Use this URL to cite or link to this record in EThOS:
Title: An empirical investigation into the effectiveness of statistical process control techniques, with management data from a product development environment
Author: Julien, Denyse
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 1998
Availability of Full Text:
Access through EThOS:
Access through Institution:
The study reported on in this thesis was an empirical investigation into the implementation and use of, Statistical Process Control (SPC) techniques and tools in a product development environment. The data used originated from four different business units in the European flavour division of a large International company, belonging to the Flavour and Fragrance industry. The study highlights many of the problems related to the use of real data, and working with individuals throughout an organisation. The data distributions were positively skewed, and a comparison of the effectiveness of various methods for calculating the position of both the center line and the process control limits, on individual measurements control charts was made. The author was able to show empirically that SPC is a useful project management tool. Additionally, the author demonstrated that the use of either the median or trimmed mean approaches, were more effective in use when dealing with these types of skewed data distributions. Additionally, it was possible to define the relationship between the numbers of outside out-of-control signals and the numbers of run out-of-control signals. The study also provided some interesting insights into possible barriers to the transfer of the techniques, from the manufacturing floor into more traditional management areas. It also highlighted some areas for improvement in the product development laboratories of the company and potentially the industry.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TS Manufactures Management Mathematical statistics Operations research