Download - In-line optimization Cleaning In Place (CIP)
OptiCIP+: In-line monitoring, optimisationand control of cleaning in place
A. J. van Asselt, D. Allersma, F. Smit, G. van Houwelingen and P. De [email protected]
AbstractThe current way of CIP cleaning is in most cases
based on experience and often longer than strictly
necessar y due to the lack of reliable monitoring
tools. Currently, NIZO food research is developing a
real-time monitoring system, based on sensors and
process simulation tools. This will ensure a further
reduction of cleaning costs and an increase in
production time.
IntroductionCleaning in Place (CIP) is an important unit-
operation that is commonly applied throughout the
whole food industr y. In the dair y industr y, CIP is
applied daily for the major part of the equipment.
This ensures a constant product quality, efficient
heat transfer in heat exchangers and avoids possible
growth of micro-organisms. It is clear that a high
frequency of cleaning has a large impact on the
availability of the processing equipment and on the
environment (ennerg y use, product loss) . If cleaning
times can be reduced, production capacity will
increase without additional investments. In
addition, energ y savings and reduced product loss
can be obtained. An evaluation study in the industr y
showed that CIP procedures are based on worst case
scenarios and there is a potential for 30% saving in
cleaning efficiency.
An objective analysis is needed to evaluate whether
reduction of cleaning time is possible without
affecting product quality and safety.
OptiCIP+In order to answer this need, NIZO food research has
developed a model that is able to optimise the CIP
procedure in a food factor y. By using that CIP model
in combination with a model based process control
system (Premic), a tool is available to monitor,
optimise and control the CIP procedure. Optmisation
of cleaning prcedures is carried out in three steps:
1. Based on the actual production data, the type
of product and the temperature difference the
amount of fouling is calculated.
2. After production, a database file is searched
and depending on the degree of fouling , an
initial CIP procedure is loaded into the system.
3. During cleaning all CIP related data is linked
with the production and product composition
data and stored in a database file.
By making use of the sensor values, the CIP
procedure will continuously be optimized during
cleaning. A schematic over view of OptiCIP+ and
the different steps of the process is shown in Figure 2.
ResultsOne of the first targets within this project was to
find the right in-line sensor systems to monitor the
fouling removal. The results of the fouling removal
monitored by this in-line turbidity sensor and an
off-line turbidity device are shown in Figure 3.
Figure 3: Turbidity – in-line versus off-line – during
cleaning
The results show that the in-line measurement of
turbidity is ver y well comparable with the off-line
measurement.
The in-line measurement of calcium is currently
under investigation.
Cost reductionApplication of OptiCIP+ can result in significant cost
savings for the dair y industr y. For a company with
500 000 tons of milk processing preliminar y
calculations showed when the cleaning time is
reduced by 25% and fouling is reduced by 5%, annual
savings up to € 200 000 can be possible. With regard
to the environmental aspects 9000 GJ of energ y can
be saved and the product loss can be reduced by 550
tons.
AcknowledgementThis work has been supported by the Dutch Dair y
Association, Honeywell and the Netherlands Agency
for Energ y and Environment (SenterNovem).
ConclusionNIZO food research has developed a system, called OptiCIP+, that makes it possibleto optimize the CIP procedure in-line.By using OptiCIP+ the food industry can achieve a significant cost reduction byshorter cleaning times and higher production capacities of up to 10-20%. Thesystem is currently being demonstrated in the dairy industry.
Figure 2: Principle OptiCIP+
Figure 1: Cleaning efficiency before and afteroptimisation based on fouling removal
