control systems can be integrated. There are various methods
that can be adopted. This may involve highly disparate
approaches, as the following enumeration of the most important
• cognitive algorithms like artificial neuronal networks,
fuzzy logic and also hybrid systems
• adaptive systems
• prediction systems
• self-learning systems (machine learning)
• Cloud learning, though here a balance has to be found
between Cloud knowledge and data protection
If this is maximally optimised, we shall in future achieve
self-organising systems that intelligently optimise their
production and CIP schedules to suit the product involved,
and perform a cleaning routine only when it’s
actually needed. Systems of this kind, however, are still
in their infancy, but will in the next few years exert an
increasing influence on the food and beverage markets.
In conclusion, this means that an intelligent optimised
strategy for a CIP system, and its design, should
incorporate the following:
• Cleaning/Hygiene concept: application-tailored (CIP)
cleaning program to suit the line, product and production
• Line concept: harmonised CIP cleaning for the entire line
at the touch of a button
• Cleaning optimisation: provision of additional options to
handle anticipated problem cases
• Cleaning-optimised design: fast cleanability is factored in
directly at the design stage
• Intelligent, demand-responsive cleaning: intelligent
programming and sensors ensure that the entire line is
cleaned as needed
• Cleaning documentation for hygiene certification: altered
regulations may compel the client to provide detailed
documentation of the cleaning success
The results clearly show that a suitable CIP strategy can be
defined in particular through definitions of the stipulations
and requirements applying for the cleaning success desired.
Embedded in the framework and boundary conditions of the
production facility concerned, an optimal design of the CIP
system can be determined. Basically, a line cipping system is
always a holistic concept that begins with hygienic design and
in which correct utilisation of materials and components must
not be neglected, which covers the entire production process
and ends with evaluation of the cleaning success. Demand-responsive
cleaning and the concomitant intelligent cleaning
regimes will in future gain steadily in perceived importance.
The future will open up all options offered by digitalisation.
However, it has to be said that many of these are still in their
infancy. But that’s the opportunity that has to be seized.
1 Zacharias, J.: “Auslegung von CIP Anlagen”, presentation
at the EHEDG seminar on Cleaning-in-Place
of Pipes and Tanks, Hygienic Design Processes Part I,
2 Zacharias, J.: “Prozessdesign bei Membranprozessen
und Reinigungsstrategien in der Wasseraufbereitung aus
der Sicht eines Anlagenbauers der Getränkeindustrie”,
presentation at the 15th FEI Cooperation Forum: Reinigungsstrategien
für die Getränkeindustrie, Bonn, 2016.
3 Zacharias, J.; Feilner, R.: “Optimierte CIP-Anlagenauslegung
– Ein ganzheitliches Konzept”, BRAUWELT No. 45,
S. 1329 - 1332, 2017.
4 Zacharias, J.: “Intelligente Reinigung – Sichtweisen eines
führenden Getränkeanlagenherstellers”, presentation at
the VVD-Workshop FutureClean 2018: Digitalisation of
Cleaning”, IVLV and Fraunhofer IVV, Dresden, 2018.
5 Zacharias, J.: “Strategie für optimierte CIP-Anlagenauslegung”,
presentation at the Food Safety Forum, TÜV
South, Munich, 2019.