Optimisation algorithms for improvement of a multihead weighing process Online publication date: Fri, 17-Jan-2020
by Alexander Pulido-Rojano; J. Carlos García-Díaz
International Journal of Productivity and Quality Management (IJPQM), Vol. 29, No. 1, 2020
Abstract: Mathematical optimisation is widely used to find the optimal value for an objective function, subject to constraints that try to simulate reality, and is fundamental to improving industrial processes. In this paper, we compare different optimisation approaches to solve the packaging problem in multihead weighing machines. In this problem, each package is made up from the loads in a subset of the multihead weigher's hoppers. The total weight of the packed product must be as close to a specified target weight as possible. We designed and evaluated a set of algorithms for this problem, considering both single-objective and bi-objective optimisation criteria. A new criterion for creating the packages is considered, and a different way of filling of the hoppers is studied with the aim of reducing process variability. Numerical experiments considering both a set of real data and the most important process performance parameters show the usefulness of our study.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Productivity and Quality Management (IJPQM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook