Process mean, process tolerance, and use time determination for product life application under deteriorating process

Robust design can significantly improve a producer’s competitive ability to deliver high-quality products with low development cycle time, quality loss, failure cost, and tolerance cost. However, during usage by a consumer, the functional performance of a product or some of its components may change as use time passes, leading to unexpected product failure that is usually costly in both time and money. The cost of these failures may influence the determination of optimal use time and optimal initial settings as compensation for the possible process mean changes during consumer usage. In addition to finding use time and initial settings for proper quality performance, the determination of process mean and tolerance also needs to be considered. As is known, changes in process means acquired quality loss and variability, while process tolerance has an effect on tolerance-related costs and quality loss. Because there exists a dependency among use time, initial setting of process mean, process mean, and process tolerance, these values must be determined simultaneously. Thus, in this paper, an optimization model with an acceptable reliability value is developed to minimize total cost, including quality loss, failure cost, and tolerance cost, by determining optimal use time, initial settings, process mean, and process tolerance, simultaneously. Applications of single and multiple components are presented to explain the proposed models. Finally, sensitivity analysis and model discussions on some decision variables are performed.

[1]  S. A. Irani,et al.  Tolerance chart optimization , 1989 .

[2]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[3]  Bryan Kok Ann Ngoi,et al.  A matrix approach to tolerance charting , 1993 .

[4]  Hans-Joachim Mittag,et al.  Statistical Methods of Quality Assurance , 1993 .

[5]  Madhan Shridhar Phadke,et al.  Quality Engineering Using Robust Design , 1989 .

[6]  Angus Jeang,et al.  A computer model for time-based tolerance design with response surface methodology , 2002, Int. J. Comput. Integr. Manuf..

[7]  G. O. Wesolowsky,et al.  Optimal Control of a Linear Trend Process with Quadratic Loss , 1989 .

[8]  Hong-Chao Zhang,et al.  Tolerancing techniques: the state-of-the-art , 1992 .

[9]  A. K. Sheikh Optimal tool replacement and resetting strategies in automated manufacturing systems , 1999 .

[10]  Bryan Kok Ann Ngoi Applying linear programming to tolerance chart balancing , 1992 .

[11]  John H. Sheesley,et al.  Quality Engineering in Production Systems , 1988 .

[12]  M. A. Rahim,et al.  Optimal control of a deteriorating process with a quadratic loss function , 2001 .

[13]  M. A. Rahim,et al.  Integrated model for determining the optimal initial settings of the process mean and the optimal production run assuming quadratic loss functions , 2004 .

[14]  Angus Jeang,et al.  Optimal tool replacement with nondecreasing tool wear , 1992 .

[15]  R. N. Kackar Off-Line Quality Control, Parameter Design, and the Taguchi Method , 1985 .

[16]  Bryan Kok Ann Ngoi,et al.  A complete tolerance charting system , 1993 .

[17]  Angus Jeang,et al.  Combined parameter and tolerance design optimization with quality and cost , 2001 .

[18]  Bryan Kok Ann Ngoi,et al.  Optimum assembly using a component dimensioning method , 1996 .

[19]  L. F. Hauglund,et al.  Least Cost Tolerance Allocation for Mechanical Assemblies with Automated Process Selection , 1990 .

[20]  Samuel Kotz,et al.  Process Capability Indices , 1993 .

[21]  Toly Chen,et al.  Simultaneous process mean and process tolerance determination with adjustment and compensation for precision manufacturing process , 2007 .

[22]  Angus Jeang,et al.  Simultaneous process mean and process tolerance determination with asymmetrical loss function , 2006 .

[23]  Angus Jeang Tolerance chart balancing for machining process planning , 1996 .