Search
  Advanced Search
 
Journal search
Journal cover: Kybernetes

Kybernetes

ISSN: 0368-492X

Online from: 1972

Subject Area: Electrical & Electronic Engineering

Content: Latest Issue | icon: RSS Latest Issue RSS | Previous Issues

 

Previous article.Icon: Print.Table of Contents.Next article.Icon: .

Modeling and controlling work-in-progress in discrete manufacturing systems


Document Information:
Title:Modeling and controlling work-in-progress in discrete manufacturing systems
Author(s):Guo Cai-fen, (Department of Mechanical and Electrical Engineering, Suzhou Vocational University, Suzhou, China), Jing Ran-zhe, (Manufacturing Informatization Research Center, Suzhou Vocational University, Suzhou, China and National Engineering Research Center for Enterprise Information Software, Suzhou, China)
Citation:Guo Cai-fen, Jing Ran-zhe, (2011) "Modeling and controlling work-in-progress in discrete manufacturing systems", Kybernetes, Vol. 40 Iss: 5/6, pp.842 - 847
Keywords:Control systems, Cybernetics, Delivery, Manufacturing industries, Programming and algorithm theory
Article type:Technical paper
DOI:10.1108/03684921111142386 (Permanent URL)
Publisher:Emerald Group Publishing Limited
Abstract:

Purpose – The purpose of this paper is to apply the proportional integral (PI) control algorithm in discrete manufacturing enterprises to maintain lower and steadier work in progress so as to improve on-time delivery.

Design/methodology/approach – A sensitivity constrained optimization model is designed on the frequency domain, whose optimum algebraic solutions are then obtained easily. Two controllers, a backlog controller and an input-rate controller, are devised, which correspond to the integral control and the proportional control of PI controllers, respectively. Interacting with each other, these controllers have made the engineering implementation of PI controllers a reality.

Findings – Simulation is carried out in certain motorcycle production lines. Results confirm that PI controllers also possess good control effects in the discrete manufacturing industry, as well as in the process industry.

Research limitations/implications – A continued departure from the nominal may happen repeatedly if the root causes of changing are not detected and identified. Moreover, PI controllers can mask process defects, failures, and drifts, and this may lead to eventual catastrophic failures. So, statistical process control should be utilized in PI controlled processes to detect significant changes for long-term process improvement.

Practical implications – PI controllers possess potential in discrete enterprises.

Originality/value – PI controllers are tried for process improvement in discrete manufacturing enterprises.



Fulltext Options:

Login

Login

Existing customers: login
to access this document

Login


- Forgot password?
- Athens/Institutional login

Purchase

Purchase

Downloadable; Printable; Owned
HTML, PDF (88kb)

Due to our platform migration, pay-per-view is temporarily unavailable.

To purchase this item please login or register.

Login


- Forgot password?

Recommend to your librarian

Complete and print this form to request this document from your librarian


Marked list


Bookmark & share

Reprints & permissions