Questions tagged [quality-control]

Quality Control relates to statistical methods used for monitoring, maintaining, and/or improving either the statistical quality control of a process or the capability of a process. Use for questions about 6 sigma.

Quality Control is a subsection of the collection of statistical tools introduced by Sir Ronald A. Fisher, Joseph M. Juran, Philip B. Crosby, Walter Shewhart, W. Edwards Deming, and Genichi Taguchi. In general, the tools most often associated with quality control can refer to either:

  1. Statistical Quality Control
  2. Process Capability

Statistical Quality Control is usually monitored via Statistical Process Control (SPC) methods such as Shewhart Charts or Control Charts. Control charts are modified time series plots, usually with some average value and control limits plotted three standard deviations above and below the center line. They do not include the tolerance band of the process. Such charts include, but are not limited to:

  • $\overline{X}-R$: (Average and range)
  • $\overline{X}-s$: (Average and standard deviation)
  • $IX-MR$: (Individual and Moving Range, sometimes $X-MR$)
  • $c$: (counts)
  • $u$: (counts with varying subgroup size)
  • $p$: (proportion with varying subgroup size)
  • $np$: (proportion)
  • EWMA: (exponentially weighted moving average)

Process Capability is often measured as some relationship between the process distribution and the engineering specification for the process. Charts for such analysis are usually based upon histograms with the target value, upper specification level, and lower specification level (T, USL, and LSL) superimposed. These indexes include, but are not limited to:

  • $C_p$: It represents the best case ratio of the spec. and the process.
  • $C_r$: It is simply the inverse of $C_p$.
  • $C_{a}$: A representation of the accuracy of the process.
  • $C_{pa}$: A variation of $C_{pk}$ for asymmetrical processes.
  • $C_{pk}$: $C_{p}$ modified by the factor $k$.
  • $C_{p-}$: The difference between $C_p$ and $C_{pk}$.
  • $C_M$: "Capability of the Machine;" it uses a wider range of possible process outcomes than $C_p$
  • $C_{pm}$: Similar to $C_{pk}$, it relates the process in comparison to the spec. limits and a target value. It is most useful with asymmetrical tolerances.
  • $C_{pp}$: "Incapability Index" based upon $C_{pm}$ and similar to $C_r$.
  • $C_{pmk}$: $C_{pm}$ modified by the factor $k$.
  • $C_pT$: replaces $\hat{\mu}$ in $C_{pk}$ with target value $T$.
  • $Z_{bench}$: Represents capability as a $Z_{score}$ and works with continuous or discrete data.
  • $Q_k$: When no tolerance range exists, the Mean Standard Error of the process can be used to evaluate this index.
  • $C_{p\omega}$: A weighted index which can be used to calculate approximations for $C_p$, $C_{pm}$, and $C_{pk}$.
  • $C_p\left ( u,v \right )$: An index which can calculate $C_p$, $C_{pm}$, $C_{pk}$, and $C_{pmk}$.
  • $C_{p\log}$: Similar in use to $C_p$, it can be used for lognormal distributions.
  • $C_{p(\ln)}$: An alternate to $C_{p\log}$; used for lognormal distributions.
  • $C_{pk(\ln)}$: A version of $C_{pk}$ used for lognormal distributions.
  • $C_s$: Useful for any skewed distribution.
  • $C_{npk}$: Useful for any distribution, as long as the parameters can be determined.
  • $C_f$: Used for proportions of non-conforming units.
  • $C\%$: Used with FTY/RTY data; capability of percent non-conforming.
  • $P_p$: A long-term version of $C_p$.
  • $P_{pk}$: A long-term version of $C_{pk}$.
178 questions
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What is the rationale for the rules for detecting an out of control process in Statistical Process Control?

Statistical Process Control (SPC) can be used to determine if a process is "in statistical control". A common tool for SPC is the "mean control chart" -- essentially a time series of sample means obtained from the process one seeks to analyze. A…
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Using control charts with very large subgroup size?

I am working with a very large data set -- time-series data from an on-line process monitor with a 10 second measurement interval. I am trying to develop control limits for the process using control charts theory. Here are the methods I have tried…
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p-Chart with really tight Control Limits

I have created a process control chart that describes the fraction of deliveries sent to the ideal destination over time. The deliveries all eventually end up at the proper destination, however I am trying to track the fraction that get to the ideal…
David
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Why does the X-bar control chart not use control limits from the t distribution

In univariate statistical process control, for the $\bar{X}$ chart with $n$ subgroups each of $m$ samples, we calculate the center line, upper and lower control limits using this equation (1): Here, $Z_{1-\alpha/2}$ is a quantile of the normal…
Migwell
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How to find value of omega in CUSUM?

I am trying to understand CUSUM or Cumulative Sum Control Chart. In the example on above linked Wikipedia page, the formula for high CUSUM value indicating positive anomaly is given as: $$S_{H_{n+1}}=\max(0, S_{H_n}+Z_n-\omega)$$ Similarly, formula…
rnso
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Where can I find online notes about statistical process control?

Please could you someone help me to find online resources related to the topic of quality control (statistical process control)
Sihem
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Control Limits and Calculating them

This is going to be a very simple question, but I just need to make sure of a few basic things. I'm building some Xbar-R charts and have sample size of 4 and am looking over the Control Limits. I've been told two ways to calculate control limits.…
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standard ways to check data quality?

I have a dataset of tv viewing data (channel, time, # viewers) and want to get some confidence in its quality. What are some standard ways to do this?
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What is the mathematical difference between Cpk and Ppk?

I am trying to understand the mathematical difference between Cpk and Ppk used in Statistical Process Control (SPC). I have gone through the web but all I found a confusing and more confusing theoretical implication of the two. Before I can try to…
KMC
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Quality Control Chart for non-normal distributed data

I am interested in building quality control charts for time series data where every data point has different gradation within the range of 0 to 1. For example first data point X1 may be 0.1, 0.2,..,1 and second data point X2 may be 0, 1/3, 2/3, 1.…
Michael
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Single control limits for process with various subgroup sizes

I have a production process, which produces one or more goods on a certain day. For this example, assume the weight of the produced good is consistenlty measured. However, the operators can ofcourse differ on a day-to-day basis. I want to establish…
Jigeli
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Setting limits for process control of low probability error

I have a process which produces plastic parts. I have a requirement that states that the weight shall be > x grams. So far I have measured each individual part produced (around 250 pieces) and found that they all lie above the required weight. The…
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SPC - do the Nelson rules change if the control limits are changed from the "default" of 3 standard deviations?

I am aware that, in SPC, one can theoretically chose different control limits based on the number of standard deviations one wishes to use. If one uses a control chart with control limits with fewer than three standard deviations - e.g. x-bar +-…
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Control Chart factor $c_4$

I have found several authoritative sources with differing methods for calculating the control chart factor $c_4$. Are these methods truly equivalent, and if they are not, which method is the "real" method for calculating this…
Tavrock
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Understanding Defect Rate of Manufacturing Process

(NB: I don't have a very strong background in statistics, so I would not be surprised if this question is naive or the answer is apparent from some rather basic principle.) I'm wondering how I might analyze the following situation using principles…
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