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PhD Scholarship in Improving Overall Equipment Efficiency in Silicon Crystal Growth Production with Digital Manufacturing Technologies

Technical University of Denmark - Department of Mechanical Engineering

Qualification Type: PhD
Location: Lyngby - Denmark
Funding for: UK Students, EU Students, International Students
Funding amount: Not Specified
Hours: Full Time
Placed On: 3rd December 2019
Closes: 5th January 2020

The Section for Manufacturing Engineering at the Department of Mechanical Engineering, Technical University of Denmark, performs research based on a multi-disciplinary use of process technology, materials science, solid and fluid mechanics, and thermodynamics in the analysis, modelling and development of manufacturing processes. The research objective of the Section is to promote ‘Precision Manufacturing’ to meet the performance, durability, reliability, size, and cost requirements of modern products. 

The Section for Manufacturing Engineering at the Department of Mechanical Engineering, Technical University of Denmark, has an open position in the field of “Improving overall equipment efficiency in silicon crystal growth production with digital manufacturing technologies”. Topsil GlobalWafers has a full scale production facility and all work will address real production challenges.

The PhD project is carried out in the framework of the Horizon2020 Marie-Curie Innovative Training Network DIGIMAN4.0 “DIGItal MANufacturing Technologies for Zero-defect Industry 4.0 Production”. Please look at the project website ( before reading further. The PhD project is related to the Early Stage Researcher (ESR) position no. 3 of the DIGIMAN4.0 project. 

Responsibilities and tasks

The position focuses on research in the area of precision manufacturing engineering and manufacturing digital technologies, with focus on IoT, Big Data analytics, system integration, simulation and autonomous robots. It is the goal for the current PhD project to develop in-depth root-cause analysis and detailed Pareto analysis of failure mode using big data approach to achieve intelligent predictive maintenance. 

The project will require the integration and development of necessary manufacturing and digital technologies enabling advancements in the process capability and optimization of pure silicon wafers industrial production. 

The PhD project will have the following objectives: 

  • Intelligent use of big data to in-depth analysis of machine failure mode and increase availability of critical equipment
  • Develop a model for accurate control of the product specifications and to optimize production costs.
  • Implement a vision system data fusion for an improved process control/measurement and reduced number of failures due to human errors. 


Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. 

  • M.Sc. in Mechanical Engineering, Computer Science or Business informatics
  • Knowledge about statistical quality control methods (e.g. statistical process control, design of experiment, big data analytics)
  • Knowledge and experience with programming
  • Knowledge and experience with algorithms for Massive Data Set
  • Knowledge and experience with digital manufacturing technologies such as e.g. computer vision system, simulation
  • Knowledge and experience with measuring technologies and quality control methods
  • Ability to work independently, to plan and carry out complicated tasks, and to be a part of a large, dynamic group
  • Good communication skills in English, both written and spoken

Special requirements: Mobility and experience

At the time of recruitment, the Early Stage Researcher (ESR) must not have resided or carried out his/her main activity (work, studies, etc.) in Denmark for more than 12 months in the 3 years immediately prior to his/her recruitment under the project (January 2020).

Eligible candidates must be, at the time of the recruitment, in the first four years of their research career and have not been awarded a doctoral degree.


To apply, please read the full job advertisement at 

Application deadline: 5 January 2020 

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* Salary has been converted at the prevailing rate on the date placed
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