# What is Six Sigma statistical process control?

### Table of Contents

- What is Six Sigma statistical process control?
- What are the objectives of statistical process control?
- What is the formula for Cpk?
- What are the different types of statistical quality control chart?
- Is a process capable?
- What is an important limitation of statistical process control?
- What do you need to know about statistical process control?
- What are the steps in the statistical process?
- What is the difference between statistical process control and acceptance sampling?
- What are some examples of process control techniques?

### What is Six Sigma statistical process control?

Statistical Process Control (SPC) is **a process improvement methodology to monitor, control, and continuously optimize a process**. SPC is really a subset of six sigma. SPC is usually associated with control charts and design of experiments. SPC separates common-cause from assignable-cause variation.

### What are the objectives of statistical process control?

The aim of Statistical Process Control (SPC) is **to establish a controlled manufacturing process by the use of statistical techniques to reduce process variation**. A decrease in variation will lead to: better quality; lower costs (waste, scrap, rework, claims, etc.);

### What is the formula for Cpk?

The formula for the calculation of Cpk is **Cpk = min(USL - μ, μ - LSL) / (3σ)** where USL and LSL are the upper and lower specification limits, respectively. A process with a Cpk of 2.0 is considered excellent, while one with a Cpk of 1.33 is considered adequate.

### What are the different types of statistical quality control chart?

Quality Chart Types

Chart | Process Observation |
---|---|

Shewhart individuals control chart (I-R chart or I chart) | Quality characteristic measurement for one observation |

Three-way chart | Quality characteristic measurement within one subgroup |

p-chart | Fraction nonconforming within one subgroup |

np-chart | Number nonconforming within one subgroup |

### Is a process capable?

Process Capability (Cp) is a **statistical measurement of a process's ability to produce parts within specified limits on a consistent basis**. ... Cp tells you if your process is capable of making parts within specifications and Cpk tells you if your process is centered between the specification limits.

### What is an important limitation of statistical process control?

Although SPC swiftly reveals when quality has changed, **it does not show by how much the rejected products are defective**. For example, it does not provide an integer number for the out-of-tolerance dimensions on product pieces, which would require precise measurements.

### What do you need to know about statistical process control?

Before we break down the steps, we first need to understand what Statistical Process Control (SPC) is. SPC can help a factory measure and control quality by gathering data to monitor the production process. It not only allows factories to operate at its highest capacity but also sets the foundation for continuous improvement.

### What are the steps in the statistical process?

The Statistical Process has five steps: Design the study, Collect the data, Describe the data, Make inferences, Take action. In a designed experiment, researchers control the conditions of the study. In an observational study, researchers don't control the conditions but only observe what happens.

### What is the difference between statistical process control and acceptance sampling?

Statistical process control (SPC) is the application of the same 14 tools to control process inputs (independent variables). Although both terms are often used interchangeably, statistical quality control includes acceptance sampling where statistical process control does not.

### What are some examples of process control techniques?

Typical process control techniques. There are many ways to implement process control. Key monitoring and investigating tools include: Histograms. Check Sheets. Pareto Charts. Cause and Effect Diagrams. Defect Concentration Diagrams.