Calibration intervals are a defined period of time between calibrations for testing and measuring equipment. Calibration intervals are established to ensure that measuring equipment operates within their specified tolerance limits during their use within that interval time frame.
Initial calibration intervals are based on numerous factors such as manufacturer recommendations, industry standard regulations, or the typical ‘annual’ calibration interval.
As routine calibrations are performed over time, adjustments to the initial calibration interval may be required to ensure that the equipment is capable of producing reliable measurement results. It may be found that a piece of equipment is not used as expected, had a tendency to drift, or is not as reliable as what is required for its use. The equipment may also be used in a harsh environment or used for highly accurate and critical measurements.
Optimal Calibration Interval
An optimal calibration interval is one that balances the cost of the calibrations, the downtime associated with the calibration process, the ability to meet the stated specifications, and the quality risks that come with instruments performing outside of their specifications.
If an interval is too short it could lead to higher calibration costs and increased equipment downtime. If the interval is too long, it could lead to out of tolerance measurements, risk of recall, reduced confidence in the measurement and unscheduled maintenance.
Determining the optimal calibration interval between successive calibrations for all equipment should be one of the goals of every calibration program. It could lead to significant cost savings within an organization, streamline calibration scheduling and minimize the risk of nonconforming products.
Calibration Interval Adjustment Methods
A wide range of methods are available for reviewing and adjusting the calibration intervals. Adjustments can be either upward, if the measuring equipment is found to be in-tolerance, or downward if out-of-tolerance.
Documentation of the method used and the adjusted interval values should be retained for further analysis. To be effective, an organization must have the proper policies and procedures in place to ensure that the established calibration intervals are enforced.
Simple/Automatic Adjustment Method
With the Simple/Automatic adjustment, the interval is adjusted after every calibration or series of calibrations set between maximum and minimum values. The amount of each adjustment can be a fixed value, such as 3 months, or a fraction of the existing interval, such as one-half. One problem with this method is that the interval rarely stays the same and finding the ‘optimal’ interval is not possible.
Certain modifications to this method can minimize the sequence of fluctuating adjustments such as shortening the adjustment value at each successive calibration or making adjustments only after the equipment has been either in-tolerance or out-of-tolerance during a specific number of calibrations.
Reliability/Performance Based Methods
Reliability and performance-based methods take successive calibration results and calculate a ‘reliability’ number based on the percentage of times the item meets or fails to meet its specification. For example, if an item has been intolerance 9 out of 10 calibrations, its reliability is calculated to be 90%.
A simple table can be used to determine the interval based on the reliability number. This method establishes more frequent calibrations for items with questionable reliability to ensure that they are able to meet the required specifications. Using a percentage format smooths out the interval adjustments, especially over time, and can assist in identifying an optimal interval.
Statistical Analysis Methods
Statistical Analysis Methods are similar to reliability and performance-based methods except that they make adjustments by performing a technical analysis of critical measurement data results, instead of just using calibration pass/fail criteria. The measurement data used can be obtained through calibrations, intermediate checks, interlaboratory comparisons or proficiency tests.
Statistical methods require substantial amounts of data, and time, for analysis. Typically, twenty measurements are required to complete a control chart and thirty measurements are used for most R&R or CPK studies. For equipment on a yearly calibration cycle, it could take a decade or more to obtain the statistical data required. Implementation is more difficult and some statistical expertise is required, although statistical analysis software can be used.