Next Article in Journal
A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm
Previous Article in Journal
Approximation Algorithms for the Geometric Firefighter and Budget Fence Problems
Article Menu

Export Article

Open AccessArticle
Algorithms 2018, 11(4), 46; https://doi.org/10.3390/a11040046

Short-Run Contexts and Imperfect Testing for Continuous Sampling Plans

Department of Statistics, University of California, Riverside, CA 92521, USA
*
Author to whom correspondence should be addressed.
Received: 8 February 2018 / Revised: 5 April 2018 / Accepted: 7 April 2018 / Published: 12 April 2018
View Full-Text   |   Download PDF [11169 KB, uploaded 3 May 2018]   |  

Abstract

Continuous sampling plans are used to ensure a high level of quality for items produced in long-run contexts. The basic idea of these plans is to alternate between 100% inspection and a reduced rate of inspection frequency. Any inspected item that is found to be defective is replaced with a non-defective item. Because not all items are inspected, some defective items will escape to the customer. Analytical formulas have been developed that measure both the customer perceived quality and also the level of inspection effort. The analysis of continuous sampling plans does not apply to short-run contexts, where only a finite-size batch of items is to be produced. In this paper, a simulation algorithm is designed and implemented to analyze the customer perceived quality and the level of inspection effort for short-run contexts. A parameter representing the effectiveness of the test used during inspection is introduced to the analysis, and an analytical approximation is discussed. An application of the simulation algorithm that helped answer questions for the U.S. Navy is discussed. View Full-Text
Keywords: CSP-1; sampling plan; harold dodge; simulation algorithm; imperfect testing; short-run contexts CSP-1; sampling plan; harold dodge; simulation algorithm; imperfect testing; short-run contexts
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Rodriguez, M.; Jeske, D.R. Short-Run Contexts and Imperfect Testing for Continuous Sampling Plans. Algorithms 2018, 11, 46.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top