Measurement Traceability for the Controlled Environment
The measurement of environmental conditions is increasing in relevance and influence in industry. As efficiency standards and capabilities continue to evolve, these conditions are being better monitored and controlled to optimize performance in a number of applications. The amount of information available and its use for analytics is growing exponentially, making it more important than ever to base decisions on accurate and reliable data.
Sometimes overlooked or taken for granted, the data from environmental sensors for parameters such as relative humidity, temperature and carbon dioxide provide powerful control understanding to the operations they serve. Relevant examples are data centers, who rely on accurate humidity and temperature measurement to protect their IT infrastructure, as well as the CO2 sensors responsible for the efficiency and agility of a Demand Controlled Ventilation (DCV) system in a school or office. While the general task of these sensors is not especially difficult, problems from sensor failure or inaccuracy can have a large impact on critical operations. Measurement underperformance can lead to decreased efficiency, non-compliance of operating conditions, unplanned down-time, or production loss.
Maintaining accurate measurements is the key to long-term operational efficiency, and Computerized Maintenance Management Systems (CMMS) can use sensor data from more locations and in greater detail than ever before. Incorporating environmental sensor data into these systems and others, such as a digital twin, or Industry 4.0 and IoT networks, affect the analytics and predictive indicators that we gain from those systems. This places more responsibility on the measurements from these sensors, and our efforts to maintain them to a high standard.
Information from the calibration of humidity, temperature and CO2 sensors can be tracked to provide insight into sensor health and stability that will improve preventive maintenance schedules and to help mitigate risk. Digitalization of these operations relies on data from sensors whose readings will inherently drift in their accuracy, requiring calibration and adjustment to maintain peak performance.
Calibration ensures data integrity
All measurement sensors are going to lose accuracy over time, through normal continuous use or environmental influences. One of the best ways to understand an instrument’s measurement performance is to assess its accuracy, and calibration is the only way to definitively determine how accurate these instruments are. During calibration, it is determined how much, if at all, the measurement deviates from a defined reference, and adjustments can be made to preserve measurement accuracy, and quality data.
The maintenance activities for some of these sensors can pose challenges of their own, as it can be inconvenient or impossible to remove and send an instrument to a calibration lab for service. In many cases it is preferred to calibrate in-situ with a spot-check or in-house calibration laboratory. An example of this is in cleanrooms, where the transport of equipment in and out of the space is a time-consuming process. Difficulty lies in performing that calibration or adjustment to a high standard, as not all calibration tools are the same, and the quality of references is of decisive importance.
The right tool for the job
Portable reference equipment can provide a versatile and cost-effective way to maintain sensors at a high level by using them as transfer standards. They can be of high accuracy that meet or exceed the unit being evaluated and maintain traceability to international standards. Transfer standards are used to transfer a measurement parameter from one organization to another, from a primary standard to a secondary standard, or from a secondary standard to a working standard in order to create or maintain measurement traceability.
Traceability is the relating of the measurement back to the international system of units (SI units) through an uninterrupted chain of comparisons, all with stated uncertainties. Establishing a high degree of confidence in the measurement becomes even more important for portable instruments, as their accuracies do not often exceed that of the units under test. It is very difficult and expensive to maintain reference equipment of higher accuracy than many high end humidity, temperature, barometric pressure, and CO2 sensors for occupied condition monitoring. They are likely to be a 1:1 comparison, or slightly better, but rarely meeting the traditional 4:1 test accuracy ratio. Therefore, it is of great importance that your instrument be calibrated against an SI-traceable reference to ensure the quality of measurement data. Additionally, proper procedure and best practices must be followed, because even the best reference used improperly can degrade accuracy.
Further increasing the trustworthiness of a traceable calibration is the accreditation of the service provider that has calibrated the reference standard or transfer standard. ISO/IEC 17025 accredited calibration service providers have been certified to provide traceable calibrations with detailed uncertainty information, proper environmental conditions, and methods by competent personnel. In order to ensure these high standards, these laboratories are audited regularly.
How do you know if your instrument is indeed SI-traceable? One way is to study its calibration certificate. For example, the following information should be available:
- Calibration results include measurement uncertainties
- All calibration references are identified
- Notes on how uncertainties are determined and what uncertainty sources are included
- Description of how the SI traceability was established
- Reference and ambient conditions
The more important and integrated the sensor data is to your operation, the greater the assurance is needed for that data to be accurate and verifiable. It is encouraged that equipment and facility managers select the best methods and providers when planning their calibration and maintenance activities.
Justin Walsh, Business Development Engineer, Vaisala Inc.
Today, the emerging digital technologies empowered by Artificial Intelligence (AI) are transforming the Swedish mining industry where failure is not an option owing to severe downtime costs. Such costs can be as high as 30-40 percent of the total equipment operating costs