":"Hemant Sharma, N. Sohani, Ashish Yadav","doi":"10.1108/ijqrm-04-2021-0114","DOIUrl":"https://doi.org/10.1108/ijqrm-04-2021-0114","url":null,"abstract":"PurposeIn the recent scenario, there has been an increasing trend toward lean practices and implementation in production systems for the improvement of an organization’s performance as its basic nature is to eliminate the wastes. The increasing interest of customers in customized products and the fulfillment of customers’ demand with good productivity and efficiency within time are the challenges for the manufacturing organization; that is why adopting lean manufacturing concept is very crucial in the current scenario.Design/methodology/approachIn this paper, the authors considered three different methodologies for fulfilling the objective of our research. The analytical hierarchy process, best–worst method and fuzzy step-wise weight assessment ratio analysis are the three methods employed for weighting all the enablers and finding the priority among them and their final rankings.FindingsFurther, the best results among these methodologies could be used to analyze their interrelationships for successful lean supply chain management implementation in an organization. In this paper, 35 key enablers were identified after the rigorous analysis of literature review and the opinion of a group of experts consisting of academicians, practitioners and consultants. Thereafter, the brainstorming sessions were conducted to finalize 28 lean supply chain enablers (LSCEs).Practical implicationsFor lean manufacturing practitioners, the result of this study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process.Originality/valueThis paper is the first of the research papers that considered deep literature review of identified LSCEs as the initial step, followed by finding the best priority weightage and developing the ranking of various lean enablers of supply chain with the help of various methodologies.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49014991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-30DOI: 10.1108/ijqrm-03-2021-0078
Damla Yüksel, Y. Kazançoğlu, P. Sarma
PurposeThis paper aims to create a new decision-making procedure that uses “Lot-by-Lot Acceptance Sampling Plan by Attributes” methodology in the production processes when any production interruption is observed in tobacco industry, which is a significant example of batch production.Design/methodology/approachBased on the fish bone diagram, the reasons of the production interruptions are categorized, then Lot-by-Lot Acceptance Sampling Plan by Attributes is studied to overcome the reasons of the production interruptions. Furthermore, managerial aspects of decision making are not ignored and hence, acceptance sampling models are determined by an Analytical Hierarchy Process (AHP) among the alternative acceptance sampling models.FindingsA three-phased acceptance sampling model is generated for determination of the reasons of production interruptions. Hence, the necessary actions are provided according to the results of the proposed acceptance sampling model. Initially, 729 alternative acceptance sampling models are found and 38 of them are chosen by relaxation. Then, five acceptance sampling models are determined by AHP.Practical implicationsThe current experience dependent decision mechanism is suggested to be replaced by the proposed acceptance sampling model which is based on both statistical and managerial decision-making procedure.Originality/valueAcceptance sampling plans are considered as a decision-making procedure for various cases in production processes. However, to the best of our knowledge Lot-by-Lot Acceptance Sampling Plan by Attributes has not been considered as a decision-making procedure for batch production when any production interruption is investigated.
{"title":"A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry","authors":"Damla Yüksel, Y. Kazançoğlu, P. Sarma","doi":"10.1108/ijqrm-03-2021-0078","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0078","url":null,"abstract":"PurposeThis paper aims to create a new decision-making procedure that uses “Lot-by-Lot Acceptance Sampling Plan by Attributes” methodology in the production processes when any production interruption is observed in tobacco industry, which is a significant example of batch production.Design/methodology/approachBased on the fish bone diagram, the reasons of the production interruptions are categorized, then Lot-by-Lot Acceptance Sampling Plan by Attributes is studied to overcome the reasons of the production interruptions. Furthermore, managerial aspects of decision making are not ignored and hence, acceptance sampling models are determined by an Analytical Hierarchy Process (AHP) among the alternative acceptance sampling models.FindingsA three-phased acceptance sampling model is generated for determination of the reasons of production interruptions. Hence, the necessary actions are provided according to the results of the proposed acceptance sampling model. Initially, 729 alternative acceptance sampling models are found and 38 of them are chosen by relaxation. Then, five acceptance sampling models are determined by AHP.Practical implicationsThe current experience dependent decision mechanism is suggested to be replaced by the proposed acceptance sampling model which is based on both statistical and managerial decision-making procedure.Originality/valueAcceptance sampling plans are considered as a decision-making procedure for various cases in production processes. However, to the best of our knowledge Lot-by-Lot Acceptance Sampling Plan by Attributes has not been considered as a decision-making procedure for batch production when any production interruption is investigated.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41710133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-29DOI: 10.1108/ijqrm-03-2021-0075
M. Hossain, V. Thakur
PurposeThis paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.Design/methodology/approachThe drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.FindingsThe findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.Practical implicationsThe HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.Originality/valueThe validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.
