Author:
Oprime Pedro Carlos,Mendes Glauco Henrique de Sousa
Abstract
Purpose
The purpose of this paper is to find the configuration of the number (m) and size (n) of the sample in Phase I that would make it possible to detect the out-of-control (OOC) state of the process with the smallest number of samples and ensure a capability index (Cpk) that would meet the customer’s requirements.
Design/methodology/approach
The suggested approach addresses this problem using simulation techniques and design of experiments (DOE). The simulation techniques made it possible to reproduce the normal operating conditions of the process. The DOE was used to construct a predictive model for control chart performance and thus to determine combinations of m and n in Phase I that would meet the capability objectives of the process. A numerical example and a simulation study were conducted to illustrate the proposed method.
Findings
Using simulation techniques and DOE, the authors can find the number (m) and size (n) of the sample in Phase I that would make it possible to detect the OOC state of the process with the smallest number of samples and ensure a Cpk that would meet the customer’s requirements.
Originality/value
In the real situations of many companies, choosing the numbers and sizes of samples (m and n) in Phases I and II is a crucial decision in relation to implementing a control chart. The paper shows that the simulation method and use of linear regression are effective alternatives because they are better known and more easily applied in industrial settings. Therefore, the need for alternatives to the X control chart comes into play.
Subject
Strategy and Management,General Business, Management and Accounting
Reference36 articles.
1. The design of a new repetitive sampling control chart based on process capability index;Transactions of the Institute of Measurement and Control,2015
2. On the generalized process capability under simple and mixture models;Journal of Applied Statistics,2014
3. Conditional double sampling;Journal of Quality Technology,1996
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