Data Analysis

Transform your asset management practices with data analytics powered by Machine Learning, Artificial Intelligence and Industrial Mathematics.

Turn vast volumes of data into actionable insights.

Asset-intensive organisations are collecting increasing amounts of data from sensors, devices, IoT and other systems – and this trend is set to continue. One of the biggest challenges when having access to such vast amounts of data is how to data sets into meaningful insights, unlock patterns, identify correlations and report anomalies.

Without proper tools or methodologies for analysing data, organisations will struggle to extract meaningful information, which can lead to inefficiencies, missed opportunities and a reduced ability to gain a competitive advantage.

COSOL has over 20 years' experience in data management and analysis for asset-intensive organisations across the Natural Resources, Energy & Water, Infrastructure, Government & Defence industries.

We have expertise in advanced analytics, combined with a deep understanding of AM systems and processes. We employ state-of-the-art algorithms, advanced statistical models and AI-driven techniques to analyse vast volumes of data to transform data into valuable actionable insights that inform decision-making and facilitate proactive maintenance strategies.

Our key data analysis focus areas are:

Machine Learning
Artificial Intelligence
Industrial Mathematics.

Our EAM Data team harnesses the capabilities of Machine Learning algorithms to unlock patterns, correlations and anomalies in your data.

By applying supervised and unsupervised learning techniques, we can develop:

predictive models for asset failure
maintenance scheduling optimisation
demand forecasting
anomaly detection.

These insights can help organisations make data-driven decisions, improve uptime and minimise costly downtime.

Our EAM Data team can integrate the cognitive capabilities of Artificial Intelligence (AI) into your EAM processes to enable AI-driven solutions such as:

intelligent automation
predictive maintenance
real-time monitoring
adaptive optimisation.

By leveraging natural language processing, computer vision and deep learning algorithms, we are able to create smart systems that learn, adapt and continuously improve.

Insights: The Path to Mining Productivity

In this excerpt from our latest insights eBook, we look at how mining organisations can increase productivity, reduce costs and achieve digital asset management maturity when they utilise the abundance of asset data available as part of an integrated asset information ecosystem.

IMPROVE ASSET PERFORMANCE
Leverage the power of data analytics to enhance asset reliability, minimise downtime and optimise maintenance practices.
IDENTIFY POTENTIAL FAILURES
Predictive models and AI algorithms enable the identification of potential failures in advance, allowing for proactive maintenance interventions.
REDUCE DOWNTIME
Apply proactive maintenance from insights to reduce the risk of unexpected breakdowns or downtime.

OPTIMISE COSTS
Optimise maintenance schedules, resourcing and energy consumption to reduce costs and make informed budgeting decisions.
ENHANCED DECISION-MAKING
Access real-time analytics and data-driven insights and empower teams to make informed decisions based on accurate predictions.
SCALABLE
Scale and evolve data analytics capability to suit organisational, system or industry changes.