A fuzzy model for load-oriented manufacturing control [An article from: International Journal of Production Economics]

This digital document is a journal article from International Journal of Production Economics, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
This paper presents an original approach to load-oriented manufacturing control for job-shop scheduling, based on fuzzy theory. The model allows to cope with the pitfalls encountered by traditional approaches to job-shop scheduling in the definition of system parameters. In fact, traditional approaches to job-shop scheduling assume that system parameters are deterministically known ex-ante; on the contrary, the parameters values actually observed in the job-shop are often different due to the impact of unforeseen dynamics. As a consequence, the effectiveness of traditional approaches is undermined. In this paper the authors focus on the ''machine output in the planning horizon'' parameter and present a model allowing to represent that parameter as a neuro-fuzzy variable, whereas traditional approach represent it as a deterministic value. The case study carried out in a real manufacturing system and reported at the end of the paper shows the effectiveness of the proposed approach.