题名

生產系統於先進智能製造之展望

并列篇名

The Review of Production System for Advanced Intelligent Manufacturing

DOI

10.29416/JMS.201807_25(3).0005

作者

王立志(Li-Chih Wang)；范書愷(Shu-Kai Fan)；丁慶榮(Ching-Jung Ting)；郭財吉(Tsai-Chi Kuo)；林春成(Chun-Cheng Lin)；許嘉裕(Chia-Yu Hsu)

关键词

生產系統 ； 智能生產 ； 大數據分析 ； 物聯網 ； 智能物流 ； 永續生產 ； Production System ； Smart Production ； Big Data Analytic ； IoTs ； Intelligent Logistics ； Sustainable Production

期刊名称

管理與系統

卷期/出版年月

25卷3期（2018 / 07 / 01）

页次

381 - 412

内容语文

繁體中文
中文摘要

隨著感測技術的進步，整合資通訊技術、網路、感知等跨領域以發展智能製造技術將成為製造業未來持續發展的動能。台灣製造業在傳統產業與科技產業長期累積的優勢也開始受到鄰近亞洲國家的威脅，產業成長的表現已逐漸趨緩，製造業更需要轉變為生產智慧化，自主調整生產環境與產線之產能、資源與能源配置發展，以及自主調整上下游供應配送，並輔助人員正確快速完成各種操作組裝，建立完整產品生產履歷，可即時追蹤生產進度。另一方面，製造業面臨外部環境快速變化與成本的競爭壓力，除了硬體設備的提升外，更需要的是預測性分析的能力，以提升生產製造、行銷和資訊科技等方面的營運效率和競爭優勢。面對物聯網與大數據分析時代，生產系統與管理領域研究也開始在轉變。本研究整理現今製造業在生產系統智能化方面相關研究，針對智能生產、大數據分析、物聯網、智能物流、永續生產等不同方向說明未來值得投入的研究方向。
英文摘要

With the advanced sensing technology, the integration of communication technologies and network cross different area has become the continuously development of manufacturing industry. The long-term accumulations of competitiveness and advantage for manufacturing industry in Taiwan have also begun to be threatened by neighboring Asian countries. The industrial growth has gradually slowed down, and the manufacturing industry needs to be transformed into smarter production for self-adjustment in the production capacity. Additionally, the upstream and downstream in supply chain are adaptively adjusted and assisted to quickly and correctly complete various operations and assembly. On the other hand, the manufacturing industry is facing competition from rapid changes in the external environment. In addition to the upgrading of hardware, it also requires the ability of predictive analysis to improve operational efficiency in manufacturing, marketing, and information technology. Faced with the Internet of Things (IoTs) and the big data analytics, research in production systems and management is also beginning to change. This study reviews out the current research regarding the intelligent manufacturing, and explains the future research directions that are worth investing in smart production, big data analysis, IoTs, smart logistics, and sustainable production.
主题分类 基礎與應用科學 > 統計
社會科學 > 財金及會計學
社會科學 > 管理學
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被引用次数
  1. 趙仁德,陳彥銘,呂政芳(2022)。利用人工智慧建立石油煉製業壓縮機之異常診斷機制。石油季刊，58(1)，83-103。
  2. (2024)。智慧製造關鍵評估指標與成功要素之探討－以臺灣電子業為例。管理與系統，31(3)，343-376。
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