PhD Position in SureROB: Lightweight and additive manufacturing optimised cycloidal reducer
Listed on 2025-12-22
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Engineering
Robotics, Manufacturing Engineer
Location: Town of Italy
Organisation/Company Università degli Studi di Napoli Federico II Department Department of Industrial Engineering Research Field Engineering » Mechanical engineering Engineering » Materials engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Italy Final date to receive applications 15 Jan 2026 - 23:59 (Europe/Berlin) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Jul 2026 Is the job funded through the EU Research Framework Programme?
Horizon Europe - MSCA Reference Number DC2 Marie Curie Grant Agreement Number Is the Job related to staff position within a Research Infrastructure? No
Development of efficient, safe, green, and reconfigurable manufacturing systems requires seamless integration between software and hardware solutions, requiring cooperation between experts from different fields. The project aims to make advancements in green manufacturing systems through collaborative robots (CoBots), making them viable for SMEs. The field of robotics faces the challenge of a disconnect between experts from computer science that provide generic solutions and the end-users that work and interact with the hardware.
By bridging this gap to enable the development of lightweight, efficient, and sustainable CoBots, SureROB will holistically train skilled researchers to contribute to European manufacturing. Through a well-balanced consortium of renowned academic bodies and industrial partners from seven countries, SureROB will develop and benchmark industrially feasible solutions. The focus would be not only to make the manufacturing process sustainable but also address the sustainability of manufacturing CoBots themselves.
Green tools and techniques will be developed. An important target would be achieving up to 20% reduction in the weight of the robot's components (drives and arms), resulting in lower energy consumption without compromising on the system reliability and robustness. Structural and geometric optimisation of the drives and arms will be investigated to improve the dynamic behaviour and efficiency with software-based design solutions.
These will be supported with vibration control strategies working in sync with optimised path planning and condition monitoring strategies. Numerical and experimental evaluation of the developed solutions will be conducted for benchmarking them against the reference system. SureROB will address the cost and impact of existing technologies to make them economically feasible and eco-friendly, and will actively disseminate the results, engage with the public, and promote open science.
the DC2 Project
A precision reducer for a robot joint is an important component that governs the accuracy of machining and collaborative robots. A cycloid reducer is one of the best candidates among precision reducers, considering both the structural compliance and kinematic accuracy of the machining robots.
The optimization of cycloids, for high performance robots, involves many parameters: clearance, deformation, accuracy, backlash, stiffness, load capacity, etc. Such optimization of multi-parameter processes must be combined with low weight and small volume constraints. Hence, this optimization process can be even facilitated using scaling laws.
Nowadays, such optimized configurations can be better achieved with innovative additive manufacturing techniques. Specifically, the tooth profile can be studied to reduce the transmission error, the overall geometry can be optimized to address the carrying capacity of the reducer, its NVH and fatigue characteristics.
In addition, the new and sustainable manufacturing technologies can allow an investigation on the possibility of having a flexible cycloid disc to mitigate backlash or, more generally, can lead to a material optimization to accomplish all the above-mentioned requirements.
The project will focus on a topological optimization to analyze the best reducer configuration. This optimization will also consider the capability of additive manufacturing for the realization of prototypes. The developed prototypes…
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