Smart Manufacturing: Moving From Static to Dynamic Manufacturing Operations

Navigate the Industry 4.0 revolution

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Course Dates

STARTS ON

February 2, 2022

Course Duration

DURATION

10 weeks, online
4-6 hours/week

Course Duration

PROGRAM FEE

US$2,800

Course Information Flexible payment available

Why Enroll in MIT Professional Education's Smart Manufacturing Program?

Massachusetts Institute of Technology (MIT) is at the forefront of applied research and understands the factors that lead to successful implementation of smart technologies. From modeling to manufacturing systems to advanced data analytics, MIT draws on more than 100 years of university-industry collaboration.

31%

Nearly a third of manufacturers surveyed don’t know the timing for investing in digital technology solutions for their enterprises, noting that corporate management should lead the effort for adoption of smart manufacturing.

SOURCE: GARTNER TREND INSIGHT REPORT 2018

34%

According to a survey by Small Medium Enterprises, a third of survey respondents say that a top challenge to implementing smart manufacturing solutions was finding skilled people.

SOURCE: SME’S MANUFACTURING IN THE NEW INDUSTRY 4.0 ERA SURVEY

50%

According to Gartner, half of all organizations are projected to lack sufficient Artificial Intelligence (AI) and data literacy skills to achieve business value by 2020.

SOURCE: GARTNER TREND INSIGHT REPORT 2018
MIT Professional Education's Smart Manufacturing program brings together cutting-edge technology like artificial intelligence, Internet of Things, and data analytics to understand the current transformation of the manufacturing sector.

Who Is This Program For

This program includes a technical element, and participants will need to quickly learn how to visualize data using Excel. However, the 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

Representative Companies

  • Microsoft
  • US Air Force
  • Johnson & Johnson
  • Apple
  • Amazon
  • BMW Manufacturing
  • Deloitte
  • McElroy Manufacturing
  • Merck
  • BCG
  • Procter and Gamble
  • Accenture
  • The Boeing Company
  • Caterpillar
  • LnT Infotech

Representative Job Titles

  • CEOs and Managing Directors
  • Quality Engineer
  • Simulations Manager
  • Director of Automation
  • Manager of Operations
  • Electrician
  • CTOs and CIOs
  • Manufacturing Engineer
  • Mechanic
  • Design Engineer
  • Data Scientist
  • Graduate Research Assistant
  • Chief Engineer
  • Information Architect
  • Global Manufacturing Analyst

Participant Testimonials

"This course has imbibed in me the importance of data analysis and vision systems and how to efficiently and optimally use the available resources for process improvement. It has also given me a better systems-thinking approach and made me aware about the latest technology available in the market, the knowledge of which I plan to pass on to my fellow team members."

— Tirth Shah, Manufacturing Engineer, Insulet Corporation

"This course has provided me the ability and capacity to build the Smart Manufacturing ecosystem, will develop and learn how to implement it."

— Chandeshwar Singh, MES Developer, Tata Consultancy Services Ltd

"The new knowledge will help effectively answer the common question of "what can you do" with modern systems and tools."

— Andrew Chastain, Application Engineer, Braas Company

Program Experience

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Application: FrED, Iterating the Smart Machine

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.

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Application: Industry Examples

Explore how smart manufacturing principles have had a real impact in sports and medicine.

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Guided Learning

Explore with expert Learning Facilitators how concepts can be applied to your organization.

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Peer Learning

Share resources, engage in online discussions, and participate in live webinars with peers from around the world.

Program Modules

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 manufacturing innovation.

Module 2:

Analyzing Data: A Visualization Approach

Explore visualization tools at the convergence of manufacturing expertise and data science expertise; use time-series analysis to understand FrED.

Module 3:

Modeling to Make Sense of Data

Build block diagrams and process 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; compare 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 in sports and medicine; consider 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 the best fit for a model.

Module 9:

Statistical Process Control

Apply statistical process control to a manufacturing setting; integrate deterministic and random variation; relating control charts on FrED.

Module 10:

Advanced Data Analytics

Work with datasets derived from the manufacturing process; gain a deeper categorizing of neural networks, decision trees, and correlation analysis.

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 manufacturing innovation.

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 2:

Analyzing Data: A Visualization Approach

Explore visualization tools at the convergence of manufacturing expertise and data science expertise; use time-series analysis to understand FrED.

