Pub Date : 2022-01-07DOI: 10.1108/ijqrm-03-2020-0065
Ramon Swell Gomes Rodrigues Casado, M. M. Silva, L. C. Silva
PurposeThe paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.Design/methodology/approachThe model integrates the composition of probabilistic preferences (CPP) on the failure modes analysis and its effects (FMEA) criteria. First, the authors carried out a probabilistic transformation of the numerical evaluations of the multiple decision-makers on the FMEA criteria regarding the internal risks that affect the chain of clothing pole in the Agreste region of Pernambuco. Then, the authors proposed the use of the Kendall's concordance coefficient W to aggregate these evaluations.FindingsContrary to expectations, the two main risks to be investigated as a model suggestion was related to the context of supply chain suppliers and not related to the raw material costs. Besides, a simulation with the traditional FMEA was carried out, and comparing with the model result, the simulation is worth highlighting seven consistent differences along the two rankings.Research limitations/implicationsThe focus was restricted to the use of only internal chain risks.Practical implicationsThe proposed model can contribute to the improvement of the decisions within organisations that make up the chains, thus guaranteeing a better quality in risk management.Originality/valueEstablishing a more effective representation of uncertain information related to traditional FMEA treatment involving multiple decision-makers means identifying in advance the potential risks, providing a better supply chain control.
{"title":"Multi-criteria decision model for risk prioritisation involving multiple decision-makers: an application of composition of probabilistic preferences combined with FMEA in the supply chain","authors":"Ramon Swell Gomes Rodrigues Casado, M. M. Silva, L. C. Silva","doi":"10.1108/ijqrm-03-2020-0065","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2020-0065","url":null,"abstract":"PurposeThe paper aims to propose a multi-criteria model for risk prioritisation associated to supply chain management involving multiple decision-makers.Design/methodology/approachThe model integrates the composition of probabilistic preferences (CPP) on the failure modes analysis and its effects (FMEA) criteria. First, the authors carried out a probabilistic transformation of the numerical evaluations of the multiple decision-makers on the FMEA criteria regarding the internal risks that affect the chain of clothing pole in the Agreste region of Pernambuco. Then, the authors proposed the use of the Kendall's concordance coefficient W to aggregate these evaluations.FindingsContrary to expectations, the two main risks to be investigated as a model suggestion was related to the context of supply chain suppliers and not related to the raw material costs. Besides, a simulation with the traditional FMEA was carried out, and comparing with the model result, the simulation is worth highlighting seven consistent differences along the two rankings.Research limitations/implicationsThe focus was restricted to the use of only internal chain risks.Practical implicationsThe proposed model can contribute to the improvement of the decisions within organisations that make up the chains, thus guaranteeing a better quality in risk management.Originality/valueEstablishing a more effective representation of uncertain information related to traditional FMEA treatment involving multiple decision-makers means identifying in advance the potential risks, providing a better supply chain control.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44728822","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 : 2022-01-06DOI: 10.1108/ijqrm-03-2021-0068
S. D. Kalpande, L. K. Toke
PurposeThis paper deals with concept of total productive maintenance (TPM) and its implementation approach. It also presents the identification of critical factors for effective implementation of TPM. The reliability analysis identified potential areas where more concentration is required. The application of hypothesis testing in productivity maintenance should be promoted by parametric test and significantly instrumental in explanation of phenomena. It is also indispensable to better understand quality data and provide guidance to production control.Design/methodology/approachThe various critical success factors of TPM implementation has organised into set of eight performance measure and thirty three sub-factors for getting the in-depth details of each indicator. The paper identifies the reliability of these factors and understands the problem with greater clarity and its ramification. Researcher collected responses from forty one manufacturing organisations through structured designed questionnaire. The reliability analysis was carriedout by calculating the value of Cronbach's alpha method. To draw the meaningful conclusions supported by relevant empirical data, provisional formulation is required, and it was carried by hypothesis testing. In this test, samples are taken from a population with known distribution (normal distribution), and a test of population parameters is executed. It determines the relevancy of facts directs the researcher's efforts into productive channels. The statements were hypothetically tested by calculating the arithmetic value of Chi-Square (χ2) and MINITAB-19 software was used for identification of p-value.FindingsThis study identified that main factors and sub-factors of TPM which are critical for implementation of TPM. The study also avoids the complexities involved in implementing TPM by reliability analysis. It is found that all identified CSFs are reliable as Cronbach's alpha is above 0.6. The hypothesis testing shows that all alternative hypothesis statements are acceptable as Chi-Square (χ2) value has satisfied the conditions and null hypothesis are true as calculated p-value is less than the 0.05 for eight identified TPM critical factor.Originality/valueIn this paper researcher provides a comprehensive typology of TPM-CSFs, and its ranking and importance in manufacturing sector. The preparedness of such study related to TPM implementation is becoming a major sourcing base for the world and there is a paucity of such studies. Such studies are equally important in a global context.
