Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales

Julirose , Gonzales (2018) Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales. PhD thesis, University of Malaya.

[img] PDF (The Candidate's Agreement)
Restricted to Repository staff only

Download (1251Kb)
    PDF (Thesis PhD)
    Download (4089Kb) | Preview


      The growing environmental awareness of today’s consumers has put the manufacturing companies with the burden of taking responsibility for their own product’s environmental impact. This incited the need to develop product management systems which focus on minimizing a product’s impact across its life cycle. However, a survey conducted on Malaysian design companies suggests that there are no systems available for them to include environmental considerations in their product design processes. This dissertation presents a study on product design optimization which focuses on the inclusion of the potential environmental impact in the design consideration. The aim of this research is to develop a methodology that will aid designers to reduce the potential environmental impact of a product’s design, which does not require them to train additional skills in environmental impact analysis. Analysis of the effect of changing the product design parameters such as its dimensions, and basic features on the environmental impact of machining process in terms of its power consumption, waste produced and the chemicals and other consumables used up during the process is the key method in this research. A novel feature-based product design methodology based on an integrated CAD-LCA approach is developed which analyzes a product design’s environmental impact. Genetic Algorithm is applied to the product design parameters to create a feedback system in order to get the best possible product design solutions with the least environmental impact within the product design functionality limitation. The results using the proposed methodology yields 50 pareto optimal design solutions for every run, allowing the designers the freedom to choose the suitable design. The developed methodology aids designers in providing design solutions that satisfies the customer requirements and at the same time adding value to their work through the suggestion of eco-friendly alternatives.

      Item Type: Thesis (PhD)
      Additional Information: Thesis (PhD) - Faculty of Engineering, University of Malaya, 2018.
      Uncontrolled Keywords: Genetic algorithm; Product design; Environmental impact reduction; Eco-friendly alternatives
      Subjects: T Technology > TJ Mechanical engineering and machinery
      T Technology > TS Manufactures
      Divisions: Faculty of Engineering
      Depositing User: Mr Mohd Safri Tahir
      Date Deposited: 23 May 2018 16:05
      Last Modified: 11 Jun 2020 03:27

      Actions (For repository staff only : Login required)

      View Item