- Tytuł:
- Multiobjective optimization of multipass turning machining process using the Genetic Algorithms solution
- Autorzy:
-
Amiolemhen, Patrick Ejebheare
Eseigbe, Joshua Ahurome - Powiązania:
- https://bibliotekanauki.pl/articles/95335.pdf
- Data publikacji:
- 2019
- Wydawca:
- Politechnika Koszalińska. Wydawnictwo Uczelniane
- Tematy:
-
turning process
genetic algorithms
minimum production cost
minimum production time
single-objective model
multi-objective model
toczenie
proces toczenia
algorytmy genetyczne
minimalny koszt produkcji
minimalny czas produkcji
model wielokryterialny - Opis:
- The study involves the development of multi-objective optimization model for turning machining process. This model was developed using a GA - based weighted-sum of minimum production cost and time criteria of multipass turning machining process subject to relevant technological/practical constraints. The results of the single-objective machining process optimization models for the multipass turning machining process when compared with those of multi-objective machining process model yielded the minimum production cost and minimum production time as $5.775 and 8.320 min respectively (and the corresponding production time and production cost as 12.996 min and $6.992, respectively), while those of the multi-objective machining process optimization model were $5.841and 9.097 min. Thus, the multi-objective machining process optimization model performed better than each of the single-objective model for the two criteria of minimum production cost and minimum production time respectively. The results also show that minimum production time model performs better than the minimum production cost model. For the example considered, the multi-objective model gave a lower production time of 30.0% than the corresponding production time obtained from the minimum production cost model, while it gave a lower production cost of 16.46% than the corresponding cost obtained by the minimum production time model.
- Źródło:
-
Journal of Mechanical and Energy Engineering; 2019, 3, 2; 97-108
2544-0780
2544-1671 - Pojawia się w:
- Journal of Mechanical and Energy Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł