Proposed Space-Time Multivariate Capability Indices applied to Manufacturing Processes
Subject Areas : Multivariate Analysis
Rister Barreto Pombo
1
,
Roberto Jose Herrera Acosta
2
1 - Department of Statistics, University of the Atlantic, Atlantic, Colombia
2 - Department of Statistics, University of the Atlantic, Atlantic, Colombia
Keywords: LED technology, Multivariate Capability Analysis, Process Capability, Product Reliability, Quality,
Abstract :
This paper proposes two methods of evaluating the Space and Time Characteristics of the product within the Process Capability Analysis framework with the introduction of two Multivariate Capability Indices that incorporate the product lifetime estimation based on accelerated Time to Failure data. The measures proposed were applied to the manufacturing process of LED luminaires to provide a numerical example for the proposed methodology. Light-Emitting-Diode technology has been increasingly adopted by end-users over the past few decades because of its durability and efficacy, which result in low cost of ownership and higher energy savings. However, the research on LED technology reliability and expected lifetime has been limited due to the development of robust failure mechanism for this product. The results indicate that the integration of both technical specification compliance and product reliability into a global index can be beneficial for manufacturing process assessment since it provides a new insight into process capability. The product reliability dimension of the product supports decision-making and process optimization, which subsequently increases customer satisfaction
.
Morgan Pattison, P., Hansen, M. and Tsao, J. (2018). LED lighting Efficacy: Status and directions. Comptes Rendus Physique 19(2018), 134-145. DOI: https://doi.org/10.1016/j.crhy.2017.10.013.
Fan, J., Yung, K., and Pecht, M. (2012). Lifetime Estimation of High-Power White LED Using Degradation-Data-Driven Method. IEEE Transactions on Device and Materials Reliability 12(2), 470 – 477.
Chen, K. S., Luang, M. L. and Yung, H. (2008) Process Capability Analysis Chart with the Application of C_pm. International Journal of Production Research. DOI: 10.1080/00207540600806422.
Zainab, G., and Bahran, G. (2017). A new multivariate process capability index. Total Quality Management and Business Excellence. DOI: http://dx.doi.org/10.1080/14783363.2017.1315936.
Taam W., Subbaiah, P., and Liddy, J. (1993). A note on multivariate capability indices. Journal of Applied Statistics 20(3), 339 – 351. DOI: http://dx.doi.org/10.1080/02664769300000035.
De-Felipe, D., and Benedito, E. (2017). A Review of univariate and multivariate process capability indices. International Journal of Advanced Manufacturing Technology. DOI: 10.1007/s00170-017-0273-6.
Murthy, D. (2007). Product reliability and warranty: an overview and future research. Produção 17(3), 426 – 434.
Wang, F. K., and Chu, T. (2012). Lifetime predictions of LED-based light bars by accelerated degradation test. Microelectronics Reliability 52(2012), 1332 – 1336.
Taha, T. (2015). On Reliability Estimation for the Rayleigh Distribution Based on Monte Carlo Simulation. International Journal of Science and Research. DOI: 10.21275/ART20176044.
Wang, F. K., and Chen, J. (1998). Capability Index Using Principal Components Analysis. Quality Engineering 11(1): 21- 27. DOI: 10.1080/08982119808919208.
Tsai, C., and Chen, C. (2006). Making decision to evaluate process capability index C_p with fuzzy numbers. International Journal of Advance Manufacturing Technology 30(3-4), 334 – 339. DOI: 10.1007/s00170-005-0052-7.
