Operations research methods for the sheet metal industry
The Flexible Sheet Metal Working research group, part of the Department of Mechanical Engineering of KU Leuven, houses an interdisciplinary team of engineers and applied scientists focusing on different aspects of manufacturing processes and systems for flexible sheet metal production. The group mainly targets systems suitable for versatile small series production, thus facilitating highly customized products, often tailored to individual end-users. For this purpose, the research group develops process technology as well as software systems: from CAD, over automated process and production planning systems to fully automated CAM systems. The present focus is mainly on laser cutting, incremental forming and air bending, as well as on the integration and optimization of those processes. For the development of the different optimization algorithms, the research group is closely associated with the Centre for Industrial Management offering joint guidance for algorithmic developments and other topics related to operations research.
Moreover, the Flexible Sheet Metal Working research group works in close collaboration with major industrial partners under long-term strategic alliance agreements. This assures the relevance of the conducted research from both academic and industrial points of view. Eventually, industrially viable research output is implemented in robust commercial products by these industrial partners, thus providing opportunities for extensive validation and evaluation.
During this project, the candidate will have the opportunity to investigate the potential application of operations research techniques for optimal strategic and tactical production planning in sheet metal workshops (manufacturing facilities that produce sheet metal parts according to make-to-order or make-to-stock principles). The project will be conducted in close collaboration with a major developer and manufacturer of machines and software for flexible sheet metal working.
At discrete points in time during their existence, sheet metal workshops face fundamental decisions with far-reaching implications for their competitiveness in the long term: How many press brakes to buy? Investing in robotized bending cells? Number of laser cutting machines required? Size of the workshop? Such crucial decisions could be encompassed within the strategic capacity planning problem, which is a critical problem in most manufacturing companies as it typically involves substantial capital resources and long payback times. However, whereas advanced optimization frameworks are common for strategic capacity planning in other sectors, such decision support tools are not widely available for the sheet metal industry. In order to improve the competitiveness of sheet metal workshops, the candidate will investigate the development of a decision support tool that will allow workshops to determine the optimal number and type of machines that the workshop should ideally have to fulfill the forecasted demand with minimum cost and minimum number of late deliveries over the coming years. Since substantial differences are noted between usual manual press brakes and novel robotized bending cells, the difference in the production capabilities of those machines will have to be investigated as well.In principle, robotized press brakes will be greatly beneficial for large batches, although the exact potential will depend on the geometry and the characteristics of the part that has to be produced. As a result, the candidate will also investigate the problem of optimal assignment of bending jobs to manual/robotized press brakes with limited production capacity, where each bending job is defined by the geometry of the bent part and the number of units to be produced. In order to perform sensible assignments, the candidate will explore the application of machine learning for the estimation of setup and production time in those press brakes.
The combinatorial nature of the considered problems together with the industrial and process requirements result in the need for clever optimization techniques to assure a reasonable calculation time. Although the challenges to solve during this project are substantial, the candidate can count on the support of operations research and manufacturing specialists to develop the necessary algorithms. These algorithms will be implemented up to a level that validation based on real datasets can be accommodated. The ultimate goal is that the developed algorithms will lead to new decision-support tools and frameworks that end users (sheet metal workshops) can apply to increase their efficiency and productivity.
Genuine interest and knowledge in operations research methods and object-oriented programming are required for this vacancy. Analytical thinking, critical thinking and problem-solving skills are essential to succeed in this role. Familiarity with the implementation of (meta-) heuristic optimization methods is an advantage. Affinity with manufacturing processes in general and sheet metalworking in specific will assure a solid motivation. Working knowledge of robotics and machine learning tools are also valued. Applicants should have distinguished themselves academically to be considered. Please provide full grade transcripts to document this, as well as proof of English language proficiency.
KULeuven is a top hundred university with a strong research and innovation tradition. The research will be conducted in close collaboration with industrial partners, maximizing the societal relevance of the work and assuring the valorization of the research achievements. The candidate will have the opportunity of doing a PhD partially based on this project.
The university offers attractive financial conditions equivalent to the salary level of an engineering professional with 1-4 years of experience and full healthcare benefits. More information on working conditions and salary (scale 43):
Leuven as a city offers a very dynamic and lively living environment in an enjoyable historic setting close to Brussels, in the centre of Europe.
For more information please contact Prof. dr. ir. Joost Duflou, mail: email@example.com.You can apply for this job no later than January 02, 2023 via the online application toolKU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.
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