Abstract
ABSTRACTIn today’s competitive manufacturing environment, the challenge is to responsivelyproduce products with minimum cost and high quality. Achieving and controlling thetargeted quality level in manufacturing processes does not only increase customersatisfaction, but it can also result in significant cost and time savings. Further,measuring the process performance is a critical issue in process improvementinitiatives. The common practice in several industries is using the Univariate ProcessCapability Indices (UPCIs) to measure the process performance, which are based ononly a single quality characteristic. In most of the applications, it is not acceptable tojudge the performance based on a single quality characteristic as it actually relies onmore than one characteristic. In this paper, univariate and multivariate PCIs are usedto measure the performance of the flare making process. This process is a criticalstep in the straight fluorescent light bulb production line. In addition, multivariatecontrol charts such as the Hotelling as well as the Multivariate ExponentiallyWeighted Moving Average (MEWMA) are constructed for the collected data to verifythat the process is in control before assessing its capability. Besides, PrincipalComponent Analysis (PCA) and Joint Normal Distribution (JND) techniques areapplied in the multivariate process capability assessment. In this paper, MultivariateProcess Capability Indices (MPCIs) have been evaluated to compare the processperformance before and after improvement efforts. In the considered case study,MPCIs provide the user with an overall assessment of process capability regardlessof the fluctuations in the individual variables capabilities.
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