Atlas: Using Statistical Quality Improvement Tools to Reduce Customer Return Rates and In-House Reject Rates in a Small/Medium Enterprise. by Matt Linsley

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International Conference on Statistics, Combinatorics and Related Areas and the Eighth International Conference of Forum for Interdisciplinary Mathematics
December 19-21, 2001
School of Mathematics and Applied Statistics, University of Wollongong
Wollongong, NSW, Australia

Organizers
Satya N. Mishra (University of South Alabama), Chandra M. Gulati (University of Wollongong)

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Using Statistical Quality Improvement Tools to Reduce Customer Return Rates and In-House Reject Rates in a Small/Medium Enterprise.
by
Matt Linsley
ISRU, University of Newcastle upon Tyne, England
Coauthors: K.F.Pearce, D.J.Stewardson

Many small companies are unwilling to participate in improvement projects due to short-term work demands. This paper details how it is possible to apply statistical techniques in these types of industries whilst causing minimal disruption to a normal working schedule.

The aim of the investigation was to reduce customer return rates and in-house reject rate by making improvements to the manufacturing process. The drive towards improvement as a whole was initiated by 'brainstorming' meetings with relevant employees. Communication and the establishment of clear aims is the key to any organisation being successful. After final consultations it was decided that the assembly stage should be the area for focus.

The project involved the application of a number of statistical techniques. In larger companies it is possible to combine such methods as part of a ‘longer term’, ‘Six Sigma’ quality programme. Smaller companies often do not have the resources to participate in such an improvement drive but they can still be shown the benefits of combining different types of methodology in order to enhance performance. A ‘Repeatability and Reproducibility study’, a designed experiment, control charts and flowcharts were all successfully utilised in this project. At completion it is extremely important that self-monitoring work ethics are instilled and the employees have the confidence to use the statistical tools themselves.

Correlation analysis is now been performed between a specific manufacturing stage and a key product testing area. This work evolved as a direct result of the project described in this paper.

Date received: November 14, 2001