Sequencing jobs in an engineer-to-order engineering environment

Engineer–to-order (ETO) firms produce complex – one of a kind – products and desire shorter lead time as a key component to cost competitiveness. In ETO firms, the engineering process is the largest controllable consumer of lead time. Given that lead time is a function of completion rate and schedul...

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Main Authors: Douglas H. Grabenstetter, John M. Usher
Format: Article
Language:English
Published: Taylor & Francis Group 2015-01-01
Series:Production and Manufacturing Research: An Open Access Journal
Subjects:
Online Access:http://dx.doi.org/10.1080/21693277.2015.1035461
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spelling doaj-e07618895f2a4d48900fa7800b2abe932020-11-24T23:46:55ZengTaylor & Francis GroupProduction and Manufacturing Research: An Open Access Journal2169-32772015-01-013120121710.1080/21693277.2015.10354611035461Sequencing jobs in an engineer-to-order engineering environmentDouglas H. Grabenstetter0John M. Usher1Mississippi State UniversityMississippi State UniversityEngineer–to-order (ETO) firms produce complex – one of a kind – products and desire shorter lead time as a key component to cost competitiveness. In ETO firms, the engineering process is the largest controllable consumer of lead time. Given that lead time is a function of completion rate and scheduling policy, one critical process is to accurately sequence jobs in front of the engineering function. However, unlike other manufacturing models, such as make–to-stock or make-to-order models, the design for an ETO product is not realized until after the engineering process has been completed. Hence, the only information available does not include data normally required by most sequencing algorithms. Therefore, the problem becomes the determination of an accurate schedule within a complex transactional process for jobs which have not even been designed yet. This paper investigates this topic in the context of the engineering process within the ETO model. Based on research conducted in conjunction with multiple firms, common factors are identified which drive complexity, and a new framework and algorithm are presented for using these factors to sequence jobs. Using discrete event simulation, the performance of this new algorithm is found to be a significant improvement over current industry and published methods.http://dx.doi.org/10.1080/21693277.2015.1035461engineer-to-ordersequencingdesign
collection DOAJ
language English
format Article
sources DOAJ
author Douglas H. Grabenstetter
John M. Usher
spellingShingle Douglas H. Grabenstetter
John M. Usher
Sequencing jobs in an engineer-to-order engineering environment
Production and Manufacturing Research: An Open Access Journal
engineer-to-order
sequencing
design
author_facet Douglas H. Grabenstetter
John M. Usher
author_sort Douglas H. Grabenstetter
title Sequencing jobs in an engineer-to-order engineering environment
title_short Sequencing jobs in an engineer-to-order engineering environment
title_full Sequencing jobs in an engineer-to-order engineering environment
title_fullStr Sequencing jobs in an engineer-to-order engineering environment
title_full_unstemmed Sequencing jobs in an engineer-to-order engineering environment
title_sort sequencing jobs in an engineer-to-order engineering environment
publisher Taylor & Francis Group
series Production and Manufacturing Research: An Open Access Journal
issn 2169-3277
publishDate 2015-01-01
description Engineer–to-order (ETO) firms produce complex – one of a kind – products and desire shorter lead time as a key component to cost competitiveness. In ETO firms, the engineering process is the largest controllable consumer of lead time. Given that lead time is a function of completion rate and scheduling policy, one critical process is to accurately sequence jobs in front of the engineering function. However, unlike other manufacturing models, such as make–to-stock or make-to-order models, the design for an ETO product is not realized until after the engineering process has been completed. Hence, the only information available does not include data normally required by most sequencing algorithms. Therefore, the problem becomes the determination of an accurate schedule within a complex transactional process for jobs which have not even been designed yet. This paper investigates this topic in the context of the engineering process within the ETO model. Based on research conducted in conjunction with multiple firms, common factors are identified which drive complexity, and a new framework and algorithm are presented for using these factors to sequence jobs. Using discrete event simulation, the performance of this new algorithm is found to be a significant improvement over current industry and published methods.
topic engineer-to-order
sequencing
design
url http://dx.doi.org/10.1080/21693277.2015.1035461
work_keys_str_mv AT douglashgrabenstetter sequencingjobsinanengineertoorderengineeringenvironment
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