Multi-objective ga-based optimization to maximize sustainability for product design and manufacturing .

Abstract EN

Responding quickly and economically to the diversification of customer needs has forced manufacturing companies adopting approaches to delivering low cost, high quality sustainable products based on finding a link between the design or the manufacturing processes and other key elements of sustainability; economic, environmental, and social.

However, these approaches had limited success.

The most likely reason for the lack of integration between the design and manufacturing stages of the product and complexity of addressing the above mentioned three key elements of sustainability due to existing of many variables in relation to design, manufacturing, locations, logistic operations and so on.

Taking into account the required integration as well as the associated complexity of considering sustainability elements can lead to large space alternative solutions and it is more difficult to use only exact methods to the optimization of such problem.

This paper presents a genetic algorithm (GA) approach aiming to optimize a high sustainability performance by designing a product and the corresponding manufacturing processes for that product.

Process optimization is carried out in terms of the highest fitness function achieved where different objectives are to be optimized simultaneously.

The proposed GA approach is applied to the industrial case example.

The proposed approach can assist decision makers to help explain when justifying their decision on what are the best product design and its manufacturing processes to obtain high sustainability performance.