Hosted on the Pratexo edge-to-cloud platform, solution frameworks built by Pratexo are highly customizable and significantly accelerate your ability to stand up solutions to critical operational issues. Such solutions function wherever is most appropriate, from the far edge all the way to public clouds – even when entirely shielded from the internet.

Electrification Solution FRAMEWORK by Pratexo

Expert System Framework for Root Cause Analysis

The electrification ecosystem is a critical infrastructure for the world’s economy. Keeping it running at peak efficiency requires proactive preventive maintenance that can detect anomalous conditions, detect impending faults, analyze their root causes, and automate remediation. The Pratexo Expert System Framework for Root Cause Analysis is a computer system emulating the decision-making ability of a human expert.

ROOT CAUSE ANALYSIS: Inject high-frequency event data from historians or offline data repositories. Parameters are presented to domain experts to filter specific analytics.

EXPERT SYSTEMS STAKEHOLDERS: Algorithms and rules are configured by domain experts and data scientists to provide root-cause recommendations

EXPERT SYSTEMS ANALYTICS: Streaming or forensic data is analyzed then visualized with interactive plots and graphs

Pratexo ABB Electrification Startup Challenge Winner

Pratexo is proud to collaborate with ABB on the development and refinement of the Root Cause Analysis Expert System.

Pratexo’s Expert System Framework for data-driven, rule-based diagnosis and decision-making of electrical systems

In conjunction with its customers and partners, Pratexo creates Expert System Solution Modules (such as ABB’s CAES – Causal Analysis Expert System) that run on its Expert System Framework. These Modules contain the custom data ingestion extensions, rule sets, algorithms, and reporting templates used by the Expert System Framework and are specific to each type of machine/asset or set of machines.

The Pratexo Expert System Framework can utilize sophisticated signal processing algorithms to detect anomalies, produce a digital graph relating fault conditions in equipment to root causes, including specific component failures, and deliver automated notifications. Solution Modules can contain sets of rules to pinpoint problems that only trained experts could normally detect, in order to recommend remediation actions to heal the system and ensure operational efficiency is maximized. The ABB CAES Solutions Module has already been developed to identify root cause faults in power networks.

Solution Benefits

  • Automated fault detection

  • Automated root cause analysis resulting in significantly reduced downtime

  • Library of signal processing algorithms for anomaly detection

  • Programmable backward and forward chaining rule system
  • Reports documenting the expert system findings
  • Automated real time notification system