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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.

What is Aspen Mtell?

Recognizing patterns in operational data is essential for anticipating deterioration and potential malfunctions well in advance. By implementing precise failure pattern identification, organizations can significantly reduce the occurrence of false positives that are often problematic in model-based methodologies. The use of advanced machine learning approaches enables a rapid differentiation between typical and atypical behaviors, which can lead to the activation of equipment protection measures within weeks rather than months. Additionally, the collaboration between Aspen Mtell and Aspen Cloud Connectâ„¢ allows for seamless access to devices operating under OPC UA, further enhancing analytical capabilities. This integration serves as a crucial line of defense against asset degradation by identifying early indicators of failure through operational data analysis. Moreover, incorporating AI-driven agent development improves current maintenance practices, enabling swift deployment of autonomous agents across multiple locations or even throughout an entire organization. With the focus on accurate failure pattern detection, businesses can greatly minimize the frequency of false positives often seen in conventional model-based approaches. By utilizing streamlined machine learning techniques, companies can quickly identify and respond to both standard and irregular activities, ensuring robust protection for their equipment and optimizing operational efficiency. This proactive approach ultimately fosters resilience and reliability in asset management strategies.

Media

Media

Integrations Supported

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

Integrations Supported

SAP Store

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Rockwell Automation

Date Founded

1903

Company Location

United States

Company Website

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

Company Facts

Organization Name

Aspen Technology

Date Founded

1981

Company Location

United States

Company Website

www.aspentech.com/en/products/apm/aspen-mtell

Categories and Features

Categories and Features

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