Due to the continuous refinements in engineering operations, process parameters need to be optimised in order to improve the production quality. In this study we present a novel method based on the hybridisation of an ant colony system search mechanism with a steepest ascent method to achieve such a parameter optimisation. The proposed algorithm has been implemented and run on two real time industrial applications. Experimental results showed that the optimised parameters for a stealth laser dicing process provided by the new method were able to increase the production quality by improving production precision, which is measured in terms of average deviation from the expected result and relative variance. The novel method we propose was able to identify improved settings for a stealth laser dicing process with five parameters, resulting in a greatly reduced rate of product failures. Additionally six parameters were optimised for another industrial application, namely a grease filling system with twin towers, using only 23 experiments, leading to an increase in the tool life (objective of the optimisation) from the previous average of 9236 U produced to 13,883 U. The new method performed better than conven-B P. Luangpaiboon

The proper choices of a process parameter design (PPD) decision problem are studied in a noisy environment of a grease position process in an electronic industry. The process responses consist of the mean of parts between failures on left and right processes. A multi-response surface optimization problem is then proposed to maximize these dual process responses. The conventional modified simplex method and its hybridizations of the stochastic operators from the hunting search and ant colony optimization methods are applied to determine the proper levels of controllable design parameters affecting the quality performances. A numerical example demonstrates the feasibility of applying the proposed model to the PPD problem via two iterative methods. Its advantages are also discussed. Numerical results demonstrate that the hybridization based on the hunting search method seems to be superior when compared. In this study, the mean of parts between failures is improved by 27.04%, approximately. All experimental data presented in this research have been normalized to disguise actual performance measures as raw data are considered to be confidential.

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