A KNOWLEDGE-BASED DECISION SUPPORT SYSTEM USING ONTOLOGY FOR COST OPTIMIZATION AMONG VARIOUS MANUFACTURING ALTERNATIVES

Abstract

Various industries which are working on basically business-to-business models fulfill the customer’s demands either on a per order basis or engineering order basis. Moreover, they have to face tremendous competition among similar types of industries. Hence, they have to be very cost-competitive to secure orders from their customers. The cost calculation to produce the required part is carried out by a person who has deep knowledge in the domain. Thus, the future of these types of industries depends upon such skills and faces lots of challenges if the person is not available because of various reasons. Hence there arises the need for an intelligent system that can suggest various available options to get the required costing for the project based on the knowledge base which has been acquired from part experience in the industries, these experiences can be success or failure. Ontology is the perfect solution to build this knowledge base with the help of experts. Thus, when the database is created and also able to recall the solutions from these databases to get instant results so that the generation of quotations for the customers can be fairly quick and accurate. Hence an ontology-based knowledge base is presented in this thesis which will support the design or process decisions based on the costing optimization to acquire the bests possible results for machining industries so that they can be acquired good costing capabilities independent of human skills involvement.