
21
CLEANING
like conductivity, colour, concentrations of CIP media
and specific aromas, fluorescence or adsorptive effects.
This broad spectrum of options still clearly shows that
currently the “only true” process variable for describing
the beginning, sequence and end of a demand-responsive
cleaning process has not as yet been found. Nor, in
view of the complexity of the systems concerned, will
it be identified in the foreseeable future. Rather hybrid
solutions will (have to) be created. Nor is it surprising
that the approaches are increasingly deploying intelligent
cognitive algorithms like fuzzy systems or artificial
neuronal networks, so as to enable fuzzy measured variables
like “clean” and “dirty”, and thus the statement
“cipping has been completed”, to be implemented and
evaluated for a functional control system.
What are the questions that need
to be posed for this purpose?
Indisputably, we are here encountering an inherent tension
between cloud-based systems that collect and evaluate
data, and draw conclusions from them, and the as
yet not-definitively-clarified problems entailed by data
protection and intellectual property rights.
Nevertheless, the necessities and boundary conditions
for intelligent CIP systems essentially remain
known variables, such as:
• minimising the initial germ count and avoiding a re-infection
• reducing intermediate storage of water to the essential
minimum
• complete-coverage cleanability of the line and its piping
• sustainability: use of alternative methods: “chemical-free
sanitisation”
• correct utilisation of materials and components with hygienic
design throughout
• aroma-resistant material (particularly seals), and in this
context no aroma migration either
• definition of fit-for-purpose CIP strategies
• embedment in the boundary conditions of the production
facility and evaluation of the cleaning process concerned
Innovative strategies are called upon to kick-start a new
approach to creating innovative, sustainable, affordable
cleaning processes for the future. The details all have to
work, that’s vital, but the process as a whole must never
be lost sight of. A balance needs to be struck! It’s always
and recurrently vital to integrate the following points
(some of them already addressed above):
• What is “just-enough-but-dependably” cleaned, and
how can the “dependably” be determined?
• So how can we achieve dependable but minimised cleaning
at need?
• What leverage points can be adjusted how far, and which
ones can’t?
• So far, there has not been a suitable, generally valid modelling
of the Sinner Circle.
• A line CIP system is always a holistic concept.
• What can innovative sensors be?
• AND: how can this be achieved affordably?
And these questions always apply:
• Can this be done online?
• Where is the bottleneck?
• Is the sensor technology dependable?
And in conclusion the question remains: is integration into
the digital process possible?
For implementation, moreover, the cleaning validation
will play a progressively more significant role,
although it’s in fact already an important aspect even
today – albeit one that’s only seldom performed. Nonetheless,
recurrent evaluation of the CIP concept’s cleaning
success, and assessment of the overall system’s hygiene
status, are the foundations for long-term cleaning
success, and thus indispensable.
What are the questions that need
to be posed here for digitalisation?
Krones’ response to this is that digitalisation and the
resultant intelligent control systems are grouped in five
thematic clusters, as depicted in Figure 5. These thus
describe the necessities in a company, and the interfaces
and interactions between humans, machine and
process:
So what does that mean for the CIP process?
Primarily, it means that you have to have done your homework.
That’s the precondition that has to be met. In other
words, a CIP system must be kept in good shape to meet
the requirements of the latest state of the art. The digital
process does not relieve the user of this responsibility. If
the homework has been done, however, then intelligent
Fig. 5: The five thematic clusters of digitalisation