Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study

This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration fo...

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Autores principales:	Yuchang Won, Seunghyeon Kim, Kyung-Joon Park, Yongsoon Eun
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	internet of everything production systems engineering continuous productivity improvement smart factory fault monitoring data Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/9101fb288c24443a8324884d9a3acb55
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spelling	oai:doaj.org-article:9101fb288c24443a8324884d9a3acb552021-11-11T19:18:22ZContinuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study10.3390/s212173661424-8220https://doaj.org/article/9101fb288c24443a8324884d9a3acb552021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7366https://doaj.org/toc/1424-8220This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration for productivity improvement based on measured data. Analysis for continuous improvement of a production system requires a set of data (machine uptime, downtime, cycle-time) that are not typically monitored by a conventional fault monitoring system. Although productivity improvement is a critical aspect for a manufacturing site, not many production systems are equipped with a dedicated data recording system towards continuous improvement. In this paper, we study the problem of how to derive the dataset required for continuous improvement from the measurement by a conventional fault monitoring system. In particular, we provide a case study of an automotive parts production line. Based on the data measured by the existing fault monitoring system, we model the production system and derive the dataset required for continuous improvement. Our approach provides the expected amount of improvement to operation managers in a numerical manner to help them make a decision on whether they should modify the line configuration or not.Yuchang WonSeunghyeon KimKyung-Joon ParkYongsoon EunMDPI AGarticleinternet of everythingproduction systems engineeringcontinuous productivity improvementsmart factoryfault monitoring dataChemical technologyTP1-1185ENSensors, Vol 21, Iss 7366, p 7366 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	internet of everything production systems engineering continuous productivity improvement smart factory fault monitoring data Chemical technology TP1-1185
spellingShingle	internet of everything production systems engineering continuous productivity improvement smart factory fault monitoring data Chemical technology TP1-1185 Yuchang Won Seunghyeon Kim Kyung-Joon Park Yongsoon Eun Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
description	This paper presents a case study of continuous productivity improvement of an automotive parts production line using Internet of Everything (IoE) data for fault monitoring. Continuous productivity improvement denotes an iterative process of analyzing and updating the production line configuration for productivity improvement based on measured data. Analysis for continuous improvement of a production system requires a set of data (machine uptime, downtime, cycle-time) that are not typically monitored by a conventional fault monitoring system. Although productivity improvement is a critical aspect for a manufacturing site, not many production systems are equipped with a dedicated data recording system towards continuous improvement. In this paper, we study the problem of how to derive the dataset required for continuous improvement from the measurement by a conventional fault monitoring system. In particular, we provide a case study of an automotive parts production line. Based on the data measured by the existing fault monitoring system, we model the production system and derive the dataset required for continuous improvement. Our approach provides the expected amount of improvement to operation managers in a numerical manner to help them make a decision on whether they should modify the line configuration or not.
format	article
author	Yuchang Won Seunghyeon Kim Kyung-Joon Park Yongsoon Eun
author_facet	Yuchang Won Seunghyeon Kim Kyung-Joon Park Yongsoon Eun
author_sort	Yuchang Won
title	Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
title_short	Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
title_full	Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
title_fullStr	Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
title_full_unstemmed	Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study
title_sort	continuous productivity improvement using ioe data for fault monitoring: an automotive parts production line case study
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9101fb288c24443a8324884d9a3acb55
work_keys_str_mv	AT yuchangwon continuousproductivityimprovementusingioedataforfaultmonitoringanautomotivepartsproductionlinecasestudy AT seunghyeonkim continuousproductivityimprovementusingioedataforfaultmonitoringanautomotivepartsproductionlinecasestudy AT kyungjoonpark continuousproductivityimprovementusingioedataforfaultmonitoringanautomotivepartsproductionlinecasestudy AT yongsooneun continuousproductivityimprovementusingioedataforfaultmonitoringanautomotivepartsproductionlinecasestudy
_version_	1718431598210187264

Continuous Productivity Improvement Using IoE Data for Fault Monitoring: An Automotive Parts Production Line Case Study

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