Control Chart to Track Effectiveness of Actions to Reduce Scrap Rate

abhipatel

Involved In Discussions
#1
Hi

Need to plot some data and form a control plan based on them.

Data is weekly in form of scrap value ($ amount), revenue generated ($ amount) and allowable scrap rate (again $ value calculated based on the revenue generated) and target scrap rate ($ value).

Can I use an attribute chart (p or np) or since it is $ value have to go with continuous charts like X-MR?

I want to track effectiveness of some action items based on some implementations to reduce scrap rate. Could I possibly convert the $ value into some fractions and use it to plot an attribute chart?

Kindly suggest.
 
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Miner

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#2
Re: Control Chart

I normally would always recommend a variables control chart over an attribute control chart. However, this makes an exception.

I foresee a problem if you use $s in a variables control chart. Presumably you have a variety of product with differing values, particularly if it is scrapped at differing stages of assembly/processing. Changes in mix would result in spurious trends, runs, etc. in a control chart based on $s.

Given the options that you stated, I recommend an attributes control chart. You can use a p chart for tracking defectives, or a c chart for defects when the samples size varies. np charts would work for defectives if the sample size is constant.

Do you have an analysis of what defects are responsible for your scrap. Can you determine the cause of your scrap and monitor the cause(s) using a variables control chart?
 

abhipatel

Involved In Discussions
#3
Re: Control Chart

Thanks

I want to monitor the trends of the scrap rates...the issue is that it is not very simple to plot attribute charts for my scrap data as the causes are numerous.

If I wanted to make a conclusion that the $ value of scrap has reduced indicating that my implementations were effective can I? sounds pretty vague but I do not have some attribute data like defects and defectives to be able to plot a p,c or np chart?

Are there any other ways wherein I can track scrap rate? Any examples probably? I could monitor by saying I had 5 scrap boards this week out of 100 shipped (proportion defective) and next week maybe 3 out of 100...but this might mislead as the 3 boards scrapped might have a higher dollar value and be more bad for the company (do not want to show I made an improved in proportion defective and my manager throwing it back on my face :lmao:).

Thanks
 

Miner

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#4
There are no technical issues with running a variable control chart on $ values, but you will have the opposite problem. Did the scrap rate decrease from a process improvement or only from a change in mix to lower value product?
 

Bev D

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#5
there are many issues with control charts for dollars most of which Miner has already articulated. The main one however, is that $ is not directly actionable.

However, I understand the desire to track $. What I do is to have an X, MR chart on the $ - nothing fancy. Be aware - and take the time to educate your audience that there will be false alarms on the $ chart due to the nature of dollar values. I also have a series of drill down charts that are actionable:
a pareto by $ value of the product numbers that are scrapped and a pareto of failure modes accompanied by trends (c chart or p chart) for the top 5 items. This is actionable.
 

bobdoering

Stop X-bar/R Madness!!
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#6
I see a couple problems with the notion of variable control chart methodology. First, what is the "state of control" or "random noise" of common causes that affect every transaction ($) that you can never remove without a process change. That is what you would define your control limits upon (based on the assumptions for a valid charting methodology). If you can not determine that, you are probably not far enough along in your issue analysis to employ a control chart. Can you even do a precontrol chart? Something to ponder....depending on the data you have so far. You have your dependent variable - what independent variables are you "adjusting" to control the dependent variable? Is it a handful - or really a list of them? Either way - which have the most impact? Do you need a DOE?

I would do the Pareto chart technique for starters, and monitor the effects of your efforts on eliminating those issues one by one.
 
P

prototyper

#8
If you measure scrap rates using purely $ values it is difficult to determine trends as, if the throughput varies from week to week or month to month, it can have a distorting effect on these values.
I have always monitored scrap rates as a percentage of sales. This way you have a direct comparison irrespective of volume drops, holidays, major disruptions, etc. and trends are more apparent.
The reasons for the scrap can be monitored and actions targeted by simple pareto.
 
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