In our previous post (Calculating OEE – A Simple Example, Part 1) we saw how to calculate OEE using only the Good Parts count and the Planned Operating Time. Now we are going to calculate OEE for the same example using the Availability, Performance and Quality Losses. This is a more complex way of calculating OEE but it provides us with the data to identify the main reasons for loss.

Remember our example:

Over a 12hour shift, our Filling machine fills 11,000 bottles. The manufacturer has specified that the Standard Time for this Filler to fill one bottle is .05mins/bottle. Over the course of the shift there are some Planned Downtimes: 2 x 15minute tea breaks and 1 x 30minute lunch break.

Planned Operating Time

 Planned Downtimes:

    15mins | Morning Tea Break
    30mins | Lunch Break
    15mins | Afternoon Tea Break

 Planned Downtime:  60mins

Total Time:   720mins

Therefore:
 Planned Operating Time = 720mins – (15mins + 30mins + 15mins)
     = 660mins

Availability

Now let's look at Availability. In our previous post we defined Availability as ((Planned Operating Time) – (All Availability Losses)) / (Planned Operating Time)

We know our Planned Operating Time is 11hrs. So if we know our Availability Losses we can calculate Availability. Availability Loss are all downtimes related to Breakdowns and ChangeOvers.

Over the course of our Shift we logged downtimes as follows:

 Availability Losses:

    25mins | ChangeOver
    10mins | No Caps in Hopper
    15mins | No Air

 Availability Loss: 50mins

Planned Operating Time: 660mins

Therefore:
 Actual Operating Time = 660mins – (25mins + 10mins + 15mins)
     = 610mins

and:
 Availability  = (Actual Operating Time) / (Planned Operating Time)
     = 92.4%

 

 Performance

The Performance Loss is a combination of Short Stops and Speed Loss. Short Stops are momentary downtimes which aren't Breakdowns or ChangeOvers which stop the machine and interrupt production but do not generally require technical support. In general for Manual Systems Short Stops are ignored as it can be onerous to record each stop. This results in the loss associated with Short Stops being built in to the Cycle Time Speed Loss. In Automatic Data Capture Systems it is more realistic to log Short Stops.

Rather than take a Cycle Time measurement and assume that this Cycle Time was constant over the whole shift it is often more realistic to calculate the Net Operating Time by working back from the more easily measured Throughput (ie sum of Good Parts and Defect Parts).

We know that the number of Bottles filled was 11,000

Defects:

250 | Underfilled

100 | No Cap

Defect Parts: 350

Good Parts: 11,000

Thus we can calculate our Good Time (ie Standard Time to produce Good Parts) and our Defect Time (ie. Standard Time to produce Defect Parts).

Good Time = 11,000 x 0.05

= 550mins

 

Defect Time = 350 x 0.05

= 17.5mins

 

Where 0.05mins/bottle is our Standard Time to produce one bottle.

 

Therefore:

Net Operating Time = (Good Time) + (Defect Time)

= 567.5mins

 

and working back we see that:

 

Perfomance Loss = (Actual Operating Time) – (Net Operating Time)

= 42.5mins

 

We now know the Net Operating Time therefore we can calculate the Performance.

 

Performance = (Net Operating Time) / (Actual Operating Time)

= 93.0%

 

Just for the sake of completeness let’s say that the machine stopped 10 times due to Falling Caps. Each stop was 6 seconds in duration and didn't require any technical intervention. We can say that the machine suffered 1min of downtime due to Short Stops.

Subtracting the Short Stops from the Performance Loss gives us the Speed Loss (Slow Running). ie the Loss due to the fact that the machine was running at a slower rate than the optimum rate specified by the manufacturer.

 

Speed Loss = (Performance Loss) – (Short Stops)

= 41.5mins

As a matter of interest our average Cycle Time over the Shift was ((Net Operating Time) + (Speed Loss)) / ((Good Parts) + (Defect Parts)) = (609) / (11,350) = 0.0537mins/bottle. Thus the Filler took on average 0.0037mins more then the Standard Time to fill each Bottle.

Quality

Finally we consider Quality Losses, ie the time taken to produce Defect Parts. In the above section we have already calculated the Good Time and the Defect Time. Defect Time is another name for Quality Loss and Good Time or OEE Time is the same as Fully Productive Time.

Thus we have every thing to calculate Quality.

 Quality  = (Fully Productive Time) / (Net Operating Time)
    = 96.9%

Note: Quality is only equal to (Good Parts count) / ((Good Parts count) +(Defect Parts count)) when the Standard Time is the same for all parts run on the machine over the shift.

Now the final calculation;

 OEE   = Availability x Performance x Quality
    = 92.4% x 93.0% x 96.9%
    = 83.3%

By taking the long way round we have generated 3 additional KPIs and we have a lot more data which we can use to focus in on the causes of loss.

