Comparing the economic effectiveness of various adaptive schemes for the c chart

Quality and Reliability Engineering International

Volumn 30, Issue 5, 2014, Pages 723-743

  Lupo, Toni ^a  

^a UNIVERSITY OF PALERMO   (Italy)

Author keywords

control chart for attributes; labor resource; non linear mathematical programming model; statistical process control; Taguchi's loss function

Indexed keywords

FLOWCHARTING; MATHEMATICAL PROGRAMMING; STATISTICAL PROCESS CONTROL;

ADAPTIVE SAMPLING INTERVAL; CONTROL CHARTS; ECONOMIC EFFECTIVENESS; FRACTIONAL FACTORIAL DESIGNS; LABOR RESOURCES; NON-LINEAR MATHEMATICAL PROGRAMMING MODEL; STATISTICAL PROCESS CONTROLS (SPC); TAGUCHI'S LOSS FUNCTION;

ECONOMIC AND SOCIAL EFFECTS;

EID: 84905127283     PISSN: 07488017     EISSN: 10991638     Source Type: Journal    
DOI: 10.1002/qre.1524     Document Type: Article

References (21)

1. Tagaras G,. A survey of recent developments in the design of adaptive control charts. Journal of Quality Technology 1998; 30 (3): 212-231.
2. Woodall WH, Montgomery DC,. Research issues and ideas in statistical process control. Journal of Quality Technology 1999; 31 (4): 376-386
3. Zimmer LS, Montgomery DC, Runger GC,. Guidelines for the application of adaptive control charting schemes. International Journal of Production Research 2000; 38 (9): 1977-1992.
4. Sim SB, Xie M,. On variable sample size X chart for processes with double assignable causes. Quality and Reliability Engineering International 2004, 11: 47-58.
5. Bai, DS, Lee, KT, Variable sampling interval X control charts with an improved switching rule. International Journal of Production Economics 2002; 76 (2): 189-199. doi: 10.1016/S0925-5273(01)00161-X
6. Costa AFB, De Magalhães MS,. An adaptive chart for monitoring the process mean and variance. Quality and Reliability Engineering International 2007; 23 (7): 821-831. doi: 10.1002/qre.842.
7. Zou CA, Wang ZA, Tsung FB,. Monitoring autocorrelated processes using variable sampling schemes at fixed-times. Quality and Reliability Engineering International 2008; 24 (1): 55-59.
8. Nenes G,. A new approach for the economic design of fully adaptive control charts. International Journal of Production Economics 2011; 131 (2): 631-642.
9. Mortarino, C,. Duncan's model for X-bar control charts: sensitivity analysis to input parameters. Quality and Reliability Engineering International 2010; 26 (1): 7-26.
10. Costa, AFB, Magalhães, MSD,. Economic design of two-stage X charts: The Markov chain approach International Journal of Production Economics 2005; 95 (1): 9-20. doi: 10.1016/j.ijpe.2003.10.024.
11. - Control Charts. Operations Research 2002; 50 (5): 878-888.
12. Chan LY, Xie M, Goh TN,. Cumulative quantity control charts for monitoring production processes. International Journal of Production Research 2000; 38 (2): 397-408.
13. Epprecht EK, Costa AFB,. Adaptive sample size control charts for attributes. Quality Engineering 2001; 13 (3): 465-473.
14. Wu Z, Luo W,. Optimal Design of the Adaptive Sample Size and Sampling Interval np Control Chart. Quality and Reliability Engineering International 2004; 20: 553-570.
15. Luo H, Zhang W,. Optimal np Control Charts with Variable Sample Sizes or Variable Sampling Intervals. Economic Quality Control 2002; 17 (1): 39-61.
16. Khoo MBC,. Poisson Moving Average Versus c Chart for Nonconformities. Quality Engineering 2004; 16 (4): 525-534.
17. Lupo T,. Economic design approach for a SPC inspection procedure implementing the adaptive c chart. Quality and Reliability Engineering International 2013; accepted for the publication. DOI: 10.1002/qre.1507.
18. Baxley, RV Jr., An Application of Variable Sampling Interval Control Chart. Journal of Quality Technology 1995; 27: 275-282.
19. Duncan AJ,. The economic design of X chart used to maintain current control of a process. Journal of the American Statistical Association 1956; 51: 228-242.
20. Lorenzen TJ, Vance LC,. The economic design of control charts: a unified approach. Technometrics 1986; 28 (1): 3-10.
21. Wu Z, Shamsuzzaman M, Pan ES,. Optimization design of control charts based on Taguchi's loss function and random process shifts. International Journal of Production Research 2004; 42 (2): 379-390.