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Improved measurement of parameters

How to increase the measurement of parameters without implementing additional sensors?

Measurement of parameters in the process industry is key for optimizing process control and increasing OEE. To achieve this, sensors are one of the most common methods. The installation and integration of a sensor on the processes line however can be costly or might even lead to downtime. The responsibility of automating such process falls on the shoulders of automation and controls engineers.

Challenge

Installing sensors is one of the most common methods, to optimize process control and to increase OEE. But these can be costly and difficult to implement.

Solution

Virtual Sensors provide real-time measurements of parameters using existing data - powered with AI - to estimate the parameter to be measured.

Benefit

  • Obtain close to real-time insights from blind spot areas
  • Save time and increase the efficiency of parameter measurement
  • Be better equipped in achieving target KPIs

Challenge: How to improve measurements in diverse and complex processes

Digitalization is now becoming a key area for many companies in the process industries and automation engineers are at the forefront of this field to enable other colleagues to do more with less. Automation engineers must take care of topics like measurement (e.g. measurement of pressure), control (e.g. setting up logic based on pressure value), and actuators (e.g. activating the safety pressure relief valve if pressure is too much).

Virtual Sensors can provide real time measurements on the following parameters

Chemicals

• Viscosity

• Visual appearance

• Acid value

• Moisture

• Density

• ...

Mining

• Chemical composition

• Particle size

• Specific surface area

• Color

• Moisture

• ...

Pharma

• pH

• Impurities

• Appearance

• Viscosity

• Concentration

• Moisture

• ...

1 – 3
Chemicals
• Viscosity • Visual appearance • Acid value • Moisture • Density • ...
Mining
• Chemical composition • Particle size • Specific surface area • Color • Moisture • ...
Pharma
• pH • Impurities • Appearance • Viscosity • Concentration • Moisture • ...

Some of the typical challenges of automation engineers are:

  • How to connect a (custom) sensor to my DCS / SCADA / PLC system?
  • Which sensor is best to measure product quality / pressure or other needed parameters?
  • What are the alternative to NIR (near-infrared) / spectroscopy / other conventional measurement principles?
  • How to connect my sensor data to LIMS system?
  • How to plan sensor installation with the least downtime?
  • How to reduce downtime for sensor calibration?
  • Which sensors can be easily integrated for measuring (needed parameter)?
  • How can I install and measure sensors at locations difficult to reach?

These questions lead to the following key roadblocks

  • Increased costs
  • Loss of efficiency
  • Inefficient process control
  • Decrease in OEE

The latest study from Accenture (source) shows that the chemical plants are still thinking solely of measuring parameters using physical sensors level. Even though new technologies and methods are available.

Is there a better way to address these challenges?

Virtual Sensors provide real-time measurements of parameters to improve process data without having to physically install a sensor. They use already available data of physical effects and correlations of parameters.

Combining the physical effects and correlations to other parameters with the support of AI, the parameter to be measured can be estimated “virtually”. Thus, avoiding the hassle associated with the installation and maintenance of a physical sensor.

Example of the Virtual Sensor

We know that concentration is a function of the conductivity of the liquid. So Instead of directly measuring the concentration of a liquid with physical methods, and by using this correlation of concentration and conductivity, the concentration of the liquid can be measured “virtually”.

Conductivity needs to be measured physically and this measured conductivity gives the virtual sensor the input needed to simulate concentration.

Benefits of the Virtual Sensor

  • Obtain close to real-time insights from blind spot areas
  • Replace physical sensors where possible
  • Save time and increase the efficiency of parameter measurement
  • Reduced costs
  • Improve OEE
  • Be better equipped in achieving target KPIs

Where can I use Virtual Sensors?

To deploy the Virtual Sensor, first, the target KPI and the parameters influencing it are defined considering the physical sensor data and relevant manual measurements. The virtual sensor is deployed in such use cases to simulate the state of the parameters for the areas where there is a shortage of information and where a physical sensor cannot be applied (blind spots).

Fast decision making for fast-moving parameters

Continuously changing parameters need fast decision-making to cope up with the changes to avoid negative cascading effects, otherwise, the obtained data cannot be converted into the next action items. Taking the best decisions in such environments can be very stressful and lead to fatigue. This leads to a question “If a machine is measuring the parameters, would it not be a good idea for the same machine to also tell what to do?” So-called recommender models can help in such situations by modeling the adjustment of process parameters based on historical data, just as experienced employees do. Thus, knowledge from experience is de facto "democratized" and expanded in a data-based manner.