Setup adjustment for discrete-part manufacturing processes with asymmetric cost functions

References

• Anbar , D . 1977 . A modified Robbins–Monro procedure approximating the zero of a regression function from below . Ann. Stat. , 5 : 229 – 234 .
   Google Scholar
• Bazaara MS Sherali HD Shetty CM Nonlinear Programming: Theory and Algorithms 2nd ed. 1993 Wiley New York
   Google Scholar
• Box , GEP and Luceño , A . 1995 . Discrete proportional-integral control with constrained adjustment . Statistician , 44 : 479 – 495 .
   Google Scholar
• Box GEP Luceño A Statistical Control by Monitoring and Feedback Adjustment 1997 Wiley New York
   Google Scholar
• Del Castillo , E . 2001 . Some properties of EWMA feedback quality adjustment schemes for drifting disturbances . J. Qual. Tech. , 33 : 153 – 166 .
   Web of Science ®Google Scholar
• Del Castillo , E , Pan , R and Colosimo , BM . 2003a . A unifying view of some process adjustment methods . J. Qual. Tech. , 35 : 286 – 293 .
   Web of Science ®Google Scholar
• Del Castillo , E , Pan , R and Colosimo , BM . 2003b . Small sample performance of some statistical adjustment methods . Comm. Stat. Simul. Comput. , 32 : 923 – 942 .
   Web of Science ®Google Scholar
• Grubbs FE An optimum procedure for setting machines or adjusting processes Industrial Quality Control 1954 (reprinted in Journal of Quality Technology 1983, 15, 186–189)
   Google Scholar
• Guo RS Chen A Chen JJ An enhanced EWMA controller for processes subject to random disturbances Run to Run Control in Semiconductor Manufacturing edited by J. Moyne, E. Del Castillo and A. Hurwitz, chapter 19 2001 CRC Press Boca Raton FL
   Google Scholar
• Gyrna FM Juran JM Quality Planning and Analysis 4th ed. 2000 McGraw-Hill New York
   Google Scholar
• Harris , TJ . 1992 . Optimal controllers for nonsymmetric and nonquadratic loss functions . Technometrics , 34 : 298 – 306 .
   Web of Science ®Google Scholar
• Kalman , RE . 1960 . A new approach to linear filtering and prediction problems . Trans. ASME J. Basic Eng. , 82 : 35 – 45 .
   Google Scholar
• Krasulina , TP . 1998 . On the probability of not exceeding a desired threshold by a stochastic approximation algorithm . Automat. Rem. Cont. , 59 : 1424 – 1427 .
   Google Scholar
• Ladany SP Optimal set-up of a manufacturing process with unequal revenue from oversized and undersized items IEEE 1995 Engineering Management Conference. 1995 pp. 428–432
   Google Scholar
• Maghsoodloo , S and Li , MC . 2000 . Optimal asymmetric tolerance design . IIE Transactions , 32 : 1127 – 1137 .
   Web of Science ®Google Scholar
• Misiorek , VI and Barnett , NS . 2000 . Mean selection for filling processes under weights and measurement requirements . J. Qual. Tech. , 32 : 111 – 121 .
   Web of Science ®Google Scholar
• Moorhead , PR and Wu , CFJ . 1998 . Cost-driven parameter design . Technometrics , 40 : 111 – 119 .
   Web of Science ®Google Scholar
• Moyne J Del Castillo E Hurwitz A editors Run to Run Process Control for Semiconductor Manufacturing 2000 CRC Press Boca Raton FL
   Google Scholar
• Nembhard , H and Birge , J . 1998 . A startup procedure for process industries using a multiple objective nonlinear program . IIE Trans. , 30 : 291 – 300 .
   Web of Science ®Google Scholar
• Pan R Statistical process adjustment methods for quality control in short-run manufacturing PhD dissertation Department of Industrial and Manufacturing Engineering, The Pennsylvania State University 2002
   Google Scholar
• Pan R Del Castill E Scheduling methods for the setup adjustment problem Int. J. Prod. Res. 2003 41 1467 1481 (correction, 2004, 42, 211–212)
   Web of Science ®Google Scholar
• Robbins , H and Monro , S . 1951 . A stochastic approximation method . Ann. Math. Stat. , 22 : 400 – 407 .
   Google Scholar
• Sullo O Vandeven M Optimal adjustment strategies for a process with run-to-run variation, Part II: Quadratic loss Technical report No. 37-96-447 Department of Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute 1996
   Google Scholar
• Sullo , O and Vandeven , M . 1999 . Optimal adjustment strategies for a process with run-to-run variation and 0–1 quality loss . IIE Trans. , 31 : 1135 – 1146 .
   Web of Science ®Google Scholar
• Taguchi G Elsayed EA Hsiang T Quality Engineering in Production Systems 1989 McGraw-Hill New York
   Google Scholar
• Trietsch , D . 1998 . The harmonic rule for process setup adjustment with quadratic loss . J. Qual. Tech. , 30 : 75 – 84 .
   Web of Science ®Google Scholar
• Vaughan TS An alternative framework for short-run SPC Prod. Invent. Manage. J. 1994 48 52
   Google Scholar
• Wu , CC and Tang , GR . 1998 . Tolerance design for products with asymmetric quality losses . Int. J. Prod. Res. , 36 : 2592 – 2541 .
   Google Scholar
• Wurl , RC , Albin , SL and Shiffer , IJ . 2001 . Multivariate monitoring of batch process startup . Qual. Reliab. Eng. Int. , 17 : 269 – 278 .
   Web of Science ®Google Scholar
• Xu , D and Albin , SL . 2002 . Manufacturing start-up problem solved by mixed-integer quadratic programming and multivariate statistical modelling . Int. J. Prod. Res. , 40 : 625 – 640 .
   Web of Science ®Google Scholar