optimization of evaporation process in sugar …...optimization of evaporation process in sugar...

International Journal of Modern Trends in Engineering

and Research www.ijmter.com

e-ISSN No.:2349-9745, Date: 2-4 July, 2015

@IJMTER-2015, All rights Reserved 998

Optimization of Evaporation Process in Sugar Industry for Developing

Intelligent Control Strategies

Sebastian George1, Devendra N. Kyatanavar

2

1Department of E &TC Engineering, SRES’s College of Engineering, Kopargaon-423603, MS, India,

[email protected] 2Principal, SRES’s College of Engineering, Kopargaon-423603, MS, India

Abstract— Production of sugar contains a number of unit operations, out of which the most energy

consuming one is the evaporation process. The evaporators used in sugar industries have multiple

effects connected in series. It is used to raise the concentration of sugar cane juice from a nominal

value. While developing the control strategies for such systems, two major objectives to be

considered are concentration of sugar cane juice and steam economy. In this paper, the development

of a simulation model of an evaporator having four stages is attempted. The model is developed in

MATLAB based on the mass and energy balance at different effects. For proper understanding of the

evaporator dynamics and validation of simulation model, data are collected from different sugar

factories located in the state of Maharashtra, India. For analyzing the evaporation process, the

simulation model is subjected to a set of trials for different values of feed temperature and mass flow

rates of steam and feed. The model is further optimized using Taguchi technique. The optimized

model can be used for analysis and synthesis of intelligent control strategy on which research is in

progress.

Keywords- concentration of sugar cane juice; evaporation process; optimization; steam economy,

taguchi technique.

I. INTRODUCTION

Sugar is India‟s second largest agro-processing industry and India is among the largest producers and

consumers of sugar in the world. About 45 million Indian farmers and their families are dependent

on the cultivation of sugar[1]. Production of sugar from sugar cane route has been an age of old

practice and the technology has been fairly stabilized in India for quite some time. Sugar plant

automation packages are available now a days for improving Steam Fuel economy and quality of

sugar. Juice flow stabilization system, Lime Sulphitation pH control system, Vapour stabilization

system etc. are examples of such packages.

Vapour stabilization system is meant for automatic control and maintaining rate of vapour to the pan

section. In a sugar plant, due to non conventional operations of batch pans, the pan floor steam

consumption will always be a fluctuating demand [4]. It will affect the functioning of evaporator

stations by disturbing the pressure difference of respective bleeding effects and also preceding

effects. With fluctuating demand of pans, the vapor pressure in second effect followed by first effect

tends to fluctuate which ultimately affect the exhaust steam pressure. These fluctuations in exhaust

and vapor pressure affect the rate of evaporation in first and second effect bodies, thus resulting in

fluctuations in syrup brix which further causes variation in steam demand at pan stations. This

International Journal of Modern Trends in Engineering and Research (IJMTER)

Volume 2, Issue 7, [July-2015] Special Issue of ICRTET’2015


further aggravates the fluctuation in the vapour and exhaust steam pressures. Thus it becomes a

vicious cycle.

II. MULTIPLE EFFECT EVAPORATOR

Out of a number of unit operations involved in sugar production, the most energy consuming unit is

the evaporation process [2]. The main function of evaporator is to raise the concentration (brix ) of

sugar cane juice from a nominal value of say, 15 wt % to syrup with the brix of 72 wt %. As such,

the economy of sugar manufacturing depends strongly on the evaporation process because of the

huge amount of thermal energy (steam) required during the process.

2.1 MEE Dynamics

The evaporator process under study here has four effects as shown in Figure 1. Each effect in the

process is represented by a number of variables which are related by the mass and energy balance

equations for the feed, product and vapor flow for forward feed [5]. There are two basic equations of

mass and energy balance which are solved for each effect to get the values of mass flow rate of

product ( mP ) and total water evaporated ( mE ).

Figure. 1 Quadruple Effect Evaporator




2.2 Modeling

The quadruple effect evaporator system used at Bhogawati Sugar Industry, Kolhapur, MS, India has

been studied extensively and observations are carried out on all the four effects. A Simulink model

based on the mass and energy balance equations has been prepared and tested. Figure 2 shows the

same.

Figure. 2 Simulink Model

Table 1 summarizes the brix values for different mass flow rates of steam.

Table No. 1. Concentration for different steam mass flow rate

Sr. No. Ms %

Concentration

Sr.

No.

