Integration of missing parameters into a DES tool

Qian Wang, Reda Ahmed O. Nujoom, Maji Ibrahim Abubakar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

62 Downloads (Pure)

Abstract

Products are usually made by accomplishing a series of manufacturing processes in a sequential flow line that is also known as a manufacturing system. Today, lean methods are widely adopted by many manufacturing plants as a popular model in designing, implementing, operating or managing a manufacturing system. It has been proved as a cost-effective approach to boost system efficiency and productivity by consistently seeking and removing any non-value added activities (i.e., wastes) during a production with a small or without any additional investment. Nevertheless, identification of these wastes using the traditional lean methods does not include such wastes as amounts of energy consumption and CO2 emissions. For human centered assembly lines, for instance, it is reported that applying highly skilled, flexible and dynamic workers into production lines is also a good practice for implementing a lean manufacturing system in which each worker performs multiple tasks amongst stations. On the other hand, most studies on manufacturing systems using the modelling simulation methods failed to consider parameters of energy consumption, CO2 emissions and human factors that may also impact the overall system performance. The simultaneous prediction, which relates to amounts of energy consumption and CO2 emissions and effects of human factors (or human performance) for a manufacturing system evaluation, is often overlooked by researchers or system designers partially due to a lack of existing DES (discrete event simulation) tools that enable incorporating these parameters into an established DES model. This paper presents a study by addressing these issues aiming to incorporate these missing parameters of energy consumption, CO2 emissions and human factors (age and experience) into a DES model.
Original languageEnglish
Title of host publication2018 3rd International Conference on Advanced Materials Research and Manufacturing Technologies (AMRMT 2018)
PublisherIOP Publishing
Number of pages8
Volume436
EditionConference 1
DOIs
Publication statusEarly online - 23 Oct 2018
Event3rd International Conference on Advanced Materials Research and Manufacturing Technologies - Shanghai, China
Duration: 11 Aug 201813 Aug 2018

Publication series

NameIOP Conference Series: Materials Science and Engineering
PublisherIOP Publishing Ltd.
ISSN (Print)1757-8981
ISSN (Electronic)1757-899X

Conference

Conference3rd International Conference on Advanced Materials Research and Manufacturing Technologies
Abbreviated titleAMRMT 2018
Country/TerritoryChina
CityShanghai
Period11/08/1813/08/18

Fingerprint

Dive into the research topics of 'Integration of missing parameters into a DES tool'. Together they form a unique fingerprint.

Cite this