Matrix-based tolerance analysis for multi-component selective assembly with geometric and dimensional features using genetic algorithm
A.K. Jeevanantham,
S.V. Chaitanya and
Rajeshkannan Ananthanarayanan
International Journal of Productivity and Quality Management, 2020, vol. 30, issue 4, 527-560
Abstract:
Tolerance analysis (TA) is a method of investigating how the geometric and dimensional tolerance (GDT) deviations in each component propagate and affect the functional requirements of the product. Total deviation in an assembly fit can be controlled by selecting the components of the assembly through a purposeful strategy, called selective assembly (SA). In this paper, the matrix model of TA is applied in SA. The surface-based and shape closure analyses are done using the principles of TTRS and MGDE, and the assembly fit is modelled in terms of displacement matrices. The conventional method of dividing the components into groups only by the deviation on dimensional tolerance (DT) alone is replaced by integrated GDT. The effect of rotational displacements in component features on assembly fit is verified. A two-dimensional, worst case, rigid TA in SA is demonstrated. The best combinations of assembly components are obtained through genetic algorithm.
Keywords: selective assembly; tolerance analysis; matrix model; clearance variation; genetic algorithm. (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:30:y:2020:i:4:p:527-560
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