Automating Machine Monitoring And Data Collection
This automated machine data collection software automatically collects a wealth of information specific to machining processes and presents it in an intuitive format so users can quickly analyze the data and implement changes.
.jpg;width=70;height=70;mode=crop;format=webp)
Some shops take strides to manually collect and analyze machining data to identify and remedy hidden process inefficiencies. However, such manual data collection is often not only ineffective in determining the root cause of existing problems, but it can be challenging to put accurate, unbiased numbers on critical elements of the machining process. In addition, these efforts tend to be resource-intensive, requiring attentive, disciplined operators to accurately record production information. It also necessitates a healthy amount of data entry and database management before beginning process analysis and taking corrective actions.
To streamline and simplify such efforts, GE Fanuc developed miView, automated machine data collection software aimed at small- to medium-sized manufacturers. It not only automatically collects a wealth of information specific to machining processes, but it presents that information in an intuitive format so users can quickly analyze the data and implement changes. The company says that it is possible to improve spindle utilization by 10 percent through low-cost efforts taken after analyzing production data related to machine, part and work shift.
The software is compatible with GE Fanuc, Fanuc, Siemens and other machine controls.The three key software elements include real-time machine status monitoring, spindle utilization analysis and downtime analysis. Machine status monitoring provides a dashboard showing the actual run status of each machine, including a description of any active downtime alarms. Part identification and count fields provide a quick overview of the progress of jobs being processed on each machine.
Spindle utilization information is collected for every part produced on a machine. The software reveals exactly how much of the cycle time that a machine is actually in cutting mode. This spindle utilization analysis offers insight into, for example, the efficiency of CAM postprocessors while uncovering discrepancies between different machines producing the same part. Variations by machine or by work shift can also be evaluated for best practices and/or for process improvement opportunities. In addition, this information can help manufacturers evaluate the profitability of each job.
The miView software collects all CNC system and machine tool interface alarms to help eliminate root causes of repetitive problems. Maintenance engineers can analyze the downtime reasons for individual machines or groups of machines over any specific time period. By evaluating the top ten downtime Pareto charts, users can prioritize their efforts by eliminating the problems that have the biggest impact on machine availability. The software also provides statistics related to mean time between failures and mean time to repair, allowing users to separately analyze the root cause of a problem and the maintenance team’s ability to respond and correct it. All data collected by miView can be easily exported to a spreadsheet, Word document or PDF file for reporting purposes.
Related Content
-
How to Grow the Business with Real-Time Job Status Data
ERP systems that focus on making data more accessible can improve communication within a shop, reducing wasteful errors and improving capacity.
-
Can Connecting ERP to Machine Tool Monitoring Address the Workforce Challenge?
It can if RFID tags are added. Here is how this startup sees a local Internet of Things aiding CNC machine shops.
-
Improving Workflows in Small Shops with Custom ERP
Small shops might not be ready for all of the functionality of an off-the-shelf ERP system, but modular, custom ERP programs can help improve workflow while providing the flexibility to change as shops grow.
