Building a Cost Estimation of Plastic Injection Products and Value Analyze System for Concept Products by Feature-Based Models

• Main Authors: Chao-Ting Lin, 林照挺
• Other Authors: He-Sing Wang
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/3s29hd

碩士 === 國立臺北科技大學 === 工業工程與管理系所 === 95 === The major objective of concurrent engineering is to consider the related downstream manufacturing information during the design stage. Among those, estimating manufacturing cost during the early design stage is one area which has been drawn little attention by the researchers. However, if the product manufacturing cost can be estimated during the design stage, designers can modify a design to achieve proper function and reasonable cost in the early product development process. The purpose of research is utilizing the concept cost evaluation decision support system to assist designer to make a correct decision and shorten the time of the cycle of new product development. We will use the Feature-Based Models and neural network to construct the process of cost estimation about the new product of plastic injection parts. The first, the target costing is an innovative control system to minimize those costs that are determined in product development. And we will integrate target-costing process with Feature-Based models property in cost estimation during the early stage of concept development process. In this paper, we discuss to estimate the cost of the plastic injection parts by neural network. It is a system of profit planning and cost reduction that control costs before they incurred, is committed to continual improvement in product and process designs, is externally focused on customers and competition, and systematically relates complex web of value-chain and cross-function relationships into a cohesive and integrated planning and execution system. The last, we will construct a database that includes every kind of cost in order to become the major source of decision support system.