Ms %

Concentration

1 16000 0.44 12 18200 0.61

2 16200 0.45 13 18400 0.63

3 16400 0.46 14 18600 0.66

4 16600 0.48 15 18800 0.69

5 16800 0.49 16 19000 0.71

6 17000 0.5 17 19200 0.74

7 17200 0.52 18 19400 0.78

8 17400 0.54 19 19600 0.82

9 17600 0.55 20 19800 0.86

10 17800 0.57 21 20000 0.9

11 18000 0.59

Table 2 shows the input output values obtained from the model which are in tune with the actual

values obtained from the Bhogawati Sugar Industry.




Table 2. Input output values

III. OPTIMIZATION

In fact, the model does not predict reasonable steady state values of the output variables as measured

on the actual plant. It is therefore necessary to tune the model parameters to get reasonable steady

state predictions [3]. Due to severe mass and energy interaction among the effects, this model tuning

is very difficult. An approach based on Taguchi technique has been used to extract the plant

parameters and optimize the model.

3.1 Taguchi Technique

Tagauchi technique is a statistical method initially developed for improving the quality of goods

manufactured. Later its application was expanded for many other fields in Engineering. This

technique involves identification of proper control factors to obtain the optimum results of the

process [6]. Orthogonal Arrays are used to conduct a set of experiments and these experiments are

used to analyze the data and hence optimize the model. Here an attempt has been made to

demonstrate the application of Taguchi technique to improve steam economy and concentration

(brix) of sugar cane juice.

3.2 Taguchi Trails

Figure 3 shows the trials carried out on the Simulink model based on the Taguchi L9 Orthogonal

arrays shown in Table 3. The parameter values for this trials are given in Table 4.

Table 3. Taguchi L9 Orthogonal array

Feed Temp(0C) Ms (kg/hr) Mf (kg/hr)

Trial No 1 50 22500 90000

Trial No 2 50 23000 100000

Trial No 3 50 23500 110000

Trial No 4 65 22500 100000

Trial No 5 65 23000 110000

Trial No 6 65 23500 90000

Trial No 7 75 22500 110000

Trial No 8 75 23000 90000

Trial No 9 75 23500 100000




Table 4. Process parameters

Level

Parameters 1 2 3

Feed Temp 50 65 75

Ms 22500 23000 23500

Mf 90000 100000 110000




Figure 3. Taguchi Trials

IV. RESULTS

Table 3 summarises the results of Taguchi trials based on the L9 Orthogonal array. Analysis of

variance for brix as well as steam economy has been carried out for the optimization of the

quadruple effect evaporator model.




Table 3. Final results

V. CONCLUSION

A mathematical model of quadruple effect evaporator is developed in Simulink and it has been

optimized using Taguchi technique. Advanced automatic control is an important factor to optimize

the MEE[4]. The main objective to minimize the energy consumption can be achieved by the

development of new control scheme using soft computing tools like Fuzzy logic, Neural networks

and Genetic algorithms. The optimized model developed here should be tested under such control

environments on which further research will be carried out.

REFERENCES [1] Amitabh Sen, “India‟s Sugar Industry”, http://www.indiaonestop.com/sugar/sugar.htm.

[2] S. Lissane Elhaq, F. Giri and H. Unbehauen, “The Development of Controllers for a Multiple-Effect Evaporattor in Sugar Industry”, http://www.cds.caltech.edu/conferences/related/ECC97/proceeds/751_1000/ECC837.PDF.

[3] Arvin V. Pitteca, Robert T. F., Ah King and Harry C. Rughooputh, “Parameter Estimation of a Multiple-Effect Evaporator by Genetic Algorithms”, Proc. Joint 2nd International Symposium on Advanced Intelligent Systems, Yokohama, Japan, September 21-24, 2004.

[4] Arvin V. Pitteca, Robert T. F., Ah King and Harry C. Rughooputh, “Intelligent Controller for Multiple Evaporator in Sugar Industry”, Procceedings of IEEE International Conference on „Industrial Technology‟ pp. 1177-1182, 2004

[5] Dhara J. Shah, C. G. Bhagchandani, “Design, Modeling and Simulation of Multiple Effect Evaporators”, International Journal of Scientific Engineering and Technology, Vol. 1, Issue 3, pp. 01-05, 2012.

[6] Srinivas Athreya, Y. D. Ventatesh “ Application of Taguchi Method For Optimization of Process Parameters In Improving The Surface Roughness of Lathe Facing Operation” International Refereed Journal of Engineering and Science, Vol. 1, Issue 3, pp. 13-19, 2012.

optimization of evaporation process in sugar …...optimization of evaporation process in sugar...

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