Presentation by Senior Analysts from Cimetrics at the 2018 I2SL Annual Conference
In a presentation by Cimetrics Inc., Senior Analysts Lisa Zagura and Julianne Rhoads delved into the transformative impact of big data analytics on laboratory facilities. The talk, titled "BE A BTU HUNTER: How Big Data Analytics Can Achieve Energy and OM Savings While Improving Productivity, Comfort, and Sustainability at Laboratory Facilities," was held on October 15, 2018, from 2 p.m. to 3:30 p.m. in Session B3: Controls.
The learning objectives of the presentation included understanding energy savings, fault detection, and diagnostics, as well as learning how to evaluate big building management data as a tool for identifying faults, understanding how control strategy optimization can counter reactive maintenance, identifying the economic and environmental benefits of big data analysis, and recognizing and appreciating high-value data points and reliable data collection.
Julianne Rhoads, who joined Cimetrics in 2017, is responsible for energy analysis and reporting on over 35 buildings. Her expertise in this field has led to the identification and implementation of over $2 million in annual energy savings. Prior to joining Cimetrics, Julianne Rhoads designed Energy Performance Contracting projects at Siemens Industry, Inc.
Lisa Zagura, with over 10 years of experience in building automation and mechanical systems, is also a key player at Cimetrics. Her work involves energy analysis, implementation recommendations, and Analytika reporting for over 30 buildings in the healthcare and pharmaceutical industries. Prior to joining Cimetrics, Lisa Zagura managed the New England automation design team at Siemens.
The presentation focused on fault detection and root cause analysis of big data in high-performance healthcare, pharmaceutical, and university laboratory buildings. The impact of data quality and reliability on the outcomes was covered, as well as the economic impact of insidious HVAC faults and large scale operational issues.
BMS data from a 1.2 million square foot healthcare facility was used to demonstrate the procedure for fault detection and data analysis. The presentation quantified the energy savings that result from the appropriate corrective actions and explored fault identification, root cause analysis, and issue remediation using aggregated facility data.
Big data analytics in laboratory facilities contributes significantly to energy savings, productivity, comfort, and sustainability by enabling real-time monitoring, predictive analytics, and automation to optimize resource use and environmental controls. Key ways it achieves this include:
- Energy Savings: By collecting and analyzing detailed data from sensors and smart meters, laboratories can identify patterns in energy consumption and implement predictive maintenance and demand response strategies. This can reduce overall energy costs by 20-30%, as predictive analytics helps optimize heating, cooling, and equipment use, reducing waste.
- Productivity: Real-time data processing frameworks enable faster response to changing conditions, reducing decision latency and downtime. Operators can make informed adjustments quickly, improving operational reliability and maintenance scheduling. This results in better uptime and efficient resource allocation, driving productivity gains.
- Comfort: Data-driven automation of environmental systems such as HVAC and lighting ensures optimal comfort levels with minimum energy use. Automated adjustments based on analytics reduce fluctuations in temperature and lighting, enhancing occupant experience without unnecessary resource consumption.
- Sustainability: Analytics help balance energy use with low-carbon goals by integrating renewable energy sources and supporting microgrid management. Data-driven workflows also promote daylight optimization and low-carbon retrofitting, contributing to reduced carbon footprints in laboratory buildings.
In summary, big data analytics systems enable laboratories to operate more efficiently and sustainably by providing actionable insights into energy consumption and environmental conditions, automating control systems, and supporting strategic planning for resilience and carbon reduction. This holistic optimization leads to reduced operational costs, improved working conditions, and a smaller environmental impact.
The examples provided in the presentation focused on air handlers and laboratory ventilation equipment. The talk by Lisa Zagura and Julianne Rhoads showcased their experiences and expertise in the field of big data analytics.
- In the presentation by Cimetrics Inc., it was highlighted that big data analytics plays a crucial role in finance, particularly in terms of energy savings, as it can help laboratories reduce energy costs by 20-30% through predictive maintenance strategies and demand response strategies.
- TheBusiness and Technology sector has been greatly influenced by the implementation of data-and-cloud-computing technologies, such as big data analytics. For instance, in the talk by Lisa Zagura and Julianne Rhoads, they demonstrated how big data analytics can achieve energy and OM savings while improving productivity, comfort, and sustainability at laboratory facilities.
- As demonstrated in the presentation, technology such as big data analytics can revolutionize business operations in various sectors, including finance, by enhancing productivity, streamlining resource allocation, and promoting sustainable practices. For example, in the healthcare and pharmaceutical industries, big data analytics has been used to optimize HVAC and lighting systems, leading to improved comfort levels and reduced energy consumption.
