Fault detection and diagnostics (FDD) is the process of identifying and analyzing malfunctions or failures within a building’s systems to detect and diagnose faults as early as possible. Early detection minimizes the impacts of downtimes, prevents future failures, and improves overall system performance. FDD is crucial for maintaining the reliability and efficiency of a building’s HVAC system.
How Do FDD Systems Work?
FDD is typically achieved using sensors, monitoring systems, and diagnostic algorithms. These tools work together to continuously monitor the performance of the system and detect any abnormal patterns that may indicate a fault. The diagnostic algorithms then analyze the collected to identify the specific fault and provide recommendations for how to address it.
One of the key benefits of FDD is that organizations can proactively identify and address potential issues before they lead to costly downtime or equipment damage. Too often, building owners, maintenance staff, and systems integrators work within a reactionary model, which often follows these steps:
BMS alarm sounds for a VAV
VAV unit inspected
Maintenance request created
Repair or replacement made
This reactionary model works but is inefficient. How long was the VAV malfunctioning before the alarm? How much energy was lost before? How long as it been affecting occupant comfort levels? How much time is required for all steps? How much energy, money, and comfort are sacrificed during downtime? These questions represent the issues inherent in the reactionary model.
FDD sees the problem before the inefficiencies start by using analyzing data from fault trends to predict failures before the actual alarm sounds. If a VAV is consistently running below specification, FDD can flag the activity as consistent with a failing terminal unit. That gives maintenance longer lead times and shortens downtimes.
Diagnostic algorithms like this basic one, move through a series of steps to detect and identify solutions to equipment failures.
FDD Systems Lower Energy Costs
With the growing emphasis on energy efficiency, FDD is becoming increasingly important as a tool for improving overall system performance and reducing energy consumption. Recent studies show that between 5% – 30% of commercial building energy is wasted due to problems associated with controls (Deshmukh 2018). So, FDD offers a massive opportunity to increase energy savings by finding faults faster.
One of the most common types of FDD systems used in buildings is Building Energy Management Systems or BEMS. These computer-based systems monitor and control the HVAC, lighting, and other building systems to optimize energy efficiency. BEMS often use temperature sensors to monitor the performance of an HVAC system and detect when the system is not working as efficiently as it should. The diagnostic algorithms then analyze this data and identify the specific problem, such as a clogged filter or malfunctioning compressor.
Predictive Analytics
Another important aspect of FDD is the use of predictive analytics. Predictive analytics uses historical data and statistical models to predict when a system is likely to fail. This enables building operators and maintenance staff to take proactive measures to address potential issues before they lead to costly downtime or equipment damage. Predictive analytics can be used in a wide range of systems, including industrial equipment, vehicles, and even wind turbines.
Furthermore, the use of predictive analytics can enable organizations to take proactive measures to address potential issues before they lead to a complete system failure.
Improving System Performance
While FDD is typically associated with detecting and diagnosing equipment failures, building operators can use it to improve system performance. By identifying and addressing inefficiencies in a system, organizations can improve overall system performance and reduce energy consumption. For example, an FDD system in an HVAC system might identify that the system is running at a higher temperature than necessary, resulting in increased energy consumption. By addressing this issue, the organization can reduce energy consumption and improve overall system performance.
In conclusion, FDD is an important tool for maintaining the reliability and efficiency of various systems. By detecting and diagnosing faults early on, organizations can take steps to address the problem before it leads to costly downtime or equipment damage.
Information Technology (IT) and Operations Technology (OT) are two distinct yet interconnected fields that play critical roles in modern organizations. IT deals with the use of technology to support business processes, while OT focuses on the use of technology to control and monitor industrial and commercial processes in facilities. By looking at IT vs OT systems, it’s easy to identify their major differences.
What are IT Systems?
IT systems are primarily used to support business processes, such as data storage, processing, and communication. These systems include things like enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and enterprise-wide networks. They are responsible for maintaining the flow of data within an organization, and provide important services such as email, file storage, and data analysis. IT systems are also responsible for maintaining the security of an organization’s data, including firewalls, intrusion detection systems, and encryption.
What are OT Systems?
OT systems, on the other hand, are used to control and monitor industrial processes. These systems include things like programmable logic controllers (PLCs), distributed control systems (DCSs), and supervisory control and data acquisition (SCADA) systems. They are responsible for controlling and monitoring the physical processes within an organization, such as manufacturing processes, power generation, and water treatment. OT systems are designed to operate in real-time and are often required to operate 24/7.
When we look at IT vs OT systems, trends show they are increasingly being integrated to improve the overall efficiency of companies and facilities. For example, a building owner might use data from an OT system to optimize their HVAC systems, or an energy company might use data from an IT system to identify and respond to potential power outages.
