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What is PreCognize?

In a highly interconnected process industry characterized by a lack of historical data, the challenge of unpredictable failures remains ever-present. Our all-encompassing monitoring solution effectively detects quality issues, equipment breakdowns, operational deviations, and unusual process activities. Instead of wading through a sea of false alarms, we refine this to provide no more than five significant alerts each day. This system enables advanced warnings of potential failures, with notifications issued anywhere from a week to just 24 hours in advance, thereby preventing unexpected interruptions during off-peak hours. By focusing on proactive and scheduled maintenance, we not only boost operational efficiency but also significantly lower costs. The distinct requirements of industrial assets call for a creative strategy; we expertly combine your team's knowledge with cutting-edge machine learning technologies to establish a customized predictive monitoring framework. Using your current sensors and data, the setup is quick; within two weeks, a process engineer can map out the plant's structure and functions, after which the software becomes fully functional, laying the groundwork for enhanced reliability and performance. This swift implementation guarantees that your operations can rapidly reap the rewards of improved monitoring capabilities, ultimately fostering a more resilient industrial environment.

What is Plex Asset Performance Management?

Proactively manage the condition of machinery and facilities to ensure peak operational efficiency, productivity, and timely maintenance interventions. Harness the power of analytics in conjunction with Industrial IoT technologies to gain deeper insights into the performance of equipment on the production floor, thereby enabling advanced predictive maintenance strategies. Vigilantly monitoring the health of machines is crucial to reducing production delays caused by unforeseen breakdowns and outages. By advocating for predictive maintenance, the duration needed to diagnose machine health issues can be considerably shortened, while also improving the tracking of historical performance data. Bring together IT and OT information into a cohesive framework to connect plant floor insights with MES data, which enhances the decision-making process significantly. Utilize real-time data collection and integrated analytics to observe live metrics related to machine health and performance, evaluate machines against optimal operational benchmarks, and provide timely alerts regarding possible disruptions, thus aiding in the reduction of overtime labor costs, scrap rates, emergency maintenance expenditures, and negative effects on financial performance. This holistic strategy not only boosts operational productivity but also cultivates a proactive management culture throughout the manufacturing landscape, ensuring sustained growth and resilience in the face of challenges. Ultimately, this approach paves the way for continuous improvement and innovation in manufacturing operations.

Media

Media

Integrations Supported

PI Vision
dataPARC Historian

Integrations Supported

Plex Manufacturing Execution System (MES)
Plex Production Monitoring
Plex Quality Management System (QMS)
Plex Smart Manufacturing Platform

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

PreCognize

Company Location

United States

Company Website

www.precog.co

Company Facts

Organization Name

Rockwell Automation

Date Founded

1903

Company Location

United States

Company Website

www.plex.com/products/asset-performance-management

Categories and Features

Maintenance Management

Technician Management

Categories and Features

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