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A new global nonlinear optimization technique called Pattern search algorithm has been executed to figure the optimal tolerance allocation and asymmetric total cost to overcome the defects in the traditional tolerance allocation problem.
Additionally, we have found empirically that the optimal tolerance is SNR dependent.
By solving the formulated mathematical models, the optimal tolerance allocation can be generated.
Such a nonlinear multivariate optimal tolerance design problem results in a non-convex combinatorial solution surface.
This study deals with the optimal tolerance design for an assembly simultaneously considering manufacturing cost and quality loss.
Optimal tolerance design aims at assigning tolerances such that the functionality requirements are achieved with minimum cost.
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Optimal tolerances are then determined using a non-linear constrained optimization algorithm that minimizes the manufacturing cost while satisfying constraints on the variation of the coupled position and orientation.
This paper witnesses an application of process tolerancing which proves to be a better way of finding the optimal tolerancing of the part, leading to fewer process rejections and improved quality levels.
An improved Taguchi method is applied to determine the optimal tolerances for individual components so that the total assembly cost is minimized while satisfying the accuracy requirements of the mechanism.
This assumption might not be realistic, leading to the assign of non-optimal tolerances.
Non-optimal tolerances yield potentials for cost improvements in manufacturing and more consistency of the functional performance of the product.
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CEO of Professional Science Editing for Scientists @ prosciediting.com