Course is closed
Lead Instructor(s)
Date(s)
Jun 24 - 27, 2024
Registration Deadline
Location
On Campus
Course Length
4 days
Course Fee
$3,900
CEUs
2.5
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This course is designed to help you learn and apply advanced data tools for IIoT and smart manufacturing. The curriculum ranges from foundational concepts to in-depth, hands-on activities using production data, and covers a variety of cutting-edge approaches such as deep reinforcement learning control, encryption for data outsourcing, and predictive data analytics algorithms. 

This course may be taken individually or as part of the Professional Certificate Program in Design & Manufacturing Or the Professional Certificate Program in machine learning & artificial Intelligence.

Course Overview

Explore the latest developments in smart manufacturing 

Through interactive lectures and exercises—grounded in data and examples from the automotive, semiconductor, food production, nanofabrication, and telecommunications sectors—you will acquire core strategies and frameworks for using data driven analysis, simulation, automation, and optimization techniques to improve manufacturing processes and deploy IIoT systems. You will then put your learning into action by working with other course participants to design, simulate, and test system improvements based on information extracted from process and production data. 

  • The curriculum is organized into four sections: 
  • Data collection strategies for IIoT 
  • Data analytics and predictive modeling for production data 
  • Simulation modeling through digital twinning 
  • Process and manufacturing systems simulation and optimization

Certificate of Completion from MIT Professional Education

Advanced Data Analytics cert image
Learning Outcomes

LEARNING OUTCOMES 

  • Develop a data collection strategy for industrial networks, including non-traditional IoT data streams and cloud-based data storage 
  • Visualize, analyze, and predict relevant production outcomes based on process data 
  • Create and use digital twins of factory processes 
  • Simulate and optimize factory processes using data analytics, predictive modeling, and digital twins 

DISCUSSION AND CASE STUDY TOPICS 

You will leave this course equipped to capitalize on the latest data-driven manufacturing tools, including video analytics, learned control systems, and system security strategies. 

  • Data-driven manufacturing planning and execution analytics and services: Providing new approaches and models for manufacturing decision making in smart factories. 
  • Data-driven manufacturing asset analytics and services: Providing new whole-life asset management models and tools in smart factories. 
  • Data-driven manufacturing quality analytics 
  • Data-driven smart manufacturing analytics dashboard: Providing visibility methods and tools for smart manufacturing analytics platform. 
Who Should Attend

WHO SHOULD ATTEND 

  • Engineers and engineering managers who want to implement the latest digital strategies to maximize the value of their operations 
  • Design and manufacturing engineers or machine and process designers seeking to enhance their ability to capitalize on data and modeling in a manufacturing environment 
  • Data scientists looking to take the lead in the rapidly growing field of smart manufacturing 
  • Factory, production, or process managers who want to use advanced tools to design and deploy integrated, computational systems on the factory floor 
  • Directors of operations or manufacturing who would benefit from implementing data analytics tools as part of a continuous improvement strategy 
  • Consultants who are interested in increasing their value to clients in the manufacturing industry 
Brochure
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Advanced Data Analytics For IIOT and Smart Manufacturing - Brochure Image