that makes process control simpler
Conjecture System Identification Simple, best-fit models of your industrial systems for smoother process control
Identification uses machine learning techniques on industrial data to build models that
real-world processes - in a simple, intuitive way. These models can be used to improve
control systems, reduce energy consumption, and improve the lifespan of existing instrumentation.
Conjecture modelling can also aid in
automating instrument maintenance, allowing for early detection
of faults and maximising operation time.
Identification can be used in any industry which requires automated feedback loop
of processes, including oil and gas, minerals, and
Save on costs with enhanced automated control and select optimal operating modes
Reduce moving parts and wear-and-tear, and stabilise your plant with amazing control
Detect plant malfunctions early on by comparing model and underlying process
Identification is a software solution that models dynamic industrial processes by fitting
best-fit trends to process data (such as SCADA data). The resulting model can aid engineers
the stability of their plant controller, reducing movement and wear-and-tear in their
equipment, and improving the cost-efficiency of their system.
Identification is easy to learn and use with our online
User tutorial videos are accessible from our Resources page, and email support is available.
Enter and manipulate all your process dynamics in one place
Include delays and output shifts for estimation thanks to recent machine learning algorithms that run in the background
See your model equations take shape as you build - equations are in the time domain and easily understood
Specify initial guesses for your model estimates, or use Conjecture's defaults
See the results of your calculations in the Results pane - including estimated gain
Built in Plot Model
View your input, output, and model on the same plot
Zoom in and out to visualise how well your model fits the outputs from your process data
Watch how modelling cuts through the noise in your data, leaving the key patterns for observation
Stored results to help
choose the most useful model
Conjecture stores every model you build during a session
Each model is stored with its results and ranked by goodness of fit (measured using the mean squared error)
Use this information along with your visualised plots to select the most useful model to characterise your system