International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

In this article, the authors describe the development process of a custom internal combustion engine (ICE) for a vehicle competing in the Shell Eco-marathon. The engine will be designed to replace the Honda GX35 previously used in the vehicle. The new engine has to comply with competition regulations and improve the overall fuel efficiency of the vehicle. An engine test stand was developed for measuring the power and brake-specific fuel consumption (BSFC) of small IC engines which allowed tests to be carried out on the GX35 to collect data for the design. Based on the data obtained from the tests and the information gathered from educational materials, a suitable IC engine will be later developed.

The aim of this research is to develop and implement a smart microfactory concept for use in engineering studies as well as for the overall promotion of technical studies at TTK Tallinn University of Applied Sciences. The microfactory allows students to directly engage with a small-scale manufacturing cycle which includes many of the processes found in an actual industrial factory, such as production planning, material handling, quality control and production feedback and optimisation. Pencil sharpening was chosen as the production task. For this purpose, several devices were designed and manufactured which utilise a variety of different sensors and a collaborative robot UR3. The production unit also incorporates a manufacturing execution system (MES) that students can develop and refine themselves. Thanks to a hands-on approach which combines both theoretical studies and practical experience, students are able to observe the effect of their decisions to a production process in a miniature yet realistic environment.

An increasing number of drones with a specific purpose are being developed globally. They are used in agriculture for crop monitoring and spraying, as well as in national defence, border control, etc. Time-consuming and expensive monitoring and tracking activities can be performed more efficiently in terms of time, cost and safety. The aim of this research is to develop an unmanned aerial vehicle (UAV) platform equipped with onboard artificial intelligence capability for automated monitoring of roads and roadsides. Roadside monitoring is intended for road sections where the presence of a human supervisor is unreasonable or limited by safety standards. The UAV will be set to fly along a predetermined route without pilot intervention. By using machine vision, road sections where defects have appeared are identified and recorded for later human inspection. The solution developed as a result of this study can be adapted for industrial use, for example, maintenance monitoring of conveyors or large storage areas on the premises of factories.