The Machine Utilisation Analysis and Job Report modules can be used to generate performance reports that act upon the NMS central data repository which hosts the data collected from the Machine Monitoring and SFDC modules.
These reports can be presented as simple log files chronologically listing all events by date and time and viewed as pie charts showing machine utilisation and lost productivity with trend analysis and individual job reports detailing the time taken on the various job activities together with a comparison of planned vs actual. The collected log files are also available for export to other external; packages, e.g. spreadsheets, HTML reports, etc.

OEE - OEE data provides a valuable indication of actual resource, groups of resources or site efficiency. This data shows information that can be used to evaluate if processes are correct, highlight resources that are under utilised or identify resources that are suffering reliability problems. It provides the basis on which improvement strategies can be implemented.

The OEE Analysis software combines the measurements of machine availability, productivity and the quality of parts produced to give a simple measure of how well a machine is being used. The OEE software displays the machine performance results for individual jobs with the additional benefit of providing accumulative results for multiple jobs over a selectable period of time.

Real-time Probe - the probe data collection module automatically collects in-cycle probing results in real-time from CNC machines equipped with precision probes and a suitable data output facility. The collected data can be routed via Tricorn's NMS internal configuration facility (SBS) to create records or feed SPC systems. In turn these external packages can be used to generate records, trigger alarms/alerts and generate SMS or emails. A unique facility is incorporated whereby the software is able to support both DNC and data collection for CNC machines equipped with a single RS232 port.

Probe data collection provides information to support management reporting and can be used to generate valuable warnings of potential problems that may impact production, thus extending a level of confidence in the manufacturing support environment that a process is stable and under control.