{"title":"Reliability analysis and hypothesis testing of critical success factors of total productive maintenance","authors":"S. D. Kalpande, L. K. Toke","doi":"10.1108/ijqrm-03-2021-0068","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0068","url":null,"abstract":"PurposeThis paper deals with concept of total productive maintenance (TPM) and its implementation approach. It also presents the identification of critical factors for effective implementation of TPM. The reliability analysis identified potential areas where more concentration is required. The application of hypothesis testing in productivity maintenance should be promoted by parametric test and significantly instrumental in explanation of phenomena. It is also indispensable to better understand quality data and provide guidance to production control.Design/methodology/approachThe various critical success factors of TPM implementation has organised into set of eight performance measure and thirty three sub-factors for getting the in-depth details of each indicator. The paper identifies the reliability of these factors and understands the problem with greater clarity and its ramification. Researcher collected responses from forty one manufacturing organisations through structured designed questionnaire. The reliability analysis was carriedout by calculating the value of Cronbach's alpha method. To draw the meaningful conclusions supported by relevant empirical data, provisional formulation is required, and it was carried by hypothesis testing. In this test, samples are taken from a population with known distribution (normal distribution), and a test of population parameters is executed. It determines the relevancy of facts directs the researcher's efforts into productive channels. The statements were hypothetically tested by calculating the arithmetic value of Chi-Square (χ2) and MINITAB-19 software was used for identification of p-value.FindingsThis study identified that main factors and sub-factors of TPM which are critical for implementation of TPM. The study also avoids the complexities involved in implementing TPM by reliability analysis. It is found that all identified CSFs are reliable as Cronbach's alpha is above 0.6. The hypothesis testing shows that all alternative hypothesis statements are acceptable as Chi-Square (χ2) value has satisfied the conditions and null hypothesis are true as calculated p-value is less than the 0.05 for eight identified TPM critical factor.Originality/valueIn this paper researcher provides a comprehensive typology of TPM-CSFs, and its ranking and importance in manufacturing sector. The preparedness of such study related to TPM implementation is becoming a major sourcing base for the world and there is a paucity of such studies. Such studies are equally important in a global context.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43568241","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 : 2022-01-05DOI: 10.1108/ijqrm-03-2021-0061
A. Jibril, V. V. Singh, D. K. Rawal
PurposeThe purpose of this paper is to deliberate the system reliability of a system in combination of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance.Design/methodology/approachProbabilistic assessment of complex system consisting three subsystems, multi-failure threats and copula repair approach is used in this study. Abbas Jubrin Bin, V.V. Singh, D.K. Rawal, in this research paper, have analyzed a system consisting of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance.FindingsIn this analysis, four different cases of availability are analysed for Gumbel–Hougaard family copula and also four cases for general repair with similar failure rates are studied. The authors found that when failure rates increase, the system availability decreases, and when the system follows copula repair distribution, the system availability is better than general repair.Research limitations/implicationsThis research may be implemented in various industrial systems where the subsystems are configured under k-out-of-n: G working policy. It is also advisable that copula repair is highly recommended for best performances from the system. On the basis of mean time to system failure (MTSF) computations, the failure rate which affects system failure more needs to be controlled by monitoring, servicing and replacing stratagem.Practical implicationsThis research work has great implications in various industrial systems like power plant systems, nuclear power plant, electricity distributions system, etc. where the k-out-of-n-type of system operation scheme is validated for system operations with the multi-repair.Originality/valueThis work is a new work by authors. In the previously available technical analysis of the system, the researchers have analyzed the repairable system either supplementary variable approach, supplementary variable and system which have two subsystems in a series configuration. This research work analyzed a system with three subsystems with a multi-repair approach and supplementary variables.
