Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T20:36:38.314Z Has data issue: false hasContentIssue false

Average outgoing quality of calibration Labfacilities

Published online by Cambridge University Press:  06 March 2014

M. A. Al Reeshi
Affiliation:
METCAL, BAE Systems SA, P.O. Box 98, 31932 Dhahran, Saudi Arabia
Q. Yang*
Affiliation:
School of Engineering and Design, Brunel University, Uxbridge, Middlesex UB8 3PH, UK
*
Correspondence:[email protected]
Get access

Abstract

Quality assurance is an integrated part of any calibration facility. The calibrationfacility as well as its customers are interested in the facility production outgoingquality. In most calibration labs the inspection of calibrated items is performedaccording to a suitable sampling inspection policy. Some of these policies are very goodin assuring the quality of the calibration services they offer, but do not provide a clearassessment of the outgoing quality of the entire production of the facility. This paperhas developed two methods of calculating the average outgoing quality (AOQ) of acalibration lab that uses a multistage sampling inspection policy. The policy structure ispresented first along with the exact procedure of how to perform it by the inspectors andthe methods to calculate the AOQ. The two methods differ from each another in the type ofdata required to calculate the AOQ. The first method requires the technicians’ production,the number of items subject to inspections and the number of failing items found. Thesecond method requires only the number of technicians at each level of the multistageinspection policy. The verifications of the performances of two methods are accomplishedby building a simulation model on an Excel worksheet. The model simulates the calibrationfacility with the right parameters, and then compares the two methods with the actual AOQ.The paper further discusses the advantages and disadvantages of each method in a broadercontext of quality assurance.

Type
Research Article
Copyright
© EDP Sciences 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

E.B. Jamkhaneh, B.S. Gildeh, AOQ and ATI for double sampling plan with using fuzzy binomial distribution,Proc. of the 2010 International Conference on Intelligent Computing and Cognitive Informatics, pp. 45–49
Farnum, N.R., Closed-form approximation for the AOQL of attributes acceptance sample plans, Commun. Stat. Simulation Comput. 35, 10571065 (2006) CrossRefGoogle Scholar
Balamurali, S., Jun, C.H., Average outgoing quality of CSP-C continuous sampling plan under short run production processes, J. Appl. Stat. 33, 139154 (2006) CrossRefGoogle Scholar
Yu, H.F., Yu, W.C., An optimal mixed policy of inspection and burn-in and the optimal production quantity, Int. J. Prod. Econ. 105, 483491 (2007) CrossRefGoogle Scholar
Yang, G.L., A renewal-process approach to continuous sampling plans, Technometrics 25, 5967 (1983) CrossRefGoogle Scholar
Yang, G.L., A renewal look at switching rules in the MIL-STD-105D sampling system, J. Appl. Probab. 27, 183192 (1990) CrossRefGoogle Scholar
H.C. Yeh, H.T. Tsai, M.C. Yu, Design of one-sided screening specifications for multi-characteristic product, First International Conference on Innovative Computing, Information and Control (ICICIC’06) (2006), Vol. 2, pp. 482–485
Moskowitz, H., Tsai, H.T., A one-sided double screening procedure using individual unit misclassification error, Manag. Sci. 34, 11391153 (1988) CrossRefGoogle Scholar
Fard, N.S., Kim, J.J., Analysis of two stage sampling plan with imperfect inspection, Comput. Ind. Eng. 25, 453456 (1993) CrossRefGoogle Scholar
ISO 2859-10, Sampling procedure for inspection by attribute (2006)