Data Driven Maintenance (DDM) is the practice of using a sophisticated analytics engine to identify systems and equipment that are not performing as expected and therefore require, or will require, maintenance.
Utilising data to drive maintenance activities before resorting to visual inspections or reacting to failures offers significant cost savings.
Ecosave has developed a unique and powerful approach to DDM that allows our clients to deliver significantly improved maintenance outcomes at a lower cost.
Optimising Building Performance through Data Driven Maintenance
The Ecosave Watch analytics engine is able to analyse large quantities of data using complex algorithms to identify anomalies or ‘events’. These events typically fall into one of three categories that combine to optimise building performance:
- Energy Savings (ECM),
- Comfort Measures (CM) and
- Maintenance Measures (MM).
Many ECMs, CMs and MMs will impact a building’s energy use, the comfort of its occupants and maintenance of plant and equipment. When improving one aspect of building performance, it often has a negative impact on the other two aspects. For example, turning off the Air Conditioning to achieve energy savings will consequently lead to disgruntled occupants due to uncomfortable conditions (i.e. either too hot or too cold); or if the AC is operating more than what is required, may lead to higher energy costs and maintenance costs.
Thus the process of optimisation is to balance these three primary aspects to achieve the best overall building performance.
The three key aspects of building performance however, are not always in contention. Maintenance Measures (MM) can often deliver a positive benefit for building maintenance, comfort and energy resulting in a win win-win scenario! As an example, identifying and repairing a damper that is frozen ‘open’ avoids the maintenance costs associated with inspecting all dampers in the building, while restoring control to improve occupant comfort and the ability save energy.
For this reason data driven maintenance or DDM is a core element of any building performance tuning and energy efficiency program. If the base components that affect control of the system are not functioning, higher level control algorithms won’t perform as expected and therefore are not likely to deliver the required comfort and energy performance.
Ecosave Watch DDM framework
Ecosave has drawn on our many years of experience with building analytics and hands on Building Automation System (BAS) service experience to develop a framework to drive our DDM service. Our service technicians provide a wealth of practical hands on building maintenance experience.
A simple visual representation of our accrued corporate knowledge in DDM can be represented by a simple Fishbone Diagram. The following example defects a diagnostic process in the event Ecosave identify a lack of heating from a heating coil.
The Fishbone Diagram provides a basis for;
- remote analysis utilising Ecosave Watch analytics
- remote diagnosis by modifying BAS settings and observing the impact, and
- visual inspection and diagnosis on site
The fishbone is divided into diagnostic activities that can be undertaken internally by our analytics engine and analytics team, verses diagnostic activities that form a part of maintenance (generally requiring a site inspection and / or testing activities). In this way Ecosave Watch maximise the activities that can be delivered using our centralised analytics team remotely, and can further direct any time spent on site by maintenance staff such that site time and costs are minimised.
Once the framework for each potential issue and for each piece of equipment is established, the Fishbone Diagram is coded into the Ecosave Watch analytics engine by our dedicated Ecosave Watch R&D team.
This approach ensures we are continuously transferring our practical, hands on experience into automated algorithms in our analytics engine to facilitate cost effective DDM.