| Issue |
MATEC Web Conf.
Volume 268, 2019
The 25th Regional Symposium on Chemical Engineering (RSCE 2018)
|
|
|---|---|---|
| Article Number | 02006 | |
| Number of page(s) | 6 | |
| Section | Computer-Aided Process Engineering/Process Systems Engineering | |
| DOI | https://doi.org/10.1051/matecconf/201926802006 | |
| Published online | 20 February 2019 | |
Optimization and analysis for palm oil mill operations via input-output optimization model
1
Department of Chemical and Environmental Engineering/Centre of Sustainable Palm Oil Research (CESPOR), The University of Nottingham Malaysia Campus, Broga Road, Semenyih 43500, Malaysia
2
School of Engineering and Physical Sciences, Heriot-Watt University Malaysia, 62200, Putrajaya, Wilayah Persekutuan Putrajaya, Malaysia
3
Centre for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 1004 Manila, Philippines
Corresponding author: Denny.Ng@nottingham.edu.my
A typical palm oil mill produces crude palm oil, crude palm kernel oil and other biomass from fresh fruit bunches. While the milling process is well established in the industry, insufficient research and development has been done on analyzing the operational performance of a mill. Factors such as operating time and fruit availability affect the performance of a palm oil mill (e.g., capital, operating and labor costs). This paper presents an input-output model to optimize the operations of a palm oil mill based on maximum economic performance. Following this, feasible operating range analysis (FORA) is performed to study the utilization and flexibility of the process. A palm oil mill case study in Malaysia is used to illustrate the proposed approach. Based on the optimized results, it was found that 37% reduction in capital cost and 49% increase in economic performance is achieved. Meanwhile, the utilization index of the mill during peak season increases from 0.48 to 0.76.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.