Some Case Studies Indicating the Benefits Derived
- Ball Mill Optimisation : A cement plant had three cement
mill circuits producing PPC and PSC and none of them was operating at its rated
capacity. They tried to optimise them in every conceivable way and ultimately
commissioned our services for analysis and optimisation. Upon using our softwares
BMSIMUL, CLASANAL and
SIZEANAL, it was discovered by us that fundamentally, it was not a
grinding problem at all! It was essentially a heat transfer problem and accordingly,
using these softwares (BMSIMUL considers heat
transfer in mill circuits in great detail), alternative operating strategies were worked
out. These resulted in increased throughputs of 30% thereby enabling them to achieve
higher than rated throughputs. It was after this that they were able to sell their
plant to an MNC for Rs. 8.2 billion.
- Classifier Bypass :
In a closed raw mill circuit operating at high air speeds, the use of CLASANAL
showed that while the classifier per se was giving a decent
circulating load of nearly 100% of its fines product stream, the total
amount circulating in the circuit was extremely low at 20% of the fresh feed
to the mill. It was therefore decided to remove the classifier
altogether from the circuit and operate the mill in open-circuit mode.
As predicted by BMSIMUL, there was
hardly any effect on the throughput but there was a significant saving in
power consumption. It was thus ironic that the classifier software CLASANAL
was used to remove the classifier! CLASANAL
is thus useful to know the classifier performance parameters and BMSIMUL
is useful to study their impact on mill circuit performance and the two
softwares together are extremely useful for evaluating possible conversion
of open-circuit mills into closed-circuit ones and vice-versa.
- Raw Mill Stabilisation and Optimisation : In one cement
plant, they were puzzled by the fact that while their Raw Mill 2 circuit was apparently
similar in all respects to Raw Mill 1 circuit at the same location, similar operating
conditions led to excessive power consumption and highly unstable operation. We were
the ones to correctly identify the "finer differences" between the two mill
circuits using BMSIMUL, CLASANAL and
SIZEANAL and optimise the RM2 circuit. This led to
not only stable operation, but also a reduction in power consumption by as much as 700 kW.
- Aluminium Ore Plant Optimisation : Their wet grinding mills
were not giving the rated outputs. Without addition of any capital equipment, purely
through simulation, we were able to effect an increase of 30% in the throughput.
However, we also gave them detailed simulations on the possible effects of installation of
hydrocyclones using our softwares BMSIMUL,
CLASANAL and HCYCLONE.
- Fertilizer Granulation Plant : The overall plant software
GRAND which includes the module RDSIMUL
for rotary dryers has been successfully used to simulate and optimise over a dozen rotary
dryers and granulation plant installations. The same has also been used to design
the whole process and sizing of equipments for a number of plants which have been
successfully commissioned and are in operation in various parts of the world. The
packages have led to significant increases in throughput, reductions in fuel and power
consumption, and improvement in product moisture content by controlling moisture
Plant Optimisation : A large NPK granulation plant had two
rotary dryers in series because the CRH value was low, only 42% at
60°C. The dryers processed about 200 t/h of 19-19-19. The solids
should not get heated up beyond 70°C at dryer outlet, otherwise they
degrade. It was shown through simulations using RDSIMUL
that indeed two dryers in series were required, to
first dry from 2.8 to 1.8% followed by 1.8 to 1.4% moisture content.
The software RDSIMUL
provided vital answers to improve the throughput by
roughly 10%. It was shown that installation of an air pre-dryer was not
useful, dryers could not be run in parallel, increasing air flow
would lead to greater dust entrainment, increasing the throughput would
lead to higher outlet moisture content, and the only option was to
increase the air temperature marginally (by 10 deg.C) with air mass-flow
rate kept constant. All the other performance and quality parameters
were also predicted by RDSIMUL
and the same were found to be acceptable and
manageable. This actually led to the throughput increasing by 10%.
Further, the plant avoided wasteful expenditure of almost USD 1 million on
an air pre-dryer which they would have installed otherwise.
Plant Optimisation : An NPK plant using up
to 30% organic materials in feed was giving a production of only 4.3 t/h
although the plant was rated for a higher capacity. The outlet solids
and gas temperatures were 72 and 88°C respectively. The rotary dryer
could dry a combined feed (including recycle of 6 t/h) of 10.3 t/h from 12
to 3.1% moisture content on wet basis. GRAND
was used to increase the plant throughput from 4.3 to 7 t/h. The
simulations indicated a low material filling of 7.7% and solids residence
time of 12 min. Since the hot air generator fan was operating at only
60% damper opening, it was suggested to increase the same to effect a 30%
increase in hot air flow, increase in hot gas temperature from 400 to
500°C, and a reduction in dryer rpm from 6 to 5 to obtain a higher material
filling of 13.6% and solids residence time of 14.8 min. The resultant
higher power consumption was fortunately possible with the same drive
motor. For a further increase in throughput to 8 t/h, it was suggested
to increase steam addition rate in granulator to enable solids entering the
dryer to be heated up to 60°C from 37°C otherwise.
