After a cleaning circuit is commissioned and qualified, any changes to optimize a circuit may be difficult to implement for
multiple reasons. Organizational changecontrol procedures may be burdensome, and the presented costs of a change may lead
to skepticism from the control board. Whatever the restrictions or reservations, a case for cycle optimization can be made
for poorly designed or inadequately commissioned cleaning circuits. More often than not, a call to optimize a cleaning circuit
may lead to a long list of recommendations that can yield both time and cost savings.
When pursuing changes to a validated cleaning process, the user must understand the key cost drivers behind the optimization
process. For instance, water consumption may be creating a situation in which captial investment in additional water-system
capacity may be necessary. In this case, the optimization will save those additional capital costs. As another example, new
products may require additional facility throughput. Reducing cycle time may be a simple way to boost overall facility throughput
to achieve this goal. Often, investment of limited automation or capital resources into areas that do not directly impact
the organization's key drivers will be rejected. Worse, implementing changes without understanding the cost drivers may result
in beneficial improvements, but a failure to resolve the original problem. Additional time and resources will then be needed
to further optimize a cleaning system that is still inefficient in the focus areas.
A thorough analysis and prioritization of potential changes can help identify an improvement path that all levels of management
will endorse. Each change can be assessed with respect to its impact, ease, and necessity as well as other client constraints.
Examples of items to consider are outlined below.
Table I: Optimization analysis.
Cost reduction resulting from change. What impact will the change have on the CIP utility usage, labor costs, or maintenance costs? In the end, the ability to quantify
the tangible cost savings can make or break a proposed project.
Cycle-time reduction resulting from change. How much cycle time will be saved from parameter-value reductions or changes to procedural setup times? Cycle-time reductions
should be placed in context with the overall production process to highlight the impact. This can be expressed in terms of
an increase in production capacity or reduction in equipment downtime.
Ease of change.
How difficult will it be to implement the change? Take into account both the technical considerations as well as the impact
on the existing validation.
Necessity of change. How necessary is the change with regard to the cleaning cycle? Changes that improve the efficacy of the cleaning process are
of primary concern.
Other constraints. Are there any site, client, or other special constraints that may hinder or restrict the change? This may include additional
change record documentation, agency approvals, available resources, or field accessibility.
Costs of the change. What are the estimated cost implications from the change with respect to shutdown, parts and labor, and validation? These
costs must be weighed against the on-going benefit of the change.
Table I shows an example of the analysis and prioritization of potential optimizations. This semiquantitative analysis allows multiple
projects to be compared based on predefined criteria for each category. In this case, each category is assigned equal weight,
and a higher score indicates a more desirable project. Tables II and III show a more detailed analysis of the cost- and time-reduction calculations, which were translated to the ranked values in
Table I using the pre-established criteria. Estimates of labor and utility costs are inputs for the comparison.
Table II: Cost-savings analysis.