{"title":"Drivers of sustainable healthcare supply chain performance: multi-criteria decision-making approach under grey environment","authors":"M. Hossain, V. Thakur","doi":"10.1108/ijqrm-03-2021-0075","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0075","url":null,"abstract":"PurposeThis paper aims to explore the drivers of sustainable healthcare supply chain (SHCSC) performance measurement through extensive literature review and experts' opinions. The drivers are then scrutinized and their priority vector is calculated to provide quality and cost-effective healthcare supply chain (HCSC) services.Design/methodology/approachThe drivers of the SHCSC performance measurement are validated using the grey-Delphi technique. After validating the drivers, they are prioritized using the grey-analytic hierarchy process (G-AHP), a multi-criteria decision-making tool.FindingsThe findings of the study highlight the prioritized drivers based on the preferences given by the experts. The findings of the study highlight the most prioritized drivers of healthcare (HC) by-product management system, coordinating and facilitating green suppliers in the HCSC and green packaging of pharmaceutical as well as other essential items.Practical implicationsThe HCSC managers should coordinate with all the stakeholders across the supply chain and involve them in the decision-making process to make products and services greener and become complicit in complying with the sustainable policy guidelines. The study highlights the strategic policy and managerial implications for implementing sustainability in the HCSC.Originality/valueThe validation and prioritization of the drivers of SHCSC in developing nations' contexts is the key contribution of the study. Grey-AHP enables a practical approach towards enhancing the sustainability of the HCSC and opening the doors for generalizing the study for future research works.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47648308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-28DOI: 10.1108/IJQRM-09-2020-0300
Oscar Daniel Rivera Baena, Maria Valentina Clavijo Mesa, C. E. P. Rodriguez, F. Carazas
{"title":"Identification of asset life cycle stage: case study in heavy-duty truck fleet","authors":"Oscar Daniel Rivera Baena, Maria Valentina Clavijo Mesa, C. E. P. Rodriguez, F. Carazas","doi":"10.1108/IJQRM-09-2020-0300","DOIUrl":"https://doi.org/10.1108/IJQRM-09-2020-0300","url":null,"abstract":"","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47176575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-28DOI: 10.1108/ijqrm-06-2021-0193
R. K. Jana, Devender Kumar Sharma, S. Mitra
PurposeThe purpose of this paper is to offer improvement in routing and collection load decisions for a green logistics system that delivers lunch boxes.Design/methodology/approachA mathematical model is introduced into the literature for the 130 years old logistics systems whose delivery accuracy is better than the Six Sigma standard without using sophisticated tools. A simulated annealing (SA) approach is then used to find the routing and collection load decisions for the lunch box career.FindingsThe findings establish that we can improve the world-class lunch box delivery (LBD) system. The suggested improvement in terms of reduction in distance travel is nearly 6%. This could be a huge relief for thousands of lunch box careers. The uniformity in collection load decisions suggested by the proposed approach can be more effective for the elderly lunch box carriers.Research limitations/implicationsThe research provides a mathematical framework to study an important logistics system that is running with a supreme level of service accuracy. Collecting primary data was challenging as there is no scope for recording and maintaining data in the present logistics system. The replicability of the system for some other city in the world is a challenging question to answer.Practical implicationsBetter routing and collection load decisions can help many lunch box careers save time and bring homogeneity in workload into the system.Social implicationsAn efficient routing decision can help provide smoother traffic movements, and uniformity in collection load can help avoid unwanted injuries to about 5,000 lunch box careers.Originality/valueThe originality of this paper lies in the proposed mathematical model and finding the routing and collection load decisions using a nature-inspired probabilistic search technique. The LBD system of Mumbai was never studied mathematically. The study is the first of its kind.
