• Title of article

    Fuzzy Logic Approach for Metal Casting Selection Process

  • Author/Authors

    Daws, Kasim M. University of Baghdad - Mechanical Engineering Department, Iraq , AL-Dawood, Zouhair I. University of Baghdad - Mechanical Engineering Department, Iraq , AL-Kabi, Sadiq H. University of Baghdad - Mechanical Engineering Department, Iraq

  • From page
    162
  • To page
    167
  • Abstract
    Selecting the proper material is a vital step in the design process because the appropriateness of the choice has a significant impact on part performance and cost. A poorly selected material adds unnecessary cost and may affect the ease of processing. In this paper an automated advisory material selection system is designed. The designed system is named (CAMS). The objectives of this system are to solve the problems of Materials selection and evaluation (M/P E) activities. The designed system depends on methodology for selection and evaluation of materials that are based on a number of user-specified attributes or requirements. The decision model enables the representation of the designer s preferences over the decision factors, and it is based on weighted property index (W.P.I) algorithms to determine the relative importance of each requirements. A compatibility rating between product profile requirements and the alternatives stored in the database for each decision criteria are generated using fuzzy logic (F.L) methodology. These requirements were matched with the capabilities of each (alloy) or material. The compatibility ratings are aggregated into single rating of that alternative s compatibility. A ranked set of compatible alternative alloys is produced t by the system. This approach has advantages over the existing systems that don t have a decision module or are not integrated with a database.
  • Keywords
    Materials Selection , Fuzzy Logic , Weighted Algorithm
  • Journal title
    Jordan Journal of Mechanical and Industrial Engineering
  • Journal title
    Jordan Journal of Mechanical and Industrial Engineering
  • Record number

    2586225