Today, everything that is important to the productivity and quality of a machine is controlled by a Programmable Logic Controller (PLC), industrial PC, or embedded computer. Internet communications using standard protocols make instantaneous readings of key values from these controllers readily available to be collected as data. Examples include OPC-UA, PackML and others.
Machine data is collected online by cloud servers that gather and store key values in a database. This forms the foundation for analytic-driven insights that ultimately improve machines and production.
- Machine set points
- Machine feedbacks and states
- Machine faults
For some detailed examples of data points one might use, see the table below.
For more details on these fields and their meanings, see this article on data point creation.
Device |
TagName |
Description |
PLC Address
|
Units |
MaxValue |
MinValue |
Category |
Machine PLC |
Temp_A |
Temp A from machine |
Siemens: DB249:int12 |
Fahrenheit |
500 |
0 |
Temperature |
Machine PLC |
Tens_Rew |
Rewind Tension Actual |
Lb |
120 |
10 |
Tension |
|
Main PLC |
Print_Fault |
Printer Fault |
AllenBradley: n7:1 |
– |
– |
– |
Alarm |
Main PLC |
Perf_Start |
Perforator Cut Delay |
Seconds |
– |
– |
Delay (Time) |
|
Machine PLC |
Linespeed |
Current Machine Speed |
FPM |
1500 |
0 |
Machine Speed |
|
Machine PLC |
ReelLength |
Reel Length |
Ft |
1.0E8 |
0 |
Reel (Roll) |
The largest improvement opportunities usually come from the largest sources of unplanned machine downtime. So the most fruitful efforts start by finding these largest sources. This requires capturing every downtime event and the reason behind it. Pareto analysis and tree maps of these unplanned downtime events separates the vital few from the trivial many and quickly reveals problems that hold promise for machine improvement.
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