Research has been conducted on related machines that can meet the above three requirements. In terms of the slicing, strip cutting, and dicing of fruits and vegetables, mechanized cutting has completely replaced manual work. Agricultural machinery and equipment also need to be improved to meet the increasing demand for automated agricultural machinery. designed an intelligent control and drive system of adaptive industry 5.0 equipment for the railway industry and designed three new maintenance and test protocols, respectively. Morgan’s research showed readers the ability of next-generation industry 4.0 machines to demonstrate intelligence and reconfigurability. reviewed the basic research on these topics on the problems and challenges of reconfigurable systems (RMS) and on the related technologies and prospects of machine control and machine intelligence. proposed a communication and control architecture with a flexible assembly and a maintenance-integrated production line based on complex autonomous systems. In the process of the modern manufacturing industry’s progress from industry 4.0 to 5.0, people are now exploring technology for machine control and intelligence, trying to apply it to industries. After the adjustment, the overall dicing error was less than 10%, and the accuracy and stability were higher. The dicing error was greater than 15% due to the different damping coefficients of the materials and the variable speed movement.
Due to the structural limitations, the slice error was large, but the strip error as ideal. The results show that when the size of carrots and potatoes was 11 mm × 10 mm × 10 mm and 11 mm × 10 mm × 12 mm, the slice thickness and strip thickness error before improvement were 20% and 5%, respectively.
Performance tests are carried out on the prototype before and after improvement.
This paper looks at traditional three-dimensional fresh-cutting machines and, apart from analyzing the force-and-motion equation to determine the minimum rotational speed of the roller, the cross-cutting tool’s independent drive system, the speed detection system of the material before dicing, and shaft-speed monitoring have also been analyzed in order to develop precise control technology for three-dimensional fruit and vegetable dicing by considering dicing input-speed detection and by fine-tuning the cross-cutting tool’s dicing speed. It is hard to control the dicing size of current fresh-cutting devices for fruits and vegetables precisely, and this can be influenced by complex working environments.
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