Pub Date : 2021-11-15DOI: 10.1108/ijqrm-09-2020-0296
Sidali Bacha, A. Bellaouar, J. Dron
PurposeComplex repairable systems (CRSs) are generally modeled by stochastic processes called “point processes.” These are generally summed up in the nonhomogeneous Poisson process (NHPP) and the renewal process (RP), which represent the minimum and maximum repair, respectively. However, the industrial environment affects systems in some way. This is why the main objective of this work is to model the CRS with a concept reflecting the real state of the system by incorporating an indicator in the form of covariate. This type of model, known as the proportional intensity model (PIM), will be analyzed with simulated failure data to understand the behavior of the failure process, and then it will be tested for real data from a petroleum company to evaluate the effectiveness of corrective actions carried out.Design/methodology/approachTo solve the partial repair modeling problem, the PIM was used by introducing, on the basis of the NHPP model, a multiplicative scaling factor, which reflects the degree of efficiency after each maintenance action. Several values of this multiplicative factor will be considered to generate data. Then, based on the reliability and maintenance history of 12-year pump's operation obtained from the SONATRACH Company (south industrial center (CIS), Hassi Messaoud, Algeria), the performance of the PIM will be judged and compared with the model of NHPP and RP in order to demonstrate its flexibility in modeling CRS. Using the maximum likelihood approach and relying on the Matlab software, the best fitting model should have the largest likelihood value.FindingsThe use of the PIM allows a better understanding of the physical situation of the system by allowing easy modeling to apply in practice. This is expressed by the value which, in this case, represents an improvement in the behavior of the system provided by a good quality of the corrective maintenance performed. This result is based on the hypothesis that modeling with the PIM can provide more clarification on the behavior of the system. It can indicate the effectiveness of the maintenance crew and guide managers to confirm or revise their maintenance policy.Originality/valueThe work intends to reflect the real situation in which the system operates. The originality of the work is to allow the consideration of covariates influencing the behavior of the system during its lifetime. The authors focused on modeling the degree of repair after each corrective maintenance performed on an oil pump. Since PIM does not require a specific reliability distribution to apply it, it allows a wide range of applications in the various industrial environments. Given the importance of this study, the PIM can be generalized for more covariates and working conditions.
{"title":"Assessment of the effectiveness of corrective maintenance of an oil pump using the proportional intensity model (PIM)","authors":"Sidali Bacha, A. Bellaouar, J. Dron","doi":"10.1108/ijqrm-09-2020-0296","DOIUrl":"https://doi.org/10.1108/ijqrm-09-2020-0296","url":null,"abstract":"PurposeComplex repairable systems (CRSs) are generally modeled by stochastic processes called “point processes.” These are generally summed up in the nonhomogeneous Poisson process (NHPP) and the renewal process (RP), which represent the minimum and maximum repair, respectively. However, the industrial environment affects systems in some way. This is why the main objective of this work is to model the CRS with a concept reflecting the real state of the system by incorporating an indicator in the form of covariate. This type of model, known as the proportional intensity model (PIM), will be analyzed with simulated failure data to understand the behavior of the failure process, and then it will be tested for real data from a petroleum company to evaluate the effectiveness of corrective actions carried out.Design/methodology/approachTo solve the partial repair modeling problem, the PIM was used by introducing, on the basis of the NHPP model, a multiplicative scaling factor, which reflects the degree of efficiency after each maintenance action. Several values of this multiplicative factor will be considered to generate data. Then, based on the reliability and maintenance history of 12-year pump's operation obtained from the SONATRACH Company (south industrial center (CIS), Hassi Messaoud, Algeria), the performance of the PIM will be judged and compared with the model of NHPP and RP in order to demonstrate its flexibility in modeling CRS. Using the maximum likelihood approach and relying on the Matlab software, the best fitting model should have the largest likelihood value.FindingsThe use of the PIM allows a better understanding of the physical situation of the system by allowing easy modeling to apply in practice. This is expressed by the value which, in this case, represents an improvement in the behavior of the system provided by a good quality of the corrective maintenance performed. This result is based on the hypothesis that modeling with the PIM can provide more clarification on the behavior of the system. It can indicate the effectiveness of the maintenance crew and guide managers to confirm or revise their maintenance policy.Originality/valueThe work intends to reflect the real situation in which the system operates. The originality of the work is to allow the consideration of covariates influencing the behavior of the system during its lifetime. The authors focused on modeling the degree of repair after each corrective maintenance performed on an oil pump. Since PIM does not require a specific reliability distribution to apply it, it allows a wide range of applications in the various industrial environments. Given the importance of this study, the PIM can be generalized for more covariates and working conditions.