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    Graham Immerman
    Graham Immerman MachineMetrics / August 23, 2022

    New Automation Features and Expanded Connector Library

    Expanded offerings enable manufacturers to drive frontline worker productivity and factory systems with real-time machine data.

    NORTHAMPTON, Mass., August 23, 2022 -- MachineMetrics, a leader in machine data collection and production analytics for manufacturers, today announced the availability of new features that expand the ways in which the solution connects to and captures machine data. Additionally, powerful new automation capabilities enable manufacturers to eliminate previously time-consuming, tedious manual tasks and gain even greater visibility and efficiency throughout the shop floor. New features include:

    Automated Production Tracking: This capability enables manufacturers to capture operational data used to track production performance – such as cycle count, cycle times, part count, and more – straight from the machine with no requirement for human interaction, giving them a comprehensive view of what is happening throughout their facilities.

    Automated Operational Dataflow to Business Systems: This feature enables manufacturers to automate the flow of operational data into external systems, such as ERP or MES, in order to inform and track work orders without the need for time-consuming manual data input or manipulation.

    ifm IO-Link Connector: This connector enables manufacturers to gain more comprehensive insight into the conditions surrounding their machines in order to identify and reduce downtime associated with machine issues. With the ability to connect to 27,000 sensors available from ifm, manufacturers can easily capture environmental variables that are not measured via the machine control - such as ambient temperature, humidity, and coolant temperature - and leverage MachineMetrics to analyze and create automations to take action on that data.

    Universal Robots Connector: This connector expands MachineMetrics’ footprint on the shop floor by allowing customers to easily connect to and capture valuable data from any equipment from Universal Robots, a provider of industrial collaborative robots (or cobots) that automate and streamline repetitive industrial processes.

    Packaged CMMS Integrations: These packaged integrations enable real-time machine condition data to automatically trigger critical maintenance activities in the CMMS system, enabling manufacturers to more quickly and effectively address machine issues, reduce downtime, and improve machine health.

    Tool Wear Monitoring: This feature enables high-volume, discrete manufacturers to optimize the life of their tools using high frequency machine data captured at the source. By tracking tool wear patterns and anticipating tool breakages, customers can save on tooling costs, prevent unplanned downtime, reduce scrap, and improve product quality.

    “In the face of skilled worker shortages, supply chain disruptions, and other critical challenges, manufacturers need access to real-time data that enables them to make agile decisions, maximize resources, and outpace the competition,” said Bill Bither, CEO and co-founder of MachineMetrics. “These new features build on our mission to deliver solutions that make it easy to capture accurate, real-time insights straight from the source while minimizing the amount of manual human interaction on the shop floor.”

    About MachineMetrics

    MachineMetrics is the single platform to capture, manage, and analyze manufacturing equipment data. Transform machine data-driven insights into action with easy-to-use apps and automated workflows that empower frontline workers and other factory systems to operate more efficiently. Today, hundreds of manufacturers across global factories are using MachineMetrics as the foundation of their digital factories, leveraging plug-and-play machine data collection, real-time visualizations, predictive insights, and flexible APIs to optimize, adapt, and evolve their manufacturing processes no matter what the circumstances may be.


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