|
Other FMEA
Sources
| |
Title: Exploration methods in business process re-engineering
Author: Rajala, M; Savolainen, T; Jagdev, H
Abstract: Understanding the reasons of process variation is recognised as a key to the successful management of business processes. Various exploration methods give the prospective users a chance to tackle such complex problems by means of computer. This paper considers two key methodologies within the domain of exploration methods: simulation modelling and value analysis (VA). With worked-out examples, this paper shows, by using the techniques adopted from traditional manufacturing process control, how this problem can be tackled. For retrospective studies focusing to understand and manage internal process variation, statistical process control (SPC) charts together with the failure modes and effects analysis (FMEA) method is a powerful tool. For prospective studies, focusing to understand and manage the effects due to variability of customer needs, information generated in quality function deployment (QFD) analysis is suggested to be used. All information generated by studies can be used in simulations using Taguchi cross-product redesigns. When the object of VA is a business process instead of a product, the paper also describes how these methods can be applied to business process re-engineering (BPR). The creative problem solving power of VA is especially helpful in BPR. The small improvements can be achieved via the logical analysis and modelling methods but the radical breakthrough improvements require often creative problem solving in addition to modelling. Application of the methods is exposed through a business process example of Neste Advanced Power Systems Finland solar power systems manufacturing, using IDEFO models to be translated for simulation via coloured Petri nets, The conclusion of the paper is that the joined methodology offers a practical advantage for managing simulation studies needed in business process redesign. (C) 1997 Elsevier Science B.V.
Source: COMPUTERS IN INDUSTRY
Publication Year: 1997
Volume: 33
Issue nr: 2/03/2010
Pages: 367 - 385
Science Code: Computer Science, Interdisciplinary Applications
Tags: exploration methods; simulation modelling; value analysis; quality function deployment; statistical process control
|