stillingsbetegnelse:
PhD Project on Model Predictive Monitoring, Control and Optimization of Injection Molding Processes

jobbeskrivelse:
DTU Compute invites applications for a 3-year PhD position starting November 1st 2015. The goal of the PhD project is to improve the quality of objects produced by injection molding. We will do this by combining model predictive methods for monitoring, control and optimization with new sensor technology and injection molding process knowledge. Therefore, the position is interdisciplinary and will be conducted in collaboration with DTU Compute, DTU Mechanical Engineering and LEGO. The PhD candidate will be employed in the Scientific Computing section of DTU Compute (Department of Applied Mathematics and Computer Science) at the Lyngby Campus of DTU. The PhD candidate is expected to also spend time at DTU Mechanical Engineering (Lyngby Campus at DTU) for pilot plant tests and equipment development as well as at LEGO in Billund for industrial tests and measurement campaigns. The project is part of the Manufacturing Academy of Denmark (MADE, http://www.made.dk) and the PhD student is expected to participate actively in dissemination of results to the partners of MADE. Description of the PhD project Injection molding enables low cost production of complex elements in large volumes. Injection molding is used in many industries including the toy industry and at LEGO. In the toy industry, the production process successively expands in shape complexity and number of cavities. Because of this, the continuous at-line monitoring of element quality and the production process is essential to be able to compensate for small changes in environment and material properties together with wear of the mold. Being able to monitor the products and the process is important for reducing the fraction of scrapped products. Furthermore, new sensor technologies combined with mathematical/statistical models enable model predictive technologies and will be used to control and optimize the quality such that the product quality parameters become significantly more consistent despite variations in process conditions and feed material. In this PhD project we investigate, develop and implement methods for model predictive monitoring, control and optimization of element quality parameters and the process in injection molding. The system must be applicable for predictive maintenance and able to improve element quality and reduce scrapped elements. Advances in sensor technology, model predictive control technology, and servo electric injection molding machines have enabled such systems. These advances open an opportunity to obtain insight in the manufacturing process with real-time data (e.g. temperatures, speed, pressures, etc.) used in the molding process. The PhD project will focus on combining these advances in a model predictive quality control system for high product quality and predictive maintenance. The tasks in the PhD project includes •Literature survey of sensor technologies and quality control systems for injection molding. •Developing a good understanding of state-of-the art within process control on injection molding platforms by participation in courses and summer schools with topics in both model predictive control and precision manufacturing. •Develop a prototype system for predictive monitoring, model predictive control, and model based optimization •Test of the prototype system by simulation. •Develop a mathematical/statistical model that relates injection molding machine parameters to quality parameters. This includes development and application of methods for experimental design and participation in obtaining data used to build the mathematical/statistical models. •Participate in measurement campaigns for injection molding at DTU Mechanical Engineering and at LEGO •Implementation and test of the developed quality control and predictive maintenance system for injection molding machines at DTU Mechanical Engineering and at LEGO. •Documentation and dissemination of the results in papers published in international peer-reviewed jou

Arbejdsgiver Navn: Danmarks Tekniske Universitet

Arbejdsgiver telefonnummer: 45252525

Arbejdsgiver faxnummer: 45881799

Job kort beskrivelse:
Undervisning og forskning på universiteter og højere læreranstalter

land: Danmark

region: Hovedstaden

Kontrakt varighed: Fast

Kontrakttype: Fuldtid

krævede uddannelse: Ikke angivet

Kilde til jobtilbud: AMS, Offentlige arbejdsformidlinger, Danmark