Optimization of Energy Usage in Roughing Turning Using Firefly Algorithm Method
The development of industry in Indonesia is currently increasing, one of which is the manufacturing industry that can affect the economic development of Indonesia. However, this affecting of the high use electrical energy as the main energy for the engine. It its development, green manufacturing is...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/21180 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The development of industry in Indonesia is currently increasing, one of which is the manufacturing industry that can affect the economic development of Indonesia. However, this affecting of the high use electrical energy as the main energy for the engine. It its development, green manufacturing is a solution to reduce the negative impact of the manufacturing industry that affecting environtment, all of this is part of sustainable development of manufacturing. Lathes as one of the most widely used machines in the machining process will be analyzed of its performenace by energy usage in particular lathe process. This case will be optimized to reduce energy usage that can harm environtment. In the process, there will be energy modelling of the parameters process turning related to the energy consumption process, it will be done by using multivariable regression method so that it will get the objective function of energy. Furthermore, the firefly algorithm method will be used in optimizing the process energy to remain low at certain material removal rate (MRR). Based on the optimization results, will be obtained new parameters process that will be validated by experiment to get the actual energy process which later will be evaluated into the score of new energy decrease. Specific energy consumption (SEC) indicators will be used in determining energy levels on an engine based on certain material removal rate levels The objective function of the energy is obtained and has a trust level of 98%. The energy degradation score based on the optimization result against the reference curve is 74% and defective of 7,5% from the previous data that obtained in different paper. This proves that the process of energy optimization is successful |
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