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.

Store values shown on the machine HMI. It is better to start the IIoT journey than wait to complete a complex definition project.
A common question is: what data should be collected? A good place to start is to capture everything shown on the machine’s HMI or operator interface. These include:
  • 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
(sample formats)
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.

© 2019 ei3 Corporation. Content of this web page is proprietary to ei3 Corporation.

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