1,528
Views
53
CrossRef citations to date
0
Altmetric
Original Articles

Modular design of product families for quality and cost

&
Pages 1648-1667 | Received 24 Oct 2011, Accepted 19 Apr 2012, Published online: 06 Jul 2012
 

Abstract

The purpose of this article is to help managers early in the design of new product families. Based on product structures, sales forecasts, and constraints imposed by the marketplace, like quality and cost, the proposed method selects the product modules that meet customer requirements for the products, while respecting those constraints. The proposal includes a single-level module design formulation that considers quality and cost simultaneously. The method for testing the proposed algorithm is based on a case study of an electro–mechanical assembly device (headlamp). The performance of the algorithm is compared to that of the zero module case, where often the constraint problem cannot be resolved. The main result is a model and an algorithm that optimise quality and cost under the constraints of quality and cost. It shows what modules to manufacture, in what quantities, and in which products to use them. The output also provides the predicted quality and cost, based on improvements made to the modules. To conclude, this research enables the joint optimisation of quality and cost by defining the modules to be manufactured. It provides input for managers seeking modules designed for their supply chain. The algorithm provides key input for managing production ramp-up.

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.