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41396714","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 : 2021-11-12DOI: 10.1108/ijqrm-05-2021-0153
Sunil Nandankar, Amit Sachan, A. Mukherjee, Arnab Adhikari
PurposeAlthough comprehensive work has been conducted in several scholarly journals in electronic service quality (e-SQ) measurement, there has been no cross-functional review of these studies. The majority of the review studies focus on e-SQ assessment in the field of electronic retail. This paper explores and synthesizes e-SQ evaluation work across the various functional domains in the last two decades and maps critical methodological challenges. It further classifies the dimensions used by researchers in six broad categories for better comprehension.Design/methodology/approachTo analyze and appreciate past e-SQ measurement research, a content assessment of the 50 most relevant research papers from various functional domains drawn from prestigious repositories was undertaken.FindingsThe results indicate shortcomings noticed in methodological issues in the e-SQ measurement research like research approaches, data analysis procedures, sampling methods, generation and purification of items, validity and reliability assessment, and dimensionality analysis. It further reveals that though e-SQ is multi-dimensional and context-specific, dimensions like content/information quality, website design, ease of use/usability, efficiency, security/and privacy, responsiveness, reliability, customer service, trust and fulfillment have been consistently cited in the reviewed studies across the various functional domains.Originality/valueAn assessment of 50 publications over the past 2 decades identifies key areas of concern in the existing research on e-SQ measurement in various functional domains for scholars and professionals. This study also provides a unique categorization of e-SQ dimensions used in various functional domains and has the potential to guide future research.
{"title":"Electronic service quality (e-SQ) measurement: a cross-functional review","authors":"Sunil Nandankar, Amit Sachan, A. Mukherjee, Arnab Adhikari","doi":"10.1108/ijqrm-05-2021-0153","DOIUrl":"https://doi.org/10.1108/ijqrm-05-2021-0153","url":null,"abstract":"PurposeAlthough comprehensive work has been conducted in several scholarly journals in electronic service quality (e-SQ) measurement, there has been no cross-functional review of these studies. The majority of the review studies focus on e-SQ assessment in the field of electronic retail. This paper explores and synthesizes e-SQ evaluation work across the various functional domains in the last two decades and maps critical methodological challenges. It further classifies the dimensions used by researchers in six broad categories for better comprehension.Design/methodology/approachTo analyze and appreciate past e-SQ measurement research, a content assessment of the 50 most relevant research papers from various functional domains drawn from prestigious repositories was undertaken.FindingsThe results indicate shortcomings noticed in methodological issues in the e-SQ measurement research like research approaches, data analysis procedures, sampling methods, generation and purification of items, validity and reliability assessment, and dimensionality analysis. It further reveals that though e-SQ is multi-dimensional and context-specific, dimensions like content/information quality, website design, ease of use/usability, efficiency, security/and privacy, responsiveness, reliability, customer service, trust and fulfillment have been consistently cited in the reviewed studies across the various functional domains.Originality/valueAn assessment of 50 publications over the past 2 decades identifies key areas of concern in the existing research on e-SQ measurement in various functional domains for scholars and professionals. This study also provides a unique categorization of e-SQ dimensions used in various functional domains and has the potential to guide future research.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49194281","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 : 2021-11-09DOI: 10.1108/ijqrm-11-2020-0374
Ruoqing Zhang, Minjoon Jun, Sergio Palacios
