'the action of making the best or most effective use of a situation or resource'
Before a clean can be optimised a clear objective must be set. This enables the results of any changes to be evaluated against that objective. Objectives typically set include:
Improvement in efficacy of clean.
Reduction in the cost of cleaning. This will include:
Labour and supervision cost.
Detergent and disinfectant cost.
Energy cost.
Water and effluent cost.
Maintenance cost.
Reduction in water use due to constraints on supply or disposal.
Reduction in cleaning time allowing a greater process plant up-time.
Increase in the recovery of product from the process plant. This means less product is flushed to drain.
Effective recovery of product includes techniques such as pigging or water rinse with recovery to process / waste stream.
It is vital that a set of base data is collected before trials are undertaken. In this way any modification to the system can be monitored against the base line data.
Optimisation should be done in such a way that only one set parameter is altered at a time. The cleaning route should then be validated and allowed to run for a set period of time to determine that no issues arise from this change. Once it has been determined that the change has had no detrimental effect then other changes can be investigated.
It is important that sufficient data is collected over a number of cleaning cycles to ensure that the effects of the changes made are statistically valid and no unforeseen consequences occur after a period of time. For instance scale build following the reduction in detergent strength.
Once the optimization objective has been met the changes made must be recorded together with the validation results. This ensures that if subsequently issues are identified the original settings can be restored.
