In this first of six articles, we explore maintenance theory that is applied to Building Services, HVAC and Building Automation Systems and introduce the evolution from Planned Preventative Maintenance (PPM) to Intelligent Maintenance (IM).
What is Maintenance, and Why is it done?
To understand what Intelligent Maintenance is, it is first necessary to understand maintenance practices, why maintenance is performed and how it is currently delivered across HVAC and Building Automation Systems that are found in our built environment.
When we speak of maintenance, what we are referring to is asset management and protection by way of planned, routine, repetitive tasks that are used to prevent premature wear and tear, minimise failures, minimise efficiency degradation and therefore optimise the total cost of operation and realise the full lifecycle of the assets we are maintaining.
If we consider that an effective maintenance program that includes both planned and predictive maintenance activities is directly correlated to extending the life of equipment and minimising the energy and service costs, the value of maintenance cannot be understated.
Planned Preventive Maintenance (PPM)
Planned preventive maintenance (PPM) is a proactive maintenance strategy that incorporates predictive, recovery and optimisation activities and involves regularly performing pre-determined maintenance tasks at scheduled date/time intervals to prevent failures, ensure reliability and uptime and realise or even prolong the life of equipment.
This is achieved by inspection, measurement and recording, evaluation, cleaning, lubricating, adjustments, and timely intervention as needed.
As the term planned preventative maintenance infers, tasks are scheduled by calendar to meet intervals that are specified either by regulation/compliance, good engineering practices as specified by the Original Equipment Manufacturer (OEM) or by Industry best practice based on environment or criticality of operation.
PPM will lead to a reduction in unplanned downtime, increased equipment reliability, efficiency optimisation, extended asset life, improved safety, and lower long-term total cost of ownership and operation.
Historically, PPM has been a systematic calendar based, point in time approach to deliver physical maintenance activities. With the pervasive use of building automation throughout the built environment, these physical activities have been augmented by the ability to monitor data in real time, capture and store data that can be retrieved in trend logs and more recently the ability to correlate disparate data to reveal insights into how individual equipment, equipment systems or even entire buildings are operating using data analytics.
Creating the Maintenance Plan
In nearly all cases, no matter what the equipment or who is providing the services the maintenance plan is built on a series of documented tasks, each task having a calendar schedule (each week, each month, quarterly, bi-annual, annually and so on) a number of steps to be performed during the scheduled maintenance, the required skill set to carry out the steps and the time needed to complete those steps. The process then becomes:
Identify the asset and its operation => apply the appropriate task(s) => repeat for each asset in the system or building.
By design, by identifying all assets and applying the required task to meet the operational requirements, the assigned frequency, time, and skill set builds the maintenance plan and schedules the interval in which tasks will occur.
Extending Planned Preventative Maintenance with Predictive Maintenance
An additional layer of predictive maintenance practices is used in more complex systems to anticipate failures and plan interventions before they occur. Predictive maintenance usually includes the use of sophisticated measurement techniques such as:
Eddy current non-destructive metals testing for tube wall thickness in heat exchangers.
Vibration analysis of rotating parts.
Refrigerant and water chemical analysis.
Oil sample analysis for wear metals and unwanted by-product markers.
Recording of data along with system performance calculations and trend analysis is a common feature of planned and predictive maintenance strategies, the results of which will often determine if a physical response or intervention is needed.
The limitations of Planned Preventive and Predictive Maintenance Practices have always been the periodic nature of Maintenance carried out through a keyhole in time.
How Contractual and Workforce Silo’s Limit the Potential for Optimal Maintenance Outcomes
The practice of separating maintenance activities by equipment or system is common, many buildings have individual contracts for water treatment, airside filtration, building automation systems, chillers, refrigeration, energy metering, active and passive fire and life safety systems and so on and it becomes obvious that most data, whether captured by a building automation system, a chiller panel, water treatment system, an energy meter or by a service technician in a log book is a significant challenge to consolidate never mind correlate.
Enter the building analytics industry, an obvious step forward in the evolution in building services optimisation.
Building analytics, the process for data capture, transportation, meta tagging and root cause rule set execution will be reviewed in the next instalment of this series, however, needless to say, without exception, analytics are an enabler for building operators, managers and occupants to improve the operation of their buildings, but equally as important to service providers it is an enabler to drive innovation and deliver new ways of working that supercharge productivity and lowers cost.
Introducing Intelligent Maintenance (IM)
The (r)evolution of Maintenance Service – Intelligent Maintenance (IM) takes the power of integrated data and resultant analytics designed specifically for maintenance delivery and creates a fully automated end to end workflow system that is integrated into our ERP that drives our business. This is the same system that our technician’s use every day in the field to receive customer appointments, maintenance activities and service response calls and report on outcomes and completion.
In effect, Intelligent Maintenance includes Virtual technicians working congruently with our on-site Physical technicians to deliver more value in a "No Gaps, No Overlaps" integrated approach that is always on, always optimized, and always reporting the results.
No longer is a task simply a set of predefined steps carried out by a technician who visits site at a point in time.
Tasks are now dynamically changed to reflect what the equipment, system or building data is prioritising, task steps that are compliance based are always included in the physical technicians workflow, task steps that are calculable are assigned to the virtual technicians workflow and are executed continuously, task steps that need an adjustment or other human intervention or data that indicates degrading operation or efficiency generate new dynamic steps in the physical technicians workflow. Data that indicates an imminent pathway to failure or safety breach trigger high priority alerts direct to the technician’s smart device.
Supporting data, correlated trends, historical service information and other relevant information is transmitted as part of the technician’s appointment.
The system is a fully automated, machine to man to machine (m2M2m) platform providing a closed feedback loop that provides Machine Learning to both the root cause analytics and the workflow system, it is supported by a customer Intelligent Maintenance Portal that continuously updates and provides key metrics and reports against KPI’s and benchmarks, provides energy, emissions and cost avoidance data and access to detailed reporting.
That's it for this first instalment. In my next post, I will explore Building Data, Analytics and the Intelligent Maintenance Platform and explain how they work together to create high-quality maintenance outcomes that improve building performance at lower cost in ways that can only be delivered in a fully automated end to end system.
Noel
For further information, please contact Melvin Penman, Business Development Manager – Optimum Air at mpenman@optimumair.co.nz, or 027 705 4684.
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