Process Plant Optimization With POSy-System

Our plant optimization processes also include POSy-SystemTM, as part of our business alliance with Paradox Engineering & Technology Canada, SERVICES | pent ( The POSy-SystemTM optimization methodology is a true multivariable orthogonal resolver whereby it solves for the most optimal of a set of multivariable Set Points, Outputs, System Gain, and Nonlinear Relationships or other Disturbance Variables. POSy-SystemTM can be integrated within existing Distributed Control Systems (DCS’s), Programmable Logic Controllers (PLC’s), and in existing Advance Process Control (APC’s), and works as an APC / Optimisation numerical engine.

The diagram below illustrates 3 Controlled Variable set-point trials, where A, B & C are considered from other influential strategies to determine the desired true Optimized Set Point X. POSy-SystemTM solves for all of the Optimal Set Points simultaneously over the defined operational scenarios.

Problems With Existing Systems :

  • 3 existing systems – experiential, statistical, and predictive methods
  • All of these systems are not precise
  • Large errors are generated (predictive method)
  • Time consuming and therefore very costly
  • Dynamic changes cannot be captured
  • No guarantees – you get what you get

How POSy-SystemTM work in Process Plant Optimization

Alleviation of Problems:

  • Work from the top down instead of bottom-up
  • About 10 x faster (cost-effective) than traditional methods
  • Solutions are much more precise with 95-percentile accuracy
  • Error generated is minimized
  • System more easily adaptable to dynamic fluctuations and trends can be determined
  • Increases efficiency/productivity,
  • Improves quality and reduces waste all at the same time
  • Provides an excellent Return On Investment (ROI) for consumers (and investors)
  • Considered disruptive technology
    • Guaranteed improvements

How does it work?

Advanced Process Control with POSy-System

What processes have been tested?

  • Most testing has occurred for manufacturing – non-Newtonian fluids (non-linear systems): achieved 12% to 23.5% efficiency improvements
  • Have worked with modelling software in industry: thermodynamic modelling software – works well
  • Have worked with modelling software at U of A: simple mixing (works well); SAGD (works well); and Tennessee Eastman Process & HYSYS (works well)