The difference between IT and OT system components. Note that IT and OT must interface with one another.
Network Security
One of the major differences between IT and OT is in the level of security required. IT systems are typically more connected to the internet; hence they are more exposed to cyber threats. These systems need to comply with industry-specific standards like the Payment Card Industry Data Security Standard (PCI-DSS), HIPAA and SOC2. Organizations need to maintain regular backups, have intrusion detection and prevention systems, as well as have strong and regularly updated access controls in place.
OT systems on the other hand, are typically more isolated from the internet and have fewer connections to external networks. These systems need to comply with standards like IEC 62443 which are specific to industrial environments. Because of the real-time nature of their operations, organizations need to have redundancy in place and maintain backups that can be restored within minutes, have detailed incident response plans, as well as maintain physical security of the systems.
Conclusion
IT and OT systems play critical roles in modern organizations, with IT systems primarily focused on supporting business processes and OT systems focused on controlling and monitoring industrial processes. The two fields are becoming increasingly integrated, with organizations leveraging data from both types of systems to improve overall efficiency. However, they are also vastly different in terms of the level of security required, with IT systems being more exposed to cyber threats, and OT systems being more isolated and needing to comply with industrial specific standards.
If COVID-19 taught facilities managers and building engineers anything, it’s the importance of proper design and maintenance of air and water systems for stopping the spread of pathogens. But aside from Coronavirus, there are other deadly bugs we need to control if we are to create healthy environments for building occupants. Legionnaires’ disease is one of them.
What is Legionnaires’ disease?
Legionnaires’ disease is a serious respiratory illness caused by the bacterium Legionella pneumophila. It is typically contracted by inhaling small droplets of water that contain the bacteria and can occur when water vapor or mist from a contaminated source is inhaled into the lungs. Facility water and cooling systems can become a source of Legionella bacteria if they are not properly designed, installed, and maintained.
Outbreaks are common with facilities like hotels, vacation rentals, medical facilities and cruise ships. Public hot tubs, for example, present ideal conditions for Legionella pneumophila and are common sources for outbreaks. About 1 in 10 people who contract Legionnaires’ disease will die due to complications from the illness. In health care facilities, the mortality rate jumps to 1 in 4, according to the CDC.
Controlling the Spread
To minimize the risk of Legionnaires’ disease growing within water or cooling systems, it is important to follow best practices for the design, installation, and maintenance of these systems.
Water Cooler System Design. Design water and cooling systems to minimize the risk of Legionella growth and proliferation. This includes using materials that are resistant to corrosion and scale formation, as well as designing the system to allow for proper water flow and circulation.
Regular Maintenance. Regularly clean and maintain water and cooling systems to prevent the buildup of Legionella bacteria. This includes flushing the system to remove any sediment or debris and using water treatment chemicals to kill bacteria and prevent the growth of biofilm.
Temperature Control. Maintain your water and cooling systems at a temperature too high for Legionella bacteria to grow. This typically means keeping the water temperature preferably above 124°F (51°C), and below 68°F (20°C). (Source: CDC)
Control Your pH Levels. Legionella bacteria thrive in water with a pH between 6.0 and 8.5. To prevent the growth of these bacteria, it is important to maintain the pH of the water in the system outside this range. Studies show that a pH of 9.6 prevents the bacteria’s growth in cooling towers. (Source: Water Research).
Disinfection. Regularly disinfect water and cooling systems to kill any Legionella bacteria that may be present. This can be done using chemicals such as chlorine or monochloramine or by using UV light to kill the bacteria.
Risk Assessment. It is important to regularly assess the risk of Legionella growth in water and cooling systems. Implement appropriate control measures as needed. This may include regularly testing the water for the presence of Legionella bacteria and implementing additional measures such as water treatment or increased cleaning.
In addition to these measures, it is important to educate employees and building occupants about the risks of Legionnaires’ disease and how to prevent it. This may include providing information about the signs and symptoms of the disease and reminding people to wash their hands frequently to reduce the risk of infection.
Overall, the key to preventing Legionnaires’ disease from water and cooling systems is to properly design, install, and maintain these systems. By following these best practices, you can significantly reduce the risk of this serious and potentially life-threatening illness.
Remote work has presented challenges for both workers and their companies. Challenges include adopting flexible schedules and conducting video interviews. However, managing a team of remote workers can be a challenge, but it can also be a rewarding experience for both the employer and employees. With the right strategies in place, it is possible to effectively manage and support a team of remote workers. Here are some tips for managing remote workers:
1. Clearly Communicate Expectations
It’s important to make sure that remote workers know what is expected of them and how their role fits into the overall goals of the company. Regular meetings and clear, concise communication are best for providing expectations. When explaining your anticipations, whether verbally or written, use simple language, short instructions, and concrete examples. Anticipate potential problems and emphasize actions that are acceptable and ones that aren’t. So as not to appear negative, maybe include a few anticipated positives too.
