Advocates for using industrial internet of things (IIoT) technology in facilities management often cite room use, temperature, and air quality monitoring as examples of the technology’s benefits. Yet, multiple technologies are advancing rapidly, and while passive applications are useful to inform decisions, IIoT currently offers active and real-time benefits to optimize facilities, improve safety, and lower costs.
Synergies from Technology Advances
Three discrete technologies have combined to enable a previously unimagined potential—the implications for creative facilities management use are unlimited.
Rapid progress in condition-monitoring sensor technology includes digitization, miniaturization, and hardening for severe environments. The sensors’ low-power draw and WiFi connectivity enable applications in legacy buildings that previously required expensive infrastructure change to access the benefits of IIoT.
Cloud computing is now universal, offering unparalleled computing power and data-handling capabilities. Its flexibility, scalability, and fractional leasing model place advanced technologies such as artificial intelligence (AI) and machine learning (ML) within reach of small to midsize businesses while providing more robust security than previously possible with site-hosted infrastructure.
AI and ML Engines
Artificial intelligence and machine learning have become mainstream technologies, using analytics engines to find patterns in huge volumes of data streamed in real time. Real-time analysis of the sorted, structured, and cleaned data allows pattern recognition and the identification of divergences from established norms. From that identification, actions ranging from alerts to automated responses occur without human intervention.
Three examples follow to demonstrate current applications of IIoT that are pertinent to facilities.
Critical Task Monitoring and Alerting
Preventative maintenance and mandated inspections have long been the weapon of choice to maintain system integrity. Yet, despite the most rigorous maintenance systems, random failures occur. When system failure has a high human or financial cost, IIoT coupled with AI and ML allows real-time, always-on monitoring to identify asset deterioration and predict or alert for pending failure. Let’s look at an example.
Hospital Air Pressure Stabilizers
In hospitals, air pressure stabilizers control exogenous contamination of wounds in operating theaters via the critical role of controlling contaminated airflow, as surgical site infections form 38% of hospital-acquired infections in surgical patients. Air pressure stabilizers modulate air outflow to maintain preset pressure differentials, keeping theater pressures above surrounding rooms and preventing air inflow when opening doors.
While regulations mandate annual checks, air stabilizer failure could seriously impact patient health. However, IIoT offers a real-time monitoring service. An analytics engine can monitor stabilizer response and differential recovery times, raising alerts upon detecting deterioration before it reaches unacceptable thresholds that compromise safety. Upon catastrophic failure, the system can sound alarms to alert staff to the threat.
Automation of Maintenance Checks and Data Management
Using computerized maintenance management software (CMMS) enhances maintenance efficiency and cost savings by capturing in-service history, automating and centralizing data capture and storage, and supporting reliability initiatives. Coupled with a system of IIoT sensors, it prevents many manual inspections, improves regulatory compliance, and reduces cost.
Monitoring Legionella Compliance
Legionella compliance can be a nightmare in multi-story buildings with several bathrooms on each floor. While such compliance tasks are important, they use important resources you might better deploy.
IIoT sensors mounted externally to water pipes and linked via WiFi to a cloud-based, CMMS-linked monitoring system replace manual monitoring and reduce unnecessary system flushing. Constantly recording water movement and temperature identifies those systems remaining unflushed through normal use. This feature alone reduced engineer time-on-task by 81% for one facilities management company. The monitoring also identified unexpected temperature drops requiring investigation and automatically produced pipe monitoring reports to evidence compliance. Over 600 liters of water were saved annually, from each tap, due to ceasing unnecessary flushing.
IIoT and Prescriptive Maintenance
Firms are combining machine learning, prescriptive maintenance, and IIoT to improve client satisfaction and maintenance system effectiveness while driving efficiencies and cost savings into planned maintenance interventions.
For example, Thyssenkrupp Elevator (TKE) used the synergy of IIoT and prescriptive analytics to improve safety, enhance reliability, and reduce costs simultaneously. They implemented machine learning to analyze the data from elevator-mounted sensors and identify tasks to enhance the safety and reliability of their equipment. The system is now mature enough to accurately predict five days in advance when a client’s elevator will shut down due to door problems.
Technicians are then automatically scheduled to intervene before the predicted event, with the prescriptive analytics system raising the four actions most likely to alleviate the pending problem. This accuracy has prevented elevator outages when passengers are onboard, ensures the right resource is scheduled, and highlights the parts necessary for the repair. TKE technicians currently fix the problem with 90% accuracy.
IIoT and connected devices have moved far beyond passive data collection to support human review and decision-making. Systems now actively monitor, predict, and prescribe actions or even automate responses for low-impact or high-criticality situations.
While the take-up of technology was initially slow due to building infrastructure limitations, new products and capabilities are solving problems previously encountered with legacy assets. IIoT combined with connected devices has moved beyond being an interesting trend and is now an active participant in facilities management. When coupled with continual technological improvements, our ability to imagine new applications will make facilities management an exciting industry in the coming years.
Bryan Christiansen is the founder and CEO of Limble CMMS. Limble is a modern, easy-to-use mobile CMMS software that takes the stress and chaos out of maintenance by helping managers organize, automate, and streamline their maintenance operations.