An np chart is an attribute control chart that monitors the number of defective (nonconforming) units in each subgroup when the sample size stays constant. Because it plots raw defective counts instead of proportions, it is one of the easiest attribute charts to read on the shop floor. The centerline sits at np̄ — the […]
Xbar-R Control Chart: Create & Interpret It Online
An Xbar-R chart is a pair of Shewhart charts that monitors a process measured in small subgroups of two to eight samples: the Xbar chart tracks the subgroup averages (between-subgroup variation), while the R chart tracks the range within each subgroup (within-subgroup variation). To create Xbar-R Chart, you collect rational subgroups over time, plot each […]
How to Create an I-MR Chart Online – SPC Guide
An I-MR control chart is a statistical process control (SPC) tool that monitors a process using individual measurements taken one at a time instead of in subgroups. It pairs two charts: the Individuals (I) chart, which plots each measurement against a center line and ±3-sigma control limits, and the Moving Range (MR) chart, which plots […]
Standard Deviation Explained: Population vs. Sample
Standard deviation is a statistical measure of how spread out a set of data points is around its mean. A small standard deviation means the values cluster tightly around the average, while a large one means they are widely dispersed. It is calculated as the square root of the average squared distance between each value […]
How to Create an Xbar-S Chart Online – SPC Guide
An Xbar-S control chart is a pair of Shewhart control charts that monitors a process by plotting the average (Xbar) and the standard deviation (S) of each subgroup over time. You create one by collecting data in subgroups — usually nine or more measurements per subgroup — then plotting each subgroup’s mean on the Xbar […]
Normal Distribution: The Bell Curve, 68, 95 & 99.7 Rule
A normal distribution is a symmetric, bell-shaped probability distribution in which values cluster around the average and grow rarer the further they sit from it. Also called the bell curve or Gaussian distribution, it is defined completely by two parameters: the mean, which fixes the center, and the standard deviation, which fixes the spread. The […]
Gage R&R Study: How to Analyze Result Table & 6 Graphs
A Gage R&R study measures how much of your total observed variation comes from the measurement system rather than from the parts being measured. To interpret it, start with the Gage Evaluation table and read the Total Gage R&R row against two columns—%Study Variation and %Tolerance—where under 10% is excellent, 10–30% is acceptable, and over […]
SPC Control Charts for Variables (I-MR, Xbar-R, Xbar-S)
Variables control charts are time-ordered SPC graphs that monitor a process measured on a continuous scale — length, weight, temperature, cycle time — by plotting the data against statistically calculated control limits, typically set at ±3 standard deviations from the process average. The three most widely used types are the I-MR chart for individual measurements, […]
8D Problem Solving Methodology: The 8 Disciplines Explained
8D (Eight Disciplines) is a structured, team-based problem-solving method used to resolve serious, recurring, or customer-facing quality problems whose root cause is unknown. It moves a cross-functional team through eight sequential disciplines — D1 to D8 — plus a preparation step, D0, so every stage produces documented, data-backed evidence. Instead of jumping to a fix, […]
Skewness & Kurtosis Explained: Interpret Distribution Shape
Skewness and kurtosis are statistical measures that describe the shape of a data distribution. Skewness measures asymmetry: a value of 0 indicates a symmetric distribution, positive values indicate a longer right tail, and negative values indicate a longer left tail. Kurtosis measures tail heaviness, or how often extreme values occur compared to a normal distribution. […]