Acoem MV-x: Black Edition

Predictive maintenance powered by artificial intelligence (AI)

Acoem brings to you MV-x Black edition ,the next generation of AI-enabled vibrational analysis, with real-time edge computing, provides a pathbreaking predictive tool to pinpoint the source, direction, and intensity of the vibration. It represents a fundamental shift from reactive maintenance to predictive maintenance. More importantly, it provides vibration analysis and condition monitoring users, with a seamless industry 4.0 experience.

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Description

A CENTRALIZED SYSTEM

The data acquired by MV-x is automatically stored in the NEST software platform. Analysis of and access to the condition of production sites is simple: reports are accessible in just a few clicks, navigating from a map of the world to a detailed view of a machine

EASY TO DEPLOY

MV-x communicates and transfers its results in automatically and reliably to the NEST software via a secure Ethernet link. Operators can choose to use the local cabled network, a Wi-Fi network, or over the Internet via a3G link, for example

INTEGRATED INTO YOURENVIRONMENT

MV-x can be fully integrated into your environment. Process information is retrieved directly from the PLCs, eliminating any duplication of data. The advanced indicators defined can be transmitted in order to improve process management, and maintenance management is optimized thanks to an interface with the CMMS system

SMART MONITORING

Real-time monitoring of one or more machines. Storage of measurements required for analysis: the right information at the right time. Easy analysis of complex machines through management of operating conditions. Early detection of faults on slow shafts with Shock Finder

COMMUNICATION

Two-way communication with PLCs. Alerts by e-mail / logic outputs. Management of sub-optimal communication conditions (3G) for isolated machines

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About Condition Monitoring Solutions

Maximise the reliability of your critical rotating assets

Predictive or condition-based maintenance is a proactive maintenance strategy that allows you to monitor the performance and condition of your machinery in real time. Doing so will enable you to enhance machine reliability and accurately predict when your equipment needs to be maintained —rather than waiting for it to fail. Using a combination of wired or wireless sensors, Internet of Things (IoT), augmented mechanics, machine learning and data analytics, Acoem’s predictive maintenance tools portfolio will help your business anticipate problems before they occur. Schedule maintenance activities at the right time, receive alerts for potential issues with a degree of certainty and enhance your overall industrial productivity.

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