9.2 Control Charts for Variables Data

Key Takeaways

  • The X-bar and R (Sample Mean and Range) control chart is standard for continuous variable data collected in small subgroups (n = 2 to 6), utilizing factors A2, D3, and D4 derived from the standard deviation factor d2.
  • When subgroup sample sizes exceed n ≥ 10 (or range from n = 7 to 12), the X-bar and S (Sample Mean and Standard Deviation) chart replaces R with S, utilizing factors A3, B3, and B4 based on c4 for superior estimation of within-subgroup dispersion.
  • For individual measurements (n = 1), the Individual and Moving Range (I-MR or X-mR) chart measures process center using individual observations and dispersion via 2-point moving ranges (mR = |Xi - Xi-1|), using E2 = 2.66 and D4 = 3.267.
  • Variable control limits rely on estimated process standard deviation: σ̂ = R-bar / d2 for range charts and σ̂ = S-bar / c4 for standard deviation charts.
  • Control chart selection for variables data depends strictly on subgroup size n and measurement cost/homogeneity: I-MR for n=1, X-bar-R for 2 ≤ n ≤ 9, and X-bar-S for n ≥ 10.
Last updated: August 2026

Variables control charts monitor continuous quantitative process measurements (e.g., diameter, weight, temperature, tensile strength, cycle time) over time. They are the primary tool in the Control phase for detecting special cause variation and maintaining statistical process control.


Statistical Principles of Statistical Process Control (SPC)

Continuous process variation consists of two components:

  1. Common Cause Variation: Inherent natural background noise present in a stable process.
  2. Special Cause Variation: Unassignable external disturbances (e.g., raw material lot change, tool wear, operator error) that shift the process mean or increase variance.

$\bar{X}$ and $R$ Chart (Sample Subgroups $2 \le n \le 8$)

The $\bar{X}$ and $R$ chart is the most widely deployed variables chart for small subgroup sample sizes.

Mathematical Formulas & Limit Factors

Given $k$ subgroups of size $n$:

  1. Subgroup Mean ($\bar{x}_i$) & Range ($R_i$): xˉi=xn,Ri=xmaxxmin\bar{x}_i = \frac{\sum x}{n}, \quad R_i = x_{\max} - x_{\min}
  2. Grand Mean ($\bar{\bar{x}}$) & Average Range ($\bar{R}$): xˉˉ=xˉik,Rˉ=Rik\bar{\bar{x}} = \frac{\sum \bar{x}_i}{k}, \quad \bar{R} = \frac{\sum R_i}{k}

Control Limit Formulas

  • $\bar{X}$-Chart:

UCLXˉ=xˉˉ+A2Rˉ,LCLXˉ=xˉˉA2RˉUCL_{\bar{X}} = \bar{\bar{x}} + A_2 \bar{R}, \quad LCL_{\bar{X}} = \bar{\bar{x}} - A_2 \bar{R}

  • $R$-Chart:

UCLR=D4Rˉ,LCLR=D3RˉUCL_R = D_4 \bar{R}, \quad LCL_R = D_3 \bar{R}

Where $A_2, D_3, D_4$ are standard SPC constants derived from subgroup size $n$.


$\bar{X}$ and $S$ Chart (Sample Subgroups $n \ge 9$)

When subgroup size $n \ge 9$, sample range $R$ loses statistical efficiency because extreme values dominate $R$. The sample standard deviation $S$ utilizes all $n$ data points.

Control Limit Formulas

  • $\bar{X}$-Chart: $UCL_{\bar{X}} = \bar{\bar{x}} + A_3 \bar{S}, \quad LCL_{\bar{X}} = \bar{\bar{x}} - A_3 \bar{S}$
  • $S$-Chart: $UCL_S = B_4 \bar{S}, \quad LCL_S = B_3 \bar{S}$

Individual and Moving Range ($I$-$\text{MR}$) Chart ($n = 1$)

Used when process data consists of individual observations (e.g., continuous chemical process batch outputs, low-volume production, automated 100% inspection).

