IIoT and OEE in car manufacturing


Industry Week defines OEE (Overall Equipment Effectiveness) as “How much right-first-time product did this machine produce compared to what it should have produced in the allocated time?”


OEE (Overall Equipment Effectiveness) is the product:  OEE = availability x performance x quality


If a manufacturer wants to track their factory this way then all the data they need can be extracted from their IIoT and ERP systems.  Let’s look at an example.


The factors in the OEE are:

Availability Rate

running time / scheduled time


e.g. 10 hours out of 12 = 83%

Downtime, changeovers, and adjustments take away from scheduled time. Scheduled time is used instead of elapsed time, as no machine is scheduled to run 100% of the time.

Performance Rate

actual output / max theoretical output 


e.g. theoretical output = 60 minutes *

- 1.2 per minute = 72 

- actual output = 60 

- 60 / 72 = 83%

 Theoretical output is velocity times running time. So if a machine stamps out one device per minute under optimal conditions then it should product 60 devices in 1 hour.  To set a baseline, this threshold can be the maximum observed value over some period of time.

Quality Rate

(actual output - rejected output) / actual output 


e.g. total output = 60 

scrap = 1 

rework = 1 


(60 - 1 - 1 ) / 60 = 97%

 Rejected output includes scrap and rework.




67% = 83% * 83% * 97%



This simple math equation can be tracked in real time and continuously using ERP and IoT sensor data.  To do this the plant can measure The 6 Big Losses, which is breakdown OEE shown below. 


Availability (downtime)

1. Equipment failure (breakdowns)

2. Setup and adjustment

Performance (speed)

3. Idling and minor stoppages

4. Reduced speed of operation

Quality (defects)

5. Process defects (scrap, repairs)

6. Reduced yield (from startup to stable production)


Items 1 - 6 are calculated by looking at transactions in the ERP system and sensor data.  For example, the preventive maintenance module of the ERP system should have maintenance work orders for each equipment failure (Unless it’s very slight.).  Quality numbers come from the ERP production planning, quality management, and material management modules, for those manufacturers using SAP.  For manufacturers using other software, defects, yield, scrap, etc. data can come from whatever those modules are called in that software. Of course, this only works as long as those transactions are entered into those systems. Metrics not in ERP can be pulled from IoT.


Download relayr's



IoT Checks on Quality

Improving car manufacturing with IoT

IoT sensors can measure operating time, starts and stoppage, breakage, and quality.  


For example, harmonics can be used to determine whether a component needs rework or should be scrapped.  This pings a device with acoustic waves and listens for the resonance.  It’s the same as tapping on a finished item, such as a side panel on a vehicle, and listening that it sounds solid and nothing is rattling around.


The harmonics data goes up into the IoT cloud. Operators too can key rejects into the ERP system.


IoT Checks on Process

IoT sensors include stress, vibration, power usage, temperature, ambient light, humidity, etc.  Some of these, like power usage, are inexpensive and can be added to the manufacturing device in order to gather that data without requiring any kind of large, disruptive change to the device. 


For example, to know whether a press is operating, the plant can monitor electrical usage.  Then pair that metric up with the schedule time for the press, which is contained in the ERP system or just a static number.  Then match up that data in the analytics cloud and to calculate availability.


The RPM gauge on an electric motor shows how fast a machine is running.  That provides the slowdown metric needed to measure slowdowns needed to calculate performance.


The Required Infrastructure

To draw all of this data together, and have an automated way to calculate OEE, the plant needs to have IoT sensors, an IoT analytics cloud, and a big data database and programs to pair that data up with ERP transactions.  If the auto manufacturer is following the principles of Industry 4.0 they will, by definition, have all of those things.


Download relayr's