智能制造系统的理论与技术分析

Anandakumar Haldorai
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引用次数: 0

摘要

本研究对智能制造系统(SMS)的现状进行了全面评估,特别强调了它们在技术管理和技术发展背景下的理论意义。本文通过罗杰斯的创新扩散理论考察了技术发展的理论基础。此外,本文采用Rieck和Dickson的技术战略模型(TSM)来强调技术管理的重要性。本文结合技术管理(MOT)理论,旨在提供一个理解和塑造技术发展的综合框架。SMS系统内几种技术的集成一直是与专利有关的讨论主题。为了分析这一新兴技术系统的综合组成部分,研究了智能制造系统(SMS)的特征。建议的SMS模型的服装制造单位已被用来表示全球纺织综合体。这项研究结合了最近的学术出版物和技术进步,以提供对未来制造系统视图的全面理解。目标是尽量减少人力参与,提高生产效率在制造业务。SMS的主要组成部分已被确定为网络物理系统,人工智能(AI),数字孪生,企业资源规划,增材制造和大数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Theoretical and Technological Analysis of Smart Manufacturing Systems
This study presents a comprehensive evaluation of the current status of smart manufacturing systems (SMS), with a specific emphasis on their theoretical significance in the context of technology management and technology development. The paper examines the theoretical underpinnings of development of technology through the lens of Rogers' Diffusion of Innovation (DoI) theory. Additionally, the paper employs Rieck and Dickson's Technology Strategy Model (TSM) to emphasize the importance of technology management. By incorporating the Management of Technology (MOT) theory, the paper aims to provide a comprehensive framework for understanding and shaping technology development. The integration of several technologies inside the SMS system has been the subject of discussion in relation to patenting. The features of Smart Manufacturing Systems (SMS) have been examined in order to analyze the comprehensive components of this emerging technological system. The suggested SMS model of the clothing manufacturing unit has been used to represent the global textile complex. This research incorporates recent scholarly publications and advancements in technology to provide a comprehensive understanding of future manufacturing system views. The objective is to minimize human involvement and enhance production efficiency within the manufacturing business. The primary components of the SMS have been identified as the cyber-physical system, artificial intelligence (AI), digital twin, enterprise resource planning, additive manufacturing, and big data.
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