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Manufacturing Systems Engineering

manufacturing systems engineering

The Manufacturing Systems Engineering (MFG) track offered by the ISE department is designed to provide students with the knowledge, skills, and abilities to successfully meet the most difficult challenges of modern manufacturing industries on a global scale. The track provides engineers with detailed state-of-the-art knowledge of both traditional and advanced manufacturing technologies, systems integration techniques, economic analysis methods, and operations management practices and principles. Based upon this knowledge, students develop the ability to perform analysis, evaluation, and synthesis for a broad range of problems related to the design, implementation, and efficient operation of manufacturing systems.

Prerequisites for any manufacturing systems engineering degree are an ABET-accredited B.S. degree in engineering (or equivalent).

Students within the graduate program in the manufacturing systems engineering track are assumed to have had undergraduate courses in simulation and optimization. If this is not the case, such students must make up this deficiency by either taking the appropriate undergraduate courses or by taking graduate courses in these areas. If graduate courses are taken, they can be used in the plan of study as elective credits towards the degree requirements.

Manufacturing Engineers focus on the design and operation of integrated systems for the production of high-quality, economically competitive products. These systems may include computer networks, robots, machine tools, and materials-handling equipment.

Manufacturing science and engineering play a critical role in driving technological innovation.  Continuing its history of excellence and innovation in manufacturing, ISE is currently leading manufacturing innovation in various areas, including emerging manufacturing processes, data analytics, sensor and biosensor design and analytics, quality control, and cyber security.  ISE has expertise in: bio-manufacturing processes; process monitoring, sensing, and biosensing; sensor- and data-driven quality control; and cyber-physical security for manufacturing.  Partnerships have been formed between manufacturing faculty and partners from a variety of industrial sectors including the aerospace, automotive, transportation, healthcare, biomedical device, semiconductor and electronics, and pharmaceutical industries.

Master's Level Doctoral Level

M.S. or MEng in Manufacturing Systems Engineering

  • The Manufacturing Systems Engineering track offered by the ISE department is designed to provide students with the knowledge, skills, and abilities to successfully meet the most difficult challenges of modern manufacturing industries on a global scale. 

Ph.D. in Manufacturing Systems Engineering

  • The Ph.D. degree in Manufacturing Systems Engineering is intended primarily for those desiring to develop expertise in a particular, focused problem domain. Degreed students typically seek research-oriented industrial positions or academic appointments.

  • Sensing
  • Analytics
  • Controls
  • Automation
  • Digital Twin
  • Cyber-physical Security
  • Machine Learning
  • Artificial Intelligence
  • Data-driven Process
  • Quality Control
  • Materials MFG
  • BioMFG
  • Lean MFG

Affiliated Faculty Research & Labs

  • Process engineer
  • Data analyst/scientist
  • Quality control engineer
  • Quality assurance technician

AFFILIATED FACULTY

Natalie Cherbaka

Research Areas: Warehousing, Supply Chain, Logistics applications

Kimberly Ellis

Research Areas: Logistics and manufacturing systems analysis and design, production and process planning, applied operations research

Ran Jin

Research Areas:  Data Trade, Cyber Resilience, Manufacturing Industrial Internet

Blake Johnson

Research Areas: Biomanufacturing, Biosensing, Sensor Data Analytics, Autonomous Experimentation

Zhenyu "James" Kong

Research Areas: AI/ML for advanced manufacturing; in-situ process monitoring; closed loop control for advanced manufacturing

Andrea L'Afflitto

Research Areas:  Robust adaptive control; Data-Driven Methods; Robotics

Win Nguyen

Research Areas: On-time graduation data analytics

Prahalada Rao

Research Areas: Smart additive manufacturing, sensing, analytics

Subhash Sarin

Research Areas:  Production operations, mathematical programming and design

Laura Savage

Teaching Areas: Manufacturing systems engineering

John Shewchuck

Research Areas: Sustainable manufacturing, lean manufacturing, remanufacturing

Tao Sun

Research Areas:  Microfabrication, flexible electronics, IoT sensors