Module 7:

Applications of Machine Vision

Explore applications of machine vision to video search in sports and medicine; consider applications of machine vision in additional contexts.

Module 3:

Modeling to Make Sense of Data

Build block diagrams and process models to examine and improve FrED; explore how the length of a production run can affect results.

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 the best fit for a model.

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 9:

Statistical Process Control

Apply statistical process control to a manufacturing setting; integrate deterministic and random variation; relating control charts on FrED.

Module 5:

Control of Manufacturing Processes

Explore manufacturing process control, the role of feedback, process modeling, and monitoring; compare actual versus predicted dynamics.

Module 10:

Advanced Data Analytics

Work with datasets derived from the manufacturing process; gain a deeper categorizing of neural networks, decision trees, and correlation analysis.

Note: While we make every effort to share accurate information, this curriculum is subject to change at the discretion of MIT faculty and its learning team.

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Faculty

Faculty Member Dr. Brian W. Anthony

Dr. Brian W. Anthony

Associate Principal Research Scientist, MIT Institute of Medical Engineering & Science; Principal Research Scientist, MIT Mechanical Engineering; Director, Master of Engineering in Manufacturing Program, MIT; Co-Director, Medical Electronic Device Realization Center, Institute of Medical Engineering & Science; Associate Director of MIT.nano, MIT

With more than 25 years of experience in product realization, Dr. Anthony designs instruments and techniques to monitor and control physical systems. His work involves systems analysis and design, calling upon mechanical, electrical, and optical engineering, along with computer science and optimization. More info

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

Get recognized! Upon successful completion of the program, MIT Professional Education grants a certificate of completion to participants. This program is scored as a pass or no-pass; participants must receive 80 percent to pass and obtain the certificate of completion.

Participants will be awarded 6.0 continuing education units towards professional development.

Download Brochure

Note: After successful completion of the program, your verified digital certificate of completion will be E-mailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of MIT Professional Education.

Still Have Questions?

  • How do I know if this program is right for me?

    This program is right for you if…

    • You want to learn the organizing principles of smart manufacturing using real data to create statistical models for a feedback loop of continuous improvement.
    • You work in a manufacturing environment that is seeking to eliminate pain points and improve efficiency by exploring technologies such as sensors and machine vision, and you want to learn the latest methods from an industry-leading expert.
    • You are comfortable with mathematical and statistical concepts typical of engineering or data science backgrounds.

    Are there any prerequisites for this program?

    This program includes a technical element, and participants will need to quickly learn how to visualize data using Excel. However, the 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.


    What is the typical class profile?

    MIT Professional Education’s online programs draw professionals from around the globe, from every industry imaginable. This program is designed for technical professionals from a wide variety of industries, including industrial goods, electronics/hardware, healthcare, IT services, consulting, aerospace, defense, and energy. Please see the program brochure for more details on the participant profile and representative companies.


    What are the learning requirements for passing this program?

    This program is scored as a pass or no-pass; participants must complete 80% of the assignments to pass and obtain the certificate of completion from MIT Professional Education. Elements that contribute to the score are the assessments (which can be completed multiple times, if needed), the application exercises, and engagement with the discussion boards.


    Are there continuing education units offered?

    Yes! This program offers 6.0 continuing education units. To learn more about continuing education units visit MIT Professional Education’s website.

  • How much time is required each week?

    You will need to dedicate approximately 4-6 hours per week. While this will vary for each person somewhat, you can expect to devote a few hours to watching the video lectures, an hour for contributing to discussion boards and reflecting on your learning, the live faculty webinars held on certain weeks, and 1-2 hours for application exercises. There will also be a resource library on the learning platform for you to access additional resources at your convenience.


    What types of assignments will be included in this program?

    Some examples of the type of assignments in this program are:

    • Calculating the moving average and plotting amplitude
    • Creating histograms and time series/frequency plots
    • Evaluating sensors for accuracy and repeatability
    • Identifying and evaluating sources of variation (raw material, equipment, operator, environmental) in a manufacturing setting

    The machine used as the teaching tool is a fiber extrusion machine (FrED). What if my equipment is different?

    We fully expect that the equipment and processes of your production environment will be different than what is used in this program. FrED is used as a teaching tool that serves to illustrate the organizing principles of smart manufacturing, such as using sensors and cameras to collect, and then analyze, data. You can take these principles and apply them to your own situation.


    What is it like to learn online with MIT?