{"title":"Probabilistic assessment of complex system consisting three subsystems, multi-failure threats and copula repair approach","authors":"A. Jibril, V. V. Singh, D. K. Rawal","doi":"10.1108/ijqrm-03-2021-0061","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2021-0061","url":null,"abstract":"PurposeThe purpose of this paper is to deliberate the system reliability of a system in combination of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance.Design/methodology/approachProbabilistic assessment of complex system consisting three subsystems, multi-failure threats and copula repair approach is used in this study. Abbas Jubrin Bin, V.V. Singh, D.K. Rawal, in this research paper, have analyzed a system consisting of three subsystems in a series configuration in which all three subsystems function under a k-out-of-n: G operational scheme. The supplementary variable approach with implications of copula distribution has been employed for assessing the system performance. Based on computed results, it has been demonstrated that copula repair is better than general repair for system better performance.FindingsIn this analysis, four different cases of availability are analysed for Gumbel–Hougaard family copula and also four cases for general repair with similar failure rates are studied. The authors found that when failure rates increase, the system availability decreases, and when the system follows copula repair distribution, the system availability is better than general repair.Research limitations/implicationsThis research may be implemented in various industrial systems where the subsystems are configured under k-out-of-n: G working policy. It is also advisable that copula repair is highly recommended for best performances from the system. On the basis of mean time to system failure (MTSF) computations, the failure rate which affects system failure more needs to be controlled by monitoring, servicing and replacing stratagem.Practical implicationsThis research work has great implications in various industrial systems like power plant systems, nuclear power plant, electricity distributions system, etc. where the k-out-of-n-type of system operation scheme is validated for system operations with the multi-repair.Originality/valueThis work is a new work by authors. In the previously available technical analysis of the system, the researchers have analyzed the repairable system either supplementary variable approach, supplementary variable and system which have two subsystems in a series configuration. This research work analyzed a system with three subsystems with a multi-repair approach and supplementary variables.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44078595","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 : 2022-01-04DOI: 10.1108/ijqrm-08-2021-0291
Satish Kumar, Tushar Kolekar, K. Kotecha, S. Patil, A. Bongale
Purpose Excessive tool wear is responsible for damage or breakage of the tool, workpiece, or machining center. Thus, it is crucial to examine tool conditions during the machining process to improve its useful functional life and the surface quality of the final product. AI-based tool wear prediction techniques have proven to be effective in estimating the Remaining Useful Life (RUL) of the cutting tool. However, the model prediction needs improvement in terms of accuracy.Design/methodology/approachThis paper represents a methodology of fusing a feature selection technique along with state-of-the-art deep learning models. The authors have used NASA milling data sets along with vibration signals for tool wear prediction and performance analysis in 15 different fault scenarios. Multiple steps are used for the feature selection and ranking. Different Long Short-Term Memory (LSTM) approaches are used to improve the overall prediction accuracy of the model for tool wear prediction. LSTM models' performance is evaluated using R-square, Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) parameters.FindingsThe R-square accuracy of the hybrid model is consistently high and has low MAE, MAPE and RMSE values. The average R-square score values for LSTM, Bidirection, Encoder–Decoder and Hybrid LSTM are 80.43, 84.74, 94.20 and 97.85%, respectively, and corresponding average MAPE values are 23.46, 22.200, 9.5739 and 6.2124%. The hybrid model shows high accuracy as compared to the remaining LSTM models.Originality/value The low variance, Spearman Correlation Coefficient and Random Forest Regression methods are used to select the most significant feature vectors for training the miscellaneous LSTM model versions and highlight the best approach. The selected features pass to different LSTM models like Bidirectional, Encoder–Decoder and Hybrid LSTM for tool wear prediction. The Hybrid LSTM approach shows a significant improvement in tool wear prediction.
{"title":"Performance evaluation for tool wear prediction based on Bi-directional, Encoder–Decoder and Hybrid Long Short-Term Memory models","authors":"Satish Kumar, Tushar Kolekar, K. Kotecha, S. Patil, A. Bongale","doi":"10.1108/ijqrm-08-2021-0291","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2021-0291","url":null,"abstract":"Purpose Excessive tool wear is responsible for damage or breakage of the tool, workpiece, or machining center. Thus, it is crucial to examine tool conditions during the machining process to improve its useful functional life and the surface quality of the final product. AI-based tool wear prediction techniques have proven to be effective in estimating the Remaining Useful Life (RUL) of the cutting tool. However, the model prediction needs improvement in terms of accuracy.Design/methodology/approachThis paper represents a methodology of fusing a feature selection technique along with state-of-the-art deep learning models. The authors have used NASA milling data sets along with vibration signals for tool wear prediction and performance analysis in 15 different fault scenarios. Multiple steps are used for the feature selection and ranking. Different Long Short-Term Memory (LSTM) approaches are used to improve the overall prediction accuracy of the model for tool wear prediction. LSTM models' performance is evaluated using R-square, Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) parameters.FindingsThe R-square accuracy of the hybrid model is consistently high and has low MAE, MAPE and RMSE values. The average R-square score values for LSTM, Bidirection, Encoder–Decoder and Hybrid LSTM are 80.43, 84.74, 94.20 and 97.85%, respectively, and corresponding average MAPE values are 23.46, 22.200, 9.5739 and 6.2124%. The hybrid model shows high accuracy as compared to the remaining LSTM models.Originality/value The low variance, Spearman Correlation Coefficient and Random Forest Regression methods are used to select the most significant feature vectors for training the miscellaneous LSTM model versions and highlight the best approach. The selected features pass to different LSTM models like Bidirectional, Encoder–Decoder and Hybrid LSTM for tool wear prediction. The Hybrid LSTM approach shows a significant improvement in tool wear prediction.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41523999","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 : 2021-12-31DOI: 10.1108/ijqrm-10-2021-0357
