Siemens’ ManageMyMachines App Enables Full Data Tracking of Machine Kinematics
Appears in Print as: 'App Enables Full Data Tracking of Machine Kinematics'
Siemens’ Manage MyMachines app gives shops and production departments a transparent display of all CNC equipment on the floor, regardless of location, brand, function or usage.
Edited by Angela Osborne
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Manage MyMachines securely connects CNC machines to the Cloud so users can quickly ascertain the status of their machine tools and improve their maintenance and service programs.
Siemens’ Manage MyMachines app enables full data tracking of machine kinematics as well as production data. It is one of the MindApps within the company’s Mindsphere concept, a cloud-based “platform as a service.” The app can serve as an initial point of entry for machine shops, production departments or contract manufacturers looking for company digitalization.
The company says that digitalization is or soon will be an essential component in the operating philosophies at all companies. In response to this evolution of Industry 4.0, Siemens developed the Manage MyMachines app to create new and viable possibilities for increasing productivity (in combination with the highest achievable quality output and adherence to production schedules), plus reduced maintenance and service costs.
The concept is designed to be a gateway to the digital factory for Siemens’ associates in the machine tool world, including builders, integrators and end-users of all shapes and sizes. For the builder, the app is said to offer an immediate ability to monitor the global install base. Shops and production departments, in tandem with their system integrators and other business partners, are said to benefit from a transparent display of all CNC equipment on the floor, regardless of location, brand, function or usage.
As a MindApp within the Mindsphere portfolio, Manage MyMachines is integrated in the cloud-based, open IoT operating system, as it enables access to all critical machine tool information — from bearing temperature to production by shift or job — all in a selectable priority scale, based upon user needs. Unexpected line downtimes and off-normal machine kinematic conditions can be quickly identified and rectified. Also, predictive maintenance can be programmed, so an upcoming failure can be anticipated with alerts sent to a local distributor, for example, to deliver the needed components.
Complete asset management is further possible via the app, as resource consumption and energy usage are trackable, all in the cloud and accessible through the app in real time.
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