Smart manufacturing is a convergence of modern data science techniques and artificial intelligence to form the factory of the future. Smart manufacturing is about increasing efficiency and eliminating pain points in your system. It’s characterized by a highly connected, knowledge-enabled industrial enterprise where all organizations and operating systems are linked, leading to enhanced productivity, sustainability, and economic performance.
This online program brings together cutting-edge technology like machine learning, Internet of Things, and data analytics to understand the current transformation of the manufacturing sector.
In keeping with MIT’s founding principle, Mens et Manus (Mind and Hand)—the synergy of theory and practice being at the heart of the learning experience—you’ll learn by doing. The program centers around a smart machine—a fiber extrusion device, fondly referred to as FrED—to demonstrate concepts as well as incorporate problem-solving skills into the curriculum. Furthermore, you'll have a chance to engage with your peers and expert learning facilitators to explore how these concepts can be leveraged in your organization. Regardless of where you are on your smart manufacturing journey, this program provides the latest thought leadership in smart manufacturing techniques. The factory of the future is here.
Participant Takeaways
- Learn the basic tenets of smart manufacturing as Dr. Brian W. Anthony and his team of researchers continuously improve FrED's software and hardware components.
- Explore with expert Learning Facilitators how concepts can be applied to your organization.
- Explore how smart manufacturing principles have had a real impact in sports and medicine.
- Share resources, engage in online discussions, and participate in live webinars with peers from around the world.
Who Should Attend
This program is somewhat technical in nature, however this program material is highly accessible for those new to smart manufacturing concepts, while also being valuable for those who already have some experience with these concepts. There are no prerequisites for this program. It is designed for:
- Plant managers working in manufacturing
- Design and manufacturing engineers seeking to learn about data and modeling in a manufacturing environment
- Data scientists looking to apply their craft to the growing field of smart manufacturing
- Consultants who want to add value around the latest technology transformations in manufacturing
- Functional and cross-functional teams are encouraged to attend together to accelerate the smart manufacturing adoption process
Program Outline
Module 1: Introduction to Smart Manufacturing and FrED
- Identify global trends bringing major changes to society, products, and the manufacturing process
- Learn how FrED serves as a prototype for innovations that are possible within smart manufacturing
Module 2: Analyzing Data: A Visualization Approach
- Explore the convergence of manufacturing expertise and data science expertise in the field of smart manufacturing
- Use time series analysis to understand FrED
Module 3: Modeling to Make Sense of Data
- Build models to examine and improve FrED
- Explore how the length of a production run can affect results
Module 4: Sensors
- Review the integral role that sensors play in smart manufacturing
- Evaluate sensors and assess the types of data that sensors produce
Module 5: Control of Manufacturing Processes
- Explore manufacturing process control, the role of feedback, process modeling, and monitoring
- Discuss actual versus predicted dynamics
Module 6: Machine Vision
- Take test measurements using a camera
- Explore how machines use cameras and images to inform decisions and improve the manufacturing process
Module 7: Applications of Machine Vision
- Explore applications of machine vision to video search, sports and medicine
- Discuss applications of machine vision in additional contexts
Module 8: Model Fitting and Sensitivity Analysis
- Make the connection between machine vision as a tool and statistical process control
- Explore the process of discovering best fit for a model
Module 9: Statistical Process Control
- Apply statistical process control to a manufacturing setting
- Integrate deterministic and random variation
Module 10: Advanced Data Analysis
- Work with datasets derived from manufacturing process to control multiple machines
- Explore concepts in cloud computing to control multiple machines