Smart Manufacturing Introduction, Smart Manufacturing in the context of Additive Manufacturing, Data Analytics and AI, Human-machine interaction, augmentation, Smart Digital Supply Chain, Executing a Smart Manufacturing Pilot Project.

Professionals with a technical background and/or education in engineering, manufacturing, and data/information technologies.

With this credential, learners will establish a foundational understanding of Smart Manufacturing, from the core underlying technologies to its impact on an organization and its people. Intended for anyone in a manufacturing company seeking to understand how modern technologies are being applied to drive value for the business. This credential will help define Smart Manufacturing in terms that can be translated into operational business value.

• Senior leaders in plant management and operations roles are responsible for business decisions and the financial bottom line.
• Design and manufacturing engineers seeking to learn about data and modeling in a manufacturing environment.
• Production plant supervisors and managers who are responsible for data flow, capture, storage and system modification for greater process flows and production improvements.
• Junior level operations and line specialists who are committed to a career in manufacturing and having a greater understanding of the changes in the future of the industry.
• Consultants who want to add value around the latest technology transformations in manufacturing.

Practical Pathways to Smart Manufacturing / Industry 4.0 – Smart Manufacturing, its business value, and practical technologies and techniques.  The difference between Industry 3.0 and 4.0. Developing a practical modernization roadmap based on your current capabilities. Resources available to help manufacturers.

The Impact of IIoT Sensors & Platforms Applied to Smart Manufacturing – Learn how Smart Manufacturing can be implemented at low cost without the need for advanced infrastructure and  skills. Hands-on examples and demonstrations of successful business use cases.

Plant managers and executive leaders. Those in charge of Continuous Improvement (CI), Digital Transformation, and Lean Initiatives. Associates, engineers, managers, and supervisors in Operations, Quality, Production, Maintenance, Automation, and IT

Introduction to Smart Manufacturing; Using sensors in FrED extrusion machine for Data Capture, Visualization, Analysis, and Modeling; Control of Manufacturing Processes; Machine Vision and manufacturing applications; Model Fitting and Sensitivity Analysis; Statistical Process Control; Advanced Data Analytics

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.

Smart Manufacturing Introduction. Streaming Data from Device to the Cloud.  Smart Factory Floor OT/ITSystem. Machine Vision for Quality Inspection.

Any graduate student in Engineering can take this class.

This course covers the Smart Manufacturing definition, characteristics and principles. An overview of the Industrial Internet of things software stack and a specific focus on the MQTT protocol. The course also demonstrates a hands-on-guided activity on implementing MQTT with Node-Red and MQTT with Python using the Python library – Paho-Mqtt library.

Engineers who are interested in learning MQTT Protocol and the SparkPlug Specification that enables a core data infrastructure required for Smart Manufacturing implementation.

Smart Manufacturing Essentials. Industrial Internet of Things. Data Analytics and Machine Learning. Digital Twin Development and Implementation.

Professionals with a technical background and/or education in engineering, manufacturing, and data/information technologies.

Examples of current Smart Manufacturing practices.  Application of critical thinking, communication, problem solving, ideation, and teamwork. Quality principles including planning, assurance, control, and improvement. Data analysis and visualization for decision making. Examples in digital lean manufacturing, digital design tools, and basics of digital twins.

Individuals looking to enter the manufacturing field with little to no current experience in traditional or digital manufacturing or those who are looking to grow, strengthen or refresh fundamental future-ready skills needed to be competitive in the field.

Smart Manufacturing Introduction. Data Collection Fundamentals, Cybersecurity, How Smart Manufacturing is related to Business Strategy, the convergence of IT and OT, IIoT, Big Data, Digital Thread, Digital Twin, Analytics, AI/Machine Learning, Workforce Augmentation, Digital Lean, Continuous Improvement and Digital Supply Chain.

Professionals with a general background in manufacturing and information technologies.