Mendoza Trejo, Omar
- Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences
Research article2022Peer reviewedOpen access
Lopez Rojas, Arturo D.; Mendoza-Trejo, Omar; Padilla-Garcia, Erick A.; Morales, Daniel Ortiz; Cruz-Villar, Carlos A.; La Hera, Pedro
Forestry cranes are of paramount importance in forestry operations, so considerable efforts have been carried out to improve their performance in recent years. However, all these efforts have focused on automation technology, leaving aside other alternatives for improvement. Among these alternatives is model-based design, which has the potential to be game-changing for the forest industry. Because research on model-based design is almost non-existent for forestry cranes, there are many gaps that should be filled before presenting improved designs of forestry cranes. The purpose of this article is to fill two of those gaps: (1) the high cost-benefit ratio and safety concerns when testing new designs, components or algorithms in industrial-scale forestry cranes and (2) the dynamic modeling of forestry cranes as mechanical systems with closed kinematic chain. Under these premises, this article first presents a reduced-scale platform resembling a forwarder crane with closed-kinematic chain, where the components of the mechanical structure are manufactured with 3D printing technology, and second, the modeling and experimental validation of the reduced-scale forwarder, where the closed kinematic chain is considered as a system of multiple constrained open kinematic chains. For the experimental validation, a comparison between both experimental and simulation results is presented. Results presented in this article broaden the options to design and test new concepts and/or technology to improve forestry cranes performance.
Forestry cranes; dynamic modeling; 3D printing; simulations; experimental validation
Mechanics Based Design of Structures and Machines
2022, Volume: 51, number: 12, pages: 6748-6773 Publisher: TAYLOR AND FRANCIS INC
Forest Science
DOI: https://doi.org/10.1080/15397734.2022.2063889
https://res.slu.se/id/publ/116894