Dear Experts,

I am measuring the Overal Equipment Efficiency (OEE). What chart and how should I be using to see whether my process is stable or no...

For OEE we measure the availability of the machine (Total available time-breakdown hours), we measure the utilisation of the machine(Available time-downtime affecting utilisation of machine) and also we measure rejection status.

OEE= Availability*Utilisation*Quality performance

Please help with an example so as to get a clear understanding as o what should be in the x and y axes, what data should I take for x, i.e. whether days or time....

Dear Experts,

I am measuring the Overal Equipment Efficiency (OEE). What chart and how should I be using to see whether my process is stable or no...

For OEE we measure the availability of the machine (Total available time-breakdown hours), we measure the utilisation of the machine(Available time-downtime affecting utilisation of machine) and also we measure rejection status.

OEE= Availability*Utilisation*Quality performance

Please help with an example so as to get a clear understanding as o what should be in the x and y axes, what data should I take for x, i.e. whether days or time....

Your time interval (days, weeks, months, quarters) will relate to how much equipment you have, and how fast you need to be able to detect a shift versus the cost of collecting, processing, and posting the data. If you are plotting an individual machine, I'd probably shoot for monthly. If you are consolidating many machines together, then probably weekly or daily. It also depends on how fine of a time increment you have for outages. Once a machine breaks down, if it is down for days before repair, plotting every day may not make sense. If we are worried about a machine being not available for even 10 minutes, you may be plotting shiftly.

I'd use a p-chart control chart for these charts. For each time interval you are collecting the sum total of all available hours of all machines being considered. This will be the denominator. The numerator will be the total available hours, minus any downtime hours. You will then plot this percentage on the y axis, and time increments on the x axis. Add the baseline average and control limits, and you are done.

Hi Steve,

Thanks for the input. We are having only one machine. And the data trackinng of loss hours is done shiftwise and modelwise. My concern here is that what should I be plotting, when you say total available hrs - any downtime....because availability is the actual time that is available in a day - the downtime when the machine has been down and totally not available for production.

Utilisation is separately tracked....it is available time after downtimes - time when the machine was not utilised.

Then it may not be possible to plot with sum total of all downtimes....

Also for rejections, I may be able to plot the charts as mentioned I suppose...Pls. correct me incase I am wrong.

It seems you could use a I-MR chart here, since the parameter is continuous.

Let me make sure I understand the situation. Suppose that during an 8 hr shift, the machine was down for repairs for 1 hr. Then

Availability = 7/8 = 0.875 = 87.5%

Now suppose the machine is actually use for 5 of the 7 available hours. Then

Utilization = 5/7 = 0.714 = 71.4%

During that 5 hr, 95% of the parts produced were good. The final OEE would be

OEE = 0.875 * 0.714 * 0.95 = 0.59 = 59%


You should be able to just plot the 0.59 on an I-MR chart. Each shift you could update the chart and watch for trends.

By the way, it would seem logical to plot each of the three factors (Availability, Utilization, and Quality) separately. That would make it easier to track the root cause of the variations.


Tim F

P.S. The % of parts that are good might not be the best metric for quality performance. Some measure of the true cost of quality could be better. For instance, if the machine is producing 80% good parts, it could well be that the costs for scrap, rework, overhead, etc for the bad parts eat up all the profits. In this case, running the machine for that shift has not produced any profits for the company, and the OEE might be considered zero in this case!

Hi Tim,

Thanks for your valuable inputs:) . You are absolutely right that OEE at the rate of quality performance taken only @ rejection is not right.

And that is the reason I also did not want to plot OEE separately. Because there could be a measurement variation also by the operators in mentioning the rejections. This I m telling because the in production scrap (not rejection) that is produced per model is defined. So when I compare the scrap details with the model for a particular day I got a figure less than reported which means that the reported scrap included rejections as well. But the rejection rate for that day was 0. How do I tackle such issues....

On many of the days there are no rejections at all. But on those days there is production scrap that is generated. Earlier the production scrap and the rejections were merged and it was not easy to get the rejction figures.
Now it has been segregated.

