Operations Management Chapter 6: Statistical Process Control

Purpose of Control Charts

• Control charts monitor process behavior over time, highlighting variations and maintaining process stability.
• They signal when assignable causes of variation occur, prompting investigation and corrective action.

Central Limit Theorem (CLT) Role

• CLT indicates that, regardless of the original distribution, the sampling distribution of the sample mean approaches a normal distribution as sample size increases.
• This theorem underlies the statistical reasoning in SPC, enabling the use of control limits based on sample means.

Steps in Building Control Charts

• Identify key characteristics to measure and collect historical data.
• Analyze data to establish control limits and determine the process's normal operational range.

Objectives of a Process Control System

• Aim to maintain process consistency, enhance product quality, and reduce variability.
• Help identify and mitigate sources of process variation.

Statistical Signals in SPC

• Statistical signals arise from deviations outside specified control limits, indicating potential assignable causes of variation.

Acceptance Sampling

• A technique used to make decisions about a batch of products based on the inspection of a subset of items.
• Utilizes statistical methods to determine if a lot meets quality standards.

Overall Purpose of Statistical Process Control (SPC)

• SPC aims to improve and maintain the quality of processes and outputs by managing variability.
• Employs statistical tools for monitoring, controlling, and making decisions about processes.

Natural Variations

• Also referred to as common cause variations, these are inherent in processes and affect overall quality.

Discovering Assignable Causes

• The objective is to identify specific factors causing significant changes in process variability, enabling effective corrective measures.

Type of Characteristics Tracked by X and R-charts

• X-charts monitor the mean of the process outputs.
• R-charts track the range of variability within the process.

Specific Variations Explained

• Special cause variations can be traced to identifiable reasons, leading to abrupt changes in process performance.

Historical Data in Control Charts

• Control charts constructed from historical data assist in setting control limits and understanding process behavior over time.

Acceptable Limits Implications

• When the distribution of outputs falls within acceptable control limits, it indicates stable and predictable process performance.

Sample Measurement and Analysis

• Involves collecting samples, calculating sample statistics, and interpreting these following planned statistical methods.

Inherent Process Variability

• Refers to natural variations, which are expected and predictable fluctuations in a process.

Key Terms in Statistical Process Control

• Common causes of variation affect virtually all production processes and do not signify specific faults.
• P-charts and C-charts are specific control charts used for monitoring proportion defects and count data respectively.