Logical Knowledge-based Advanced Cost Estimation Methodology (LKACEM) Applied to Metal Matrix Composite Aero-Engine Blisk

Nikhil Thakur, Pathmeswaran Raju, Michal Krzyzanowski, Phani Chinchapatnam

    Research output: Contribution to journalArticlepeer-review


    Cost estimation is an important activity for advanced understanding of product/process knowledge that is used to plan activities accordingly. For composite material parts, choices of materials and their methods of manufacturing are broad and thus complexity is high. Design is complex too involving tight tolerances leading to need of a new and advanced costing system. Proper knowledge management followed by improving the current cost estimation methods is a viable solution. This paper proposes a logical knowledge-based advanced cost estimation methodology that uses a mathematical set theory-based knowledge management system designed by utilising a generic product life-cycle for Knowledge Information & Data collection. This acquired KID is represented as parent sets, subsets and elements. The knowledge structure so created is coupled to a mixed method of cost estimation for developing logical advanced cost estimation system that can be used for both composite and conventional costing. Standard rules governing the parameters of cost and their relationships with the knowledge base is included in this methodology as a part of logical layer which interacts with other layers to form a reliable cost estimate. This methodology is then applied to develop a factory cost model for an aero-engine blisk design made up of metal matrix composite. This is done by using both simple and advanced software tools. Finally the outcome from these softwares are analysed by comparison study. The comparison is shown graphically for machining, material and overall cost parameters as a difference in their output cost values. As an outcome it is proved that the methodology is flexible for use with different softwares, is capable of reliable estimates, is less complex and thus can be used for cost estimation.
    Original languageEnglish
    Pages (from-to)53-65
    Number of pages13
    JournalInternational Journal of Computer Science and Technology
    Issue number2
    Publication statusPublished (VoR) - 15 Jun 2018


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