Deploying automation diagnostics for predictive safety management

Your existing automation assets can forewarn you of the impending disaster. Are you reaping the benefits of your investment?

By Vimal Ghumman – Director of Sales – Rotex, North America

When the need arises to forecast events with actionable precision, one of the best practices is ac-cessing credible, dynamic asset information and the means to predict future failures with considerable accuracy.

Predictive safety management is achieved by monitoring online devices and any shifts in key operating parameters that warn of potential safety issues. Risk mitigation, reduced downtime, and significant cost savings can be achieved by deploying predictive safety management. This must be viewed as a direct profit-impacting function by process owners and operators.

Post-mishap findings report that only 35% of the capability of automation equipment is utilised, and either the available asset data was never analysed or used as historical offline data. Mostly, the operating staff either bypassed most of the advanced features of state-of-the-art equipment or shut it off completely, defeating the very purpose of the tool. Unfortunate safety events can easily erode a bottom line and distract end users from their primary business focus, resulting in heavy fines and negative press.

Efficient asset management comes first

Efficient asset management is basic to implementing predictive safety management and can be broadly divided into primary and secondary assets. Primary assets are raw materials, physical equipment, and all forms of energy. These include vessels, piping, valves, and pumps other than the automation equipment. Secondary assets improve the efficiency of the plant’s primary assets.

These are the automation systems, information systems, human assets, distributed control systems (DCS), and programmable logic controllers (PLCs). Primary assets also include safety systems such as safety instrumented systems (SIS), human-machine interface systems (HMI), advanced process control, and multivariable predictive control (MPC). Production planning and scheduling, batch management, enterprise resource planning (ERP), customer relationship management (CRM), and supply chain management are other essential secondary assets.

Additionally, robust operational excellence including human performance, control performance, asset performance and safety and environmental performance all need to be deployed prior to implementation of predictive safety management.

Common strategies for deployment

Once the basic measurement and controls are reliable, then technology can be applied with no additional capital outlay. As plants operate, process dynamics change rapidly, calibration of the instruments shift, and the parameters need adjustments.

Below tools exist to deploy predictive safety management:

• Multivariable Predictive Control (MPC) is effective in measuring process variables relative to a dynamic process model to control the outcomes by simultaneously managing these variables.
• Loop Management Software maintains all process loops in efficient conditions via automatic continuous loop tuning.
• SCADA (supervisory control & data acquisition) monitors and controls capability beyond the confines of a traditional plant infrastructure, such as cross-country pipelines or large petrochemical complexes.

In situations involving critical valves, such as emergency shutdown valves (ESD), reliability of the valve on demand is of utmost importance since a failure would result in the process attaining an unsafe state. As media is transferred via enclosed piping for processing, untoward incidents could be developing inside the pipes with the operators unaware until it results in a major event.

If operators have no means to be forewarned in advance that a safety hazard is brewing up, then its remedial steps are ruled out. The hazard assumes inevitable circumstances. This dangerous scenario can be mitigated by automated data acquisition assimilated by the valve positioner software that plots the feedback of the valve performance from inside the pipeline onto a graph via a graphic user interface (GUI).

This is active valid data that is relayed online and visible in an easy-to-understand and interpret format.

Challenges in deploying predictive safety management solutions

Though effective, there are shortcomings of methodologies and tools.

• MPC is prone to errors and spurious data capture leading to erratic conclusions.
• Loop management software may become too slow in gathering data especially when the loops increase in number.
• SCADA rely heavily on electronics which is affected by harsh weather conditions.

Since a one-size-fits-all solution is not viable, a few golden rules exist that can be considered universal to all industry in each segment or vertical.

Moving forward

Early identification, efficient asset management and operational excellence, coupled with predictive safety management tools, can minimise or eliminate safety incidents. Artificial Intelligence tools need to gather actionable data and seamlessly relay to a third-party software, which in turn, can process the data and “hot feed” the remedial inputs back into the process. This corrects and adjusts the parameters on the go. The quote attributed to Benjamin Franklin, “an ounce of prevention is worth a pound of cure,” holds up well, even today.

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