Developing A New Variables Sampling Scheme for Product Acceptance Determination

Chien-Wei Wu, James C. Chen

2012

Abstract

Acceptance sampling is a useful tool for determining whether submitted lots should be accepted or rejected. With the current increase in outsourcing production processes and the high quality levels required, it is very desirable to have an efficient and economic sampling scheme. This paper develops a variables repetitive group sampling (RGS) plan based on the third generation of process capability index. The plan parameters are determined by minimizing the average sample number (ASN) for inspection and fulfilling the classical two-point-condition on the operating characteristic (OC) curve. Besides, the efficiency of the proposed plan is investigated and compared with the existing variables single sampling plan. Tables of the plan parameters are also provided.

References

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Paper Citation


in Harvard Style

Wu C. and Chen J. (2012). Developing A New Variables Sampling Scheme for Product Acceptance Determination . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: OMDM, (ICINCO 2012) ISBN 978-989-8565-22-8, pages 589-593. DOI: 10.5220/0003972505890593


in Bibtex Style

@conference{omdm12,
author={Chien-Wei Wu and James C. Chen},
title={Developing A New Variables Sampling Scheme for Product Acceptance Determination},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: OMDM, (ICINCO 2012)},
year={2012},
pages={589-593},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003972505890593},
isbn={978-989-8565-22-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 2: OMDM, (ICINCO 2012)
TI - Developing A New Variables Sampling Scheme for Product Acceptance Determination
SN - 978-989-8565-22-8
AU - Wu C.
AU - Chen J.
PY - 2012
SP - 589
EP - 593
DO - 10.5220/0003972505890593