# A Soft Computing Framework to Support Consumers in Obtaining Sustainable Appliances from the Market
## 3 Material & Research Method
### Strengths, Weakness, and Limitations of the Work  
The approach presented here uses a lifecycle cost assessment (LCCA) method to predict the cost regarding each solution during its usage phase and according to the consumer's profile.  
However, the LCCA calculations only accounts for the cost in terms of water and CO\({}_{2}\) emissions involved, and do not consider the materials involved in the production and final phase of the product itself. Further developments regarding this issue should be accounted for in future.  
Issues such as the minimal lighting illuminance requirements, the dishwasher capacity, and the air conditioner thermal power (among others) are also accounted for in order to support the consumer with suitable appliances from the market and according to their needs.  
Besides the economic and environmental concerns, the consumer's social preferences, such as comfort requirements related to different dimensions (thermal, acoustic, and visual) are also considered here together with different preferences regarding such issues as the (perceived) quality of the product and reliability, among others. The consumer's relative importance, regarding each dimension (economics, social, and environment) are also accounted for here.  
Another advantage from the use of this approach is the diversity (although still optimal) of solutions from the market, which allows facing a contingency problem with the availability regarding a specific appliance (e.g., when it is out of stock).  
However, the model to calculate the consumer's needs in terms of the air conditioner capacity needs to account not only for the dimensions of the divisions to be climatized but also other issues (e.g., wall materials, the windows, the facade orientation) to increase the precision in obtaining the results by using the model.  
Still regarding the lack of precision in the estimation of air conditioner capacity, the model should also account for the dynamics in terms of interdependence between air conditioner and the new lighting system, since that a new lighting system could impact the requirements in terms of building's thermal needs.  
Regarding the weakness and strengths already discussed here, there were some limitations within this work. One had to do with dimensions of the database (and, therefore, the sample) that was used, and by considering only the Portuguese market, although the main purpose here was (as an initial phase) to validate the proposed model.  
Some attributes used here are only adjusted to the European Union context (e.g., the use of European Union's Energy Labelling Framework as an energy label classification framework), which brings about the requirement to make necessary (and future) adjustments of the method to account for other contexts with respect to the countries or regions involved.  
The lack of previous research studies on this topic, given the issues referred to before, also represents a limitation, due to the lack of other approaches to be used as a mean to compare the obtained results for example. Therefore, such limitations have allowed for the identification of new gaps in the literature, which point to the need for further developments.