PurposeThe present study seeks to identify the salient mobile shopping (m-shopping) service quality dimensions as perceived by mobile shoppers (m-shoppers) and examines the linkages between the derived m-shopping service quality dimensions, customer trust and customer loyalty.Design/methodology/approachThe research instrument is developed based upon the mostly validated measures of prior studies. A pretest of the questionnaire is conducted to assess the content validity of the measurement scales. An online survey is used to collect the required data. We employ structural equation modeling (SEM) to analyze data collected from 286 m-shoppers.FindingsWe identify five key m-shopping service quality dimensions: responsiveness, personalization, ease of use, aesthetics and perceived risk based on an extensive review of relevant literature. The SEM results show that all the five m-shopping service quality dimensions significantly impact, directly and/or indirectly, customer loyalty. Moreover, the results show that trust plays a partial mediating role in the effects of responsiveness and personalization on loyalty; a full mediating role in the effects of aesthetics and perceived risk on loyalty and no mediating role in the effect of ease of use on loyalty.Practical implicationsMobile retailers (m-retailers) can use the quality measurement tool developed in this study to detect service quality weaknesses and strengths. Based on their quality assessment, m-retailers can effectively allocate corporate resources to the important service quality attributes uncovered by this study, thereby improving their overall service quality performance and in turn expanding their loyal customer base.Originality/valuePrior studies have demonstrated that service quality and customer trust play a pivotal role in enhancing customer loyalty in both offline and online settings. Unfortunately, no research has empirically examined the relationships between service quality dimensions, trust and loyalty in the context of m-shopping. Therefore, a major contribution of this study is to address this research gap and add knowledge to the limited body of post-adoption m-shopping research.
{"title":"M-shopping service quality dimensions and their effects on customer trust and loyalty: an empirical study","authors":"Ruoqing Zhang, Minjoon Jun, Sergio Palacios","doi":"10.1108/ijqrm-11-2020-0374","DOIUrl":"https://doi.org/10.1108/ijqrm-11-2020-0374","url":null,"abstract":"PurposeThe present study seeks to identify the salient mobile shopping (m-shopping) service quality dimensions as perceived by mobile shoppers (m-shoppers) and examines the linkages between the derived m-shopping service quality dimensions, customer trust and customer loyalty.Design/methodology/approachThe research instrument is developed based upon the mostly validated measures of prior studies. A pretest of the questionnaire is conducted to assess the content validity of the measurement scales. An online survey is used to collect the required data. We employ structural equation modeling (SEM) to analyze data collected from 286 m-shoppers.FindingsWe identify five key m-shopping service quality dimensions: responsiveness, personalization, ease of use, aesthetics and perceived risk based on an extensive review of relevant literature. The SEM results show that all the five m-shopping service quality dimensions significantly impact, directly and/or indirectly, customer loyalty. Moreover, the results show that trust plays a partial mediating role in the effects of responsiveness and personalization on loyalty; a full mediating role in the effects of aesthetics and perceived risk on loyalty and no mediating role in the effect of ease of use on loyalty.Practical implicationsMobile retailers (m-retailers) can use the quality measurement tool developed in this study to detect service quality weaknesses and strengths. Based on their quality assessment, m-retailers can effectively allocate corporate resources to the important service quality attributes uncovered by this study, thereby improving their overall service quality performance and in turn expanding their loyal customer base.Originality/valuePrior studies have demonstrated that service quality and customer trust play a pivotal role in enhancing customer loyalty in both offline and online settings. Unfortunately, no research has empirically examined the relationships between service quality dimensions, trust and loyalty in the context of m-shopping. Therefore, a major contribution of this study is to address this research gap and add knowledge to the limited body of post-adoption m-shopping research.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46332402","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 : 2021-11-05DOI: 10.1108/ijqrm-09-2020-0315
M. Arunmozhi, J. Persis, V. Sreedharan, A. Chakraborty, Tarik Zouadi, Hanane Khamlichi
PurposeAs COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective.Design/methodology/approachThe present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions.FindingsAfter successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated.Research limitations/implicationsUsing probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition.Practical implicationsThe study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference.Originality/valueFurther, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization.
