查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

109-2 287435 製造聯網整合技術 1 3.0 3 ★ 黃榮堂機械四甲
機械四乙
機械四丙
智慧感測與應用學程 12 0 機械四合開和智慧感測學程合開

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
109-2	287435	製造聯網整合技術	1	3.0	3	★	黃榮堂	機械四甲機械四乙機械四丙智慧感測與應用學程	12	0	機械四合開和智慧感測學程合開

教學大綱與進度：

教師姓名黃榮堂

Email jthuang@ntut.edu.tw

最後更新時間 2020-12-25 15:48:34

課程大綱製造聯網整合技術配合感測器、控制器、網路系統等，讓人、機器人、原物料、零組件、重要物品或設備，取得人、機、料、法、環的訊息，透過大數據分析與人工智慧，執行各種事前診斷預防、維護、事發處置及事後重建與改善的動作。本課程著重於製造聯網整合技術與實施方法，特別在智能工廠技術包含IoT、感測器設計與選擇、機電整合、數據分析、預防診斷與維修、智慧適應控制等。 This course provides a practical guide that lets you discover the technologies and the use cases for the industrial IoT. Taking you through the implementation of industrial processes, specialized control devices, and protocols, it covers the process of identification and connection of different industrial data sources gathered from different sensors. You will be able to connect these sensors, such as AWS IoT, Azure IoT, OEM IoT platforms, and Google IoT, to the cloud network, and extract this data from the cloud itself to your devices. Over time, you will gain the knowledge to obtain the hands-on experience necessary for using open source Node-RED, Kafka, Cassandra, and Python. You will develop streaming and batch-based machine learning algorithms. By the end of this book, you will have mastered the features of Industry 4.0 and will be able to build strong, faster, and more reliable IoT infrastructure within your industry.

課程進度 Week 1 Introduction to Industrial IoT Week 2 Understanding the Industrial Process and Devices Week 3 Industrial Data Flow and Devices Week 4 Implementing the Industrial IoT Data Flow Week 5 Applying Cybersecurity Week 6 Performing an Exercise Based on Industrial Protocols and Standards Week 7 Developing Industrial IoT and Architecture Week 8 Implementing a Custom Industrial IoT Platform Week 9 Midterm Week 10 Understanding Industrial OEM Platforms Week 11 Implementing a Cloud Industrial IoT Solution with AWS Week 12 Implementing a Cloud Industrial IoT Solution with Google Cloud Week 13 Performing a Practical Industrial IoT Solution with Azure Week 14 Understanding Diagnostics, Maintenance, and Predictive Analytics Week 15 Implementing a Digital Twin – Advanced Analytics Week 16 Deploying Analytics on an IoT Platform Week 17 Deploying Analytics on an IoT Platform Week 18 Final project (oral report)

評量方式與標準 Participation 10 % Midterm Exam 40% Final Project 50%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
Authors: Giacomo Veneri, Antonio Capasso Hands-On Industrial Internet of Things Copyright c 2018 Packt Publishing Some technical papers may be offered for reference

課程諮詢管道

備註

教師姓名	黃榮堂
Email	jthuang@ntut.edu.tw
最後更新時間	2020-12-25 15:48:34
課程大綱	製造聯網整合技術配合感測器、控制器、網路系統等，讓人、機器人、原物料、零組件、重要物品或設備，取得人、機、料、法、環的訊息，透過大數據分析與人工智慧，執行各種事前診斷預防、維護、事發處置及事後重建與改善的動作。本課程著重於製造聯網整合技術與實施方法，特別在智能工廠技術包含IoT、感測器設計與選擇、機電整合、數據分析、預防診斷與維修、智慧適應控制等。 This course provides a practical guide that lets you discover the technologies and the use cases for the industrial IoT. Taking you through the implementation of industrial processes, specialized control devices, and protocols, it covers the process of identification and connection of different industrial data sources gathered from different sensors. You will be able to connect these sensors, such as AWS IoT, Azure IoT, OEM IoT platforms, and Google IoT, to the cloud network, and extract this data from the cloud itself to your devices. Over time, you will gain the knowledge to obtain the hands-on experience necessary for using open source Node-RED, Kafka, Cassandra, and Python. You will develop streaming and batch-based machine learning algorithms. By the end of this book, you will have mastered the features of Industry 4.0 and will be able to build strong, faster, and more reliable IoT infrastructure within your industry.
課程進度	Week 1 Introduction to Industrial IoT Week 2 Understanding the Industrial Process and Devices Week 3 Industrial Data Flow and Devices Week 4 Implementing the Industrial IoT Data Flow Week 5 Applying Cybersecurity Week 6 Performing an Exercise Based on Industrial Protocols and Standards Week 7 Developing Industrial IoT and Architecture Week 8 Implementing a Custom Industrial IoT Platform Week 9 Midterm Week 10 Understanding Industrial OEM Platforms Week 11 Implementing a Cloud Industrial IoT Solution with AWS Week 12 Implementing a Cloud Industrial IoT Solution with Google Cloud Week 13 Performing a Practical Industrial IoT Solution with Azure Week 14 Understanding Diagnostics, Maintenance, and Predictive Analytics Week 15 Implementing a Digital Twin – Advanced Analytics Week 16 Deploying Analytics on an IoT Platform Week 17 Deploying Analytics on an IoT Platform Week 18 Final project (oral report)
評量方式與標準	Participation 10 % Midterm Exam 40% Final Project 50%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 Authors: Giacomo Veneri, Antonio Capasso Hands-On Industrial Internet of Things Copyright c 2018 Packt Publishing Some technical papers may be offered for reference
課程諮詢管道
備註