    It’s interactive, flexible, and designed to include personal attention so that you can reach your learning goals more effectively. Participants are highly encouraged to contribute to the discussion boards to enhance their own learning, and to enhance the learning of others. It’s a community of learners who are generally excited to share and grow their knowledge. Here are a few elements that make it unique:

    • There will be live sessions with MIT faculty and/or learning facilitators with Q&A, so that you can get your questions answered in real time.
    • Learning facilitators monitor the discussion boards to keep things moving along and offer insights and advice. These are individuals with domain expertise who help supplement the knowledge from the recorded videos and live teaching sessions.
    • Live office hours with Learning Facilitators are offered regularly throughout the program to address questions or ask for clarification on the learning concepts.
    • There is no group work requirement for this program, but peer learning is achieved through the discussion boards.

    Can I interact with MIT faculty directly?

    Yes, though live webinars you will be able to ask questions in real time. In addition, there are content experts who moderate the discussion boards, which is an essential element to facilitate learning for you and your peers from around the world.


    When are the live sessions scheduled?

    Because participants join from different time zones all over the world, we strive to offer the live sessions at times when the vast majority of participants would be able to join. Typically, that would be between 8 am and 10 am ET, with announcements going out a few days/weeks ahead of time for a live session. All sessions are recorded, so if you are unable to attend live, you will receive a link to the recording. Moderated discussion boards are designed to supplement the live sessions.


    How do I interact with other program participants?

    We believe that peer learning adds to the overall experience substantially. You can connect and communicate with other participants through our learning platform. For this program, one example of peer learning is by sharing your data visualization assignments on the discussion boards to learn from each other’s interpretations of the data.

  • What do I receive upon successful completion of the program?

    Upon successful completion of the program, you will receive a certificate of completion from MIT Professional Education. This program is scored as a pass or no-pass; participants must receive 80% to pass and obtain the certificate of completion. Elements that contribute to the score are the assessments (which can be completed multiple times, if needed), the application exercises, and engagement with the discussion boards.

    You will receive a digital certificate approximately two weeks after your successful completion of the program, once scoring is complete.

    You will also be eligible to receive 6.0 continuing education units from MIT Professional Education. To learn more about continuing education units visit MIT Professional Education’s website.


    Can I get the hard copy of the certificate?

    No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, Twitter, etc.


    Do I receive alumni status after completing this program?

    No, however you can receive 6.0 continuing education units from MIT Professional Education upon successful completion of the program, plus a certificate of completion directly from MIT Professional Education.


    How long will I have access to the learning materials for?

    You will have access to the online learning platform and all the videos and program materials for 1 full year following the program start date. This information is intended only for registered participants and access to the learning platform is restricted only to that individual per the terms of agreement.

  • What equipment or technical requirements are there for this program?

    Participants MUST have administrative control over their computers or laptops to take part in the exercises. If you are using a company computer, participants should contact their IT department to determine if they will need a loaner laptop to complete the program.

    Participants also need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access content such as documents, spreadsheets, presentations, PDF files, and transcripts.


    Do I need an active internet connection to access the program content?

    Yes, the learning platform is accessed via the internet and video content is not available for download. You can download files of video transcripts, assignment templates, readings, etc., however, the video lectures must be streamed via the internet.

  • What is the program fee and what forms of payment do you accept?

    • The program fee can be seen at the top of this page and payment is accepted only in US dollars.
    • Payment can be made online through credit/debit cards: Visa, MasterCard, and Amex

    What if I don’t have a credit card – is there another mode of payment accepted?

    Yes, you can do the bank remittance in USD via wire transfer.


    Is there an option to make flexible payments for this program?

    Yes, the flexible payment option allows a participant to pay the program fee in installments. This option is made available in the payment form and should be selected before making the payment.


    Does the program fee include taxes? Are there any additional fees?

    Yes, the program fee is inclusive of any taxes with the exception of GST for Singapore residents.

  • Withdrawals and Refunds

    You may request a full refund up to 7 days of your payment or 14 days after the program commences, whichever comes later. If your enrollment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to: admissions@emeritus.org


    Deferrals

    After a cohort commences, you can request to change to a future cohort of same program within 50% of program completion. A deferral request must be submitted along with a selected reason and explanation. Cohort changes may be made only once per enrollment and is subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period and the limit of one deferral per enrollment remains. All deferral requests should be sent to: admissions@emeritus.org

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