Acceptance sampling plan for multiple manufacturing lines using EWMA process capability index

The problem of developing a product acceptance determination procedure for multiple characteristics has attracted the quality assurance practitioners. Due to sufficient demands of consumers, it may not be possible to deliver the quantity ordered on time using the process based on one manufacturing l...

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Bibliographic Details
Main Authors: Osama H. ARIF., Muhammad ASLAM, Chi-Hyuck JUN
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2017-01-01
Series:Journal of Advanced Mechanical Design, Systems, and Manufacturing
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/jamdsm/11/1/11_2017jamdsm0004/_pdf/-char/en
Description
Summary:The problem of developing a product acceptance determination procedure for multiple characteristics has attracted the quality assurance practitioners. Due to sufficient demands of consumers, it may not be possible to deliver the quantity ordered on time using the process based on one manufacturing line. So, in factories, product is manufactured using multiple manufacturing lines and combine it. In this manuscript, we present the designing of an acceptance sampling plan for products from multiple independent manufacturing lines using exponentially weighted moving average (EWMA) statistic of the process capability index. The plan parameters such as the sample size and the acceptance number will be determined by satisfying both the producer's and the consumer's risks. The efficiency of the proposed plan will be discussed over the existing sampling plan. The tables are given for industrial use and explained with the help of industrial examples. We conclude that the use of the proposed plan in these industries minimizes the cost and time of inspection. Smaller the sample size means low inspection cost. The proposed plan for some non-normal distributions can be extended as a future research. The determination of sampling plan using cost model is also interested area for the future research.
ISSN:1881-3054