- Sophia Lee
- October 3, 2024
How do you ensure your machines are running like a well-oiled… machine?
The Evolution of Asset Management
Traditionally, asset management was a reactive process. Equipment would fail, and you would scramble to repair or replace it, leading to unplanned downtime and soaring maintenance costs.
However, the rise of Asset Performance Monitoring has completely changed this landscape. APM involves integrating data from multiple sources to create a holistic view of asset health, allowing for early detection of issues, performance trend analysis, and improved asset lifecycle management in general.

An APM dashboard might collect data on machine downtime, operational efficiency, and historical performance metrics. This information, when processed through advanced analytics, enables companies to identify anomalies before they lead to failures.
Analytics in Action
Predictive Maintenance of Critical Assets for Logistics Provider
Key Benefits of Asset Performance Monitoring
Gone are the days when asset management meant waiting for something to break before fixing it. With asset performance monitoring, you’re not just fixing problems – you’re predicting and preventing them. Here’s how:
Trend Spotting
By analysing historical data, you can identify performance trends and anomalies.
Example:
A particular machine’s energy consumption has been gradually increasing over the past six months, indicating a potential efficiency issue. This kind of trend analysis can help you pinpoint subtle changes that might otherwise go unnoticed until they become major problems.
Early Warning System
You can detect potential issues before they escalate into major problems. Advanced monitoring systems can use machine learning algorithms to detect anomalies in vibration patterns, temperature fluctuations, or other key performance indicators (KPIs).
Example: A slight increase in bearing temperature might signal the need for lubrication long before any noticeable performance degradation occurs.
Predictive Maintenance
Shift from “fix it when it breaks” to predictive maintenance models. Instead of putting out fires, you’re preventing them from starting in the first place.
Example: By analysing factors such as equipment age, usage patterns, environmental conditions, and real-time sensor data, a predictive model might determine that a specific conveyor belt has an 85% chance of failure within the next 100 operating hours.
This allows you to schedule maintenance during planned downtime, minimising disruption to operations and extending the asset’s useful life.
Data-Driven Decisions
Enhance decision-making based on actionable insights. No more guesswork – just evidence-based facts. By analysing performance data across your asset portfolio, you can make informed decisions about equipment replacement, upgrades, or reallocation.
Example: You might discover that newer models of a particular machine consistently outperform older ones in terms of energy efficiency, helping you build a strong business case for upgrading.
Cost Control
Early exposure to potential rises in replacement costs allows for better budgeting and resource allocation. By tracking the performance and maintenance history of your assets, you can more accurately predict their lifespan and replacement needs.
Example: You can negotiate better deals with suppliers, take advantage of bulk purchasing opportunities, or even explore refurbishment options when full replacement isn’t necessary.
What is Required for Effective Asset Performance Monitoring?
For Asset Performance Monitoring to truly deliver its promised benefits, certain elements must be in place. Let’s break down the key requirements for a successful asset performance monitoring strategy:
Comprehensive Data Integration
Effective asset monitoring requires data from multiple sources, including IoT devices, maintenance records, and operational logs. Without proper data integration, it becomes impossible to form a complete picture of an asset’s health.
A successful APM system needs to bring together diverse data streams into a unified platform where they can be processed and analysed holistically.
Advanced Analytics Capabilities
Collecting data is only the first step. Organisations must be equipped with advanced analytics tools capable of processing this data in real time.
Techniques like predictive analytics and machine learning can identify patterns that might be missed by human operators, helping to predict potential failures and enabling timely interventions.
Real-Time Monitoring and Alerting
Real-time monitoring is a non-negotiable feature of any effective APM system. Assets need to be monitored continuously to ensure that any deviations from normal performance are flagged immediately. Alerts can be automated based on pre-set thresholds, allowing maintenance teams to respond quickly.
User-Friendly Dashboards and Reports
Asset Performance Monitoring data must be presented in a clear, accessible way. Decision-makers need intuitive dashboards that highlight key insights about machine uptime, asset performance optimisation metrics, and cost savings.
Customisable reports tailored to the organisation’s needs help ensure that the right information reaches the right people.
Asset Performance Monitoring Without an Internal Data Department
Until recently, the requirements for effective Asset Performance Monitoring were impossible to meet without access to an internal data department.
Our Analytics as a Service solution was created to democratise access to advanced analytics for the built environment professionals who want their data working harder for them.
AaaS provides advanced technology, skilled data & industry experts and proven methodology, at a fixed monthly subscription, to turn your raw data into insights into actions.
Let's discuss how you can introduce Asset Performance Monitoring with AaaS! 😉
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