Dharshini Devi Subramaniam, Soon Chong Johnson Lim
{"title":"An Interactive Visualization Web Application for Industrial-Focused Statistical Process Control Analysis","authors":"Dharshini Devi Subramaniam, Soon Chong Johnson Lim","doi":"10.30880/jst.2022.14.02.003","DOIUrl":null,"url":null,"abstract":"Statistical process control (SPC) implementation plays a major role in quality assurance during the manufacturing process. Nevertheless, the adoption rate of SPC commercial software solutions is unsatisfactory in most Malaysian manufacturing companies due to high software subscription costs and difficulties in applying the software without proper know-how, guidance, and training. This study proposes the development of a purpose-built interactive data visualization web application for rapid SPC analysis in the manufacturing industry using open-sourced software packages. An agile software development model is applied as the software development methodology. In the requirement phase, an interview session was conducted to identify project requirements among stakeholders, i.e. industrial practitioners that are involved with SPC analysis. Based on the feedback and expectations from stakeholders, a design of a web application for SPC analysis that incorporates interactive parameter settings and automated reporting was proposed. The web application was developed using the R programming language and the Shiny package library, and deployed at ShinyApps.io, a web service provider. For evaluation, a usability testing procedure was designed and conducted with five industrial SPC practitioners to determine the usefulness of the web application. The outcome of the usability testing indicated positive results and feedback from evaluators. In conclusion, the developed web-app can assist users, particularly from the manufacturing industry sectors, to perform fast SPC data analytics, visualization, and reporting with ease.","PeriodicalId":21913,"journal":{"name":"Songklanakarin Journal of Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Songklanakarin Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30880/jst.2022.14.02.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Multidisciplinary","Score":null,"Total":0}
引用次数: 0
Abstract
Statistical process control (SPC) implementation plays a major role in quality assurance during the manufacturing process. Nevertheless, the adoption rate of SPC commercial software solutions is unsatisfactory in most Malaysian manufacturing companies due to high software subscription costs and difficulties in applying the software without proper know-how, guidance, and training. This study proposes the development of a purpose-built interactive data visualization web application for rapid SPC analysis in the manufacturing industry using open-sourced software packages. An agile software development model is applied as the software development methodology. In the requirement phase, an interview session was conducted to identify project requirements among stakeholders, i.e. industrial practitioners that are involved with SPC analysis. Based on the feedback and expectations from stakeholders, a design of a web application for SPC analysis that incorporates interactive parameter settings and automated reporting was proposed. The web application was developed using the R programming language and the Shiny package library, and deployed at ShinyApps.io, a web service provider. For evaluation, a usability testing procedure was designed and conducted with five industrial SPC practitioners to determine the usefulness of the web application. The outcome of the usability testing indicated positive results and feedback from evaluators. In conclusion, the developed web-app can assist users, particularly from the manufacturing industry sectors, to perform fast SPC data analytics, visualization, and reporting with ease.
期刊介绍:
Songklanakarin Journal of Science and Technology (SJST) aims to provide an interdisciplinary platform for the dissemination of current knowledge and advances in science and technology. Areas covered include Agricultural and Biological Sciences, Biotechnology and Agro-Industry, Chemistry and Pharmaceutical Sciences, Engineering and Industrial Research, Environmental and Natural Resources, and Physical Sciences and Mathematics. Songklanakarin Journal of Science and Technology publishes original research work, either as full length articles or as short communications, technical articles, and review articles.