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Control Chart Confusion

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  • #54118

    chris reid
    Participant

    Often when I create a control chart I have a large number of data points outside of the control limits. I find this difficult to understand as minitab only has my sample to work with.

    Also I really appreciate pointers on a generic approach-

    A) If the process is out of control?

    B) If the process is in control but has high varience?

    Thanks all.

    Chris.

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    #193724

    Chris Seider
    Participant

    A. Yes, points outside your control limits mean you are exhibiting special causes so you are out of control.

    B. A process can be in control but have high variation. The SPC looks for special causes related to trends and outside 3 sigma limits (typically). Process capability /variability is independent of evaluation of process control.

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    #193728

    Prabhu V
    Participant

    Hi,

    Adding to the above point, always an user has to ensure that the user is using the correct control chart for the situation faced by the user.

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    #193730

    chris reid
    Participant

    Hi thank you very much both.

    The thing I’m struggling with is if I have 100 data points in a sample how can so many of them be outside 3 sigma in that samle, it doesn’t make sense to me?
    )-:

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    #193731

    Robert Butler
    Participant

    I think you are going to have to provide more details before anyone can offer much in the way of guidance. Offhand it sounds like you are making the wrong program choices with respect to control chart construction. Is there any chance you could post the 100 numbers? If you could some of us could look at what you have and perhaps offer some additional thoughts.

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    #193767

    Euston
    Participant

    If, indeed, it is a problem you encounter often, it could be incorrect construction as suggested, but you should check your CC setup parameters under tools>options. Specifically, make sure you are set to the defaults (see help menu if you don’t know) and your 1st test is set for K=3. And is your data normally distributed?

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    #193768

    Joel Smith
    Participant

    @christopher10 I doubt you’re going to get much hep without providing the data. My first two thoughts are that you have either (a) an Individuals control chart that has a drifting mean over time or (b) highly skewed data. But without context or seeing data it’s really hard for anyone to provide advice.

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    #193769

    Darth
    Participant

    @dabrewajeff Are you suggesting that the needs to be normally distributed for the control chart to be effective?

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    #193770

    Chris Seider
    Participant

    @Darth
    LOL, you gonna reopen that age old discussion? :)

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    #193772

    Darth
    Participant

    @cseider No, just asking an innocent question and being non-cranky.

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    #193773

    chris reid
    Participant

    Hello all,
    Thank you for helping, here is 1 of my examples ( I appreciate i should have 100 data points but I think this will show you what I mean )

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    #193774

    Joel Smith
    Participant

    @christopher10 It doesn’t look like the attachment came through…perhaps a different file type? Katie isn’t sdhowing any love towards Minitab and doesn’t have .mpj or .mtw files as an allowed type for attachments! (hint, hint Katie…)

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    #193775

    Euston
    Participant

    @Darth I don’t think my question was suggestive, was it? I’m with everyone here….I’d love to touch that data. Anyway, the thought behind the question was the distribution could explain why you would see more points in violation of the limits.

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    #193776

    Katie Barry
    Keymaster

    @joelatminitab – Sent the question of file allowance to Cyger. I’m not sure if that’s something we have control over, but I’m looking into it!

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    #193777

    Joel Smith
    Participant

    Thanks Katie! In the meantime hopefully the data can be provided in another format.

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    #193780

    Chris Seider
    Participant

    Suggestion….if you have the data in Excel or Minitab…copy the column of data and paste into the comments field and we can just paste into our field.

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    #193786

    chris reid
    Participant

    Hi here is an example
    3031
    3072
    3136
    3023
    3290
    3282
    3319
    3544
    3436
    3482
    3434
    3449
    3707
    3560
    3618
    3472
    3456
    3342
    3457
    3660
    3657
    3852
    3926
    4006
    *
    3676
    3555
    3100
    2720
    3141
    3219
    3251
    3110
    2814
    2872
    3034
    3171
    3118
    3019
    3006
    3186
    3100
    3100
    3340
    3275
    3148
    3192
    3313
    3214
    3040
    2992
    2997
    3210
    2846
    2838
    3017
    3273

    Ive been using an I Chart for this, I think the problem is I misunderstand how stdeviation is calculated. I’ll refresh my memory today but any help or comments you can give would be very much appreciated.

