Problem with Falsified Data in PPAP Submission

Wes Bucey

Quite Involved in Discussions
#21
FWIW:
I always found a straightforward approach to be the most efficient.

If it were my supplier, I'd just say, "This chart looks like it was generated by a random number program. Do you have some samples we can examine to see if we can come close to replicating your results? The ideal, of course, would be if you had retained marked samples from your original data measurements."

Four years ago, I wrote (in http://elsmar.com/Forums/showpost.php?p=105469&postcount=18)
We had no quality inspectors (we did have quality trainers and guys who acted as "court of last resort" when a question would arise.) Operators did own first article inspections, based on control plan/inspection plan agreed with customer as part of contract review. Another operator would perform a redundant first article inspection with different inspection instruments. Marked sample with BOTH inspection reports was sent to customer for confirmation before production began.

In-process inspection, SPC, etc. was performed by operator in real time. If nonconformance was discovered, production would halt - all operators would collaborate on finding and curing cause, only calling in outside help if solution eluded them. Inspection records, charts, etc. went right to computer where they were available in real time to in-house folk and customers.
Our measurements were with instruments hard-wired (today I'd use wireless) directly to the computers where the measurements were entered into the software. They could have been fudged, but fudging was more difficult than just doing it legitimately.

We made a big deal out of having customers approve our production and inspection process as part of their contract review process. If you had done a thorough approval process of the supplier BEFORE granting a contract, you'd have more confidence in the quality data supplied with your products.

Under no circumstance would I fire the supplier without more proof of top management at the supplier instigating and approving data falsification.
 
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bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#22
Under no circumstance would I fire the supplier without more proof of top management at the supplier instigating and approving data falsification.
Good point, and add that to:

Even though our processes were were set to run at the low end of a spec (in order to save those dollars that were a requirement in the lower costs drive) and the statistics were all set to run dead center in the tolerance range. It never made much sense to me that we could produce everything in spec (no complaint for out of tolerance product for size in the 4 years I was there doing QS) yet the indices were all whack because they were offset from center.
....and you may have a vendor with a perfect process, but their data set does not "generate" an acceptable Cpk (far any number of statistically valid reasons). This - and their weak knowledge of statistics - could have painted them into a desperate corner, in which this data was an attempt to get the PPAP approved.

I can see this as a scenario - as I have witnessed it before.
 

Jim Wynne

Staff member
Admin
#23
FWIW:
I always found a straightforward approach to be the most efficient.

If it were my supplier, I'd just say, "This chart looks like it was generated by a random number program. Do you have some samples we can examine to see if we can come close to replicating your results? The ideal, of course, would be if you had retained marked samples from your original data measurements."
If the data had been the output of a "random number program," how would you be able to tell that the data was non-random? The fact is that people who are ignorant of the power of statistical analysis probably aren't even aware of random-number generators, and wouldn't know what to do with one if they were aware. Not only that, but people who are aware can probably fudge data without a random-number generator and present a report that probably won't arouse suspicion.

We made a big deal out of having customers approve our production and inspection process as part of their contract review process. If you had done a thorough approval process of the supplier BEFORE granting a contract, you'd have more confidence in the quality data supplied with your products.
To extend the tautology, if you do a good enough job of qualifying your suppliers, you won't need to have them submit data at all. The sad fact is that there are few people who are fortunate enough to work in a perfect shop with omniscient leadership. Things are a lot more difficult for mere mortals.

Under no circumstance would I fire the supplier without more proof of top management at the supplier instigating and approving data falsification.
"Instigating" usually isn't an overt or direct act; all it takes is for "leadership" to require people to defy the laws of physics in order to meet all of the requirements and then claim ignorance when the inevitable happens.

Another thing about PPAP submissions and data integrity--the PPAP elements should never be viewed in isolation (from one another). If you're suspicious of the data in a capability report, look at the GR&R and dimensional reports for the same dimension(s). Another way to tell that something might not be right is when, for example, the sample mean in the GR&R is significantly different from that in the capability report.
 

Sidney Vianna

Post Responsibly
Staff member
Admin
#24
Under no circumstance would I fire the supplier without more proof of top management at the supplier instigating and approving data falsification.
And how, do you propose, such proof would be gathered? Do you envision hiring a private investigator? Or calling the supplier top management and asking, point blank: Did you tell your employees to falsify data in my submission package?