Please could you guide me as to what other measures should I take into consideration w.r.t. the quality performance for measuring OEE.....
Do you have any excel sheets which you could share please...

Attached are 2 sheets we have been using in the past.

Best regards,

Antoine

Thank you for the excel sheets.

Awsome OEE sheets

thanks for your valueable ELS!:thanx:

anyone can help me with another problem?
that is: is there a standard or criteria to assess OEE result, which is good and which is bad.

thanks for your valueable ELS!:thanx:

anyone can help me with another problem?
that is: is there a standard or criteria to assess OEE result, which is good and which is bad.

The following measures are typically defined as being at the world-class level:

Availability 90.00%
Performance 95.00%
Quality 99.90%

These can also be found at the bottom of the attached worksheet (just enter your data in the yellow fields only).

Wayne

The following measures are typically defined as being at the world-class level:

Availability 90.00%
Performance 95.00%
Quality 99.90%

These can also be found at the bottom of the attached worksheet (just enter your data in the yellow fields only).

Wayne

hi, good friend,
your information is costful! this level must be world-class level, right?
is there a normal level?
but i think your attached excel is too simple, other downtime, set-up & adjustment time, scrap & rework parts also should be considered.

Never mind the world class level or even " normal level "

The following should be the normal thing to do :
1) Check where you are
2) Search for reasons why the " better " situation is not achieved
3) Discuss which steps to take against those reason(s)
4) Implement actions
5) go back to 1)

Hope this helps,

Best regards,

Antoine

Please find here a sort presentation of oee
If you want a complete exel file please let me know

merry christmas

hi, good friend,
your information is costful! this level must be world-class level, right?
is there a normal level?
but i think your attached excel is too simple, other downtime, set-up & adjustment time, scrap & rework parts also should be considered.

That's correct, those levels are for what would be considered world-class. While there may be "common" scores for specific machinery, operations, industries, etc.; that is something that perhaps a local university or industry organization could better assist you with. The goal of using OEE is to constantly improve and provide a means of identifying problem areas, the cause of the problem, and to benchmark your results.

All the items you mentioned, are included in the excel sheet, it just isn't broken down into all the tidbits of information. For instance, scrap and rework are entered into field "G" (Reject Pieces). Set-up and adjustments are entered into field "D" (Down Time).

If you reference the powerpoint slides posted by Dhaenens, which is very nice by the way :), you see set-up listed under the down-time category. What is interesting is that Dhaenens identified eight key areas for loss as opposed to the original six that were commonly used. I've seen a few instances where as many as 16 areas of loss were identified.

If you want a great reference: Introduction to Tpm: Total Productive Maintenance, Seiichi Nakajima (http://www.amazon.com/Introduction-Tpm-Productive-Maintenance-Preventative/dp/0915299232/ref=sr_1_3?ie=UTF8&s=books&qid=1197990247&sr=1-3) or check out the list of books at: Productivity Press - TPM (http://www.productivitypress.com/shopping_cart/categories/categories_products.asp?parent_id=28).

Wayne

Gents

Here is a sample of a OEE XLS file that you can use

Gents

Here is a sample of a OEE XLS file that you can use

Hello Dhaenens,

Have you tried to attach the file? It's not there.

Stijloor.

Nog een keer proberen?

Hello Dhaenens,

Have you tried to attach the file? It's not there.

Stijloor.

Nog een keer proberen?

Another OP that was under 5 posts... now as his 7th post he will be able to post attachments... deja vu...

another excel about OEE calculation.
its data is based on real monthly statistic, just used for example.:notme:

gtttang

I have a little problem with this OEE. I count it for a one compay. There are 3 shifts, and in one or more shifts i have sometimes mold changing. So i have for example: shift1 (product1), shift2 (product1,change, product2), shift3 (product2, change, product1) Am not sure, how should i count it properly, when i have only 3shifts in my OEE xls calculator, (every product has different cycle-time). Should i take a middle quantity from each product of one shift or make a different calculator, more standarised.

If anyone understood what i mean, please for reply:) Thanks.