TY - GEN
T1 - Multi objective optimization of vulcanization process parameters for reducing quality loss cost based on BPNN-PSO method
AU - Aji, Hardimuko Setoa
AU - Soepangkat, Bobby Oedy Pramoedyo
AU - Santosa, Budi
AU - Norcahyo, Rachmadi
N1 - Publisher Copyright:
© 2019 Author(s).
PY - 2019/6/26
Y1 - 2019/6/26
N2 - Rubber material has been used in footwear sole manufacturer for many years due to its low price and provides better physical properties. Vulcanization process is one of rubber sole manufacturing processes that affects the quality of rubber sole. Elongation at break (E) and slip resistance (COF) are some responses that are used to evaluate the performance of vulcanization process. The quality characteristics of these responses are "higher-is-better". The optimization was conducted by using backpropagation neural network method and particle swarm optimization method. Three important process parameters such as mold temperature, mold pressure, and holding time were used as input parameters. Each process parameter was set at three different levels. Hence, a 3 x 3 x 3 full factorial was used as design experiments, the experiments were replicated three times along with randomizations. The architecture of developed BPNN network had 3 neurons, which are input layer, 1 hidden layer with 12 neurons and 4 neurons in output layer. The activation functions of hidden layer, output layer and network training were tansig, purelin, and trainlm respectively. PSO optimization showed the optimal conditions were 220.93% for elongation at break and 0.174 for slip resistance, at these optimum points of mold temperature, the mold pressure and holding time were 161°C, 87 bar and 4 minutes, respectively. The total reducing loss cost of the process was IDR 507/unit or 30% of loss cost before optimization.
AB - Rubber material has been used in footwear sole manufacturer for many years due to its low price and provides better physical properties. Vulcanization process is one of rubber sole manufacturing processes that affects the quality of rubber sole. Elongation at break (E) and slip resistance (COF) are some responses that are used to evaluate the performance of vulcanization process. The quality characteristics of these responses are "higher-is-better". The optimization was conducted by using backpropagation neural network method and particle swarm optimization method. Three important process parameters such as mold temperature, mold pressure, and holding time were used as input parameters. Each process parameter was set at three different levels. Hence, a 3 x 3 x 3 full factorial was used as design experiments, the experiments were replicated three times along with randomizations. The architecture of developed BPNN network had 3 neurons, which are input layer, 1 hidden layer with 12 neurons and 4 neurons in output layer. The activation functions of hidden layer, output layer and network training were tansig, purelin, and trainlm respectively. PSO optimization showed the optimal conditions were 220.93% for elongation at break and 0.174 for slip resistance, at these optimum points of mold temperature, the mold pressure and holding time were 161°C, 87 bar and 4 minutes, respectively. The total reducing loss cost of the process was IDR 507/unit or 30% of loss cost before optimization.
UR - http://www.scopus.com/inward/record.url?scp=85068263423&partnerID=8YFLogxK
U2 - 10.1063/1.5112396
DO - 10.1063/1.5112396
M3 - Conference contribution
AN - SCOPUS:85068263423
T3 - AIP Conference Proceedings
BT - Exploring Resources, Process and Design for Sustainable Urban Development
A2 - Setiawan, Wisnu
A2 - Hidayati, Nur
A2 - Listyawan, Anto Budi
A2 - Hidayati, Nurul
A2 - Prasetyo, Hari
A2 - Nugroho, Munajat Tri
A2 - Riyadi, Tri Widodo Besar
PB - American Institute of Physics Inc.
T2 - 5th International Conference on Engineering, Technology, and Industrial Application: Exploring Resources, Process and Design for Sustainable Urban Development, ICETIA 2018
Y2 - 12 December 2018 through 13 December 2018
ER -