2. Set Regular Check-ins
Scheduling regular check-ins with remote workers can help to ensure that they are on track with their work and address any concerns they may have. They also make up for the emotional gap left from the absence of face-to-face communication. The non-verbal cues we get from personal interactions are critical to building trust, empathy, and understanding, even in a professional relationship. Regular check-ins help make up for this deficient.
3. Keep Meetings Short
Employees can’t maximize remote work benefits if they spend too much time in lengthy online meetings. They might as well be at the office. Set a start and stop time and stick to it. One easy way to do this is to set a timer on your phone or your Windows Clock app. Better yet, use the free version of Zoom conference calling, which limits a call to forty minutes. The service will pop up a reminder that your meeting is about to end so you can wrap up your discussion. Also, use a meeting agenda with bullet points to keep the meeting on track.
4. Shift to a Results-based Appraisal
Your employees’ workflows will inevitably change with remote work. It’s just the nature of remote work for more time to be spent on other things like family responsibilities during “normal” work hours. Besides, the whole appeal of remote work is that workers can have a healthier work-life balance. So, shift your appraisal from the “correct” process, to goals and results. Dedicated, honest workers will find the shortest distance from A to B in their new workflow. Let them find their way. Ask yourself “Are they delivering results?” If the answer is “Yes”, then base your appraisal more on that fact rather than how unorthodox or non-traditional the approach to the work may seem.
5. Provide support
It is important to make sure that remote workers have the resources and support they need to be successful in their role. This can include access to training and development opportunities, as well as any necessary equipment or software. Create virtual “happy hours” or other informal events to build relationships.
6. React to Signs of Stress
Change is hard. Adjusting to a new workflow is a major change for employees. New problems crop up, along with opportunities. The stress may be overwhelming at time. Be sensitive to signs of over-work or excessive stress. Stressed workers may seem more argumentative, report more sick time, or complain more. Identify signs quickly so you can make changes. Check in regularly and facilitate an honest and open dialogue so workers aren’t afraid to tell you about problems.
Conclusion
In addition to these tips, there are a few best practices that can help to ensure the success of a remote team. For one, it is important to establish a process for tracking and managing work. This can include using project management software or creating clear, actionable to-do lists to ensure that work is completed efficiently and effectively.
Also, it’s critical to provide regular feedback to remote workers. This can help to keep them motivated and engaged, as well as provide opportunities for growth and development.
Managing a team of remote workers can be a challenge, but with the right strategies in place, it’s easy to ensure success for workers and the company. By following these tips, employers can create a positive and productive work environment for their remote team members.
Although often overlooked by building managers and engineers, data schemas are essential to the efficient building management, data analysis and system automation. That’s because schemas are the building blocks of effective database management. Without them, you foreclose your property’s potential to save energy, adopt tech, and compile valuable operational data that make your buildings run at more efficiently and at lower costs. But what are schemas and how do they work?
Database Schema Basics
Databases of all kinds must be organized in pre-determined ways. Otherwise, it’s impossible to store and retrieve data in any workable sense. Think of a schema as a naming standard “language” for how you write, store, and retrieve the information about your building—from the status of its assets to the historical data around energy use.
Just like any language, schemas have rules and conventions. Language has rules around naming things (e.g., noun, verb, etc.) and grammar (subject + verb + director object). If we don’t follow the rules, communication turns into confusion or completely breaks down. In the same way, database schema standards outline how things are stored, what they’re called, and how they’re related (i.e., relational database).
Schemas deal in metadata or “data about data”. For example, books have metadata in the form of their title, author, publisher, or call number. In the same way, buildings have data about their assets, such as asset name, location, site, or type.
For managers and engineers, schemas make recording and managing your asset database easier by ensuring your library is mapped, tagged and organized in a way that’s easily understood by machines and software. So, these standards are intended for both building owners and developers, ensuring both parties are speaking the same language.
Too often, managers and engineers use schemas customized to their site or ad hoc naming conventions that get lost when buildings change and people move on. Such informality creates confusion over time, but maintaining a standard schema ensures your software, BMS and assets can always communicate effectively.
Like advanced schemas, pictures are worth a thousand words.
Basic vs Advanced Schema
Some schemas are basic, recording only a few pieces of metadata (e.g., asset name, location, serial number). Other schemas are complex, recording many pieces of data. The more complex your schema, the more descriptive it is, and a more description means a “deeper” more powerful database, just as a long sentence is more descriptive than a short one. For example, consider the following two sentences:
“The dog fetched.”