- Particle Size Analysis : In one case, implementation of
resulted in a direct saving of Rs. 3 million in expensive
instruments' cost besides improvement in the operation of equipments. This case has
been published in ZKG, 41, 82-86 1988 and World Cement, 13,
38-44, Oct. 1991. The theory of the same has been published in a number of reputed
research journals including those of the American Chemical Society and summarised in our
series of technical reports on the subject.
SIZEANAL has greatly helped to understand the
extent of fines in sub-sieve ranges in a number of powders which has, in
turn, helped to optimise a number of grinding circuits. Further, the
size distributions predicted by SIZEANAL have
enabled understanding the operation of a number of classifiers (by
measuring feed, overflow and underflow) leading to their optimisation.
- Cyclone Design and Optimisation : In one process plant, for
collection of dust for pollution control purposes, a cyclone followed by a multiclone was
being employed. Yet, the emission norms were not being met. The cyclone design
was analyzed using the CYCLONE software.
Various combinations of cyclone dimensions were tried and the one that met the required
collection efficiency was chosen. With this, not only were the emission norms met,
but the multiclone was also rendered redundant. Numerous such studies have been
carried out in which the companion software SIZEANAL
been extremely useful.
- Energy Conservation Using TEAM : The implementation of
TEAM software in a cement plant led to the identification of
optimisation potential in each individual equipment, over-loading and under-utilisation of
specific equipments, identification of optimum throughput range for each equipment,
elimination of idle running of auxiliaries etc. which has guided them to effect a
reduction in overall specific energy consumption from 120 to 90 kWh/t of cement.
This improvement was gradually achieved over a period of 3 years by the plant personnel
whose diligence and commitment in implementation can not be underestimated.
- Brick Lining Life Optimisation : The refractory brick
linings in the kiln get damaged and fall which need replacement. Sometimes this can
become frequent and pose serious problems to the operation of the plant itself. In
one 0.6 million TPA cement plant, this problem was so acute that the bricks would fall within
two weeks of their laying in the kiln. The problem was analysed and traced to
faulty raw-mix design which was giving poor liquid content and coating index, and improper
estimation of coal consumption. The problem was solved using RAWMEAL
software. The brick lining life eventually reached the normal figures of 6
months enabling the plant to improve its capacity utilisation from a dismal 35% to over
- Technical Forecasting : Kiln feed is controlled by
controlling the differential pressure in cement plants. Conventionally, a linear fit
is attempted to establish the relationship using the few data available. It was
found in this plant that while most of the time, the kiln would operate stably with a
linear fit, on some days especially with low throughput, the kiln would become unstable
with the clinker getting hard-burnt. The software GITA
was used to simply determine the best "curve" for the data points. The
predictions of this curve were shown to match well with those of the straight line fit for
most of the cases (of high throughput), but the same deviated markedly for low
throughputs. Further, GITA's predictions clearly indicated
that for achieving a certain low throughput, one needed to actually set a higher
differential pressure than was being done following the straight line fit which explained
why they were getting hard-burnt clinker. A simple change from a straight line fit
to the best curve thus resulted in improved and stable kiln operation as well as avoidance
of loss of hard-burnt clinker.
- Sale Forecasting : Sale forecasting is an application where
the software GITA has been found to be extremely useful. This
has been actually done for an FMCG company making personal care and hygiene
products. Here, an innovative method was employed before applying GITA.
The "weekly sales" figures were converted into "cumulative sales till the
week" figures, which then increase monotonically with the week number. This
monotonic relationship is amenable to mathematical analysis using GITA.
The cumulative sales for future weeks can then be predicted from past values.
The sales for any future week N equals the cumulative sales predicted for week N
minus the same for week N-1. The accuracy obtained using this method was in excess
of 95%! This seems to be an excellent procedure because the influence of all the
important parameters are already factored in into the past sales figures and therefore the
future trend predicted using GITA can be used to take policy
decisions like advertisement budget, field sales personnel, sales outlets etc. This
method of sale forecasting using GITA is especially useful for
FMCG, pharma companies etc.