Research Article
Confidence Interval for Multivariate Process Capability indices in Statistical Inventory Control
@INPROCEEDINGS{10.4108/eai.2-8-2019.2290488, author={Mustafid Mustafid and Dwi Ispriyanti and Sugito Sugito and Diah Safitri}, title={Confidence Interval for Multivariate Process Capability indices in Statistical Inventory Control}, proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia}, publisher={EAI}, proceedings_a={ICSA}, year={2020}, month={1}, keywords={confidence interval inventory control multivariate capability indices}, doi={10.4108/eai.2-8-2019.2290488} }- Mustafid Mustafid
Dwi Ispriyanti
Sugito Sugito
Diah Safitri
Year: 2020
Confidence Interval for Multivariate Process Capability indices in Statistical Inventory Control
ICSA
EAI
DOI: 10.4108/eai.2-8-2019.2290488
Abstract
Multivariate process capability indices (MPCI) has important role in the analysis of statistical inventory control determined by several consumer demand as quality characteristics that are correlated. In the inventory control management is also needed confidence interval for MPCI to overcome the uncertain from consumer demand. The research aims to apply the confidence interval for MPCI in statistical inventory control. The case studies conducted on the apparel industry to implement the confidence interval for the MPCI using several types of apparel which is used as the quality characteristics. The upper and lower limits for the intervals from the MPCI are obtained using sample data assuming multivariate normal distribution and stable. Process sample data in stable conditions are obtained by using analysis of multivariate control diagram designed by T2 Hotelling. The MPCI confidence interval can be used as the indicator in determining the number of products provided in inventory based on the number of consumer demand.