{"title":"Routing and collection load decisions in a green logistics system for delivering lunch boxes","authors":"R. K. Jana, Devender Kumar Sharma, S. Mitra","doi":"10.1108/ijqrm-06-2021-0193","DOIUrl":"https://doi.org/10.1108/ijqrm-06-2021-0193","url":null,"abstract":"PurposeThe purpose of this paper is to offer improvement in routing and collection load decisions for a green logistics system that delivers lunch boxes.Design/methodology/approachA mathematical model is introduced into the literature for the 130 years old logistics systems whose delivery accuracy is better than the Six Sigma standard without using sophisticated tools. A simulated annealing (SA) approach is then used to find the routing and collection load decisions for the lunch box career.FindingsThe findings establish that we can improve the world-class lunch box delivery (LBD) system. The suggested improvement in terms of reduction in distance travel is nearly 6%. This could be a huge relief for thousands of lunch box careers. The uniformity in collection load decisions suggested by the proposed approach can be more effective for the elderly lunch box carriers.Research limitations/implicationsThe research provides a mathematical framework to study an important logistics system that is running with a supreme level of service accuracy. Collecting primary data was challenging as there is no scope for recording and maintaining data in the present logistics system. The replicability of the system for some other city in the world is a challenging question to answer.Practical implicationsBetter routing and collection load decisions can help many lunch box careers save time and bring homogeneity in workload into the system.Social implicationsAn efficient routing decision can help provide smoother traffic movements, and uniformity in collection load can help avoid unwanted injuries to about 5,000 lunch box careers.Originality/valueThe originality of this paper lies in the proposed mathematical model and finding the routing and collection load decisions using a nature-inspired probabilistic search technique. The LBD system of Mumbai was never studied mathematically. The study is the first of its kind.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43450366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-24DOI: 10.1108/ijqrm-12-2020-0409
A. Sharma, I. Mukherjee, Sasadhar Bera, R. Sengupta
PurposeThe primary objective of this study is to propose a robust multiobjective solution search approach for a mean-variance multiple correlated quality characteristics optimisation problem, so-called “multiple response optimisation (MRO) problem”. The solution approach needs to consider response surface (RS) model parameter uncertainties, response uncertainties, process setting sensitivity and response correlation strength to derive the robust solutions iteratively.Design/methodology/approachThis study adopts a new multiobjective solution search approach to determine robust solutions for a typical mean-variance MRO formulation. A fine-tuned, non-dominated sorting genetic algorithm-II (NSGA-II) is used to derive efficient multiobjective solutions for varied mean-variance MRO problems. The iterative search considers RS model uncertainties, process setting uncertainties and response correlation structure to derive efficient fronts. The final solutions are ranked based on two different multi-criteria decision-making (MCDM) techniques.FindingsFive different mean-variance MRO cases are selected from the literature to verify the efficacy of the proposed solution approach. Results derived from the proposed solution approach are compared and contrasted with the best solution(s) derived from other approaches suggested in the literature. Comparative results indicate significant superiorities of the top-ranked predicted robust solutions in nondominated frequency, closeness-to-target and response variabilities.Research limitations/implicationsThe solution approach depends on RS modelling and considers continuous search space.Practical implicationsIn this study, promising robust solutions are expected to be more suitable for implementation than point estimate-based MOO solutions for a real-life MRO problem.Originality/valueNo evidence of earlier research demonstrates the superiority of a MOO-based iterative solution search approach for mean-variance MRO problems by simultaneously considering model uncertainties, response correlation and process setting sensitivity.
本研究的主要目的是提出一种鲁棒的多目标解搜索方法来解决均值-方差多相关质量特征优化问题，即所谓的“多响应优化(MRO)问题”。求解方法需要考虑响应面模型参数的不确定性、响应的不确定性、过程设置的灵敏度和响应的关联强度等因素，迭代导出鲁棒解。设计/方法/方法本研究采用一种新的多目标解搜索方法来确定典型均值方差MRO公式的鲁棒解。采用一种微调的非支配排序遗传算法- ii (NSGA-II)，求解不同均值方差MRO问题的高效多目标解。迭代搜索考虑了RS模型的不确定性、过程设置的不确定性和响应的关联结构，从而得到有效的前沿。根据两种不同的多准则决策(MCDM)技术对最终的解决方案进行排名。研究结果从文献中选择了五个不同的均值方差MRO病例来验证所提出的解决方法的有效性。从所提出的解决方法得出的结果与从文献中建议的其他方法得出的最佳解决方案进行了比较和对比。比较结果表明，排名靠前的预测鲁棒解在非支配频率、接近目标和响应变量方面具有显著优势。研究局限/启示解决方法依赖于RS建模并考虑连续搜索空间。在本研究中，对于现实生活中的MRO问题，期望有希望的鲁棒解决方案比基于点估计的MOO解决方案更适合实施。原创性/价值先前的研究证据表明，同时考虑模型不确定性、响应相关性和过程设置敏感性的基于微信号的均值方差MRO问题迭代解搜索方法具有优越性。
{"title":"A robust multiobjective solution approach for mean-variance optimisation of correlated multiple quality characteristics","authors":"A. Sharma, I. Mukherjee, Sasadhar Bera, R. Sengupta","doi":"10.1108/ijqrm-12-2020-0409","DOIUrl":"https://doi.org/10.1108/ijqrm-12-2020-0409","url":null,"abstract":"PurposeThe primary objective of this study is to propose a robust multiobjective solution search approach for a mean-variance multiple correlated quality characteristics optimisation problem, so-called “multiple response optimisation (MRO) problem”. The solution approach needs to consider response surface (RS) model parameter uncertainties, response uncertainties, process setting sensitivity and response correlation strength to derive the robust solutions iteratively.Design/methodology/approachThis study adopts a new multiobjective solution search approach to determine robust solutions for a typical mean-variance MRO formulation. A fine-tuned, non-dominated sorting genetic algorithm-II (NSGA-II) is used to derive efficient multiobjective solutions for varied mean-variance MRO problems. The iterative search considers RS model uncertainties, process setting uncertainties and response correlation