{"title":"Managing the resource allocation for the COVID-19 pandemic in healthcare institutions: a pluralistic perspective","authors":"M. Arunmozhi, J. Persis, V. Sreedharan, A. Chakraborty, Tarik Zouadi, Hanane Khamlichi","doi":"10.1108/ijqrm-09-2020-0315","DOIUrl":"https://doi.org/10.1108/ijqrm-09-2020-0315","url":null,"abstract":"PurposeAs COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective.Design/methodology/approachThe present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions.FindingsAfter successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated.Research limitations/implicationsUsing probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition.Practical implicationsThe study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference.Originality/valueFurther, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46451718","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 : 2021-10-27DOI: 10.1108/ijqrm-09-2020-0318
Avirag Bajpai, S. Misra
PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.
{"title":"Barriers to implementing digitalization in the Indian construction industry","authors":"Avirag Bajpai, S. Misra","doi":"10.1108/ijqrm-09-2020-0318","DOIUrl":"https://doi.org/10.1108/ijqrm-09-2020-0318","url":null,"abstract":"PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49473142","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 : 2021-10-26DOI: 10.1108/ijqrm-06-2021-0161
Rohit Gupta, Bhawana Rathore, Baidyanath Biswas
PurposeThis study aims to review and organize the research articles which focused on the impact of COVID-19 pandemic in the supply chain (SC) domain through a bibliometric and network analysis.Design/methodology/approachInitially, a total of 772 research articles with selected keywords were retrieved from the Scopus database for the year 2020 (with the commencement of COVID-19 outbreak). After the filtration and refinement, 484 research articles were found relevant and unique. Further, this study systematically reviews and evaluates the 484 research articles including influential authors, keys journals, influential research work, and collaboration among the countries and institutes with the help of bibliometric analysis tool. The emergent research clusters are identified and established.FindingsThe findings reveal that the total number of related publications are steadily growing with the United States leading the way. European countries have made notable accomplishments as well. In addition, both the most cited publications and the keyword distribution provide research guidance for future research.Practical implicationsThis study focuses on the need and advancement of the literature on the impacts of the COVID-19 pandemic on SCs to frame a research agenda for researchers and practitioners.Originality/valueThe present study offers future research directions in the area of SC under the pandemic situation.
{"title":"Impact of COVID-19 on supply chains: lessons learned and future research directions","authors":"Rohit Gupta, Bhawana Rathore, Baidyanath Biswas","doi":"10.1108/ijqrm-06-2021-0161","DOIUrl":"https://doi.org/10.1108/ijqrm-06-2021-0161","url":null,"abstract":"PurposeThis study aims to review and organize the research articles which focused on the impact of COVID-19 pandemic in the supply chain (SC) domain through a bibliometric and network analysis.Design/methodology/approachInitially, a total of 772 research articles with selected keywords were retrieved from the Scopus database for the year 2020 (with the commencement of COVID-19 outbreak). After the filtration and refinement, 484 research articles were found relevant and unique. Further, this study systematically reviews and evaluates the 484 research articles including influential authors, keys journals, influential research work, and collaboration among the countries and institutes with the help of bibliometric analysis tool. The emergent research clusters are identified and established.FindingsThe findings reveal that the total number of related publications are steadily growing with the United States leading the way. European countries have made notable accomplishments as well. In addition, both the most cited publications and the keyword distribution provide research guidance for future research.Practical implicationsThis study focuses on the need and advancement of the literature on the impacts of the COVID-19 pandemic on SCs to frame a research agenda for researchers and practitioners.Originality/valueThe present study offers future research directions in the area of SC under the pandemic situation.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45566130","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 : 2021-10-26DOI: 10.1108/ijqrm-11-2020-0368
J. Suthar, J. Persis, Ruchita Gupta
PurposeCasting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.Design/methodology/approachA systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.FindingsThis study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.Research limitations/implicationsThis paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.Originality/valueThe systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.