Moving Range ($MR_i$) Formula

MRi=xixi1MR_i = |x_i - x_{i-1}|

Using $d_2 = 1.128$ for $n = 2$ moving range pairs:

UCLI=xˉ+2.66MRˉ,LCLI=xˉ2.66MRˉUCL_I = \bar{x} + 2.66 \bar{MR}, \quad LCL_I = \bar{x} - 2.66 \bar{MR}

UCLMR=D4MRˉ=3.267MRˉ,LCLMR=0UCL_{MR} = D_4 \bar{MR} = 3.267 \bar{MR}, \quad LCL_{MR} = 0


Construction Algorithms & Calculation Formulas for Variables Charts

1. Construction of $\bar{X}$ and $R$ Charts

Given $k$ historical subgroups ($k \ge 20-25$) each containing $n$ observations ($2 \le n \le 8$):

Step 1: Calculate Subgroup Statistics

For each subgroup $i = 1, 2, \dots, k$:

xˉi=1nj=1nxij,Ri=xi,maxxi,min\bar{x}_i = \frac{1}{n} \sum_{j=1}^{n} x_{ij}, \quad R_i = x_{i,\max} - x_{i,\min}

Step 2: Calculate Overall Averages

xˉˉ=1ki=1kxˉi,Rˉ=1ki=1kRi\bar{\bar{x}} = \frac{1}{k} \sum_{i=1}^{k} \bar{x}_i, \quad \bar{R} = \frac{1}{k} \sum_{i=1}^{k} R_i

Step 3: Compute Control Limits Using SPC Tabular Constants

  • Range Chart ($R$-Chart): UCLR=D4Rˉ,Center LineR=Rˉ,LCLR=D3Rˉ\text{UCL}_R = D_4 \bar{R}, \quad \text{Center Line}_R = \bar{R}, \quad \text{LCL}_R = D_3 \bar{R}
  • Mean Chart ($\bar{X}$-Chart): UCLXˉ=xˉˉ+A2Rˉ,Center LineXˉ=xˉˉ,LCLXˉ=xˉˉA2Rˉ\text{UCL}_{\bar{X}} = \bar{\bar{x}} + A_2 \bar{R}, \quad \text{Center Line}_{\bar{X}} = \bar{\bar{x}}, \quad \text{LCL}_{\bar{X}} = \bar{\bar{x}} - A_2 \bar{R}

Standard SPC Tabular Constants Table ($n = 2$ to $10$)

Subgroup Size ($n$)$A_2$$A_3$$d_2$$D_3$$D_4$$B_3$$B_4$
21.8802.6591.12803.26703.267
31.0231.9541.69302.57402.568
40.7291.6282.05902.28202.266
50.5771.4272.32602.11402.089
60.4831.2872.53402.00401.970
80.3731.0992.8470.1361.8640.1851.815
100.3080.9753.0780.2231.7770.2841.716

Worked Calculation Example: $\bar{X}$ and $R$ Chart

A Black Belt monitors shaft turning diameters. Subgroup size $n = 5$, number of subgroups $k = 20$. Baseline calculations yield grand mean $\bar{\bar{x}} = 25.040\text{ mm}$ and average range $\bar{R} = 0.080\text{ mm}$. From the table for $n = 5$: $A_2 = 0.577$, $D_3 = 0$, $D_4 = 2.114$.

  1. $R$-Chart Limits: UCLR=D4Rˉ=2.114×0.080=0.1691 mm\text{UCL}_R = D_4 \bar{R} = 2.114 \times 0.080 = 0.1691\text{ mm} LCLR=D3Rˉ=0×0.080=0.000 mm\text{LCL}_R = D_3 \bar{R} = 0 \times 0.080 = 0.000\text{ mm}
  2. $\bar{X}$-Chart Limits: UCLXˉ=xˉˉ+A2Rˉ=25.040+(0.577×0.080)=25.040+0.04616=25.0862 mm\text{UCL}_{\bar{X}} = \bar{\bar{x}} + A_2 \bar{R} = 25.040 + (0.577 \times 0.080) = 25.040 + 0.04616 = 25.0862\text{ mm} LCLXˉ=xˉˉA2Rˉ=25.0400.04616=24.9938 mm\text{LCL}_{\bar{X}} = \bar{\bar{x}} - A_2 \bar{R} = 25.040 - 0.04616 = 24.9938\text{ mm}

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Variables Control Chart Selection Decision Logic
Test Your Knowledge

An analyst evaluates an X-bar and R chart for a machining operation using subgroups of size n=5. The overall grand mean X-double-bar = 50.00 mm and average range R-bar = 1.50 mm. Given control chart factors A2 = 0.577, D3 = 0, and D4 = 2.114, what are the upper and lower control limits for the X-bar chart?

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Test Your Knowledge

Why is an Individual and Moving Range (I-MR) control chart designed with an E2 factor of 2.66 for calculating the Upper Control Limit (UCL_X = X-bar + E2 * mR-bar)?

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Test Your Knowledge

A chemical processing plant collects batch viscosity measurements in subgroups of n=12 samples per lot. Why is an X-bar and S chart preferred over an X-bar and R chart for monitoring this process?

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