In response to the imperative of sustainability and resource efficiency, this article introduces an innovative framework for the remanufacture of hydraulic drive system components, firmly rooted in the tenets of the circular economy. This method mixes cutting-edge additive manufacturing technologies, meticulous 3D scanning techniques, and the rigorous discipline of reverse engineering to rebuild active elements within hydraulic drive systems. Fundamental to this framework is a resolute commitment to the repurposing of non-defective components, fostering a closed-loop system that systematically curtails waste generation and significantly diminishes the environmental footprint associated with hydraulic drive system maintenance. This article presents a meticulous examination of the remanufacturing process for a flowmeter, elucidating the intricate integration of additive manufacturing technology and the precision of 3D scanning to restore a previously damaged rotor. Through this interdisciplinary approach, we aim to elucidate the manner in which contemporary engineering practices can be harnessed to catalyze circularity, enhance resource efficiency, and increase sustainability within industrial operations. By demonstrating the efficacy of additive manufacturing and reverse engineering in hydraulic system remanufacturing, this article contributes significantly to the discourse on sustainable engineering methodologies, underlining their pivotal role in shaping a more environmentally conscientious, circular economy.
This article presents novel research on the utilization of a neural-network-based time control system for microwave oven heating of food items within a solar-powered vending machine. The research aims to explore the control of heating time for various food products, considering multiple variables. The neural network controller is calibrated through extensive experimentation, allowing it to accurately predict optimal heating times based on input parameters such as food type, weight, initial temperature, water content, and desired doneness level. The results demonstrate that the neural-network-controlled microwave oven achieves precise and desirable heating durations, mitigating the risk of overheating and ensuring superior food quality and taste. Moreover, the solar-powered vending machine showcases a commitment to sustainable energy sources, effectively reducing dependence on non-renewable energy and minimizing greenhouse gas emissions. To maintain food quality and freshness, a food refrigeration unit is integrated into the vending machine, employing load-balancing technology to control the refrigeration chamber’s temperature effectively. Energy efficiency is prioritized in both the refrigeration unit and the microwave oven through intelligent algorithms and system optimization. The combination of a neural-network-controlled microwave oven, a solar-powered vending machine, and a food refrigeration unit introduces a novel and sustainable approach to food preparation and energy management.
The article presents several current methods of remanufacturing hydraulic components, a trend that is encouraged, on the one hand, by concerns about reducing material consumption in the context of the circular economy - some of these materials being expensive or in short supply. On the other hand, remanufacturing by modern methods can lead to a decrease in energy consumption in the devices concerned, due to obtaining shapes that are difficult to achieve by classical procedures. Among the remanufacturing processes considered there are additive manufacturing, metal coating, reverse engineering, etc. An important step in the remanufacturing process is testing of components, which certifies the achievement of performances at least equivalent to those of the original products. To this end, the article presents a test bench solution with the help of which tests can be carried out on hydraulic devices such as hydraulic pumps and (linear or rotary) motors, hydraulic directional control valves or other types of valves.