J. Antony, M. Sony, Olivia McDermott, Raja Jayaraman, David Flynn
Purpose Quality 4.0 incorporates the role of automation and digitization and provides competitive advantage for organizations by enhancing customer experience and increase profitability. The purpose of this study is to critically examine the organizational readiness factors for the successful implementation of Quality 4.0 implementation and assess their importance.Design/methodology/approach This study applies a quantitative research methodology to examine readiness factors of Quality 4.0 in organizations by 147 senior management professionals in various organizations including manufacturing and service companies in America, Asia and Europe participated through an online survey.FindingsThe readiness factors for Quality 4.0 were critically ranked amongst manufacturing and service organizations by senior management professionals from three continents. Five significant reasons for non-adoption of Quality 4.0 were lack of resources, inability to link Quality 4.0 with the corporate strategy and objectives, lack of understanding of benefits, high initial investment and the current quality management strategy and methods are already delivering good results hence unsure of the need for Quality 4.0. The handling of big data in quality management was the most important factor for adopting Quality 4.0, irrespective of the size and nature of the organization. More accuracy and less errors and improved decision-making the factors of adopting Quality 4.0 in service sector were not significant for manufacturing sector. Small and medium-sized enterprises (SMEs) reported that costs and time savings over the long run were not so significant.Practical implications This study is focussed on the significance of pros and cons of adopting Quality 4.0 in organizations. Senior managers in both large and SMEs can benefit immensely from understanding before investing heavily towards implementing Quality 4.0. The importance of identified organizational readiness factors for the successful adoption of Quality 4.0 can be used as indicators to understand how ready an organization is to implement Quality 4.0. The top three readiness factors for the successful adoption of Quality 4.0 were identified as: top management commitment, leadership and organizational culture. Improved understanding of the readiness factors can be highly beneficial to senior quality professionals in both manufacturing and service companies in the journey towards successful implementation of Quality 4.0.Originality/value This is the first empirical study on assessing Quality 4.0 readiness factors at an intercontinental level and therefore serves as a foundation for many future studies. The study provides a theoretical foundation for the Quality 4.0 in terms of organizational readiness for successful adoption and overcoming implementation challenges. During the planning, implementation and progress review of Quality 4.0, review the readiness factors while planning and resourcing a Quality 4.0 implementatio
{"title":"An exploration of organizational readiness factors for Quality 4.0: an intercontinental study and future research directions","authors":"J. Antony, M. Sony, Olivia McDermott, Raja Jayaraman, David Flynn","doi":"10.1108/ijqrm-10-2021-0357","DOIUrl":"https://doi.org/10.1108/ijqrm-10-2021-0357","url":null,"abstract":"Purpose Quality 4.0 incorporates the role of automation and digitization and provides competitive advantage for organizations by enhancing customer experience and increase profitability. The purpose of this study is to critically examine the organizational readiness factors for the successful implementation of Quality 4.0 implementation and assess their importance.Design/methodology/approach This study applies a quantitative research methodology to examine readiness factors of Quality 4.0 in organizations by 147 senior management professionals in various organizations including manufacturing and service companies in America, Asia and Europe participated through an online survey.FindingsThe readiness factors for Quality 4.0 were critically ranked amongst manufacturing and service organizations by senior management professionals from three continents. Five significant reasons for non-adoption of Quality 4.0 were lack of resources, inability to link Quality 4.0 with the corporate strategy and objectives, lack of understanding of benefits, high initial investment and the current quality management strategy and methods are already delivering good results hence unsure of the need for Quality 4.0. The handling of big data in quality management was the most important factor for adopting Quality 4.0, irrespective of the size and nature of the organization. More accuracy and less errors and improved decision-making the factors of adopting Quality 4.0 in service sector were not significant for manufacturing sector. Small and medium-sized enterprises (SMEs) reported that costs and time savings over the long run were not so significant.Practical implications This study is focussed on the significance of pros and cons of adopting Quality 4.0 in organizations. Senior managers in both large and SMEs can benefit immensely from understanding before investing heavily towards implementing Quality 4.0. The importance of identified organizational readiness factors for the