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Process simulation, exergy analysis and optimisation of palm oil milling process using aspen plus


Citation

Mohd Nadzim, Ummi Kalsum Hasanah (2020) Process simulation, exergy analysis and optimisation of palm oil milling process using aspen plus. Doctoral thesis, Universiti Putra Malaysia.

Abstract

One of the main concerns in Malaysian palm oil industry is the energy consumption issue which may jeopardize the sustainability of palm oil milling process as an energy-intensive process. Apart from reducing the oil loss during processing, it is crucial to determine whether the energy of the process is utilised efficiently and sustainably. The production of crude palm oil (CPO) involves a complex process influenced by the processing variables and environmental factors. To evaluate the relationship of oil loss and processing variables and also energy aspects of the CPO production, it is important to assess the performance of various unit operations in the palm oil milling process. Therefore, application of simulation tool is seen as an alternative and sustainable approach to resolve the abovementioned issues. Thus, this study performed a steady state process simulation of palm oil milling process using ASPEN Plus V8.6. By considering assumptions and limitations of the process, modelling and simulation of palm oil milling process was successfully conducted. The simulation model of palm oil milling process was validated with the results obtained from experimental analyses based on the component composition in several streams, namely oil, water (moisture), glucan and xylan contents through absolute error. It was found that most of components have error values below 5%. All the outlet streams from the simulation model were also compared with the estimated process mass balance retrieved from the palm oil mill and defined by absolute relative deviation. It was found that most streams have deviation values below 10% and between 10-15%. This indicated that the actual results were in good agreement with model prediction, although some unit operations indicated limitation during validation. Subsequently, exergy analysis of each unit operation of palm oil milling process was also conducted, where the physical exergy was obtained from the ASPEN Plus, and the chemical exergy and exergy of mixing were determined from the calculations. The exergy analysis revealed that steriliser has the highest exergy destroyed (69%) among other unit operations, signifying opportunity to improve the energy use of milling process. Thus, process optimisation was conducted using Central Composite Design (CCD) of response surface methodology (RSM) coupled with ASPEN Plus to investigate the effect of varying pressure (3-7 bar), sterilisation time (20–120 minutes) and steam mass flow (20–45% of FFB) on carbohydrate degradation and exergy destroyed of the sterilisation process. Results showed that glucan and xylan degradations producing glucose and xylose, respectively, were the highest at 5 bar pressure, 17550 kg/hr steam mass flow and 70 min sterilisation time with minimum exergy destroyed of 3493.9 MJ/hr. Under these conditions, the energy loss was reduced by 33.6% compared to that of conventional sterilisation conditions (5259.3 MJ/hr) at 3 bar pressure, 14500 kg/hr steam mass flow and 90 min sterilisation time. It can be inferred that the application of simulation tool such as ASPEN Plus is able to assist in predicting the performance and the use of energy of complex and energy-intensive process sustainably. The energy consumption of palm oil milling process could be effectively reduced using more appropriate operating conditions.


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Additional Metadata

Item Type: Thesis (Doctoral)
Subject: Oil palm - Research
Subject: Exergy
Subject: Palm oil - Milling
Call Number: ITMA 2021 2
Chairman Supervisor: Prof. Robiah Binti Yunus, PhD
Divisions: Institute of Advanced Technology
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 14 Jul 2022 05:02
Last Modified: 08 May 2023 03:41
URI: http://psasir.upm.edu.my/id/eprint/98071
Statistic Details: View Download Statistic

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