{"title":"Critical parameters influencing the quality of metal castings: a systematic literature review","authors":"J. Suthar, J. Persis, Ruchita Gupta","doi":"10.1108/ijqrm-11-2020-0368","DOIUrl":"https://doi.org/10.1108/ijqrm-11-2020-0368","url":null,"abstract":"PurposeCasting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.Design/methodology/approachA systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.FindingsThis study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.Research limitations/implicationsThis paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.Originality/valueThe systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45311612","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 : 2021-10-26DOI: 10.1108/ijqrm-04-2021-0101
Patanjal Kumar, Dheeraj Sharma, P. Pandey
PurposeAn apparel supply chain primarily consists of geographically distant suppliers, manufacturers and retailers. The coordination among the members of the supply chain becomes difficult when we consider the triple bottom line of sustainability in it. Moreover, the complexity increases with the change in dominance power of the respective members. However, the task of managing the channel further becomes complicated after incorporating sustainability and dominance power simultaneously into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of three-echelon model to coordinate sustainable supply chain.Design/methodology/approachIn this paper, the noncooperative game theoretic method has been applied for the exploration of models. The various structures of the centralized and decentralized supply chain are considered on the basis of a player's dominance power. The model uses simultaneous and sequential move games to analyze optimal profit of supply chain agents, total channel profit, green innovation level and corporate social innovation level.FindingsAnalytical results show that simultaneous game performs better than the sequential game. The consumer sensitivity toward green and social innovations increases total channel profit. We also proposed a linear two-part tariff contract model. The proposed model enhances the sustainability level and leads to perfect channel coordination. Using a numerical example, we present the effectiveness of multiple game structures under centralized and decentralized settings. The results reveal that channel efficiency is the highest in the two-part tariff contract followed by a simultaneous move game structure and lower in the cases of sequential move game.Research limitations/implicationsIn this research, model setting are deterministic and there is no any information asymmetry. Therefore researchers are encouraged to study multiechelon sustainable supply chain coordination models under stochastic and information asymmetry settings.Practical implicationsThe paper includes implications for the development of sustainable supply chain coordination model to tackle the problems of dominance power, sustainability issues and lower channel efficiency of supply chain.Originality/valueThis study proposes game-theory-based three-echelon sustainable supply chain for the channel coordination.
{"title":"Three-echelon apparel supply chain coordination with triple bottom line approach","authors":"Patanjal Kumar, Dheeraj Sharma, P. Pandey","doi":"10.1108/ijqrm-04-2021-0101","DOIUrl":"https://doi.org/10.1108/ijqrm-04-2021-0101","url":null,"abstract":"PurposeAn apparel supply chain primarily consists of geographically distant suppliers, manufacturers and retailers. The coordination among the members of the supply chain becomes difficult when we consider the triple bottom line of sustainability in it. Moreover, the complexity increases with the change in dominance power of the respective members. However, the task of managing the channel further becomes complicated after incorporating sustainability and dominance power simultaneously into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of three-echelon model to coordinate sustainable supply chain.Design/methodology/approachIn this paper, the noncooperative game theoretic method has been applied for the exploration of models. The various structures of the centralized and decentralized supply chain are considered on the basis of a player's dominance power. The model uses simultaneous and sequential move games to analyze optimal profit of supply chain agents, total channel profit, green innovation level and corporate social innovation level.FindingsAnalytical results show that simultaneous game performs better than the sequential game. The consumer sensitivity toward green and social innovations increases total channel profit. We also proposed a linear two-part tariff contract model. The proposed model enhances the sustainability level and leads to perfect channel coordination. Using a numerical example, we present the effectiveness of multiple game structures under centralized and decentralized settings. The results reveal that channel efficiency is the highest in the two-part tariff contract followed by a simultaneous move game structure and lower in the cases of sequential move game.Research limitations/implicationsIn this research, model setting are deterministic and there is no any information asymmetry. Therefore researchers are encouraged to study multiechelon sustainable supply chain coordination models under stochastic and information asymmetry settings.Practical implicationsThe paper includes implications for the development of sustainable supply chain coordination model to tackle the problems of dominance power, sustainability issues and lower channel efficiency of supply chain.Originality/valueThis study proposes game-theory-based three-echelon sustainable supply chain for the channel coordination.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46174803","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 : 2021-10-25DOI: 10.1108/IJQRM-06-2021-0184
C. Cubo, R. Oliveira, A. C. Fernandes, P. Sampaio, M. Carvalho, P. Afonso
Purpose – This paper aims to presentand discuss an innovativematurity model (MM) to assess supply chain quality management (SCQM). The SCQM MM can be used to guide organizations in the development and improvement of quality in their supply chains (SCs). Additionally, this paper intends to better understand that integration and its impacts on organizational performance. Design/methodology/approach – The proposed MM was developed based on an exhaustive literature reviewofthemostrelevantMMsdevelopedintheareasofqualitymanagement,supplychainmanagementand otherrelevantdomains. Findings – The proposed MM consists of a matrix with 100 criteria organized in five organizational dimensions and five maturity levels, embracing the most relevant SC issues and describing a progressive path towards a state of full maturity. Originality/value – It is an innovative tool useful for both academic experts and practitioners to integrate quality management across the SC, thus promoting and improving organizational performance from an integrated and sustainable perspective.
