Prediction of Sugar Yield From Sugar Cane using Process Modeling : Current School News

Prediction of Sugar Yield From Sugar Cane using Process Modeling

Prediction of Sugar Yield From Sugar Cane using Process Modeling.

Abstract

A study was undertaken to developed a model that will be used to predict sugar and the by-products from sugar cane.

The model developed from MATLAB was used to predict the sugar, bagasse, filter cake and molasses yield from sugar cane.

The predicted values from the model were compared to yield data obtained from the production of sugar cane from the Savannah Sugar Company, Numan, Nigeria for 90 days.

The analysis of variance (ANOVA) at p ≤ 0.01 was used to determine if there were significant difference in the yield predicted by the model and the measured factory yield. The F-LSD at p ≤

0.01 was used to separate the means. The model is validated where there was no significant difference between its predicted yield and the factory-obtained yield.

The sugar cane input of 2,150.52 MT was obtained from the Savannah Sugar factory. The corresponding imbibitions water pumped into the mixed juice was 673.12 MT.

The predicted sugar, bagasse, molasses and filter cake yield using the MATLAB model was 279.5MT (13%), 1,049.46MT(48%), 111.828MT(5.2%) and 101.1MT(4.7%) respectively.

The ANOVA showed that there was no significant difference between the MATLAB model and the factory-based model. It is concluded that the ANOVA validated MATLAB model for sugar yield prediction.

Consequently, this model is recommended for use in predicting sugar and by-products yields from sugar cane.

Table Of Contents

Title Page     i

Approval Page          ii

Certification          iii

Dedication             iv

Acknowledgments          v

Abstract                 vi

Table of Contents              vii

List of Tables            xi

List of Figures              xii

List of Plates       xiii

CHAPTER ONE

  • Introduction 1
  • Objectives 6
  • Justification 6

CHAPTER TWO

  • Literature Review 8
  • The Sugarcane Plant 8
  • Sugars 14
    • Classification of Sugar into Types 16
    • Reducing Sugars 19
    • Other Types of Sugar and their Sources 20
  • Sugar Cane Processing 22
    • Bagasse 22
    • Filter Cake 23
    • Molasses 23

2.4.0 Quality Control          24

  • Clarification of Soluble or Insoluble Impurities in Mixed Juice 25
  • Phosphate as a Clarification Agent 27
  • Flocculation 27

2.6.0  Pollution Control               28

2.7.0 Thermal Behavior of Sugar Extraction Process               29

2.8.0  The Concept of Mathematical Modeling Equations         30

2.9.0  Stages of Modeling                   32

  • Classification of Models 35
  • Classification Based on time Reference 36
  • Classification Based on the Degree of Certainty 36
  • Classification Based on Structure: 37
  • Classification Based on Function or Purpose 38

2.11.0  Classification of Mathematical Models         39

2.12.0 Sugar Yields                    39

2.13.0  Some Applications of Mathematical Models             40

2.14.0 Mathematical Modeling of Motion Systems      41

2.15.0  Programming for Systems Analysis          42

2.16.0 MATLABB         43

2.17.0  Application of MATLAB in Systems Modeling            44

  • Review of Existing Models Related to Sugar Manufacture 44
  • Thaval and Kent 44
  • Lauret et al 46
  • Sotudedeh-Gharebagh et tal 48
  • Saurez et tal 49
  • El-Belgiti and Vorobiev 50
  • Thaval and Kent Mass Balance Model 51

2.19.0  Mass and Energy Balance           53

3.20  Prevailing Extraction Theory         54

3.21.0  Extraction Performance Parameters        55

3.22.0 Filling Ratio         55

3.23.0 Reabsorption Factor         56

3.24.0 Imbibition Coefficient        58

  • Status quo and Main Knowledge gap in the Study of Sugar

yield from Sugar cane         58

  • Main Knowledge Gap in the Study of Yields of Sugar from Sugar cane 60

CHAPTER THREE

  • MATERIALS AND METHODS 61
  • General 61
  • The Savannah Sugar Company, Numan 63
    • Description of Sugar Production Plant 64
    • Milling Department 64
    • Processing Department 64
    • Laboratory 64
  • Determination of Sugar Yield 64
  • Determination of Bagasse Yield 65
  • Determination of Filter cake Yield 66
  • Determination of Molasses Yield 66
  • Development of Models 67
    • The MATLAB Simulation Model 67

3.7.2.1  Source Code of the Model Developed for the MATLAB Simulation           68

3.7.3  Validation of the Models       69

  • Milling Process 70
  • The Milling Train 70

3.9  Analysis of Sugar Prediction Model using MATLAB Software      70

CHAPTER FOUR

  • RESULTS AND DISCUSSION 75
  • Results 75
  • Discussion 75
    • The Comparative Behavior of Factory Versus Predicted Sugar Results 75
  • Results and Discussion of Bye Products of Sugar 78
    • Bagasse 78
    • Filter cake (scum or mud) 80
    • Molasses 81
  • Analysis of Variance (ANOVA) Discussions 82

CHAPTER FIVE

  • SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 84
  • Summary 84
  • Conclusion 85
  • Recommendations 86
  • Contributions to the Literature/Knowledge 86

REFERENCES        87

Introduction

Background Of Study

Sugar, particularly edible sugar is a global item found in the recipes and menus of the diets consumed in almost every home.

It is a major product of sugarcane processing. Sugar cane contributes well about 100% of all the sugar manufactured in Nigeria.

However, sugar can also be manufactured in other parts of the world from other plants such as sugar beets (Atiku, 1999).

Industrial cultivation and processing of raw and refined sugar in Nigeria is currently being undertaken by Savannah sugar company, Numan; Bacita sugar company (now Josepdam Sugar Company), Dangote and Bua refineries in Apapa Lagos.

These companies import raw sugar and manufacture white sugar from it to complement the requirements demanded by the Nigeria populace.

The process of manufacturing sugar from sugarcane is a very interesting subject given the merits of this exercise. It presents us with the advantages of realizing the production of the primary product as well as bagasse, filter cake, molasses, and so on.

Of greater interest still is the need to have an instrument through which the sugarcane weighed to be grinded can be used to predict the end sugar that it can yield as well as the amount all the important bye products realizable.

References

Alder M. D.(2001). An Introduction to Mathematical Modelling. Heavens for For Books.com.Pp193-110.
Ale S. O.(2011). Matlab/Scilab For Data Analysis And Visualization: Platform For
National    Development    National    Centre    for    Equipment Maintenance     & Development (NCEMD) Equip. Maintenance Course, Vol. 5, pp.11-16.
Antoine, R. (2000). Sugar Industry Training Center, Maurituis Pp4-12.
Arrascaete, A. and Friedman, P.(1987). Energy Management – Bagasse drying. International Sugar Journal Vol. 89 No.1060 Pp68 -71.
Atiku,  N.A.(1999). Strategies for  Achieving Self-sufficiency in Sugar Production in Nigeria, Focus on Savannah Sugar Company, Numan, Adamawa State. Pp1-10
Barnes, A. C. (1974). The Sugarcane: Leonard Hill Books

 

 

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