A tolerance allocation framework using fuzzy comprehensive evaluation and decision support processes
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Tolerances play an important role in product fabrication. Tolerances impact the needs of the designer and the manufacturer. Engineering designers are concerned with the impact of tolerances on the variation of the output, while manufacturers are more concerned with the cost of fitting the parts. Traditional tolerance control methods do not take into account both these needs. In this thesis, the author proposes a framework that overcomes the drawbacks of the traditional tolerance control methods, and reduces subjectivity via fuzzy set theory and decision support systems (DSS). Those factors that affect the manufacturing cost (geometry, material etc) of a part are fuzzy (i.e. subjective) in nature with no numerical measure. Fuzzy comprehensive evaluation (FCE) is utilized in this thesis as a method of quantifying the fuzzy (i.e. subjective) factors. In the FCE process, the weighted importance of each factor affects the manufacturing cost of the part. There is no systematic method of calculating the importance weights. This brings about a need for decision support in the evaluation of the weighted importance of each factor. The combination of FCE and DSS, in the form of Conjoint Analysis (CA), is used to reduce subjectivity in calculation of machining cost. Taguchi's quality loss function is considered in this framework to reduce the variation in the output. The application of the framework is demonstrated with three practical engineering applications. Tolerances are allocated for three assemblies; a friction clutch, an accumulator O-ring seal and a Power Generating Shock Absorber (PGSA) using the proposed framework. The output performances of the PGSA and the clutch are affected by the allocated tolerances. On using the proposed framework, there is seen to be a reduction in variation of output performance for the clutch and the PGSA. The use of CA is also validated by checking efficiency of final tolerance calculation with and without use of CA.