Machine Monitoring Platform Increases Throughput, Productivity
IMTS 2018: Memex’s Merlin Tempus Enterprise Edition software platform, constructed using HTML5, .NET and RESTful APIs, offers machine monitoring and management functionality.
Memex’s Merlin Tempus Enterprise Edition software platform, constructed using HTML5, .NET and RESTful APIs, offers machine monitoring and management functionality. Real-time data collection capabilities capture machine-generated information and sensor data, including alarm states, feed and speed rate overrides, and other metrics. The platform displays this data on visual dashboards and KPI reports.
Features include role-based dashboards for production personnel, engineers, operators and managers; Op-Step management functionality; priority and alternate machine routings; asset management; traceability; event manager pan and zoom; analytics; and advanced data source conditioning. The Operator Portal features freeform text, serialization, rework and scanner support. An optional DNC software module facilitates program file transfer to machines with support for native machine protocols and FTP networking. Gateway architecture enables multi-plant operations across time zones.
The platform can connect to legacy machines and to a plant’s ERP system. According to the company, it reduces downtime, increases throughput and improves productivity.
CNC machine tools that operate like self-contained, automated smart factories can be an introduction or an addition to digital manufacturing workflows.
Introduced at IMTS 2008, this communications protocol for CNC machines and other manufacturing equipment is already helping shops and plants implement effective machine monitoring systems. Although these "early adopters" are motivated by the long-term promise of enterprise-wide efficiency gains, their experience with pilot projects shows that benefits derived in the short term are substantial and worthwhile.
A panel discussion at the recent Top Shops Conference focused on various points of view regarding the value of connecting machine tools to a network for monitoring performance and recording results. Because machine monitoring helps a shop make better decisions about manufacturing processes, it is a good example of data-driven manufacturing in action.