- Title
- Performance evaluation of multivariate non-normal process using metaheuristic approaches
- Creator
- Ahmad, S.; Abdollahian, Mali; Bhatti, M.I.; Huda, Shamsul; Yearwood, John
- Date
- 2014
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/35649
- Identifier
- vital:6150
- Identifier
- ISSN:1067-5817
- Abstract
- Multivariate process performance indices generally rely on the assumption that the process follow normal distribution but in practice its non-normal with correlated characteristics patterns. This paper proposes two metaheuristic-based approaches to fit Burr distribution to such data; a single candidate model based approach using a Simulated Annealing (SA) technique and a population based approach using a constraint-based Evolutionary Alogorithn (EA). The fitted Burr distribution is then used to estimate the proportion of Non-conforming (PNC) which is then used to fit an appropiate Burr distribution to individual Geometric distance variables. Empirical performance of the proposed methods have been evaluated on real industrial data set using PNC criterion. Experimental results demonstrate that the new approach perform well than the existing.
- Relation
- Journal of Applied Statistical Science Vol. 20, no. 3 (2014), p. 299-315
- Rights
- Copyright Nova-Science Publishers
- Rights
- This metadata is freely available under a CCO license
- Subject
- Performance evaluation model; Burr distribution; Proportion of non-conformance; Constraint-based evolutionary algorithm
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