This work deals with cost optimization in cement production using Particle Swarm Optimization (PSO) modeling and the results was compared with Genetic Algorithm (GA) and Pattern Search (PS). The process took into account mixtures of primary fuel (mineral coal, pet-coke and heavy oil), alternative fuel which are agricultural waste (rice husk, sugar waste and ground shell) and the raw materials used. The simulation models predict the cost benefit of using alternative fuel to the manufacturer and the quality of the final product. Sugar cane waste (X9) generates 80% - 99% of the specific energy needed to produce one ton of clinker. Production cost for one ton of cement using PSO is $23 = (4945naira), GA $33= (7095naira), PS $38.2 = (8170naira). The oxides in the final product met standard cement specification: i.e. Silica Modulus (M.S-2.9), Alumina Modulus (M.A= 1.3), Lime Saturation factor (LSF=93.3%). The research further shows that the cost of cement production can be reduced by 30-70% with the use of alternative fuel (Rice husk, Sugar cane waste, ground nut shell) and without greatly affecting the final product.
Book Details: |
|
ISBN-13: |
978-613-9-94399-9 |
ISBN-10: |
613994399X |
EAN: |
9786139943999 |
Book language: |
English |
By (author) : |
Joseph Sunday Oyepata Omotayo |
Number of pages: |
152 |
Published on: |
2018-11-21 |
Category: |
Mechanical engineering, manufacturing technology |