With CNC machines capable of generating production data in real-time and their interconnectivity via Ethernet networks, managing data becomes essential to improving current manufacturing processes. We now have the real-time capabilities to monitor equipment and make decisions in real-time instead of waiting until the job is complete, to realize that some process took longer than it should have. The old way was to manually account for time at each machine and for each job, and in the end tally up the time that it took to complete the job. This sort of batch analysis does not allow for real-time monitoring of machines and is certainly not conducive to making on-the-fly decisions and improvements.
Continual improvement in the manufacturing process is essential to remaining competitive. Real-time data enables processes to be measured as they occur, and as data accumulates over time, to measure process consistency. Without data and the means to store and analyze the data, then there is also no means to measure the process. But real-time data goes far beyond process analysis by also providing the triggers for automated systems to also make real-time decisions.
Automated systems do not need human intervention to initiate a process, they only need a trigger. The trigger can be data driven or logic driven. In any case the trigger is mostly logic based, if X trigger exists then do Y. When a job is released by a production planning system to the Nesting system, the system can automatically separate the job by material type, thickness and due dates. It can then make decisions as to when the job needs to be nested based on due dates and or having sufficient parts to yield a high material utilization. The nesting system can release the finished nest to the machine based on achieving a minimum material utilization yield. The trigger to the machine and the automated material handling system is the job data which contains not only the material information but the machine CNC code itself. Once this data is received the machine automatically begins its process of setting up the proper machine parameters to process the material and the automated material handling system to load the material onto the machine table. Machine operators can access the real-time maintenance task list which is kept in sync with the number of actual hours that the machine has been in operation. The system will prompt when maintenance is due on all aspects of the cutting machine. When a prompt appears for a specific item to be maintained the operator can select the adjacent maintenance icon and go directly to the instructions for performing that specific maintenance task.
At the highest level of information knowledge is the ability of machines to communicate in a standardized format so that 3rd party OEE (Overall Equipment Effectiveness) and OPE (Overall Production Efficiency) software can analyze the data. The OPC communications protocol is an industry standard communications protocol and OPC software serves as a data interface to 3rd party OEE and OPE software for high level analysis of manufacturing processes, machine performance and total quality. With OEE data, companies can identify opportunities through analysis, where predictive measures can be implemented to offset unplanned downtimes. With OPE, all aspects of the production data including job and individual part times are analyzed, machine uptime and performance is analyzed, quality and non-conformances are also analyzed. All of this data enables managers to monitor their process and their equipment and make the proper decisions in real-time.
By Frank Arteaga, Head of Product Marketing, NAFTA Region
Bystronic Inc., Elgin, IL – Voice.firstname.lastname@example.org