Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria
The proposed model of the neural network describes the task of planning the assembly sequence on the basis of predicting the optimal assembly time of mechanical parts. In the proposed neural approach, the k-means clustering algorithm is used. In order to find the most effective network, 10,000 netwo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/21/10414 |
| _version_ | 1797411002503921664 |
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| author | Marcin Suszyński Katarzyna Peta |
| author_facet | Marcin Suszyński Katarzyna Peta |
| author_sort | Marcin Suszyński |
| collection | DOAJ |
| description | The proposed model of the neural network describes the task of planning the assembly sequence on the basis of predicting the optimal assembly time of mechanical parts. In the proposed neural approach, the k-means clustering algorithm is used. In order to find the most effective network, 10,000 network models were made using various training methods, including the steepest descent method, the conjugate gradients method, and Broyden–Fletcher–Goldfarb–Shanno algorithm. Changes to network parameters also included the following activation functions: linear, logistic, tanh, exponential, and sine. The simulation results suggest that the neural predictor would be used as a predictor for the assembly sequence planning system. This paper discusses a new modeling scheme known as artificial neural networks, taking into account selected criteria for the evaluation of assembly sequences based on data that can be automatically downloaded from CAx systems. |
| first_indexed | 2024-03-09T04:38:41Z |
| format | Article |
| id | doaj.art-0dbe4c5ebfe34499ace77773711ef69b |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T04:38:41Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0dbe4c5ebfe34499ace77773711ef69b2023-12-03T13:23:34ZengMDPI AGApplied Sciences2076-34172021-11-0111211041410.3390/app112110414Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected CriteriaMarcin Suszyński0Katarzyna Peta1Institute of Mechanical Technology, Poznan University of Technology, 60-965 Poznan, PolandInstitute of Mechanical Technology, Poznan University of Technology, 60-965 Poznan, PolandThe proposed model of the neural network describes the task of planning the assembly sequence on the basis of predicting the optimal assembly time of mechanical parts. In the proposed neural approach, the k-means clustering algorithm is used. In order to find the most effective network, 10,000 network models were made using various training methods, including the steepest descent method, the conjugate gradients method, and Broyden–Fletcher–Goldfarb–Shanno algorithm. Changes to network parameters also included the following activation functions: linear, logistic, tanh, exponential, and sine. The simulation results suggest that the neural predictor would be used as a predictor for the assembly sequence planning system. This paper discusses a new modeling scheme known as artificial neural networks, taking into account selected criteria for the evaluation of assembly sequences based on data that can be automatically downloaded from CAx systems.https://www.mdpi.com/2076-3417/11/21/10414assembly sequence planning (ASP)modellingartificial neural networks |
| spellingShingle | Marcin Suszyński Katarzyna Peta Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria Applied Sciences assembly sequence planning (ASP) modelling artificial neural networks |
| title | Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria |
| title_full | Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria |
| title_fullStr | Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria |
| title_full_unstemmed | Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria |
| title_short | Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria |
| title_sort | assembly sequence planning using artificial neural networks for mechanical parts based on selected criteria |
| topic | assembly sequence planning (ASP) modelling artificial neural networks |
| url | https://www.mdpi.com/2076-3417/11/21/10414 |
| work_keys_str_mv | AT marcinsuszynski assemblysequenceplanningusingartificialneuralnetworksformechanicalpartsbasedonselectedcriteria AT katarzynapeta assemblysequenceplanningusingartificialneuralnetworksformechanicalpartsbasedonselectedcriteria |