SUNConferences, 27th Annual Conference of the SA Institute for Industrial Engineering

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Decision Support Heuristics for Cost Estimation Model of Injection Moulds
Mncedisi Trinity Dewa, Andre Francois Van der Merwe, Stephen Matope, Lungile Nyanga

Last modified: 2016-10-07

Abstract


Cost estimation of products in the tooling industry is a complex task requiring a lot of expert knowledge and sound judgement. Higher estimates may lead in losing orders or customer goodwill while lower estimation will affect business profitability. Hence accurate and timely cost estimation before tool, die and mould production is a key attribute for sustaining global competitiveness. Due to the skills shortages the South African tooling industry has experienced, a majority of Toolmaking firms take long times to quote a job. Furthermore results from benchmarking exercises of these firms have shown that a majority of quotes generated lack accuracy due to methods employed.  In the paper, the key parameters to be considered when quoting the price of injection moulds are identified and ranked. The method of knowledge engineering was employed and heuristic data collected through interviews with five job quoting experts in the Western Cape Province tooling sector. Based on the information gathered, the Analytical Hierarchical Process (AHP) was used to rank the main parameters identified. The result of the survey can be used in the development of an expert system for quoting injection moulds in the South African Tooling industry.

Keywords


Multi-Criteria Decision Making