Optimizing energy savings of the injection molding process by using a cloud energy management system
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Abstract
The injection molding (IM) process is a widely used manufacturing process for injecting material into a mold for producing a diverse array of parts. It includes several energy-consuming procedures, such as heating plastic pellets, forcing melted polymer into a mold cavity, and cooling down the molded products. In this study, developmental factors of IM machines and processes along with energy savings progress are reviewed. In addition to several machining factors and process parameter optimizations, applying an energy management system (EMS), as well as new tools to reduce energy consumption in the IM process, has the potential for great improvements in the long term. A cloud energy management system (CEMS), called the intelligent Energy Management Network (iEN), which was launched by Chunghwa Telecom, was installed on two IM machines to illustrate the optimization of energy savings by a variable-frequency drive (VFD) and process parameter optimization. Through the recorded process dynamics, the energy usage, and product quality of the IM process using the iEN, the energy savings could be analyzed by the expert, measurement and verification (M&V) systems on the software as a service (SaaS) platform. The electricity savings on the IM machine after installing a VFD were 41.3%. Further optimization by using the one-factor-at-a-time (OFAT) approach to measure the process parameters, such as melting temperature (310.0~350.0 °C), mold temperature (110.0~130.0 °C), and clamping force (120.0~160.0 T), was carried out. The experimental and analyzed results indicated that the optimal operating conditions were at a melting temperature of 330.0 °C, a mold temperature of 120.0 °C, and a clamping force of 140.0 T. Through the optimization procedure of the process parameters carried out by the iEN, further electricity savings of 12.2% were added. Therefore, the saved electricity cost and payback period of installing the VFD and the iEN were NT$ 26,363/month and within 4 months, respectively. The saved electricity and reduced carbon dioxide (CO2) amounts were 107,200.5 kWh/year and 55,851.5 kg/year, respectively. Continuous analysis of the optimization process, energy savings, resource conservation, and waste reduction of the IM process using the iEN has shown overall benefits to the IM process, the machines, and the future decisions and designs regarding new products.
Keywords
Injection molding (IM) process Variable-frequency drive (VFD) Cloud energy management system (CEMS) intelligent Energy Management Network (iEN) Energy savings OptimizationAbbreviations
- ANN
artificial neural network
- CEMS
cloud energy management system
- EMS
energy management system
- GA
genetic algorithm
- IaaS
infrastructure as a service
- iEN
intelligent energy management network
- IM process
injection molding process
- M&V systems
measurement and verification systems
- OFAT
one factor at a time
- PaaS
platform as a service
- SaaS
software as a service
- VLANs
virtual local area networks
- VDP
variable-displacement pump
- VFD
variable-frequency driver
- VSD
variable-speed drive
Notes
Acknowledgments
Special thanks to Prof. Dasheng Lee for the useful discussions. The authors would like to acknowledge the cooperation project of “iEN, the cloud energy management service” provided by ChungHwa Telecom, Taiwan.
Funding information
The authors would like to acknowledge the financial support from the Ministry of Science and Technology (project number: NSC 103-2622-E-027-001), the Foundation of Taiwan Industry Service, and the Institute for Information Industry (Ministry of Economy Affairs, Republic of China).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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