Leveraging the domain knowledge and on-site experience of our highly skilled operational and process engineering professionals, combined with the skills of our leading data scientists, Interlate has developed a practical and targeted software application.
Clarofy is suitable for busy or time-poor work environments of minerals processing operational professionals, allowing common and often avoidable problems to be addressed. It is primarily developed around continuous processes but has an ever-expanding capability.
Data science application for mining professionals
Clarofy is a complete end-to-end industrial data science application covering data description, exploration, prediction, prescription, and comparative statistics. The plant asset, commodity and value-chain agnostic solution helps companies explore relationships between their plant operating variables and update their operating strategies. It also helps our customers build predictive process models and optimisation solutions and share results with teammates.
Clarofy has been made with one objective: to enable process plant operators, engineers, and analysts to deliver fast, easily interrupted, high-value results to their organisations while upskilling in modern data science.
The app is streamlined for operators, people on the ground and for time-sensitive analytics. The necessary tools are right at your fingertips so you can spend less time analysing data and more time implementing value.
Clarofy also allows users to create summative reports of results to share with other personnel, and even save your workflow settings for improved automation.
In upcoming releases, integrate with common industrial data systems and output your results in an operational technology (OT) layer-friendly format.
Companies can use Clarofy for a variety of applications, including advanced data preparation, exploration of plant relationships, process modelling, plant process optimisation, and output formatting and sharing.
Innovative features of Clarofy
Clarofy has different visualisation features, resulting in a variety of benefits.
A data science and visualisation tool can be applied to various operating assets, or to any dataset from continuous processing industry while a visually interactive interface allows users to explore and uncover hidden relationships between plant operating variables and quickly and consistently evaluate outcomes from plant analysis and related trials.
Clarofy allows rapid, visual data filtering and preparation: understand, condition and constraint the data set rapidly for further analysis, as well as isolate strategies for specific raw material inputs / feed types or operating scenarios.
The platform also allows users to directly input their own aggregated data – input flat file formats are easily derived from plant historians or databases, reducing time spent analysing while increasing time to implementing value.
- +2% in additional full plant Au recovery through upgraded collector dosage strategies derived from quick exploratory analytics and comparative statistics.
- +134kt product iron ore concentrate through updated fines flotation operating strategies.
- +1.5% equivalent full plant Cu and Au recovery through optimisation of product grade targets across multiple parallel minerals processing lines.
- +5% increase in additional coal product output through upgrade DMC operating strategies aggregated across multiple plant feed types.
- +0.6% in additional full plant Au recovery through real-time optimisation of flotation supervisory control system inputs.
Upskilling on-site workforce
Upskill in industrial data science over an easy, operational-centric platform so you can do the work you want to do and reduce dependency on external providers.
Clarofy begins with visual data exploration in various ways, performing statistical tests (including T-tests and CuSum analysis) and preparing the results for presentation, in an easily interrupted format for corporate types.
In addition to its rapid analysis capability, Clarofy is an engine for upskilling the site workforce in data science and data management. Processing plants are data-rich but can often be information-poor without the application of data-driven tactics and strategies. Data-driven decision making requires a robust foundation of statistics to cut through the ‘noise’ of plant data, isolating issues and allowing operations to maximise recoveries.
With Clarofy, there is now no reason for operating on a ‘hunch’ or ‘gut-feel’.