A new right-skewed loss function in process risk assessment
by Onur Köksoy; Pelin Ergen; Melis Zeybek
European J. of Industrial Engineering (EJIE), Vol. 13, No. 4, 2019

Abstract: Due to globalisation, competitive companies realise that providing a more reliable, predictable, and robust product/process is a prerequisite for satisfying their customers and running a successful operation. Many quality improvement techniques focus on reducing process variation in line with the 'loss to society' concept. The widespread use of loss functions in industrial applications has increased their popularity with different loss-handling features. Developments relating to the inverted probability density functions (PDFs) have allowed the application of particular loss functions in a wide range. This paper presents the inverted Wald loss function as a new member of the inverted probability loss family. The important features of the proposed right-skewed loss function are discussed, and the risk functions associated with some process distributions of interest are obtained. Moreover, the proposed loss function and its performance are illustrated on the basis of a comparative study and an industrial example, including the monitoring of loss. [Received: 22 May 2018; Revised: 11 August 2018; Revised: 29 October 2018; Revised: 14 January 2019; Accepted: 23 January 2019]

Online publication date: Fri, 19-Jul-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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 European J. of Industrial Engineering (EJIE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your 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