质量控制模型分析

Chapter 17 Statistical Quality

Control

Learning Objectives Students will be able to:

1.Define the quality of a product

or service.

2.Develop four types of control

charts 3.Understand the basic theoretical

underpinnings of statistical

quality control, including the

central limit theorem.

4.Know whether a process is in

control .

c

and p, R, ,x

Chapter Outline

17.1Introduction

17.2Defining Quality and TQM 17.3Statistical Process Control 17.4Control Charts for Variables 17.5Control Charts for Attributes

Introduction Quality is a major issue in today’s organizations.

Quality control (QC),or quality management, tactics are used throughout the organization to assure deliverance of quality products or services.

Statistical process control (SPC)uses statistical and probability tools to help control processes and produce consistent goods and services.

Total quality management(TQM)refers to a quality emphasis that encompasses the entire organization.

Definitions of Quality “Quality is the degree to which a specific product conforms to a design or specification.” “Quality is the totality of features and characteristics of a product or service that bears on its ability to satisfy stated or implied needs.” “Quality is fitness for use.”

“Quality is defined by the customer; customers want products and services that, throughout

their lives, meet customers’needs and

expectations at a cost that represents value.”

“Even though quality cannot be defined, you know what it is.”

(SPC)

Statistical technique used to ensure process is making product to standard. It can also monitor, measure, and correct quality problems.

Control charts are graphs that show upper and lower limits for the process we want to control.

Thus, SPC involves taking samples of the process output and plotting the averages on a control chart.

(SPC) (continued)

All processes are subject to variability.

¾Natural causes: Random variations that

are uncontrollable and exist in processes

that are statistically ‘in control.’

¾Assignable causes: Correctable

problems that are not random and can

be controlled.

o Examples: machine wear, unskilled

workers, poor material.

The objective of control charts is to identify assignable causes and prevent them from reoccurring.

Produce Good

Provide Service

Stop Process Yes

No Assign.

Causes?

Take Sample Inspect Sample Find Out Why

Create

Control Chart Start Statistical Process Control Steps