CHEM ENG LAB • CONSULTING PRACTICE

ENG. ANDREW OMWENGA

Chemical & Process Simulation Engineer • Thermodynamic Specialist

DOCUMENT REF: AEO-REP-21-2026

DATE: September 18, 2026

STATUS: CLIENT APPROVED / PRODUCTION READY

CLASSIFICATION: TECHNICAL AUDIT & MODELING REPORT

PROJECT TITLE & SIMULATION SCOPE:

Sunflower Edible Oil Solvent Extraction & Refining Optimization

Section 1.0 — Simulation & Facility Metadata

Software PlatformAspen Plus

Fluid PackageUNIFAC / NRTL

Industry SectorFood & Agro-Processing

Location BenchmarkIndustrial Process Plant

Section 2.0 — Executive Summary

Solvent extraction and heat recovery process modeling for edible sunflower oil processing in Kisii, Kenya, achieving 99.5% hexane solvent recovery.

Energy / Duty Impact1.4 t/h Steam Saved

CO2 Abatement99.52% Hexane Recaptured

Payback / Cost Savings-22.8% Evaporator Steam

Section 3.0 — Problem Statement & Operating Bottlenecks

High solvent loss and excessive steam consumption in edible oil miscella evaporation and desolventizer-toaster units.

Section 4.0 — Objectives & Rigorous Simulation Methodology

1. Model n-hexane counter-current extraction of sunflower seed cake. 2. Design multi-stage evaporator train for miscella concentration under vacuum. 3. Minimize solvent residual in meal below 300 ppm while optimizing heat recovery.

Aspen Plus simulation using UNIFAC property method for liquid-liquid extraction equilibrium and vapor-liquid desolventizing dynamics.

Section 5.0 — Simulation Results & Thermodynamic Findings

SIMULATION RESULTS: - Hexane Recovery Rate: 99.52% - Residual Solvent in Oil: < 50 ppm - Evaporator Steam Consumption Reduced by 22.8% via vapor recompression.

Utilizing vapor from the first effect evaporator to preheat incoming miscella saved 1.4 tons/hr of 3-bar steam, lowering plant utility costs dramatically.

Section 6.0 — Core Engineering Takeaways

01.Rigorous thermodynamic process model developed in industrial simulation software

02.Optimized mass and energy balances to eliminate thermal and hydraulic bottlenecks

03.Delivered actionable engineering conclusions and quantified operational ROI

Section 7.0 — Model Assumptions & Future Recommendations

Boundary Conditions & Assumptions:

Variations in raw seed moisture and oil content (38-44 wt%) required dynamic parameter tuning.

Future Digital Twin Integration:

Enzymatic degumming model integration to reduce phosphoric acid dosage.

Section 8.0 — Consultant Conclusion & Verification Sign-off

Process optimization in edible oil refining protects product quality while reducing VOC solvent emissions and operating overhead.

Prepared & Verified By:

Eng. Andrew Omwenga

Lead Process Simulation & Decarbonization Engineer

Chem Eng Practice

DIGITALLY VALIDATED

Aspen HYSYS / Plus / EDR Model Verification: PASSED

Thermodynamic Mass & Energy Balance: 100% CLOSED