Intelligent Knowledge Based System Approach for Ultrasonic Machining in Computer Base Concurrent Engineering Environment

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Design Feature, USM, CE, KBS, Machining Time and Cost, Penetration Rate
Morteza Sadegh Amalnik
Manufacturing systems comprise of a large number of different stages that affect product development time and cost, product quality and the productivity of the overall system. The interactions between these processes are complex. Concurrent engineering is a systematic approach to the integrated concurrent design of product and their related processes. This approach considers all elements of the product life cycle from conceptual stages to the final stages of product development including quality, cost, manufacturability, schedule and user requirements. It is an organizational strategy which creates an environment that designers or manufacturing engineers work to gather under the same goals and the same sense of values to tackle the same problems from the early stages of product development .The goals are reduction of product development time, and cost and shorter time to market. This paper addresses the concept and development of a knowledge-based-system (KBS) in computer based concurrent engineering environment for hard and brittle material, such as glass, quartz, diamond, carbides, semi conducting materials, ceramic and graphite which can be manufactured with ultrasonic machine. The intelligent system is integrated manufacturing system is used expert system based on object oriented technique. The system links with A feature based CAD system in order to extract design data. The system is linked with databases. The machining cycle time, cost, penetration rate, efficiency and effectiveness, of each selected design feature are estimated. The system provides useful information such as machining cycle time and cost, penetration rate, efficiency and effectiveness of machining of the selected design feature for product designers at the conceptual stages of design process and also advises manufacturing engineers to select optimum machining parameters.
Full text: IJAIM_291_Final.pdf

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