Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia

Research Article

Confidence Interval for Multivariate Process Capability indices in Statistical Inventory Control

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  • @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
Mustafid Mustafid1,*, Dwi Ispriyanti1, Sugito Sugito1, Diah Safitri1
  • 1: Department of Statistics, Diponegoro University, Semarang, 50275, Indonesia
*Contact email: mustafid55@gmail.com

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.