Society faces tremendous challenges to meet demands on efficiency, sustainability, and safety of complex processes. In the logistics and production domain Multi-Machine Engineering address these challenges with an integrated perspective that combines core (mechanical systems’) design with real-time operation and distributed machine-machine interactions.
In the track MME you develop the skills necessary to design such integrated multi-machine systems, combining science-based methodologies, with state-of-the-art tools, and hands-on lab and industrial case experience.
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Industry requires that all kinds of processes become more efficient, sustainable, and safe than ever before, in particular related to logistics and production processes. To achieve this, flexibility is needed by designing mechanical systems as large groups of interacting systems, viz., multi-machine systems. At the same time, economies of scale challenge the larger and larger physical scale at which the individual subsystems/equipment in such distributed systems can be designed. The advances in robotization, computation technology, connectedness, higher degrees of autonomy, and new energy technology are key technologies that enable new innovative design solutions for such multi-machine systems.
I took the opportunity to follow courses in smart transport, control theory and intelligent railway systems. This prepared me for my second year, in which I wanted to do research in the field that triggered me the most: intelligent transport.
The program teaches you new and innovative techniques and methods, allowing you to understand, analyse, and solve a variety of real-world problems from both a scientific as a practical point of view.
In the track Multi-Machine Engineering you develop those skills necessary to design the integrated multi-machine systems to face tomorrow’s machine design, operation, maintenance, and interaction challenges. You will grasps the fundamental ideas of widely applicable generic techniques, such as mechanical analysis, drive & energy system design, finite / discrete element modelling, mathematical optimization, distributed control, large-scale vehicle routing, dynamic and multi-agent simulation, and (industrial) systems process analysis and improvement. You will learn how to master specific tools for modelling, designing, operating, and maintaining individual machines, as well as analysing in a structured way the impact of design choices on interactions between groups of machines. Optimising the design for operational performance of multi-machine systems, taking into human limitations in the management of complex systems, and interactions between environment, material properties, and equipment/machinery is hereby the main objective.
There is a strong emphasis on solving current and foreseen challenges in industry, using both scientific, practical, and applied knowledge. Specific application cases in which you gain hands on experience with the skills developed come from ongoing scientific research and industrial practice, in particular related to challenges faced in (port) logistics, container and bulk terminals design, off-shore floating platform design, autonomous ground and ship vehicles, intelligent material handling systems, and production and distribution systems. Analytical models, detailed and validated simulation models, as well as newly developed lab facilities and on sight experiments can all be part of your studies. These types of case studies and experimental facilities are directly relevant for preparing you to optimally anticipate the currently seen developments in industry: Industry 4.0.
