PARTNERS: West Virginia University
PROBLEM STATEMENT: Curricula for manufacturing tends to be fragmented, without the needed continuity as students’ progress through the education system to higher levels – often with disruptions and/or different pathways. Typically, lower-level training programs often utilize training equipment focused on a specific technologies but not in the context of a working manufacturing cell or complex smart manufacturing systems.
PROJECT GOAL: Our proposal aims to address this critical gap in engineering and industrial education. We propose to create a modular and scalable curriculum that allows students of diverse backgrounds to learn in a hands-on manner how Industry 4.0 technologies and data-driven analytics are applied and utilized in a complex smart manufacturing systems context without losing scope of the details.
TECHNICAL APPROACH: To achieve this goal, we will develop novel composition framework that allows to individually create curriculum based on modules and sub-modules for the unique needs of educational stakeholders and their students in a scalable and expandable way. The idea is to provide a comprehensive series of modules for Manufacturing and Energy data analytics on top of basic smart manufacturing & foundational content. The composition framework will be designed open to allow for expansion with additional modules and content beyond the modules developed in the project.
KEY TASKS AND MILESTONES:
- T1.1 – Definition of scope for educational stakeholders
- T1.2 – Requirements elicitation (SW & HW) for ind. modules
- T2.1 – Basic module development
- T2.2 – Connectivity & mfg. data acquisition module develp.
- T2.3 – Energy data analytics module development
- T2.4 – Manufacturing data analytics module development
- T3.1 – Evaluation of individual modules
- T3.2 – Composition framework development
- T3.3 – Definition of use cases
- T3.4 – Integration in CESMII marketplace
- T4.1 – Project Management
- T4.2 – Outreach & dissemination
The key outcomes of this project include i) the Festo Didactic use case specific smart manufacturing data analytics curriculum for the CPlab enabling students to learn valuable skills in on a realistic and scalable industrial system, and ii) scalable, flexible curriculum for K12 to postgraduate education adaptable to industry specific needs (qualification 4.0) within the CESMII ecosystem and among the institutes members.
BENEFITS: The developed curricula will directly support CESMII’s institutional strategy to democratize SM to make it accessible to everyone. Each of the strategy’s core pillars is addressed: i) developing new SM knowledge in form of curricula, ii) utilize state of the art SM technology in form of the Festo Didactic CPlab, and iii) lead innovation with new system scale analytical modules.
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