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Detecting, Identifying and Managing Sources of Variation in Production and Product Development

Alexander Chakhunashvili (Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling)
Göteborg : Chalmers University of Technology, 2006. ISBN: 91-7291-751-2.- 161 s.

It is well known that customers have varying needs and wants and thus expect to have a broad spectrum of products to choose from. However, they hardly tolerate variation in products produced to the same specifications. This variation, which originates from multiple sources and adversely affects product quality, should be detected, identified and managed throughout the Product Realization Process (PRP). While the PRP is a widely defined concept, this thesis focuses on its two distinct parts, namely production and product development. There are essentially two strategies for dealing with variation. One is to detect and eliminate sources of variation. This is usually done using Statistical Process Control (SPC) procedures. The second is to minimize the impact that the sources of variation have on important product characteristics. This is usually done using Robust Design Methodology (RDM) tools. The main objective of this thesis has been to develop statistical methods that support the execution of both strategies. More specifically, in order to identify and assess the risks related to variation from early phases of product development, a new statistically based engineering method, Variation Mode and Effect Analysis (VMEA), has been developed. Furthermore, to effectively address variation-related problems in production, especially when traditional control charts cannot detect assignable causes of variation, a number of modifications to Shewhart’s criteria and Exponentially Weighted Moving Average (EWMA) control charts have been proposed and applied in practice. Finally, some contributions have been made to the understanding and definition of predictability as an important notion in statistical quality control.

Nyckelord: sources of variation, Statistical Process Control (SPC), Robust Design Methodology, Key Product Characteristics, Variation Mode and Effect Analysis (VMEA).

Denna post skapades 2006-06-01. Senast ändrad 2013-09-25.
CPL Pubid: 20933


Institutioner (Chalmers)

Institutionen för teknikens ekonomi och organisation, Industriell kvalitetsutveckling (2005-2016)


Industriell teknik och ekonomi

Chalmers infrastruktur

Relaterade publikationer

Inkluderade delarbeten:

An EWMA Solution to Detect Shifts in a Bernoulli Process in an Out-of-Control Environment

Variation Mode and Effect Analysis: a Practical Tool for Quality Improvement


Datum: 2006-03-17
Tid: 10.00
Lokal: 10.00 Vasa A
Opponent: Professor Murat Kulahci, Arizona State University, USA

Ingår i serie

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie 2433

PhD thesis - Department of Quality Sciences 4