successful adoption of Quality 4.0 can be used as indicators to understand how ready an organization is to implement Quality 4.0. The top three readiness factors for the successful adoption of Quality 4.0 were identified as: top management commitment, leadership and organizational culture. Improved understanding of the readiness factors can be highly beneficial to senior quality professionals in both manufacturing and service companies in the journey towards successful implementation of Quality 4.0.Originality/value This is the first empirical study on assessing Quality 4.0 readiness factors at an intercontinental level and therefore serves as a foundation for many future studies. The study provides a theoretical foundation for the Quality 4.0 in terms of organizational readiness for successful adoption and overcoming implementation challenges. During the planning, implementation and progress review of Quality 4.0, review the readiness factors while planning and resourcing a Quality 4.0 implementatio","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42966632","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 : 2021-12-30DOI: 10.1108/ijqrm-04-2021-0105
Amit S. Patil, G. Soni, Anuj Prakash, Kritika Karwasra
PurposeIn today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies.Design/methodology/approachA systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed.FindingsFor the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation.Practical implicationsFrom the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifyi
在当今竞争激烈的行业中，选择最合适的维修策略依赖于大量的定量和定性因素，成为维修工程师普遍面临的难题。多年来，已经开发了各种解决方法来解决这个多标准决策(MCDM)问题。在本文中，作者对最新的维护策略范例和解决方案进行了全面的回顾，以便在不同的行业中选择合适的策略。它将系统地反映这一领域的发展情况，并确定一些研究差距，以探索进一步的研究。设计/方法/方法本研究对维修策略范例和选择方法进行了系统的、最新的综合文献综述。本研究回顾了自2012年以来发表在同行评议期刊上的87篇研究论文。为了选择合适的维护策略，考虑了各种标准来更好地评估替代方案。在本研究中，讨论了当代战略，并描述了它们在不同行业的应用。此外，通过对现有文献的分析，选择关键标准并将其分为六大类(即经济，技术，安全，环境，可行性和社会)，并进一步分为定量和定性类。这些标准组可以作为调查的一组初始标准，然后可以列出特定于案例或行业的标准，以供进一步的替代评估。从维护管理人员的角度来看，考虑到影响决策过程的众多因素，维护管理可能是一项非常困难的任务。为了在决策过程中提供帮助，本研究以系统的方式提出了当代维护策略。在之前的一项研究中(Kothamasu et al.， 2006)，这些策略仅被分为修复类和预防类。随着自主维护和设计出维护(DOM)的发展，在系统中加入持续改进类是合理的。它将帮助管理人员和实践者根据组织策略，确定资产的适当维护策略替代方案。一组最先进的维护策略的基准与其应用程序一起列出。本研究中讨论的工业案例总结了各自行业的最佳维护策略。此外，从各种行业的现有研究中确定了大多数关键标准，这些标准可以帮助维护从业者认识到关键因素并做出适当的决策。维修策略选择(MSS)的评价参数通常相互冲突，并且考虑到定性度量的量化难度，确定最优权衡是一项具有挑战性的任务。为了克服这些挑战，讨论了流行的MCDM方法，并在不同行业中展示了有效的结果，以及它们的局限性和应用。决策者可以参考本研究，在他们所选择的行业中，找出最适合MSS问题的决策技术。维护经理和工程师可以参考表1和表2中所示的案例研究，以分析先前研究提出的具有特定行业应用的MSS技术。社会意义本研究旨在为研究维修管理和维修策略框架的学者提供一个参考点。本研究提供了在MSS领域所做的努力的关键的最新的审查。通过各自的案例研究，讨论了当代工业中正在实施的主要维护策略。感兴趣的研究人员和学者可以在本研究中熟悉这些策略及其独特的特点。为了指导未来的研究，并为学者提供参考点，我们确定了现有文献中使用的MSS关键标准，并将其分类为一个全面的基准框架。此外，对行业案例研究进行了讨论，讨论了不同行业的最关键的MSS标准，以及基于这些标准的哪个战略最适合各自的行业。表1展示了不同的MCDM技术及其用于解决MSS问题的混合应用，这些技术可以帮助研究人员识别研究差距。未来的研究可以针对现有研究中采用的MCDM方法的局限性，并比较所提出的方法所获得的结果的差异。 表2中列出了不同的工业案例研究和考虑的维护策略替代方案，这可以帮助研究人员确定尚未研究的行业。此外，并非所有现有的研究都考虑了所有提出的基准策略，这可以由感兴趣的研究人员在未来的研究中解决。关于研究差距的更详细讨论将在下一节中提出。原创性/价值通过对现有文献的分析，作者可以观察到，许多研究采用的决策过程仅限于经典维修策略，而不包括积极的维修策略替代方案。为了克服这些限制并帮助维护管理人员进行决策，本研究以结构化的方式描述了当代维护策略、关键评估标准和MCDM框架(用于解决工业案例研究中的MSS问题)。
{"title":"Maintenance strategy selection: a comprehensive review of current paradigms and solution approaches","authors":"Amit S. Patil, G. Soni, Anuj Prakash, Kritika Karwasra","doi":"10.1108/ijqrm-04-2021-0105","DOIUrl":"https://doi.org/10.1108/ijqrm-04-2021-0105","url":null,"abstract":"PurposeIn today's competitive industries, the selection of best suitable maintenance strategy is dependent on large number of quantitative and qualitative factors, and it becomes an extensively difficult problem for maintenance engineers. Over the years, a diverse range of solution methodologies have been developed for solving this multi-criteria decision-making (MCDM) problem. In this paper, the authors have presented a comprehensive review of latest maintenance strategy paradigms and solution approaches proposed for the selection of an appropriate strategy in various industries. It would provide a systematic mapping of developments in this field and identify some research gaps to explore further studies.Design/methodology/approachA systematic state-of-the-art comprehensive literature review on maintenance strategy paradigms and selection approaches is presented in this study. In this study, 87 research articles published in peer-reviewed journals, since year 2012, are reviewed.FindingsFor the selection of a suitable maintenance strategy, a variety of criteria are considered to better evaluate the alternatives. In this study, contemporary strategies are discussed, and their applications in different industries are also depicted. Moreover, through the analysis of extant literature, critical criteria are selected and classified in six major categories (namely, economic, technical, safety, environmental, feasibility and social) and further sub-categorized in quantitative and qualitative classes. These clusters of criteria can be helpful as an initial set of criteria for survey and then case- or industry-specific criteria can be shortlisted for further alternative evaluation.Practical implicationsFrom the perspective of maintenance managers, maintenance management can be a very difficult task, considering the numerous factors affecting the decision-making process. In order to help in the decision-making process, this study presents the contemporary maintenance strategies in a systematic manner. In a previous study (Kothamasu et al., 2006), these strategies were classified into repair and prevent classes only. With the developments of autonomous maintenance and design out maintenance (DOM), it was fair to include continuous improvement class. It will help managers and practitioners to identify, according to organization policy, appropriate maintenance strategy alternatives for the asset. A benchmark set of state-of-the-art maintenance strategies are laid out with their applications. The industrial case studies discussed in this study summarizes the optimal maintenance strategies for respective industries. Also, most critical criteria are identified from the existing studies for various industries that can help maintenance practitioners in acknowledging the critical factors and making appropriate decisions. Evaluation parameters for the maintenance strategy selection (MSS) generally conflict with each other, and considering the difficulty of quantifyi","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45995757","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 : 2021-12-30DOI: 10.1108/ijqrm-04-2020-0125
