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https://open.uns.ac.rs/handle/123456789/3535
Title: | Dynamic optimization of the cam-lever mechanism for thermoforming machine tool driving | Authors: | Čavić, Maja Penčić, Marko Rackov, Milan Knežević, Ivan Zlokolica M. |
Issue Date: | 1-Jan-2017 | Journal: | Lecture Notes in Mechanical Engineering | Abstract: | © Springer International Publishing AG 2017. Considering that the most important use of thermoforming is in the production of plastic packaging for the food and pharmaceutical industry, it is essential that formed products remain sterile through the entire thermoforming process. Most machines used for thermoforming have a tool holder with one degree of freedom-DOF, which allows only vertical motion of the tool. After the thermoforming process, the formed products are ejected from the tool with compressed air, which may cause contamination and/or deformation of the products. We propose a working mechanism for driving the tool, which, compared to conventional machines, guarantees both a shorter working cycle and sterility of the formed products during the entire process. Products are punched out after forming and accepted and transported with an adequate mechanism to the manipulation module, where they are sorted and packed. This paper presents a dynamic optimization of the thermoforming machine working mechanism with 2 DOFs which consists of two cam-lever mechanisms that enable translation, rotation and complex motion of the tool. Based on the set of technical requirements, kinematic synthesis of the cam-lever mechanism is performed. SVAJ diagrams for the cams and the dimensions of the lever mechanism links are defined. Based on the kinetostatic analysis, a dynamic model of the cam-lever mechanism is formed and the driving torque for both lifting and rotation of the tool is determined. The optimization problem is formed and the objective function is defined as the minimization of the required driving torque. Based on the set constrains, a dynamic optimization is performed using the method of genetic algorithm. By comparing the results before and after optimization, it is concluded that the driving torque is lower by 50.3%. | URI: | https://open.uns.ac.rs/handle/123456789/3535 | ISSN: | 21954356 | DOI: | 10.1007/978-3-319-56430-2_13 |
Appears in Collections: | FTN Publikacije/Publications |
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