Advantages in Using a Stock Spring Selection Tool that Manages the Uncertainty of the Designer Requirements
This addresses efficiency and accuracy challenges for engineering designers in selecting stock springs, though it appears incremental as it builds on existing computer-assisted methods.
The paper tackles the problem of manual spring selection in engineering design by developing a computer-assisted tool that uses multi-criteria analysis and fuzzy logic to handle uncertain requirements. The results show significantly better outcomes compared to manual searches, with examples demonstrating improved specification detailing and increased design flexibility.
This paper analyses the advantages of using a stock spring selection tool that manages the uncertainty of designer requirements. Firstly, the manual search and its main drawbacks are described. Then a computer assisted stock spring selection tool is presented which performs all necessary calculations to extract the most suitable spring from within a database. The algorithm analyses data set with interval values using both multi-criteria analysis and fuzzy logic. Two examples, comparing manual and assisted search, are presented. They show not only that the results are significantly better using the assisted search but it helps designers to detail easily and precisely their specifications and thus increase design process flexibility.