Abstract
The paper presents a simple approximation technique for statistical tolerance analysis, namely, the allocation of component tolerances based on a known assembly tolerance. The technique utilizes a discretized, multivariate kernel density estimate and a simple transformation to approximate the probability distribution of the overall assembly characteristic. The data-driven approach is suitable for real-world settings in which components are randomly selected from their respective manufacturing processes to form mechanical assemblies. Demonstrated is the numerical approach in two dimensions for two distinct cases: first, when component characteristics are non-normal, independent random variables, and second, when they are highly correlated, normal random variables. The results are promising in initial test problems.
Original language | English (US) |
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Pages (from-to) | 337-352 |
Number of pages | 16 |
Journal | International Journal of Production Research |
Volume | 40 |
Issue number | 2 |
DOIs | |
State | Published - 2002 |
All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering