E. Shevtshenko, Rene Maas, Lea Murumaa, Tatjanja Karaulova, Ibrahim Oluwole Raji, Janek Popell
{"title":"Digitalisation of Supply Chain management system for customer quality service improvement.","authors":"E. Shevtshenko, Rene Maas, Lea Murumaa, Tatjanja Karaulova, Ibrahim Oluwole Raji, Janek Popell","doi":"10.36897/jme/147803","DOIUrl":null,"url":null,"abstract":"The main idea of the current research is to apply customer satisfaction level Key Performance Indicators (KPIs) for supply chain reliability improvement. The Supply Chain Operations Reference (SCOR) model-based KPI metrics increase the quality of product/service by monitoring, visualising, and digitalising directly involved processes. In the long run, the solution will ultimately help reduce/eliminate the number of customer reclamations in the supply chain. An industry-oriented performance measurement model based on SCOR can be easily adapted for different sectors. The approach proposed in the current research is based on identifying key factors of supply chain performance of the SCOR model connected with the predictive and diagnostic capability of Bayesian Believe Networks. The difference in performance can be reached via applying the best practices to processes, affecting the performance on a larger scale.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Machine Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36897/jme/147803","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The main idea of the current research is to apply customer satisfaction level Key Performance Indicators (KPIs) for supply chain reliability improvement. The Supply Chain Operations Reference (SCOR) model-based KPI metrics increase the quality of product/service by monitoring, visualising, and digitalising directly involved processes. In the long run, the solution will ultimately help reduce/eliminate the number of customer reclamations in the supply chain. An industry-oriented performance measurement model based on SCOR can be easily adapted for different sectors. The approach proposed in the current research is based on identifying key factors of supply chain performance of the SCOR model connected with the predictive and diagnostic capability of Bayesian Believe Networks. The difference in performance can be reached via applying the best practices to processes, affecting the performance on a larger scale.
期刊介绍:
ournal of Machine Engineering is a scientific journal devoted to current issues of design and manufacturing - aided by innovative computer techniques and state-of-the-art computer systems - of products which meet the demands of the current global market. It favours solutions harmonizing with the up-to-date manufacturing strategies, the quality requirements and the needs of design, planning, scheduling and production process management. The Journal'' s subject matter also covers the design and operation of high efficient, precision, process machines. The Journal is a continuator of Machine Engineering Publisher for five years. The Journal appears quarterly, with a circulation of 100 copies, with each issue devoted entirely to a different topic. The papers are carefully selected and reviewed by distinguished world famous scientists and practitioners. The authors of the publications are eminent specialists from all over the world and Poland. Journal of Machine Engineering provides the best assistance to factories and universities. It enables factories to solve their difficult problems and manufacture good products at a low cost and fast rate. It enables educators to update their teaching and scientists to deepen their knowledge and pursue their research in the right direction.