Control Limit Calculation with multi-cavities molding


Hi everyone,
First I have to thank all the people here to answer question. It's a very nice and friendly place for me to ask any question I faced.

Back to the problem, currently our company wants to implement SPC to control the IPQC performance in the plastic part which produced by multi-cavities mold.
Our sampling plan is choosing 1 pc from each cavity every 8 hrs. Currently we have 25 batches data to calculate the history control limits for the control chart we want. But I have some questions to ask : (assuming we use 8 cavities molding)

Problem 1 :
Background :
We already know that different cavity have different performance. Some cavity produce parts with larger inspection results than other cavities. So we decide to use Xbar-S chart to calculate mean of all the 8pcs in a single inspection. We plan to use Xbar-S chart to detect mean shift in the production. The sigma here I use the formula comes from mintab. However, I found the control limit is very narrow that nearly every Xbar from different batch OOCL. I realize it may because the calculation use to estimate sigma only consider within batches variation instead of Between batch variation.
Question :
1. In this situation, Control Limit seems not very reasonable. Would it be better to use other control chart? (For example, 3-way control chart.)
2. Is using historical data to monitoring future performance reasonable? Or is it better to control only within batches variation by each batches (calculate control limit for each batches every time)?

Problem 2 :
Background :
We already know that QC sometimes may misuse their measuring equipment. We want to use I-MR chart to detect this variation every time QC do the inspection. I gather all 25 batches data to calculate the control limit by using sigma of I chart = MR-bar/1.128. 1.128 comes from the constant d2 with moving range every 2 data point. The calculation of MR use the all data points arrange by their inspection period and cavity. For example, 8 cavities molding, 2 batches with 2 inspection period in each batch. So totally 8*2*2 = 32 data points. I calculate the mean of these 31 MR as MR-bar in the formula. By implement this process, I calculating all the control limits by 25 batches we have. However the control limit seems too narrow that make a lot OOCL point when mapping back to the historical data.
Question :
1. Instead of monitor Xbar of 8 cavities, if I want to control the each individual to the real time detection for QC misuse. Is I-MR chart reasonable?
2. The same with problem 1, the batches variation seems not well consider in the sigma calculation. Any other way to have a better estimate that contain batches variation? The calculation I can come up with is the total standard deviation of all the data.

Between batches variation seems a big resource in our data. So SPC suffer us from implementing. In this situation, It's better to dig into it and make the process more stable, then use SPC to detect future out of control. However, I still wondering about is there any method that can include between batches variation in the calculation.

Thank you for reading the post in advanced. I am not very familiar with SPC control. So the post may make no sense. Hope I can learn something and experience with all of you.

Bev D

Heretical Statistician
Super Moderator
I rarely use all cavities in a subgroup as the difference between each cavity is systemic rather random which inflates the within subgroup SD resulting in silly control limits. (The within subgroup variation should be homogenous for a control chart to do it’s job properly)

Welsh Wizard is correct we would need to see your data to provide teh best advice. Unfortunately you can’t post attachments until you’ve reached 5 or 10 posts…I can’t remember which right now. A way to increase your posts is to answer several clarifying questions one per post.

Here are few questions to get you started. I’m sure others will add some questions too.
- what makes you think that QC is ‘misusing’ their measurement equipment? Can you provide more details on this?
- what kind of characteristics are you measuring? Adn what is the measurement method for each? (CMM, hand held analog caliper, drop gage, optical comparator…)
- have you performed any MSAs on these equipment/characteristics? What were the results?


Hi Welshwizard,
Sure I can post some data here but as Bev D said I can't post right know. I will use Delimiter-separated values format to show some data here after I go to work on Monday. Hope it will demonstrate the problem more clearly.

Hi Bev D,
Thanks for the reply. As you reply the subgroup of all cavities, does it mean we need to monitoring the performance by each cavities?
For your question, here are my answers:
1. We have done the MSA to every measurement equipment we have by GR&R. However, we have relative easy criteria that GR&R < 30% are all acceptable without any evaluation to the one with GR&R is between 10% to 30%. It should be check.
2. In some of the characteristic, we need to cut of the plastic parts and measure the length or angle. Some characteristic may really sensitive to the cutting and refining. Look into the data, it will very clearly see the data is very stable from the start to the end of batch. But there are 2 or 3 point that is extremely larger/smaller than other. We want to use Control Chart to detect it in real-time. However, I know, this variation is needed to be consider when doing MSA, we may not do this in the PD phase.


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I’ll just throw this out there for thought. Rather than SPC a part dimension, any possibility you can get what you need monitoring a process parameter? Most modern molding machines can spit out process data you can use. Something like pressure or fill rate etc. might be easier. Or maybe part or shot weight?

Also, I think your MSA needs to be under 10% to be useful for SPC. Do a MSA search on here, some of the stats gurus provide good guidance.

Johnny Quality

Quite Involved in Discussions

I'll refer you to Howard Atkins fantastic paper on SPC and Injection Moulding.

My experience with injection moulding was as long as we had standard machine settings that were used batch to batch and the tools and machines had the maintainence they needed; in the overwhelming majority of tools, measuring parts was a formality. If the parts were within specification at the start of production, end of production and any restarts of the machine, we could be confident that dimensionally the parts were fine.

The big issues we had were stop/starts in the process, inconsistent cycle times, common visual defects (short shots, flash, splay, etc), ensuring the machine didn't run out of material and keeping mould heater temperatures stable.
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