Abstract
This investigation confronts the note-worthy improvement configuration gap in which such a design method could be better focused on the multi-objective optimization design of a compliant gripper mechanism as a robot arm through an effective hybrid algorithm of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS). We found that the proposed bi-algorithm approach is more compelling than theoretical ideas like auxiliary shape changes, materials, and directors of mechanisms when designing the compliant gripper mechanism with a set of novel multi-objective optimization design recently. In particular, it explores whether the compliant gripper mechanism shapes affect picking things up. In this unique study, we considered displacement values and the frequency values as response parameters during the simulation and the optimization design process. To test the effectiveness of the optimal design method, we proposed an initial compliant gripper mechanism carried out through the numerically experimental matrix—the Box–Behnken design. After that, we simulated the numerical model by utilizing the finite element method incorporating the approaches of desirability function, fuzzy logic system, and ANFIS. The results turn larger than those of the previous approaches. Moreover, numerical results reveal that the suggested hybrid method has a computational exactness more conspicuous than that of the Taguchi method. In short, the principle accomplishments with variables to the compliant gripper mechanism optimization design can be summarized up as follows: (i) the promising and potential proposed approach could meet the clients’ prerequisite, (ii) the idea of multi-objective optimization design ought to be re-considered when designing compliant gripper mechanism as well as applying related designing fields at the diminished expenses and the shortage time.
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Abbreviations
- 2D:
-
Two-dimension
- 3D:
-
Three-dimension
- ANFIS:
-
Adaptive neuro-fuzzy inference system
- ANOVA:
-
Analysis of variance
- BCM:
-
Beam constraint model
- CGM:
-
Compliant gripper mechanism
- DOF:
-
Degree of freedom
- FEA:
-
Finite element analysis
- FEM:
-
Finite-element-method
- FIS:
-
Fuzzy inference systems
- DFA:
-
Design for assembly
- FLS:
-
Fuzzy logic system
- GRA:
-
Grey relational analysis
- TMFL:
-
Taguchi method and fuzzy logic
- LAPO:
-
Lightning attachment procedure optimization
- MOO:
-
Multi-objective optimization
- MPCI:
-
Multi-characteristic performance index
- SR:
-
Scott-Russell mechanism
- TLBO:
-
Teaching learning-based optimization algorithm
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Acknowledgements
The authors acknowledge and thank the Ministry of Science and Technology of the Republic of China for their partial financial support of this study under Contract Number MOST 108-2221-E-992-028.
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TVTN: Data curation, methodology, visualization, validation, investigation, and writing—original draft, and software. NTH: Data curation and models. N-CV: Data analysis and software. VDNK: Data collection and editing. S-CH: Conceptualization, methodology, review, and editing.
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Nguyen, T.V.T., Huynh, NT., Vu, NC. et al. Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: fuzzy logic and ANFIS. Microsyst Technol 27, 3389–3412 (2021). https://doi.org/10.1007/s00542-020-05132-w
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DOI: https://doi.org/10.1007/s00542-020-05132-w