Let's briefly take a look at the Level 1 Losses in a table ordered by size of loss

Availability Loss	50.0mins
Performance Loss	42.5mins
Quality Loss	17.5mins

This tells us that in this example downtimes are the most significant type of loss.

And now look at the individual losses in a similar table

Speed Loss (Slow Running)	41.5
ChangeOver	25.0
No Caps in Hopper	15.0
No Air	10.0
No Cap (Defect Time)	12.5
Underfilled(Defect Time)	5.0
Short Stops	1.0

Here we see that Speed Loss is in fact the biggest individual loss. In the absence of a downtime monitoring system Speed Losses are often missed as it can appear that the machine is running perfectly well when in fact it is producing much less then it should.

When generated on a shift by shift basis these tables are helpful in the day to day operational management of the machine. However when calculated over longer periods of time you can build up a very insightful picture as to the real causes of loss – as opposed to your presumptions – which may or may not in fact be correct.

In our next post we will show how Provideam can help to organise the data you have collected manually into a database which can be analysed in many different ways. The beauty of a database over a spreadsheet, like Excel, is that the data can easily be grouped and filtered by all sorts of interesting criteria in a rapid and flexible manner.
 

OEE and Lean Manufacturing Lean Manufacture, OEE, OEE and Lean Manufacturing, OEE Loss

Our previous post ‘Modern Producton Metrics – OEE‘ explains that OEE is a measure of how effectively we are using our equipment (ie how much of our time is spent producing good products compared with how much time we planned to operate).

Very simply we can say that

 OEE = (Fully Productive Time) / (Planned Operating Time)

Where Fully Productive Time is equivalent to (No. of Good Parts) x (Standard Time to produce 1 Part)
and Planned Operating Time is equivalent to (Total Time) – (All Planned Downtime)

Expressed as a percentage this simple calculation gives us our headline OEE value.

Simple Example:
Over a 12hour shift, our Filling machine fills 11,000 bottles. The manufacturer has specified that the Standard Time for this Filler to fill one bottle is .05mins/bottle.

Therefore our Fully Productive Time = (11,000) x (0.05) = 550mins

Over the course of the shift there are some Planned Downtimes: 2 x 15minute tea breaks and 1 x 30minute lunch break.

Thus the Planned Operating Time = (12hrs) – (2 x 15mins + 1 x 30mins) = 660mins

Giving us an OEE = (550) / (660) = 0.833 = 83.3%

Note we have lost out on 110minutes of possible productive time.

Now we know how effective we were but we have no idea where we lost time. Typically at this point various stake holders might suggest that the losses are due to one thing or another. These suggested losses are generally not based on any objective data. Before investing in improvement activity we need more definition on the causes of our 110minute loss.

The beauty of the OEE system is that it is much more than a simple measure of overall equipment effectivity. It also provides a framework for measuring and categorising losses in a manner which simplifies the analysis of the losses. This categorised framework helps greatly to identify the major losses and sets us on the path to finding and eliminating the root causes.

3 basic categories of losses

The OEE system considers that there are 3 basic categories of losses (OEE Level 1 Losses);

 Availability Losses: time lost due to Breakdowns and Changeovers
 Performance Losses: time lost due to Short Stops and Speed Loss (Slow Running)
 Quality Losses: time lost producing defect parts

In our previous post (Modern Production Metrics – OEE) we have explained that this categorisation of losses leads to 3 further KPIs

•  Availability: a measure of Uptime versus Planned Operating Time
    = ((Planned Operating Time) – (All Availability Losses)) / (Planned Operating Time)
    = (Actual Operating Time) / (Planned Operating Time)
   
•  Performance: a measure of the actual machine Cycle Time versus the Standard(ideal) Time
    = ((Actual Operating Time) – (All Performance Losses)) / (Actual Operating Time)
    = (Net Operating Time) / (Actual Operating Time)
   
•  Quality: a measure of the time spent producing Good Parts versus the time making all parts, Good and Defect.
    = ((Net Operating Time) – (All Quality Loss)) / (Net Operating Time)
    = (Fully Productive Time) / (Net Operating Time)

Note: We use the term OEE Time interchangeably with Fully Productive Time.

Multiplying these three KPIs together, by cancelling above and below the line, results in the following fraction;

 Availability x Performance x Quality = (Fully Productive Time) / (Planned Operating Time)

Which we already stated at the top of this post is OEE.

So these three KPIs when multiplied together produce the OEE value. We have seen at the top of this post how to calculate OEE from the Good Parts count and the Planned Operating Time. Now we see that we can also calculate OEE if we know the Availability Losses, Performance Losses and Quality Losses.

In our next post we will describe how to calculate OEE from these losses.
 

OEE and Lean Manufacturing