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|Authors: ||鄭國宏;Cheng, Kuo-Hung|
|Keywords: ||智能吊掛系統;效率改善;自動化;即時性;ERP;MES;Intelligent Hanging System;Efficiency Improvement;Automation;Real Time;ERP;MES|
|Issue Date: ||2019-09-03 15:09:52 (UTC+8)|
本研究對Ｇ公司所導入推行的智能吊掛系統所收集的生產數據分析，除了與傳統生產方式有重大的改革外，更能即時性反應生產線的效率，進而提供管理者，對生產線的調度能有科學數據及合理性的改善。;Garment processing industry is a labor-intensive industry. In today′s world, labor costs increase gradually, causing the industry switch production bases continuously to countries with lower labor costs; and production efficiency is also one of the factors that affects labor costs. Therefore, importing automatic machines and new technologies are significant issues for garment processing industry to survive in the future.
By improving information technology and automatic equipment, many new automatic machines have been put into production lines of garment factories. Additionally, besides traditional ERP system management, intelligent hanging system developed under demand of MES system also put into garment production.
In comparison, when MES system was launched to production lines in early garment industry, data collection was difficult and introduction cost was too high due to many factors, causing many garment factories don′t want to implement it at that time.
But due to maturity of various technologies and reduction of equipment costs now, there is a growing and more garment factories have begun to pay attention to MES system. In recent years, the introductions of intelligent hanging systems have been greatly promoted to improve efficiency of production. Intelligent hanging system combines the Internet of Things technology to improve the old MES system which data collection is difficult and has material transportation problems.
In this study, the analysis of production data was collected by the intelligent hanging system by G Company. Besides major reforms of traditional production methods, it can reflect the efficiency of production line more quickly, and provides rational improvements on production line allocation/scheduling with scientific base to managers.
|Appears in Collections:||[高階主管企管（EMBA）碩士班] 博碩士論文|
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