Allowing, fostering and/or creating a corporate culture where an employee feels empowered and/or compelled to falsify submission data is as bad as directing a subordinate to do it.

To this date, former top brass of defunct Enron and Arthur Andersen claim ignorance of the wrong doings being perpetrated at lower levels. Do you know what? It does not matter if they instigated it or not. If your governance model and controls are not robust enough to prevent fraud, you, as a supplier is not deserving of doing business with reputable customers.
 
D

Dave Dunn

#25
If you're suspicious of the data in a capability report, look at the GR&R and dimensional reports for the same dimension(s). Another way to tell that something might not be right is when, for example, the sample mean in the GR&R is significantly different from that in the capability report.
I'd be cautious about using this as a flag for something wrong with the GR&R. I've had numerous cases in the past where we performed GR&R studies, but then had to tweak the tool to improve capability, but we do not re-do the GR&R study because the measurement system has not changed.

On other occasions our customers have accepted GR&R studies that cover multiple parts where the design is the same but key dimensions were slightly different size. The measurement system is the same, but the results don't necessarily match up with the capability results.
 

Jim Wynne

Staff member
Admin
#26
I'd be cautious about using this as a flag for something wrong with the GR&R. I've had numerous cases in the past where we performed GR&R studies, but then had to tweak the tool to improve capability, but we do not re-do the GR&R study because the measurement system has not changed.

On other occasions our customers have accepted GR&R studies that cover multiple parts where the design is the same but key dimensions were slightly different size. The measurement system is the same, but the results don't necessarily match up with the capability results.
Lack of congruence between PPAP elements is a "flag," as you put it, and it highlights a need for further investigation. No one should jump to conclusions without understanding what's actually going on. It's possible to infer from the dates of the GR&R and capability reports that something happened in the interim that would explain any disparity that might be there, but the inference should be confirmed.
 

bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#27
Equally heinous is allowing, fostering and/or creating a supplier relationship where an supplier feels compelled to falsify submission data because your interpretation of data is so faulty you can not accept valid results - albeit not 1.33.
 
S

swarbur4

#28
All,

Very interesting varied discussion on the issue.

1. The use of SPC, Run Charts PPAP information is to provide an insight to the capability, stability of the process / processes at the time they where taken. They are an estimate of the performance of a process / system.
2. The use of numerical goals (1.33) or stability rules (1 point outside of 3 sigma) etc is right - as long as you know what you are looking at, understand the data and the processes that make that data. Then you can make an informed decision on any actions needed or not.
3. Therefore the purpose of the data is to enable informed decisions to be made.
4. The main issue with PPAP, SPC, Run Charts, GR&R etc is that the results are not understood by the people who need to understand them either at your supplier, within your own company or at your customer.

5. Falsified data shows a company out of control not just a process.

Reply to my e-mail questioning the data is below.

-Dear Mr. Simon,

We also agree with you that this type of data is not possible in production process.

We analyzed at our end & found that Operators are measuring the parts but not entering the data into the run charts at same time. This is the reason to filled up the wrong data in run charts., because operators are not so much aware about the importance of the run charts & also there in no verification by the supervisor on regular basis.

We have trained our line operators about the importance of the run charts & educate them how important are these run charts & now they are filling the data on daily basis.& our line supervisors also started to verify that run chart data is filled up on daily basis .

We have enclosed the run chart data for your analysis for the month of Sep 09.

Thanks & Regards
 

Helmut Jilling

Auditor / Consultant
#29
I'll add my two cents. If data is inaccurate due to ignorance and not understanding how to do something right, then the motive may not be suspect and there is room to correct and improve.

If however, top management promotes a culture to willfully decieve and falsify data, just to get and keep business, that is MUCH more difficult to correct and will likely lead to continuing problems. This is one of the big issues with dealing with some overseas suppliers and is rarely calculated into the "savings analysis" that accountants do when they are discussing outsourcing. It is why much of the overseas outsourcing does not generate the "savings" they were expected to generate.
 
L
#30
Just something to think about... when supplier is cheating with false information who is being cheated?? the customer who is getting the data or the supplier is cheating himself.

It is clear that even if a supplier gets an approval sooner or later by cheating, he is gone to be in trouble because of the lack of capability. Is he going to say that he has lost capability or variation has increased? Higher scrap rates?

A lie has short legs!
 
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