Nse-Obong Udoh, E. Effanga
PurposeThis work seeks to develop a geometric imperfect preventive maintenance (PM) and replacement model (GIPMAR) for aging repairable systems due to age and prolong usage that would meet users need in three phases: within average life span, beyond average life span and beyond initial replacement age of system.Design/methodology/approachThe authors utilized the geometric process (GP) as the hazard function to characterize the increasing failure rate (IFR) of the system. The GP hazard function was incorporated into the hybridized preventive and replacement model of Lin et al. (2000). The resultant expected cost rate function was optimized to obtain optimum intervals for PM/replacement and required numbers of PM per cycle. The proposed GIPMAR model was applied to repairable systems characterized by Weibull life function and the results yielded PM/replacement schedules for three different phases of system operation.FindingsThe proposed GIPMAR model is a generalization of Lin et al. (2000) PM model that were comparable with results of earlier models and is adaptive to situations in developing countries where systems are used across the three phases of operation depicted in this work. This may be due to economic hardship and operating environment.Practical implicationsThe proposed model has provided PM/Replacement schedules for different phases of operation which was never considered. This would provide a useful guide to maintenance engineers and end-users in developing countries with a view to minimizing the average cost of maintenance as well as reducing the number of down times of systems.Social implicationsA duly implemented GIPMAR model would ensure efficient operation of systems, optimum man-hour need in the organization and guarantee customer's goodwill in a competitive environment.Originality/valueIn this work, the authors have extended Lin et al. (2000) PM model to provide PM/replacement schedules for aging repairable systems which was not provided for in earlier existing models and literature.
本研究旨在开发一个几何不完美预防性维护(PM)和更换模型(GIPMAR)，用于老化的可修复系统，并延长使用时间，以满足用户在三个阶段的需求:在平均寿命内，超过平均寿命和超过系统的初始更换年龄。设计/方法/方法作者利用几何过程(GP)作为危险函数来表征系统不断增加的故障率(IFR)。Lin et al.(2000)将GP危害函数纳入了杂交预防和替换模型。所得到的期望成本率函数进行了优化，以获得最佳的PM/更换间隔和每个周期所需的PM数量。将提出的GIPMAR模型应用于具有威布尔寿命函数特征的可修系统，得到了系统运行三个不同阶段的维修/更换计划。研究结果:提出的GIPMAR模型是Lin等人(2000)PM模型的推广，该模型与早期模型的结果可比较，并适用于发展中国家的情况，在这些国家中，系统在本工作中描述的三个操作阶段中使用。这可能是由于经济困难和经营环境。实际影响建议的模型提供了从未考虑过的不同操作阶段的PM/更换时间表。这将为发展中国家的维修工程师和最终用户提供有用的指南，以期尽量减少维修的平均费用，并减少系统停机的次数。适当实施GIPMAR模型将确保系统的有效运行，组织的最佳工时需求，并保证客户在竞争环境中的善意。原创性/价值在这项工作中，作者扩展了Lin等人(2000)的PM模型，为老化的可修复系统提供PM/更换计划，这在早期的现有模型和文献中没有提供。
{"title":"Geometric imperfect preventive maintenance and replacement (GIPMAR) model for aging repairable systems","authors":"Nse-Obong Udoh, E. Effanga","doi":"10.1108/ijqrm-04-2020-0125","DOIUrl":"https://doi.org/10.1108/ijqrm-04-2020-0125","url":null,"abstract":"PurposeThis work seeks to develop a geometric imperfect preventive maintenance (PM) and replacement model (GIPMAR) for aging repairable systems due to age and prolong usage that would meet users need in three phases: within average life span, beyond average life span and beyond initial replacement age of system.Design/methodology/approachThe authors utilized the geometric process (GP) as the hazard function to characterize the increasing failure rate (IFR) of the system. The GP hazard function was incorporated into the hybridized preventive and replacement model of Lin et al. (2000). The resultant expected cost rate function was optimized to obtain optimum intervals for PM/replacement and required numbers of PM per cycle. The proposed GIPMAR model was applied to repairable systems characterized by Weibull life function and the results yielded PM/replacement schedules for three different phases of system operation.FindingsThe proposed GIPMAR model is a generalization of Lin et al. (2000) PM model that were comparable with results of earlier models and is adaptive to situations in developing countries where systems are used across the three phases of operation depicted in this work. This may be due to economic hardship and operating environment.Practical implicationsThe proposed model has provided PM/Replacement schedules for different phases of operation which was never considered. This would provide a useful guide to maintenance engineers and end-users in developing countries with a view to minimizing the average cost of maintenance as well as reducing the number of down times of systems.Social implicationsA duly implemented GIPMAR model would ensure efficient operation of systems, optimum man-hour need in the organization and guarantee customer's goodwill in a competitive environment.Originality/valueIn this work, the authors have extended Lin et al. (2000) PM model to provide PM/replacement schedules for aging repairable systems which was not provided for in earlier existing models and literature.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47907189","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 : 2021-12-28DOI: 10.1108/ijqrm-06-2021-0168
A. Alarifi, K. S. Husain
