A Lifecycle Approach to Optimizing Cleaning Systems - Pharmaceutical Technology

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A Lifecycle Approach to Optimizing Cleaning Systems
Clean-in-place systems should be optimized during design and commissioning and after validation.


Pharmaceutical Technology
Volume 36, Issue 12

Continuing optimization

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 II: Cost-savings analysis.
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.


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