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Please use this identifier to cite or link to this item: http://ir.lib.stu.edu.tw:80/ir/handle/310903100/630

Title: SMT自動化生產線製造彈性能力評估模式之發展
A Study SMT automated production line manufacturing flexibility in the development of competency assessment model
Authors: 陳俊凱
Chen Jyun-Kai
Contributors: 蔡聰男
經營管理研究所
Keywords: 表面黏著技術;製造彈性;偏好模糊關係
Surface mount technology;manufacturing flexibility;preference fuzzy relations
Date: 2010
Issue Date: 2011-05-23 15:59:06 (UTC+8)
Publisher: 高雄市:[樹德科技大學經營管理研究所]
Abstract: 近年來隨著科技進步,消費者對於產品要求更形多樣化與嚴苛要求,促使產品生命週期逐漸縮短。消費電子產品的種類日新月異,如智慧型手機、筆記型電腦各項產品皆趨於輕薄短小、功能強大,價格不再只是消費者所要求的重點,故企業對消費者各類需求,須縮短研發時程且具備高度彈性製造能力。而表面黏著製程(Surface mount technology, SMT)為電子組裝(Electronics assembly)之主要製程,SMT生產線常配置多部自動化機台,機台皆有能力與運作速度之分,故SMT彈性生產便成為電子組裝重要彈性來源。有鑑於上述需求,企業無不投入大量人力於生產製造上,以提升顧客滿意度與彈性製造能力用以快速反應瞬息萬變的市場變化。
本研究運用模糊偏好關係(Fuzzy preference relations, FPR)演算法則,提出一個客觀彈性製造能力評估模式,其中藉由文獻探討與專家意見整理出製程彈性能力(Manufacturing flexibility capability)評選準則,繼而採用模糊問卷表達用以評估彈性準則(八大構面:機器彈性、製程彈性、新產品彈性、途程彈性、生產彈性、擴充彈性、作業彈性、混合生產彈性)之語意式意見,再經由此類語意評比計算各項彈性因子權重,最後經模糊數運算後獲得製程彈性能力評估得分以決定SMT製造彈性能力評估模式。
In recent years, 3C consumer products have become diversified and innovative that drives a progressively shorter product life-cycle. The products (such as smart phones, PC and laptops), all emphasize on short, light and powerful, therefore the types of consumer electronics products are rapidly changing. Surface mount assembly usually installs several types of machines and their functions are different and limited. To meet the diversity of consumer demand, R&D development schedule must be shortened and the manufacturing process must have a flexible scheme. In view of the above needs, the manufacturers have invested a lot of effort in upgrading the manufacturing flexibility into in order to quickly response the rapidly changing market and the customer requirements.
This work employs fuzzy preference relation algorithm to develop a manufacturing flexibility assessment model. We reviewed the literature with respect to manufacturing flexibility and consult with experts to select the key flexibility criteria, followed by a questionnaire to capture experts’ opinions on fuzzy evaluation criteria (such as machine flexibility, process flexibility, new product flexibility, routing flexibility, production flexibility, expansion flexibility, operation flexibility, mixed production elasticity) through semantic comments. These semantic appraisals of the elasticity of factor weights are then calculated through to determine SMT manufacturing flexibility capability.
Appears in Collections:[經營管理研究所] 博碩士論文

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