PurposeThe main purpose of this study is to compare e-customer satisfaction in Saudi banks before and during coronavirus disease 2019 (COVID-19) pandemic by assessing the e-service quality dimension before and during the pandemic.Design/methodology/approachTo examine e-customer satisfaction among Saudi bank e-customers, data were collected using convenience sampling methods utilizing two questionnaires before and during COVID-19, distributed to Saudi bank e-customers. The sample size of collecting data of 588 bank e-customers was analyzed through a well-known statistical technique, multiple regression and paired sample t-test, using Statistical Product and Service Solutions (SPSS) software and Excel.FindingsIt is found that efficiency is the major determinant of e-customers’ satisfaction with banks in Saudi Arabia. The Saudi context is different from other countries. There are differences between the impact of Internet banking e-service quality on e-customer service before and during the COVID-19.Practical implicationsThis research has a crucial inference for the managerial level practically. This study has important implications for the banks to satisfy their e-customers by increasing customer service level and enhancing the interaction in the site to solve the e-customers problem immediately by creating an effective support team to encourage the effect of responsiveness. In particular, website managers should review their website framework and create an easily organized site for e-customers.Originality/valueThe research improves past studies' methodology by testing the impacts between the constructs before and during COVID-19. This research is a significant addition to the current literature collection.
本研究的主要目的是通过评估2019冠状病毒病(COVID-19)流行之前和期间的电子服务质量维度，比较沙特银行在2019冠状病毒病(COVID-19)流行之前和期间的电子客户满意度。设计/方法/方法为了检查沙特银行电子客户的电子客户满意度，采用便利抽样方法收集数据，在COVID-19之前和期间使用两份问卷收集数据，分发给沙特银行电子客户。利用SPSS (statistical Product and Service Solutions)软件和Excel软件，通过多元回归和配对样本t检验等知名统计技术，对588家银行电子客户的采集数据进行样本容量分析。研究发现，效率是沙特阿拉伯电子客户对银行满意度的主要决定因素。沙特的情况与其他国家不同。新冠肺炎疫情前和疫情期间，网上银行电子服务质量对电子客户服务的影响存在差异。实践意义本研究对管理层面具有重要的实践意义。本研究对银行如何通过提高客户服务水平和增强网站互动来满足电子客户的需求具有重要的启示意义，通过建立一个有效的支持团队来鼓励响应效果，从而立即解决电子客户的问题。特别是，网站管理人员应该审查他们的网站框架，并为电子客户创建一个易于组织的网站。独创性/价值本研究通过测试COVID-19之前和期间结构之间的影响，改进了过去的研究方法。这项研究是对当前文献收集的重要补充。
{"title":"The influence of Internet banking services quality on e-customers’ satisfaction of Saudi banks: comparison study before and during COVID-19","authors":"A. Alarifi, K. S. Husain","doi":"10.1108/ijqrm-06-2021-0168","DOIUrl":"https://doi.org/10.1108/ijqrm-06-2021-0168","url":null,"abstract":"PurposeThe main purpose of this study is to compare e-customer satisfaction in Saudi banks before and during coronavirus disease 2019 (COVID-19) pandemic by assessing the e-service quality dimension before and during the pandemic.Design/methodology/approachTo examine e-customer satisfaction among Saudi bank e-customers, data were collected using convenience sampling methods utilizing two questionnaires before and during COVID-19, distributed to Saudi bank e-customers. The sample size of collecting data of 588 bank e-customers was analyzed through a well-known statistical technique, multiple regression and paired sample t-test, using Statistical Product and Service Solutions (SPSS) software and Excel.FindingsIt is found that efficiency is the major determinant of e-customers’ satisfaction with banks in Saudi Arabia. The Saudi context is different from other countries. There are differences between the impact of Internet banking e-service quality on e-customer service before and during the COVID-19.Practical implicationsThis research has a crucial inference for the managerial level practically. This study has important implications for the banks to satisfy their e-customers by increasing customer service level and enhancing the interaction in the site to solve the e-customers problem immediately by creating an effective support team to encourage the effect of responsiveness. In particular, website managers should review their website framework and create an easily organized site for e-customers.Originality/valueThe research improves past studies' methodology by testing the impacts between the constructs before and during COVID-19. This research is a significant addition to the current literature collection.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48143282","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 : 2021-12-28DOI: 10.1108/ijqrm-05-2021-0150
R. Ranjith Kumar, L. Ganesh, C. Rajendran
PurposeIndustry 4.0 has brought about a paradigm shift in value delivery with the introduction of disruptive technologies. This has resulted in efforts by organizations to re-invent their business processes and reskill their workforce while attempting to realize digital transformation. Quality management in the context of Industry 4.0 is still in its nascent stage with researchers trying to identify key and relevant components of quality management with respect to Industry 4.0. The current study attempts to address the knowledge gap through a literature review and subsequently provide a conceptual framework for quality in the digital transformation context.Design/methodology/approachAn integrative literature review was conducted to analyze and abstract knowledge from the literature on Quality 4.0 and a conceptual framework was developed based on the review.FindingsThe review revealed the motivators, building blocks and challenges for Quality 4.0. The conceptual framework discusses the salient points relevant to Quality 4.0 with respect to the people, process and technology dimensions and their sub-dimensions that can be used to build 4.0 capabilities. The proposed framework is represented to depict the conceptualization and the relationships among its components.Originality/valueThis study aims to contribute to the model building efforts of researchers towards Quality 4.0. The points discussed here provide an actionable direction to augment the efforts of practitioners and organizations in quality management in the context of Industry 4.0, especially digital transformation.
