International Journal of Quality & Reliability Management最新文献

{"title":"A generalized model selection framework for multi-state failure data analysis","authors":"R. Patil, S. Patil, G. Gupta, A. Bewoor","doi":"10.1108/ijqrm-08-2021-0280","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2021-0280","url":null,"abstract":"PurposeThe purpose of this paper is to carry out a reliability analysis of a mechanical system considering the degraded states to get a proper understanding of system behavior and its propagation towards complete failure.Design/methodology/approachThe reliability analysis of computerized numerical control machine tools (CNCMTs) using a multi-state system (MSS) approach that considers various degraded states rather than a binary approach is carried out. The failures of the CNCMT are classified into five states: one fully operational state, three degraded states and one failed state.FindingsThe analysis of failure data collected from the field and tests conducted in the laboratory provided detailed understandings about the quality of the material and its failure behavior used in designing and the capability of the manufacturing system. The present work identified that Class II (major failure) is critical from a maintainability perspective whereas Class III (moderate failure) and Class IV (minor failure) are critical from a reliability perspective.Research limitations/implicationsThis research applies to reliability data analysis of systems that consider various degraded states.Practical implicationsMSS reliability analysis approach will help to identify various degraded states of the system that affect the performance and productivity and also to improve system reliability, availability and performance.Social implicationsIndustrial system designers recognized that reliability and maintainability is a critical design attribute. Reliability studies using the binary state approach are insufficient and incorrect for the systems with degraded failures states, and such analysis can give incorrect results, and increase the cost. The proposed MSS approach is more suitable for complex systems such as CNCMT rather than the binary-state system approach.Originality/valueThis paper presents a generalized framework MSS's failure and repair data analysis has been developed and applied to a CNCMT.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43356628","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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}

{"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":" ","pages":""},"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}