Questions to Ask About Toolkit-based FDD: Part 1

This is part 1 of a short series on evaluating different approaches to Fault Detection and Diagnostics. 

Building owners, managers and their service providers are accelerating their investment in a variety of Fault Detection & Diagnostics (FDD) solutions to help monitor facility mechanical systems, diagnose maintenance priorities, identify energy savings opportunities and keep building occupants comfortable. We have a new White Paper that dives into the critical differences between a toolkit approach to FDD and Diagnostics as a Service. Here's a short summary:

The majority of building analytics solutions on the market today fit into the category of toolkits. The user writes rules using proprietary programming languages and creates alerts and visualizations that turn those rules into value. The stated benefit of this approach is that it is completely custom, but this type of custom solution also brings a number of downside concerns.

Here are some initial questions to ask if you are deciding whether to invest in a toolkit based FDD solution or have deployed such an approach and are interested in scalability:

• Rule Library Limitations: Many toolkit users struggle with the limitations of the rules libraries that are set up. Rules are typically following standard engineering calculations - Identifying when a valve is leaking, a damper is stuck, or a sensor is broken is not very difficult logic. The key question is how will that logic scale across many different system configurations and sequences of operation?
• Simple Rules vs. Complex diagnostics: The first wave of FDD primarily allowed for simple rule creation. Can custom coding of toolkits move from simple rules to complex diagnostics that incorporate many layers of rules together? What is the future cost to get there with custom rule writing?
• Model System Interactions: Is it possible in the rule set to quickly model complex interactions and reduce false positives by making sure that faults incorporate additional learned knowledge in the data model?

Simple rules have an inevitable tendency to turn into false positives fast. False positives are the Achilles heel of the entire FDD value proposition, and if they are not well managed, they quickly devalue the entire strategy of incorporating FDD into facility operations.

To address these challenges, a new generation of FDD solutions takes a fundamentally different approach to how diagnostics are set up and maintained over time. Automated FDD solutions, such as KGS Buildings own Clockworks®, are deployed as a ready to use SaaS platform with a core hierarchical diagnostics library that is both shared by all, and configured to be accurate for unique buildings, systems and equipment without requiring any custom code development. In other words, an approach that can truly be termed “Diagnostics as a Service.”

Download our white paper to delve more into the critical questions to ask when evaluating toolkit-based FDD vs. Diagnostics as a Service.

Until next time.

The KGS Buildings Team
Automated Analytics. Smarter Facilities