PRODUCTION SYSTEMS (PS) Curriculum
In early 2016, my colleague Maria Papadakis started developing a vision for a holistic production and operations curriculum that had sustainability and social responsibility at its core. Recognizing that the context and ecosystem for production is rapidly changing, and understanding that continuous improvement and innovation are no longer optional, we aimed to develop a curriculum that would prepare students to engage in socially responsible work in the product and service industries, at all scales of material transformation, from artisanal craft production to complex global supply chains.
The curriculum is based on the Society for Manufacturing Engineering's (SME) Four Pillars of Manufacturing Engineering, and considers the ABET requirements for manufacturing engineering and industrial engineering programs, the US Department of Labor competency model for Advanced Manufacturing, and the visionary work of the Deloitte Center for the Edge. All students are prepared to sit for the Association of Technology Management and Applied Engineering (ATMAE) certification exams for Lean Six Sigma, and two American Society for Quality (ASQ) entry-level certifications, the Certified Quality Improvement Associate (CQIA) and Certified Quality Process Analyst (CQPA).
Although the curriculum is under active development right now, here is one representation that reflects what we will offer in 2016-2017 academic year. Students are currently enrolled in the program.
Topics Include:
Systems, modeling, and architecture for production & manufacturing systems and supply chains
Sustainability, lean manufacturing, and materials selection in life-cycle engineering
Quality management and continuous improvement across the product life cycle
Automation in smart manufacturing & cognitive production systems with embedded artificial intelligence and intelligent agents
Real-time data analytics for predictive modeling for manufacturing system performance (including industrial meteorology and weather analytics)
Cyber-physical infrastructure and material information modeling for design, analysis and control of smart manufacturing systems across the product life cycle
Resiliency and recovery of smart manufacturing systems and supply chains
Industrial Internet of Things (IIoT), cloud computing, and digital manufacturing
Business model innovation, cryptocurrency, and new sources of value
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