Last year, Metropolitan Water Reclamation District (MWRD) of Greater Chicago was looking for a suitable sensor system to monitor water level at their Lockport Powerhouse. They wanted in-depth insights on the water level monitoring equipment for their operators that regulate water levels in the canal to prevent local flooding and reverse the water flow back to Lake Michigan during rainy seasons. MWRD’s search for an intelligent sensor solution provider led them to run a pilot project of critical infrastructure monitoring using SIGA-OT Solutions’ SigaPlatform.

Headquartered in Wilmington, Delaware, SIGA-OT Solutions has developed a leading-edge “incipient failure detection” solution, SigaPlatform. The platform uses machine learning-based predictive analytics algorithms to protect critical industrial equipment and systems by monitoring the I/O electrical signals that control the equipment. This approach helps to ensure proper equipment operation and provides an immediate warning at the first sign of an anomaly that could indicate a malfunction or a potential threat. “Our control system monitoring solution provides an important early warning in the event of an anomaly to ensure seamless operation of equipment,” says Amir Samoiloff, CEO of SIGA-OT Solutions.

SigaPlatform monitors electric signals to detect process anomalies in the operation of industrial control systems (ICS). SigaPlatform leverages data logging hardware with its proprietary software—installed on on-site server— that connects with ICS. The ICS is placed at a point where PLC and the sensor devices meet. This strategic placement of data logging hardware helps the platform in identifying anomalies at the earliest stage possible to enable operators to prevent damage to people, equipment, and the environment. Installed on the input/output lines (I/Os) between the sensor/actuator and the PLC, SIGA-OT Solutions employs machine learning and predictive analytics to detect process anomalies in real time, whether due to a technical malfunction or a cyber-attack. The solution enhances the security of level 0 (Process) and level 1 (Basic Control and Safety) layers of the Purdue Enterprise Reference Architecture model.

An OT protocol and equipment agnostic solution, SigaPlatform analyzes raw electrical signals— exchanging data packets between the platform and the system it is monitoring, and thus bring new and unmatched visibility into physical processes to support intelligent decision making.

Our control system monitoring solution provides an important early warning in the event of an anomaly to ensure seamless operation of equipment

Consequently, the platform can be connected to monitor and analyze any end device or sensor connected to a PLC or a remote terminal unit (RTU). The isolated placement of SigaPlatform and the end devices defend them from any network hacking or interventions.

Recently during the activation of General Electric’s Mark V gas turbine at a power station, operators encountered a problem in which the turbine failed to stabilize. It would deactivate every time fuel was fed into the system. Even after replacing a control card on the central controller, the situation still could not be remedied. However, the in-depth report from SigaPlatform allowed the chief engineer to examine the reports from the platform and precisely identify the issue. The report showed them the precise issue that was not visible in their SCADA system. The resulting adjustment allowed for safe turbine activation, and mitigation of time-consuming and costly downtime.

SIGA-OT Solution has already carved out a niche of its own through the proven ability of its monitoring platform. Currently, the company is strengthening its equipment failure prediction system. Simultaneously, SIGA-OT Solution is also looking at new integrations to enhance their product and get the best out of SigaPlatform. To conclude, Samoiloff says, “No one likes a surprise failure in their daily operations. Through our partnerships, we want to prepare all the businesses for any unwanted failures in their system.”