{"title":"An innovative maturity model to assess supply chain quality management","authors":"C. Cubo, R. Oliveira, A. C. Fernandes, P. Sampaio, M. Carvalho, P. Afonso","doi":"10.1108/IJQRM-06-2021-0184","DOIUrl":"https://doi.org/10.1108/IJQRM-06-2021-0184","url":null,"abstract":"Purpose – This paper aims to presentand discuss an innovativematurity model (MM) to assess supply chain quality management (SCQM). The SCQM MM can be used to guide organizations in the development and improvement of quality in their supply chains (SCs). Additionally, this paper intends to better understand that integration and its impacts on organizational performance. Design/methodology/approach – The proposed MM was developed based on an exhaustive literature reviewofthemostrelevantMMsdevelopedintheareasofqualitymanagement,supplychainmanagementand otherrelevantdomains. Findings – The proposed MM consists of a matrix with 100 criteria organized in five organizational dimensions and five maturity levels, embracing the most relevant SC issues and describing a progressive path towards a state of full maturity. Originality/value – It is an innovative tool useful for both academic experts and practitioners to integrate quality management across the SC, thus promoting and improving organizational performance from an integrated and sustainable perspective.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45975419","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 : 2021-10-21DOI: 10.1108/ijqrm-08-2020-0274
V. E. Kane
PurposeThe goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects.Design/methodology/approachUsing a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis.FindingsSeven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification.Research limitations/implicationsAny starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list.Practical implicationsLearners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities.Originality/valueAny successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.
{"title":"Useful paths for identifying Lean Six Sigma improvement opportunities","authors":"V. E. Kane","doi":"10.1108/ijqrm-08-2020-0274","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2020-0274","url":null,"abstract":"PurposeThe goal of this work is to clarify seven useful DMAIC Analyze phase options for developing process improvement opportunities required for successful projects.Design/methodology/approachUsing a scientific method problem solving structure, IO possibilities are shown to be predicted by rejecting a conceptual testable hypothesis.FindingsSeven analysis paths are identified that enable learners to develop multiple IO discovery strategies and to narrow tool selection options. Four benefit areas for identifying analysis paths are given: improved training, continuous improvement foundation, leadership support and framework clarification.Research limitations/implicationsAny starting list of analysis paths for developing IOs would be incomplete. The diversity of application experiences and tools will add to the current list.Practical implicationsLearners participating in LSS activities are aware of management's expectation that they will develop IOs to justify the LSS investment. Tool-focused training may leave some learners unclear about the multiple possible sources for IOs. Identifying useful analysis paths with associated tools for IO discovery will address any learner's Analyze phase uncertainty and facilitate expanded opportunities.Originality/valueAny successful LSS project must discover IOs to develop improvement actions. Clarifying IO discovery alternatives will encourage team brainstorming on Analyze phase investigative options. This framework identifying LSS improvement paths will assist practitioners in training and communicating with leadership and learners the range of approaches for developing improvement actions.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48718382","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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