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Process modelling and optimisation using artificial neural networks and gradient search method

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Abstract

Process modelling refers to the development of a process model that serves to provide the input-output relationship of a process, while process optimisation provides the optimum operating conditions of a process for a high-yield, low cost and robust operation. Normally, process modelling is a starting point of process optimisation. In this paper, a method of integrating artificial neural networks with a gradient search method for process modelling and optimisation is presented. Artificial neural networks are used to develop process models while a gradient search method is used in process optimisation. Application of the method to the modelling and optimisation of epoxy dispensing for microchip encapsulation is described. Results of the validation tests indicate that good quality of encapsulation can be obtained based on the proposed method.

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Authors and Affiliations

  1. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, People’s Republic of China

    C. K. Kwong & Y. C. Tsim

  2. Shenzhen Tourism College, Jian University, Overseas Chinese Town, Shenzhen, People’s Republic of China

    H. Bai

Authors
  1. H. Bai
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  2. C. K. Kwong
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  3. Y. C. Tsim
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Corresponding author

Correspondence to C. K. Kwong.

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Bai, H., Kwong, C.K. & Tsim, Y.C. Process modelling and optimisation using artificial neural networks and gradient search method. Int J Adv Manuf Technol 31, 790–796 (2007). https://doi.org/10.1007/s00170-005-0256-x

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  • DOI: https://doi.org/10.1007/s00170-005-0256-x

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