“The black Labrador fetched the yellow tennis ball from its toy box.”
What are the major differences between these two sentences, and (more important) what can we do with the second sentence that we can’t do with the first?
For one, Sentence 2 contains more descriptive words (“black Labrador” “yellow” “toy box”), so we have a better understanding of the context. Second, the shorter sentence lacks an object. We know the dog fetched, but we don’t know what it fetched. The second sentence tells us—it’s the ball. In the longer sentence, we’re even given information about the situation (i.e., the Lab has a toy box). More importantly, Sentence 2 creates a relationship between the subject and the object. We can say, therefore, that the longer sentence is “relational” in that it describes how one thing (the dog) is related to another (the ball), which is related to another thing (the toy box).
These same differences exist between informal and standardised schemas. Longer, more descriptive schemas provide more context and meaning around a building asset. They’re also relational, in that they describe how one asset (e.g., temperature sensor) is related to another (e.g., AHU). Consider these two naming schemas for a temperature sensor housed on Level 9 of a hospital.
Examples of basic and advanced standard schemas
While the basic schema lists only the location (LV09) and asset name (TempS), the advanced schema extends the description to include the building, system, asset type, point type, specific location, and the device class. With these added details, we now have a relational description of the sensor. For example, we know it is part of the mechanical (M) system and part of an AHU. Therefore, we can say Schema 2 is part of a relational database, and that it gives us a greater understanding of the asset and its place in the system.
Overall, Schema 2 gives us more context and meaning than Schema 1, and we can use this information to learn more about how our buildings operate. Once we extend this schema strategy to our entire building, we have a powerful way to analyze its contents and functional efficiency.
Schema Benefits
There are many benefits to adopting and maintaining a standard database schema. Here are a few of the most important.
Software Deployment
Standard schemas create a common lexicon and database structure for software developers to use. Adopting a standard naming schema makes software deployment and management much simpler. Developers and building systems benefit from a common, predictable set of rules and naming conventions. Such standards make software development and deployment easier and cheaper because both stakeholders are working from a shared data structure. The developer can simply bolt their software package to your system, and everything works out-of-the-box.
Advanced Queries and Dynamic Lists
Conventional BMS pages are static. Their queries are hard-baked, with pre-built graphics that deliver data around points such as fault detection, temperatures, run speeds and statuses. They are “static” in that their queries never change. Your BMS will only “ask” specific questions about your system. They may be important questions, but they are, to be sure, limited. Contrary to their appearances, however, buildings aren’t static with respect to the data they produce, and managers and engineers often need to run queries and generate dynamic lists that exist outside the BMS purview. Using a relational, standardised schema allows this limitless flexibility.
For example, say you suspected one of your AHUs was starting to fail. You could run a query that identified all room temperature sensors that have been reading above 21 degrees for the last 24-hours for that specific AHU. If your schema is relational, it understands which specific sensors to target. You could then upload the data to a dynamic page to help troubleshoot performance issues. Dynamic lists like these can improve predictive failure and shorten downtimes.
Boilers in a mechanical room.
Asset Replacement
With a standard relational schema, you can identify an asset’s effect on the system and impact to service. For example, a standard schema can show you the effects to other systems when you plan to replace a failed actuator. Before work begins, you can ask questions like: “Will replacing the actuator stop chilled water to the whole building or just the data center?” or “How will the replacement affect Tenant X, Y and Z?” Such insights give you and your service engineers the right information for estimating costs, cutting downtime, and ensuring better tenant outcomes.
Updating Building Data
Buildings go through many evolutions in their life cycle, and these changes affect your asset database. Standard relational schemas make updating metadata much easier and more accurate. Recording changes only requires updating one specific piece of data, like a room number or new part. After that, your system automatically adjusts names and relationships, both upstream and downstream. Standard schemas cut the time and costs of updating asset databases.
Popular Schema Standards
Today’s most popular standard schemas differ in their approach, but all attempt to standardise asset description and storage to aid interoperability and software deployment. Project Haystack is a tag-based schema focusing on streamlining operation between smart devices within buildings, homes, factories, and cities. The Brick Ontology standardises both asset labels and connections, allowing the user to create a relational database.
Conclusion
It’s difficult to make big data work for you without first putting it into a standard structure. Schemas are that structure—they’re the digital architecture of your building systems. By building your asset database with standard schema, you’re ensuring your building, tenants and occupants benefit from future invocations such as advanced analytics, AI, machine learning, and cloud computing. These are the future of building operations and facilities management. Once all buildings graduate to smart status, they’ll be connected to everything, and proptech will help managers do everything from calculating asset depreciation to managing carbon emissions.
