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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Online Access: | http://dx.doi.org/10.1080/21693277.2015.1035461 |
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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 AT johnmusher sequencingjobsinanengineertoorderengineeringenvironment |
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