A hierarchical model for eco-design of consumer electronic products

Designing environmentally friendly products has become a tighter requirement in the marketplace because of both the increasing trend in awareness of consumers and the obligations from legislation requirements. Unfortunately, this is not a straight forward decision for designers to evaluate whether their design options are satisfactory in terms of balancing various factors (for examples, different forms of environmental assessment) or not. This is partly attributed to the fact that there is no universally accepted approach for conducting such analysis. In this connection, this research makes reference to a European Union (EU) directive as a reference model and makes use of Analytic Hierarchical Process (AHP), which is a useful tool to help designers to make decision, for evaluating eco-design options. The AHP model is developed based on two case studies on consumer electronic products. Pairwise comparisons, one of the key steps in AHP, are conducted with the expertise gained from the case studies and the help from the software package Expert Choice. The paper also reveals how design options can be evaluated, or be screened out. The proposed method does not require the designers to conduct detailed analysis (life-cycle assessment for example) for every new product options and hence can save their time. This is particularly important when they are facing shorter and shorter product life cycle nowadays. First published online: 18 Jun 201

Rule-based life cycle impact assessment using modified rough set induction methodology

Life cycle assessment (LCA) is a methodology for assessing environmental burdens of products or processes on a cradle-to-grave basis. The impact assessment phase necessitates use of decision analysis methods to account for multiple environmental criteria in the comparison of technological alternatives. Valuation or weighting of the impact criteria is usually accomplished by eliciting relative or absolute scores from an expert. This paper presents an alternative streamlined approach wherein heuristic rules are derived from a set of training data in the form of example alternatives ranked in order of preference by the expert. These decision rules are generated using an induction process based on rough set theory. The heuristic rules can subsequently be used to compare and rank new alternatives, and lead to a decision consistent with the expert preferences embodied in the training data. © 2004 Elsevier Ltd. All rights reserved

A long-term energy efficiency prediction model for the Brazilian automotive industry

According to law number 12.715/2012, Brazilian government instituted guidelines for a program named Inovar-Auto. In this context, energy efficiency is a survival requirement for Brazilian automotive industry from September 2016. As proposed by law, energy efficiency is not going to be calculated by models only. It is going to be calculated by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in market will be a key factor on profits of each automaker. Energy efficiency and its consequences should be taken into consideration in all of its aspects. In this scenario, emerges the following question: which is the efficiency curve of one automaker for long term, allowing them to adequate to rules, keep balancing on investment in technologies, increasing energy efficiency without affecting competitiveness of product lineup? Among several variables to be considered, one can highlight the analysis of manufacturing costs, customer value perception and market share, which characterizes this problem as a multi-criteria decision-making. To tackle the energy efficiency problem required by legislation, this paper proposes a framework of multi-criteria decision-making. The proposed framework combines Delphi group and Analytic Hierarchy Process to identify suitable alternatives for automakers to incorporate in main Brazilian vehicle segments. A forecast model based on artificial neural networks was used to estimate vehicle sales demand to validate expected results. This approach is demonstrated with a real case study using public vehicles sales data of Brazilian automakers and public energy efficiency data. According to our results Inovar-Auto targets will be reached in spite of little progress over last four years