24Dec 2019

DESIGN OF A MONITORING AND CONTROL SYSTEM IN THE BIODIESEL PURIFICATION PROCESS

  • Department of Electrical Engineering, Lhokseumawe State Polytechnic, Aceh, 24375, Indonesia
  • Department of Agricultural Industrial Engineering, IPB University, Bogor, West Java, 16002, Indonesia
Crossref Cited-by Linking logo
  • Abstract
  • Keywords
  • References
  • Cite This Article as
  • Corresponding Author

Methyl esters in the transesterification process containing impurities can cause problems when they are used and stored. Some things that are strictly related to the biodiesel purification process are the monitoring and control process. A real-time monitoring system with multiple sensors and controls in the purification process is needed to ensure temperature, pH, level and dielectric can be achieved in optimal washing and drying times. This study aims to provide a conceptual model design of monitoring and control systems in the biodiesel purification process through a needs analysis using Business Process Modeling and Notation. The conceptual model in the biodiesel purification process that was built with BPMN produced four stakeholders who integrated each other and outlined each task and rule to optimize each function. The formulation in the monitoring and control system recommends the installation of Arduino and Xbee-based sensors that can be accessed through the Local Area Network. The system has been designed to facilitate the monitoring process in real-time and accurately.


  1. Anuja P, Murugeswari T. 2013. A novel approach towards Building Automation through DALI-WSN Integration. International Journal of Scientific and Research Publications. 3(4)
  2. Bazhenova E, Zerbato F, Oliboni B, Weske M. 2019. From BPMN process models to DMN decision models. Information Systems. 83:69-88
  3. Dijkman R, Hofstetter J, Koehler J. 2011. Business Process Model and Notation: Springer.
  4. Djatna T, Anggraeni E, Sailah I. 2018. An Analysis and Design of Downstreaming Decision System on Palm Oil Agroindustry Based on Multilabel Classification. 2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS), IEEE.
  1. Elkhtem SS, Gasmelseed G, Karama B. 2014. Transfer function identification and tuning of crude distillation unit controller at Khartoum refinery-Sudan. Journal of Applied and Industrial Sciences.
  2. Fonseca RR, Frattini Fileti AM, Franco IC, da Silva FV. 2016. Experimental fuzzy/split-range control: novel strategy for biodiesel batch reactor temperature control. Chemical Engineering Communications. 203(9):1251-1259
  3. Gorantla K, Mani V. 2015. Simulink model for Zigbee transceiver using OQPSK modulation under fading channels. 2015 International Conference on Communications and Signal Processing (ICCSP), IEEE.
  4. Irzaman, Agustina A, Khabibi J. 2014. Electrical properties of Indonesian hardwood case study: Acacia mangium, Swietenia macrophylla and Maesopsis eminii.
  5. Knothe G. 2005. Dependence of biodiesel fuel properties on the structure of fatty acid alkyl esters. Fuel Processing Technology. 86(10):1059-1070.doi:10.1016/j.fuproc.2004.11.002.
  6. Ko RK, Lee SS, Wah Lee E. 2009. Business process management (BPM) standards: a survey. Business Process Management Journal. 15(5):744-791
  7. Mehta A, Duran SK. 2015. Canola biodiesel: an experimental investigation for production of biodiesel and performance measurement in diesel engine. International Journal of Research in Engineering and Technology. 4(4):535-541
  8. Noor E, Harmi L, Maddu A, Yusron M. 2015. Fabrication of nanogingerol by combining phase inversion composition and temperature. RESEARCH JOURNAL OF PHARMACEUTICAL BIOLOGICAL AND CHEMICAL SCIENCES. 6(1):38-47
  9. Noriyanto RD, Musyafa A. 2019. Reliability and safety study on heat exchanger control system: Case study in ortho xylene process-petrochemical industry. AIP Conference Proceedings, AIP Publishing.
  10. Rahayu SS, Mindaryani A. 2007. Optimization of biodiesel washing by water extraction. Proceedings of the world congress on engineering and computer science, WCECS San Francisco, USA.
  11. Rao Y, Zhao G, Wang W, Zhang J, Jiang Z, Wang R. 2019. Adaptive Data Acquisition with Energy Efficiency and Critical-Sensing Guarantee for Wireless Sensor Networks. Sensors. 19(12):2654
  12. Wali W, Cullen J, Hassan K, Mason A, Al-Shamma\'a A. 2011. Comparison between Adaptive and Fuzzy logic controllers for advance microwave biodiesel reactor. 2011 IEEE Symposium on Computers & Informatics, IEEE.
  13. Wasson CS. 2005. System analysis, design, and development: Concepts, principles, and practices: John Wiley & Sons.
  14. White SA, Miers D. 2008. BPMN modeling and reference guide: understanding and using BPMN: Future Strategies Inc.
  15. Xiaoqing Z. 2004. Self-tuning fuzzy controller for air-conditioning systems
  16. Yanfei L, Cheng W, Chengbo Y, Xiaojun Q. 2009. Research on zigbee wireless sensors network based on modbus protocol. 2009 International Forum on Information Technology and Applications, IEEE.

[Rahmawati, Taufik Djatna, Erliza Noor and Irzaman (2019); DESIGN OF A MONITORING AND CONTROL SYSTEM IN THE BIODIESEL PURIFICATION PROCESS Int. J. of Adv. Res. 7 (12). 245-256] (ISSN 2320-5407). www.journalijar.com


rahmawati gunawan
Politeknik Negeri Lhokseumawe

DOI:


Article DOI: 10.21474/IJAR01/10149       DOI URL: http://dx.doi.org/10.21474/IJAR01/10149


Share this article