## Class Details

- Class Name:
- SPC Overview 211
- Difficulty:
- Intermediate
- Number of Lessons:
- 20

## Class Outline

- Defining Quality
- What is Statistical Process Control?
- Common Cause Variation and Special Cause Variation
- Controlling Processes
- SPC Review
- SPC Data
- Control Charts
- Control Limits
- Types of Control Charts
- The X Bar Chart
- The X Bar Chart: In Detail
- The R Chart
- The R Chart: In Detail
- The P Chart
- Control Charts Review
- Process Capability vs. Process Control
- The In-Control Process
- The Out-of-Control Process
- Control vs. Out-of-Control Review
- Process Improvement

## Objectives

- Describe how customer demands relate to product specifications.
- Define statistical process control.
- Distinguish between common cause variation and special cause variation.
- Describe how processes are determined to be in control in SPC.
- Describe the effects of variation on sample averages.
- Describe the purpose of a control chart.
- Describe SPC control limits.
- Distinguish between control charts used for continuous data and control charts used for discrete data.
- Describe the appearance and purpose of an X bar chart.
- Describe the appearance and purpose of an R chart.
- Describe the appearance and purpose of a P chart.
- Distinguish between process capability and process control.
- Identify signs that a process is in control.
- Identify signs that a process is out of control.
- Describe how SPC leads to process improvement.

## Job Roles

## Certifications

## Glossary

Vocabulary Term | Definition |
---|---|

attribute data | Data that represents a characteristic or individual count. Attribute data, also known as discrete data, cannot be added to or subtracted from other attribute data sets. |

bell curve | A graph of continuous data characterized by a high center, tapered sides, and flared edges. A bell curve reflects conditions that exhibit natural variation. |

centerline | The horizontal line on a control chart that represents the expected average for a process. |

common cause variation | A deviation that is normal and expected. Common cause variation, or natural variation, cannot be traced back to a single source. |

continuous data | Data that can be measured on a scale and compared with other data. Continuous data, also known as variable data, can be added to or subtracted from other continuous data. |

control charts | A graph used in SPC to show trends in data over time. Control charts include upper and lower limits between which the process should perform. |

data | Factual information that is used for analysis and problem solving. Data is often in the form of values or numbers. |

discrete data | Data that represents a characteristic or individual count. Discrete data, also known as attribute data, cannot be added to or subtracted from other discrete data sets. |

external customers | An outside organization or individual that receives a product or service from a company. External customers dictate a product's key quality characteristics. |

frequency distribution chart | A chart that displays the number of occurrences in a continuous data set. On a frequency distribution chart, common cause variations typically create a bell curve. |

grand average | The expected average of all sample averages. The grand average is the centerline on an X bar chart. |

internal customers | A department or individual within a company that relies on others to satisfy the external customer. For any cell, the next cell in a process is always the internal customer. |

key quality characteristics | A measurable characteristic of a product that greatly impacts customer satisfaction. Key quality characteristics are the focus of SPC efforts. |

lower control limit | LCL. A control limit on a control chart indicating the boundary for the minimum permissible values. On an X bar chart, the lower control limit is located at -3 sigma. |

mean | The average of a numerical set. A mean is calculated by dividing the sum of a set of numbers by the number of members in the group. |

natural variation | A deviation that is normal and expected. Natural variation, also known as common cause variation, cannot be traced back to a single source. |

normal distribution | Variable data that clusters about an average and is symmetrical. When graphed, a normal distribution appears as a bell-shaped curve. In-control processes yield a normal distribution. |

P chart | The control chart that tracks the percentage of nonconforming items. P charts are used to track attribute data. |

P chart | The control chart that tracks the percentage of nonconforming items. P charts are used to track discrete data. |

process capability | The ability of a process to consistently meet a set of specific limitations. Process capability involves the total range of variation within a process, including common and special causes. |

process control | A method of monitoring process performance by measuring and regulating the processes that yield a product. Process control involves identifying and reducing sources of special cause variation. |

processes | A series of activities required to complete a product or provide a service to a customer. Manufacturers monitor process to ensure product quality. |

quality | The satisfaction of customer requirements. Quality products conform to specifications, are free of defects, and meet the requirements of their anticipated use. |

R chart | The control chart that tracks sample ranges over time. R charts are usually used with X bar charts to track variable data. |

range | The difference between the smallest and largest values in a numerical set. In SPC, R charts are used to track sample ranges. |

ranges | The difference between the smallest and largest values in a numerical set. In SPC, R charts are used to track sample ranges. |

sigma | A unit of standard deviation indicating the degree of spread within a set of measurements. On an X bar chart, the upper control limit is located at +3 sigma, and the lower control limit is located at -3 sigma. |

SPC | Statistical process control. The use of statistics and control charts to measure key quality characteristics and control how the related process behaves. SPC separates special causes of variation from common causes. |

special cause variation | A deviation that causes an undesirable, fundamental change in a process. Special cause variation, also known as unnatural variation, can be traced back to a single source. |

statistical process control | SPC. The use of statistics and control charts to measure key quality characteristics and control how the related process behaves. SPC separates special causes of variation from common causes. |

statistics | The science of collecting, summarizing, and analyzing numerical data. Statistics makes it possible to predict the likelihood of events. |

tolerance | A specification indicating an unwanted but acceptable deviation from a given dimension. Part tolerances are indicated on blueprints. |

unnatural variation | A deviation that causes an undesirable, fundamental change in a process. Unnatural variation, also known as special cause variation, can be traced back to a single source. |

upper control limit | UCL. A control limit on a control chart indicating the boundary for the maximum permissible values. On an X bar chart, the upper control limit is located at +3 sigma. |

variable data | Data that can be measured on a scale and compared with other data. Variable data, also known as continuous data, can be added to or subtracted from other variable data sets. |

variation | Any deviation from what is normal and consistent. In manufacturing, variation from what is normal can signal that an error has occurred. |

X bar chart | A chart used to track a series of sample averages. X bar charts are usually used with R charts to track variable data. |