A Quality-Based Business Model for Determining Non-product Investment: A Case Study From a Ford Automotive Engine Plant

Abstract: This article presents an innovative approach for determining non-product investment in the maintenance of manufacturing facilities using quality-based statistical principles. Degradation of process capability (Cpk) over time with respect to key part specifications is analyzed using a regression model to predict the need for investment. While the preferred approach is to track process capability at all stations in a production line, this becomes prohibitively expensive and impractical in many industries, including engine manufacturing plants. By modeling the trend in Cpk values from only the end of the production line, using subject matter experts (SMEs) when necessary, one can still identify production stations/areas of weakness in a manufacturing facility with reasonable effectiveness. We propose such a method to help plant managers prioritize their limited maintenance resources. The methodology is validated using a case study from an automotive engine plant of Ford Motor Company. It is being disseminated as a “best practice” to other manufacturing facilities at Ford.

[1]  P. Baruah,et al.  HMMs for diagnostics and prognostics in machining processes , 2005 .

[2]  Anthony M. Smith,et al.  Reliability-Centered Maintenance , 1992 .

[3]  Donald R. Falkenburg,et al.  An Industry-Based Engineering Management Master's Program for the Working Engineer , 1998 .

[4]  Balbir S. Dhillon,et al.  Engineering Maintenance: A Modern Approach , 2002 .

[5]  Ronald D. Fricker.  Statistical Process Control and Quality Improvement , 2000, Technometrics.

[6]  F Segues Echazarreta.  APPLICATION OF MATHEMATICAL MODELS , 1993 .

[7]  Fred Spiring,et al.  Introduction to Statistical Quality Control , 2007, Technometrics.

[8]  Andre Kleyner,et al.  A warranty forecasting model based on piecewise statistical distributions and stochastic simulation , 2005, Reliab. Eng. Syst. Saf..

[9]  F. Camci,et al.  Dynamic Bayesian networks for machine diagnostics: hierarchical hidden Markov models vs. competitive learning , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[10]  John Crocker,et al.  Age-related maintenance versus reliability centred maintenance: a case study on aero-engines , 2000, Reliab. Eng. Syst. Saf..

[11]  Rommert Dekker,et al.  Applications of maintenance optimization models : a review and analysis , 1996 .

[12]  Philip A. Scarf,et al.  On the application of mathematical models in maintenance , 1997 .

[13]  Matthias Mayer,et al.  Improving manufacturing costs and lead times with quality-oriented operating curves , 2001 .

[14]  Julian D Booker,et al.  Designing Capable and Reliable Products , 2001 .

[15]  L. D. Boer,et al.  A conceptual model for assessing the impact of electronic procurement , 2002 .