The Power of Data
Modern steam and cooling plants have objectives that go beyond the primary goal of producing heating and cooling reliably. Within the context of business, the goal is to also achieve the Least Cost Operating Scenario (LCOS).
A crucial part of increasing efficiency, and thus lowering cost, is effective data management. In order to identify opportunities for improvement, data must be accessible, usable, and reliable.
From Paper to Online
Historically, boiler and cooling paper logbooks have been maintained to collect system operating data. The primary function of logbooks was to ensure tasks were completed and identify the need for adjustments to the water treatment system. Regulatory compliance has also been a common driving force for the use of logs. Paper logs are effective for recording data for future reference, however the ability to locate a specific data point or assess historical trends is difficult with this method of data collection.
Data management was improved with the development of electronic logbooks. These logs often take the form of spreadsheets or proprietary logbook software. Historical data can be accessed more readily to confirm system events. Trends can be generated and utilized as a management tool. Out of range parameters can be flagged by the software to increase operator awareness and drive action.
The Jump to the Cloud
More recently, electronic logbooks have been integrated with cloud computing to provide even more data management opportunities and benefits! Data is now accessible remotely by anyone with the appropriate security credentials, and is stored on more powerful delocalized servers. When compared to a local workstation, these servers provide increased accessibility and computing power for analysis. These cloud capabilities have allowed for multi-site management and benchmarking, allowing operators to efficiently run and monitor a network of systems.
Case Study: University Campus
Klenzoid has launched and implemented AquaAnalytics, a cloud based online logbook, for a multitude of applications across North America. We had a great opportunity to evaluate the system’s capabilities at a large university campus with 28 boiler plants, 39 cooling plants, and over 90 closed loop systems. In order to manage all of these water systems effectively, an average of 51,000 water tests are performed every year between the operating staff and Klenzoid – that is nearly 1,000 data points every week! Analyzing and reacting to that amount of data in a meaningful way is impossible without ‘Big Data’ techniques. Paper logbooks, spreadsheets, and previous generations of electronic logbooks all proved to be inadequate because of the following three large obstacles:
- The sheer amount of data made it very difficult to catch and react to all observed program deviations in a timely manner
- It was impractical for management to ensure all testing was being performed each day
- Since testing is performed by approximately 40 operators, with varying experience levels and water treatment knowledge, there were inconsistences in the data
Results from the Online Logbook Implementation
A crucial part of increasing efficiency, and thus lowering cost, is effective data management. By simply moving the collection of data from paper logbooks to the cloud, we were able to improve results by 67% over 68 different water systems. This improvement in results generated substantial operational savings and significantly increased capital asset life, with no investment cost. The AquaAnalytics online logbook provides operator engagement and accountability, peace of mind for managers, and stability of results - ensuring overall success of the water management program.
The graph above clearly demonstrates the remarkable success of the AquaAnalytics online logbook. As more operators adopted the AquaAnalytics online logbook, the program deviations decreased almost in direct proportion campus wide. This strong correlation is the result of the management and accountability the AquaAnalytics online logbook provides for all entered logs. Automatic alarms are sent to both the Klenzoid Representative and the University in the event of a deviation, allowing for quick resolution and minimal long term implications. The centralization of data also allowed Klenzoid to conduct complex data analyses to identify long term trends to ensure problems were resolved on an ongoing basis, preventing failures, and initiating continuous improvement.