Process Monitoring

Process Monitoring in Industry and Manufacturing

Process Monitoring is an essential part of industry and manufacturing, as it helps to ensure that processes are running efficiently and effectively. It enables businesses to track the performance of their production lines in real-time, identify areas for improvement, and reduce downtime and costs while improving product quality. Monitoring is done with the help of advanced process monitoring software which utilizes algorithms to measure various parameters such as temperature, pressure, flow rate, etc., across multiple locations within a facility. This data can then be used by decision-makers to make informed decisions about how best to optimize their industrial processes. Monitoring also allows for predictive maintenance so potential issues can be identified before they become costly problems. By leveraging process monitoring technology companies have the ability to gain better insights into their operations allowing them to maximize productivity and profitability.

Benefits of Monitoring Industrial Performance

There are many benefits to monitoring the performance of industrial processes. Monitoring helps to identify problems quickly, allowing businesses to take swift corrective action before they become expensive issues. Monitoring also enables businesses to optimize their production cycles and reduce downtime which can lead to improved efficiency and reduced costs. Furthermore, by keeping track of various parameters such as temperature, pressure, etc. across multiple work centers and unit operations, companies can ensure that their products meet customer and governmental standards, thus improving quality, customer satisfaction, and governmental compliance. Additionally, process monitoring provides valuable insights into how well a business is performing compared to its past performance, helping companies make informed decisions about investments in new technology or improvements in their existing processes.

 

Overall, Process Monitoring plays an important role in industry, manufacturing, and your business.

How To Monitor Processes

Identify Your Business Goals and Objectives

It’s best to have a clear plan when it comes to monitoring processes. It’s important to identify your business goals and objectives and align technology to achieve them. What is the biggest challenge? Capacity? Consistency? Uptime? Equipment problems? By aligning technology to your goals and objectives, the probability of success is high and the effect on your bottom line is impactful.

Digitalization of Your Process

In most manufacturing, there are digital process control systems, such as “Distributed Control Systems” (DCS) or “Programmable Logic Controllers” (PLCs), or hybrid “Supervisory Control and Data Acquisition” systems (SCADA). These process control systems capture your process data in real time. These tools can provide simplistic monitoring and alarming for out-of-envelope conditions. More sophisticated tools, such as IntelliDynamics (R) Intellect software can be used not only to monitor single process variables, but combinations of them as a “system” to identify multi-variate anomalies in your process.

Quality Lab Results

Quality control systems, also known as “Lab Information Systems” (LIMS) also gather data about your raw material, semi-finished, and final product performance. Many LIMS have both useful performance data and also QC control charting to flag unusual results.

Process Monitoring Software

Each data-holding technology (DCS, PLC, SCADA, and LIMS) has data in its own silo that is used independently, but a much more effective means of performing process monitoring is to use more sophisticated tools such as IntelliDynamics’ Intellect software. Intellect “talks to” all the data holding systems to obtain real-time data and integrate the total production picture; Materials, Process, and resulting Quality to create advanced process monitoring systems. Intellect is a feature-rich enterprise tool with a dashboard robust reporting system that looks at your data individually, combined, and in a holistic manner that gives actionable insights across your entire production process landscape.

Algorithms Used

Many monitoring solutions provide simple thresholds and alerts. In state-of-the-art performance monitoring, much more sophisticated ways to look at your state of operations.

Single Variate

  1. Look at one variable at a time, put thresholds for “too high” and “too low”, and generate alerts. This is a very basic level of process monitoring. Most any system can to this.
  2. Look at one variable at a time, calculate “normal” operations based on a historical distribution, and alert when conditions are X-sigma from the mean. Also basic, but a bit more sophisticated. This can be adaptive if the historical distribution is recalculated through time to remove drift. +1 bonus point for adaptation.

Multivariate

Look at multiple variables at a time. Compute a normal N-Dimensional distribution and alert when one or more variables go outside this boundary by X-sigma.

Systemic

Look at multiple variables at a time. Compute a normalized N-Dimensional “bubble” or “sphere” and alert when the sphere becomes distorted even though all variables individually may be within their normal boundaries.

Predictive

The system computes models interrelating variables and alerts when the model suggests you will be going out of limits. For example, model product quality vs. materials and process conditions and estimate product quality in real time. If the model suggests that reject material is being made, before the lab tests come back, alert the operators and QC team and perhaps the product managers.

Sensor Validation

The system computes models interrelating variables and physical sensors and alerts when the model’s estimates vs. the physical sensor suggest you will be going out of limits. For example, model emissions sensors readings vs. process operating conditions and estimate the sensor’s values in real-time. If the model diverges from the sensor, alert the operators, maintenance, and process engineers of an impending sensor failure. This is a great process monitor solution for emissions control conformance.

Challenges Associated with Monitoring Industrial Processes

  1. Gaining access to data. We use industry-standard interfaces such as OPC and SQL as well as proprietary interfaces such as OSISoft’s PI SDK.
  2. Cultural Changes. People need to embrace new and effective ways of using data to assure the operations are performing at peak performance. There are new business processes to be worked out and adjusted to.
  3. Technology Implementation. This is no longer much of an issue, thanks to systems like Intellect. The solutions are now commercially available off-the-shelf and quickly implemented.

Summary

Process Monitoring solutions are becoming more and more powerful and sophisticated. In addition to simple threshold-based alerts, industrial processes can be monitored with algorithms that look at one variable or multiple variables in context with each other. IntelliDynamics’ Intellect software provides an advanced process monitoring system that looks at your data individually, combined, and in a holistic manner that gives actionable insights across your entire production process landscape. This way, you can ensure that your processes are running at peak performance.