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    #193787

    chris reid
    Participant

    p.s thanks for all the help so far.

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    #193788

    Joel Smith
    Participant

    @christopher10 Whoa there…you’re definitely out of control for the first 1/3-1/2 of the chart! It’s hard to give much practical advice without knowing the process, but from the data alone my observations are:

    1. Through the first 24 points, before the missing value, you clearly have an upward trend where values keep getting larger and larger.
    2. After the missing value, you have a few points in a “settling down” period through about point 30 that show high variation and maybe a lack of control initially.
    3. Following point 30 you appear to have good statistical control.

    I’m guessing from this data – and I should probably say “know” instead of “guess” – that some change was made to either the process or the data collection at the missing value. Try this:

    1. Make a second column that contains 1’s through the missing data point, and 2’s after that until the end of the data.
    2. Back in the Individual Chart dialog box (and you should really be doing I-MR to assess variation stability as well) click on I Chart Options and then the Stages tab.
    3. Enter your new column for Stages and click OK in each dialog.

    This will create a centerline and control limits independently for each part of the data and enable you to more clearly see the process change. I wouldn’t stress over the few out of control points from 26-30 since that is common after a process change…things don’t always “jump” to the new value and sometimes take a few points to stabilize. You may even stage those few points separately to get slightly more accurate control limits in the stable portion.

    If it’s something you can share – even if you mask things just a little bit – I’m sure forum visitors would like to know about this process and what change occurred at the missing point!

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    #193789

    Darth
    Participant

    @christopher10 I attached the I/MR Chart that results from your data above. Yes, the process is out of control. One thought might be that the MR chart values are small compared to the actual values and thus the avg. MR used in the I chart calculations might be “compressing” the control limits relative to the magnitude of the actual process values. As you can see at the beginning of the data there is a dramatic upward run followed by an apparent change which dropped the process down. It appears to have stablized now. If we discount the upward data as something happening and the data after that as the new steady state process things might look a little better. You can also “break” the data at the apparent point of change and recalculate the before and after. Mini will let you do that. By the way, the p value of the data set shows that the data is not different than normal. The p value is .168. The s.d. used for the calculations uses the avg. MR as the base and then adjusts using the d sub 2 and E sub two table factors based on sample size. In this case usually a sample size of 2. Hope this helps and that Joel approves.

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    #193791

    Joel Smith
    Participant

    I would approve, but I can’t see you behind that mask…

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    #193792

    Katie Barry
    Keymaster

    @joelatminitab Minitab files should now load without any trouble.

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    #193793

    Euston
    Participant

    @darth Agreed on the p value. Still even high p’s(.619/.283 respectively) when analyzed into the 2 stages. Obviously the tighter CL’s on the I/MR is driven by the slow process shift from data point to point as you articulated. @christopher10 I think Darth laid it all out for you. Curious if 1) the data reflects the startup of the process and, 2) if you indeed only collect one data point representing a given point in the process?

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    #193798

    chris reid
    Participant

    Thanks all very much for the advice. All points taken on board and the 2s and 1s tip is great.The data represents orders in delay. As ever I have another question (once I get started I cant stop)

    Q- Is there a way I can add an upper and lower spec to a control chart?

    Thanks all.

    C10

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    #193800

    Putnam
    Participant

    You could annotate it by drawing two lines.

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    #193801

    Joel Smith
    Participant

    @christopher10 Well, you could use reference lines, BUT…

    This questions has been answered in numerous places so I’ll be brief. Do not put spec limits on your control chart. If you want to assess whether you are meeting specifications, first make sure your data are in control and then use capability analysis. There are multiple reasons that have been documented many times.

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    #193802

    chris reid
    Participant

    Thanks a lot, right here is my last ( i hope ) question.

    I’m trying to use a P chart and I get this error message when I select a column

    The following column contains values that are too small, the data must be >=1.
    The thing is the data is all greater than 1. I cut it from excel so not sure what the issues is. It is very annoying

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    #193803

    Joel Smith
    Participant

    Can you share the data? @KatieBarry was so kind as to get Minitab files allowed (best), or your could share the Excel or just paste it here.

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