{"title":"Quality 4.0 – a review of and framework for quality management in the digital era","authors":"R. Ranjith Kumar, L. Ganesh, C. Rajendran","doi":"10.1108/ijqrm-05-2021-0150","DOIUrl":"https://doi.org/10.1108/ijqrm-05-2021-0150","url":null,"abstract":"PurposeIndustry 4.0 has brought about a paradigm shift in value delivery with the introduction of disruptive technologies. This has resulted in efforts by organizations to re-invent their business processes and reskill their workforce while attempting to realize digital transformation. Quality management in the context of Industry 4.0 is still in its nascent stage with researchers trying to identify key and relevant components of quality management with respect to Industry 4.0. The current study attempts to address the knowledge gap through a literature review and subsequently provide a conceptual framework for quality in the digital transformation context.Design/methodology/approachAn integrative literature review was conducted to analyze and abstract knowledge from the literature on Quality 4.0 and a conceptual framework was developed based on the review.FindingsThe review revealed the motivators, building blocks and challenges for Quality 4.0. The conceptual framework discusses the salient points relevant to Quality 4.0 with respect to the people, process and technology dimensions and their sub-dimensions that can be used to build 4.0 capabilities. The proposed framework is represented to depict the conceptualization and the relationships among its components.Originality/valueThis study aims to contribute to the model building efforts of researchers towards Quality 4.0. The points discussed here provide an actionable direction to augment the efforts of practitioners and organizations in quality management in the context of Industry 4.0, especially digital transformation.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43019202","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 : 2021-12-28DOI: 10.1108/ijqrm-09-2021-0331
C. Bhargava, P. Sharma, K. Kotecha
PurposeCapacitors are one of the most common passive components on a circuit board. From a tiny toy to substantial satellite, a capacitor plays an important role. Untimely failure of a capacitor can destruct the entire system. This research paper targets the reliability assessment of tantalum capacitor, to reduce e-waste and enhance its reusable capability.Design/methodology/approachThe residual lifetime of a tantalum capacitor is estimated using the empirical method, i.e. military handbook MILHDBK2017F, and validated using an experimental approach, i.e. accelerated life testing (ALT). The various influencing acceleration factors are explored, and experiments are designed using Taguchi's approach. Empirical methods such as the military handbook is used for assessing the reliability of a tantalum capacitor, for ground and mobile applications.FindingsAfter exploring the lifetime of a tantalum capacitor using empirical and experimental techniques, an error analysis is conducted, which shows the validity of empirical technique, with an accuracy of 95.21%.Originality/valueThe condition monitoring and health prognostics of tantalum capacitors, for ground and mobile applications, are explored using empirical and experimental techniques, which warns the user about its residual lifetime so that the faulty component can be replaced in time.
{"title":"Lifetime estimation of tantalum capacitor for mobile applications using empirical and experimental techniques: a DOE approach","authors":"C. Bhargava, P. Sharma, K. Kotecha","doi":"10.1108/ijqrm-09-2021-0331","DOIUrl":"https://doi.org/10.1108/ijqrm-09-2021-0331","url":null,"abstract":"PurposeCapacitors are one of the most common passive components on a circuit board. From a tiny toy to substantial satellite, a capacitor plays an important role. Untimely failure of a capacitor can destruct the entire system. This research paper targets the reliability assessment of tantalum capacitor, to reduce e-waste and enhance its reusable capability.Design/methodology/approachThe residual lifetime of a tantalum capacitor is estimated using the empirical method, i.e. military handbook MILHDBK2017F, and validated using an experimental approach, i.e. accelerated life testing (ALT). The various influencing acceleration factors are explored, and experiments are designed using Taguchi's approach. Empirical methods such as the military handbook is used for assessing the reliability of a tantalum capacitor, for ground and mobile applications.FindingsAfter exploring the lifetime of a tantalum capacitor using empirical and experimental techniques, an error analysis is conducted, which shows the validity of empirical technique, with an accuracy of 95.21%.Originality/valueThe condition monitoring and health prognostics of tantalum capacitors, for ground and mobile applications, are explored using empirical and experimental techniques, which warns the user about its residual lifetime so that the faulty component can be replaced in time.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45288519","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}
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