Artificial Neural Network Based Life Cycle Assessment Model for Product Concepts Using Product Classification Method

Abstract

Many companies are beginning to change the way they develop products due to increasing awareness of environmentally conscious product development. To copy with these trends, designers are being asked to incorporate environmental criteria into the design process. Recently Life Cycle Assessment (LCA) is used to support the decision-making for product design and the best alternative can be selected based on its estimated environmental impacts and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need the new approach for the environmental analysis. This paper presents an artificial neural network (ANN) based approximate LCA model of product concepts for product groups using a product classification method. A product classification method is developed to support the specialization of ANN based LCA model for different classes of products. Hierarchical clustering is used to guide a systematic identification of product groups based upon environmental categories using the C4.5 decision tree algorithm. Then, an artificial neural network approach is used to estimate an approximate LCA for classified products with product attributes and environmental impact drivers identified in this paper.