689
Views
34
CrossRef citations to date
0
Altmetric
Original Articles

Sequencing problem for a mixed-model assembly line in the Toyota production system

, &
Pages 4955-4974 | Received 01 Jun 2004, Published online: 22 Feb 2007
 

Abstract

The paper discusses a sequencing problem of a mixed-model assembly line in the Toyota Motor Corporation production system, which is well known as the Just-in-Time production system. Whenever a worker in the assembly line finds that he might fail to complete his operations within the work zone, he pushes a button to call an auxiliary worker who assists him in the operations. If he can complete the operations within his work zone with the help of the auxiliary worker, the line does not stop. Otherwise, the line stops. In the Toyota production system, it is very important to keep a constant rate of usage of every part used by the assembly line. Hence, there are two goals for the sequencing problem in the Toyota production system. The paper provides a new formulation for the sequencing problem with two goals. It considers the goal of keeping the constant rate of part usage as a constraint of the sequencing problem, and it formulates a sequencing problem of minimizing the total line stoppage time with auxiliary workers and the constraints for keeping the constant rate of part usage. Since this problem is NP-hard and the size of the practical problems at Toyota are huge, a two-phase approximation algorithm is proposed. Numerical examples show that the proposed algorithm is efficient and can find a good suboptimal solution.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 973.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.