| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1712216 | Biosystems Engineering | 2009 | 15 Pages |
A greening material has different attributes for bio-physical, market and commercial functions. In designing a material, a plant factory has to select from a large set of initial design attributes. This paper presents swarm modelling (SM) to select the desired design attributes of customisable greening material. SM was developed by hybridising desirability model and particle swarm optimization (PSO). Design attributes were selected by predicting its consumer importance in a desirability model. Subsequently, PSO was used to optimise the model based on mentality constraints.SM was demonstrated on a case study of Sunagoke moss greening material (Rhacomitrium japonicum). The materials were classified into wet and semi-dry moss. The importance of a set of 24 attributes was predicted based on 15 mentality constraints. Constraints here included consumer prior knowledge, familiarity, agreement to material function and interest. Some of the bio-physical attributes were not selected due to the limited mentality. Four attributes were found to be the desired selections for optimal design of wet moss. For the semi-dry moss, there were 14. These attributes were validated successfully using a different consumer segment with minimum error. The desired attributes for the optimal design can be selected using consumer importance and its mentality constraints.
