It is generally well known that the reliability of Life Cycle Analysis (LCA) studies depends upon exact, complete and sharp input data that, unfortunately, are not always available. Furthermore, when available, the input data are affected by uncertainty whose importance is not always adequately taken into consideration.This paper describes the software F.A.L.C.A.D.E. (Fuzzy Approach to Life Cycle Analysis and Decision Environment): a tool designed for the calculation of the eco-profile of products, based on a fuzzy logic approach. The originality of the method already treated in other papers is to use the fuzzy representation to manage the complex relationships that arise in compiling an eco-balance. In particular, the model allows to give further attributes to the numerical data of the inventory based to the expert knowledge. The uncertainty of data is clearly defined by means of four fuzzy linguistic variables: the age of the data, the kind of technology to which data are referred to, the statistical and geographic representativeness of the data.The main model’s strength is transparency. Many LCA tools appear, unfortunately, as “black boxes” leaving the actual influence of the algorithms upon the final results unclear. On the other hand, with F.A.L.C.A.D.E. the user is able to observe and control all the calculation steps from the input of data to the final results. For instance, F.A.L.C.A.D.E. uses a linear sub-model that, starting from the inventory matrixes, allows to calculate an eco-profile together with a conditioning number “CN”, which describes how sensitive is the linear model to errors when solving the system of equations. Finally, the software present a set of tables summarising the results obtained with the fuzzy model. These results can be compared with those obtained with other methods. The software represents therefore a tool to evaluate the quality of Life Cycle Inventory (LCI) study.F.A.L.C.A.D.E. has been developed using an object-oriented programming. The result is a flexible tool whose structure can be easily changed by the user (variables, linguistic rules, domains of the fuzzy groups, etc.). As case study, the software has been applied to the LCA of a plaster material commonly used in building construction.
|Number of pages||21|
|Publication status||Published - 2004|
All Science Journal Classification (ASJC) codes
- Ecological Modelling