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Thesis Work for Evaluation of Digital Twin based Optimization of Cyber Physical System

ABB Inc.
United States, North Carolina, Cary
305 Gregson Drive (Show on map)
Nov 29, 2025
At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we'll give you what you need to make it happen. It won't always be easy, growing takes grit. But at ABB, you'll never run alone. Run what runs the world. This Position reports to: R&D Team Lead In industry there are many possibilities to optimize process load with respect to electricity cost. This thesis work will focus on one such application, viz. mine dewatering. Generally, some kind of buffer is needed to act as "energy storage". The objective here is to validate possible savings for a longer period based on a realistic scenario (buffer sizes, electricity cost,...). A previous MSc thesis at ABB Corporate Research has studied optimization of mine dewatering. A large underground mine typically has multiple pumping stations, with a water reservoir at each level (see figure). The water reservoirs can be utilized to re-schedule pumping to time intervals when electricity prices are lower, and thus reduce the cost of electricity. The previously developed methods need to be improved and tested using real data and actual electricity prices for longer time period (> 6 months). We are also working on connecting in real-time such optimizations with the game engine Unity 3D for visualization. Details: Period: January/February - June/July 2026 (5 months) Number of credits: 30 ECTS Number of students for this thesis work: 1 Location: On-site at ABB Corporate Research in Vasteras Your role and responsibilities Research questions: Quantify the cost saving benefit of optimized water pumping Verify accuracy of simpler methods to predict optimization potential Approach: Calibrate the simulation model with real data from a Swedish mine Verify cost saving potential for longer time period (min 6 months) based on hourly and 15 minute energy market trading periods Derive a non-optimization based approach to predict savings Evaluate prediction method against rigorous optimizations Qualifications for the role Drive and interest in working with real-world use cases Background in control engineering, computer science, embedded systems, or a related field Knowledge on mathematical modelling and optimization Experience with programming in MATLAB/Simulink Good spoken and written English Self-driven and solution-oriented mindset Good soft skills and a collaborative spirit More about us Supervisor Alf Isaksson, alf.isaksson@se.abb.com, will answer all your questions about the thesis topic and expectations. Recruiting Manager Linus Thrybom, +46 730 809 906, will answer your questions regarding hiring. Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English. We look forward to receiving your application! A Future Opportunity Please note that this position is part of our talent pipeline and not an active job opening at this time. By applying, you express your interest in future career opportunities with ABB. We value people from different backgrounds. Could this be your story? Apply today or visit www.abb.com to learn more about us and see the impact of our work across the globe.