z-logo
Premium
Economic Models for Single Sample Acceptance Sampling Plans, No Inspection, and 100 Percent Inspection
Author(s) -
Fink Ross L.,
Margavio Thomas M.
Publication year - 1994
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1994.tb00824.x
Subject(s) - acceptance sampling , sample (material) , sampling (signal processing) , computer science , econometrics , statistics , operations management , business , operations research , sample size determination , mathematics , economics , chemistry , filter (signal processing) , chromatography , computer vision
Once a process is stabilized using control charts, it is necessary to determine whether this process is capable of producing die desired quality, as determined by the specifications, without the use of some additional inspection procedure such as 100 percent inspection or acceptance sampling. One common method of making this determination is the use of process capability ratios. However, this approach may lead to erroneous decisions due to the omission of economic information. This paper attempts to remedy this situation by developing economic models to examine the profitability of different inspection policies. These models employ the quadratic loss function to represent the economic cost of quality from external failures, which is commonly omitted or overlooked. Moreover, assuming a normal distribution for the quality characteristic allows the use of simplified formulas that are provided. Thus the calculations can be made using standard normal tables and a calculator. Additionally, these economic models may be used to determine if additional inspection procedures should be reinstated if the quality of the process was to decline, to make capital budgeting decisions involving new equipment that produces parts of a higher quality, and to determine the preferred 100 percent inspection plan or acceptance sampling plan.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here