本研究主要目的是應用Wang [16] 所提出的製程良率指標 評估當一製程之資料呈現非線性剖面情況時之點估計及其區間估計，提供一製程品質，使廠商與顧客間有一可靠的數據可以參考，在藥物反應的模擬結果發現，各種模擬情況之下，估計值與實際值皆相當的接近，且有著很小的標準差。
因此在非線性剖面資料， 製程良率指標提供了相當準確的衡量績效，而本研究在最後也提供了一塑合板密度的實際案例資料的評估結果以供參考。

The main purpose of this paper is to apply the process yield index SpkA proposed by Wang [16] for nonlinear profiles. It evaluates the point estimated and its interval estimated when the process of one system is non-linear profile case. Besides, the process yield index SpkA provide system process quality so that customers and suppliers can refer to those reliable data. From the simulation results of the drug reactions, the estimated value and the actual value are quite close and have a small standard deviation.
Therefore, the process yield index SpkA provide a fairly accurate measure performance in the non-linear profile data. Moreover, the paper also provides an actual case data about a particle board density for reference.

[1] Bothe D.R., “A capability index for multiple process streams,” Quality Engineering, 11(4), 613-618 (1999).
[2] Boyles, R.A., “Process capability with asymmetric tolerances,” Communications in Statistics-Simulation and Computation, 23(3), 615-635 (1994).
[3] Castagliola, P., “Evaluation of non-normal process capability indices using Burr’s distributions,” Quality Engineering, 8(4), 587-593 (1996).
[4] Clements, J.A., “Process capability calculations for non-normal distributions,” Quality Progress, 22(9), 95-100 (1989).
[5] Ebadi, M. and H. Shahriari, “A process capability index for simple linear profile,” International Journal of Advanced Manufacturing Technology, 64(5-8), 857-865 (2013).
[6] Hosseinifard, S.Z. and B. Abbasi, “Evaluation of process capability indices of linear profiles,” International Journal of Quality & Reliability Management, 29(2), 162-176 (2012).
[7] Hosseinifard, S.Z. and B. Abbasi, “Process capability analysis in non normal linear regression profiles,” Communications in Statistics-Simulation and Computation, 41(10), 1761-1784 (2012).
[8] Kane, V.E., “Process capability indices,” Journal of Quality Technology, 18(1) 41-52 (1986).
[9] Kang, L. and S.L. Albin, “On-line monitoring when the process yield a linear profile,” Journal of Quality Technology, 32(4), 418-426 (2000).
[10] Kunter, M.H., C.J. Nachtsheim, and W. Li, “Applied linear statistical models,” McGraw-Hill, Boston, (2005).
[11] Lee, J.C., H.N. Hung, W.L. Pearn, and T.L. Kueng, “On the distribution of the estimated process yield index Spk,” Quality and Reliability Engineering International, 18(2), 111-116 (2002).
[12] Pearn, W.L. and K.S. Chen, “New generalizations of process capability index Cpk,” Journal of Applied Statistics, 25(6), 801-810 (1998).
[13] R Development Core Team, “R: A language and environment for statistical computing,” Vienna, Austria: R foundation for statistical computing, (2013).
[14] Somerville, S.E. and D.C. Montgomery, “Process capability indices and non-normal distributions,” Quality Engineering, 9(2), 305-316 (1996).
[15] Shahriari, H. and M. Sarrafian, “Assessment of process capability in linear profiles,” Proceedings of the 6th International Industrial Engineering Conference, Tehran, Iran (in Farsi), (2009).
[16] Wang, F.K., “Process yield for simple linear profiles,” working paper, (2013).
[17] Williams, J.D., J.B. Birch, W.H. Woodall, and N.M. Ferry, “Statistical monitoring of heteroscedastic dose-response profiles from high-throughput screening,” Journal of Agricultural, Biological, and Environmental Statistics, 12(2), 216-235 (2007).
[18] Williams, J.D., W.H. Woodall, and J.B. Birch, “Statistical monitoring of nonlinear product and process quality profiles,” Quality and Reliability Engineering International, 23(8), 925-941 (2007).
[19] Woodall, W.H., “Current research on profile monitoring,” Produção, 17(3), 420-425 (2007).