structure to derive efficient fronts. The final solutions are ranked based on two different multi-criteria decision-making (MCDM) techniques.FindingsFive different mean-variance MRO cases are selected from the literature to verify the efficacy of the proposed solution approach. Results derived from the proposed solution approach are compared and contrasted with the best solution(s) derived from other approaches suggested in the literature. Comparative results indicate significant superiorities of the top-ranked predicted robust solutions in nondominated frequency, closeness-to-target and response variabilities.Research limitations/implicationsThe solution approach depends on RS modelling and considers continuous search space.Practical implicationsIn this study, promising robust solutions are expected to be more suitable for implementation than point estimate-based MOO solutions for a real-life MRO problem.Originality/valueNo evidence of earlier research demonstrates the superiority of a MOO-based iterative solution search approach for mean-variance MRO problems by simultaneously considering model uncertainties, response correlation and process setting sensitivity.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42178423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-23DOI: 10.1108/ijqrm-03-2021-0053
Jorge A. Colazo
PurposeThis study aims to look at the performance, communication structure and media choice for swift teams (STs) formed with the purpose of recovering from operational emergencies in manufacturing. The problem-solving process associated with these ad hoc teams include an early stage, where the main goal is to restore the process to working conditions, and a later stage, longer in duration, where the root cause of the problem is found and eliminated.Design/methodology/approachBased on field data from an industrial manufacturing operation, the authors test hypotheses by means of regression models.FindingsIt was found that in the evolution from early to later stage, media usage shifts from highly synchronous to asynchronous and the structural characteristics of the teams' collaboration networks mutate as well. These effects are different when comparing high- vs low-performing teams.Research limitations/implicationsThe study contains data for only one company, limiting the external validity of the conclusions. The sample was predominantly male. Participant attrition and other potential covariates not included in the study can be additional limitations.Practical implicationsMore successful teams adapt their communication patterns more rapidly, going from an initially decentralized organization to a more centralized one. These changes in network patterns open a new view of ST’s success, based on network characteristics rather than on aggregate measures. The conclusions yield insights for interventions that may increase the success rates of these teams and reduce production line downtime.Originality/valueThe two stages in the operational emergency problem-solving process have to the authors’ knowledge not been addressed simultaneously in previous research, which is attempted in this paper as its main theoretical contribution. Moreover, previous studies dealing with ST’s success have only looked at aggregated measures impacting effectiveness and never to how their communication networks evolve along the path to problem resolution. The network view of the evolution of the ST from a relatively disorganized impromptu agglomeration of individuals to an effective problem-solving organization is to the authors’ knowledge first presented.
{"title":"Problem-solving by total productive maintenance swift teams: communication network structure, media choice and team effectiveness","authors":"Jorge A. Colazo","doi":"10.1108/ijqrm-03-2021-0053","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0053","url":null,"abstract":"PurposeThis study aims to look at the performance, communication structure and media choice for swift teams (STs) formed with the purpose of recovering from operational emergencies in manufacturing. The problem-solving process associated with these ad hoc teams include an early stage, where the main goal is to restore the process to working conditions, and a later stage, longer in duration, where the root cause of the problem is found and eliminated.Design/methodology/approachBased on field data from an industrial manufacturing operation, the authors test hypotheses by means of regression models.FindingsIt was found that in the evolution from early to later stage, media usage shifts from highly synchronous to asynchronous and the structural characteristics of the teams' collaboration networks mutate as well. These effects are different when comparing high- vs low-performing teams.Research limitations/implicationsThe study contains data for only one company, limiting the external validity of the conclusions. The sample was predominantly male. Participant attrition and other potential covariates not included in the study can be additional limitations.Practical implicationsMore successful teams adapt their communication patterns more rapidly, going from an initially decentralized organization to a more centralized one. These changes in network patterns open a new view of ST’s success, based on network characteristics rather than on aggregate measures. The conclusions yield insights for interventions that may increase the success rates of these teams and reduce production line downtime.Originality/valueThe two stages in the operational emergency problem-solving process have to the authors’ knowledge not been addressed simultaneously in previous research, which is attempted in this paper as its main theoretical contribution. Moreover, previous studies dealing with ST’s success have only looked at aggregated measures impacting effectiveness and never to how their communication networks evolve along the path to problem resolution. The network view of the evolution of the ST from a relatively disorganized impromptu agglomeration of individuals to an effective problem-solving organization is to the authors’ knowledge first presented.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49410134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：