TOD Controls Engineer

Day to Day Responsibilities

• Establish goals and objectives in conjunction with Group Leader and manage the engineering activities in electrical and control system to achieve the said objectives.
• Support operations personnel via trouble shooting and provide training as needed.
• 提供项目负责人ship for facility processes - including feasibility studies, planning, AR sponsorship, complete documentation, i.e., generally accepted project management guidelines.
• Design, modify, and recommend equipment types to meet or exceed customer requirements in operation control.
• Lead developments and propose engineering programs in electrical and control engineering that can improve or enhance the current process capabilities.
• Major areas are in (but not restrict to) cut room and 2nd packing (link to inner packing) facilities.

Education & Experiences

• Ph.D. or Masters (+3 years of manufacturing experience) in Chemical, Mechanical or Electrical Engineering discipline.
• Direct experience with data analysis, machine learning (ML), advanced controls technologies and/or first-principles/physics-based modeling.

Required Skills

• Evaluate existing process control strategies and propose and develop enhancements. Utilize multivariate statistical methods and machine learning for process monitoring, fault diagnosis and isolation, defect classification, and/or predictive maintenance;
• Design and develop process controls solutions (especially model-based control techniques) for manufacturing processes. Work closely with manufacturing to develop appropriate hardware and software platforms for implementing control solutions;
• Familiarity with optimization theory and controls technologies such as optimal control, robust control, adaptive control, model predictive control (MPC), non-linear approaches, and traditional PID control;
• Experience with developing data-driven (system identification) / physics-based models (finite element models, mass and energy balances, etc.) for manufacturing process optimization;
• Extensive knowledge of ML techniques/algorithms (e.g., neural networks, random forests, etc.) and their mathematical foundation;
• Proficient in Matlab/Simulink and working knowledge of Python, C/C++, .NET;
• Must have:

(1) a thorough understanding of relevant scientific concepts, principles, and theory, particularly relating to general machine learning and algorithms and fundamental physics principles;

(2) experience demonstrating broad application of those concepts in real-world settings.