QUALITY MANAGEMENT TOOLS. COMPREHENSIVE QUALITY MANAGEMENT PROGRAM EQUIPMENT QUALITY CONTROL ADMINISTRATIVE RESPONSIBILITIES RISK MANAGEMENT RADIATION.

Slides:



Advertisements
Similar presentations
Seven Quality Tools The Seven Tools
Advertisements

Table of Contents Exit Appendix Behavioral Statistics.
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Introduction to Summary Statistics
TOTAL QUALITY MANAGEMENT
Modeling Process Quality
Introduction to Summary Statistics
Tools of quality control A-Team. Basic tools of quality control  control chart  histogram  Pareto chart  check sheet  cause-and-effect diagram 
B a c kn e x t h o m e Classification of Variables Discrete Numerical Variable A variable that produces a response that comes from a counting process.
Data Handling GCSE coursework. Hypothesis Collection of Data Data Handling GCSE coursework Hypothesis.
Chapter 191 Data Analysis and Data Presentation Chapter 19 Achieving Quality Through Continual Improvement Claude W. Burrill / Johannes Ledolter Published.
@ 2012 Wadsworth, Cengage Learning Chapter 5 Description of Behavior Through Numerical 2012 Wadsworth, Cengage Learning.
Thursday, January 30, 2014MAT 312. Thursday, January 30, 2014MAT 312.
L Berkley Davis Copyright 2009 MER301: Engineering Reliability1 LECTURE 2: Chapter 1: Role of Statistics in Engineering Chapter 2: Data Summary and Presentation.
Overview of Total Quality Tools
3. Data Presentation Graphs & Charts.
Basic Definitions  Statistics Collect Organize Analyze Summarize Interpret  Information - Data Draw conclusions.
Graphical Analysis. Why Graph Data? Graphical methods Require very little training Easy to use Massive amounts of data can be presented more readily Can.
6.1 What is Statistics? Definition: Statistics – science of collecting, analyzing, and interpreting data in such a way that the conclusions can be objectively.
Methods for Describing Sets of Data
Statistics Chapter 9. Statistics Statistics, the collection, tabulation, analysis, interpretation, and presentation of numerical data, provide a viable.
AQIP 101 Stuart E. Frew MS, RT (R) - Who - When - What - Where -Why.
Introduction to Summary Statistics. Statistics The collection, evaluation, and interpretation of data Statistical analysis of measurements can help verify.
Tuesday, March 18, 2014MAT Tuesday, March 18, 2014MAT 3122.
Data Analysis Qualitative Data Data that when collected is descriptive in nature: Eye colour, Hair colour Quantitative Data Data that when collected is.
Chapter 21 Basic Statistics.
Thursday, February 6, 2014MAT 312. Thursday, February 6, 2014MAT 312.
Seven Quality Tools The Seven Tools –Histograms, Pareto Charts, Cause and Effect Diagrams, Run Charts, Scatter Diagrams, Flow Charts, Control Charts.
Chapter 15 Basic Statistics. §15.1 thru 15.4 – Graphs Bar graphs – Example 1 p. 483 – Problems 15.1 #18, 20, 22 (p. 483) Circle graphs – Figure 15.2 p.
Graphs, Charts and Tables Describing Your Data. Frequency Distributions.
Tuesday, February 11, 2014MAT 312. Tuesday, February 11, 2014MAT 312.
Thursday, February 13, 2014MAT 312. Thursday, February 13, 2014MAT 312.
Measure : SPC Dedy Sugiarto.
Thursday, February 27, 2014MAT 312. Thursday, February 27, 2014MAT 312.
Project Management Methodology Quality Control Diagrams Seven basic tools of quality.
Exam Review Day 6 Chapters 2 and 3 Statistics of One Variable and Statistics of Two Variable.
Engineering Statistics KANCHALA SUDTACHAT. Statistics  Deals with  Collection  Presentation  Analysis and use of data to make decision  Solve problems.
Appendix B: Statistical Methods. Statistical Methods: Graphing Data Frequency distribution Histogram Frequency polygon.
Tuesday, February 3, 2014MAT 312. Tuesday, February 3, 2014MAT 312.
QUALITY MANAGEMENT IN IMAGING SCIENCES INTRODUCTION TO QUALITY MANAGEMENT CHAPTER 1.
Total Quality Management. What is Quality? Quality is a relative concept. Quality is in the eye of the beholder Perfection Doing it right at the first.
Organize verbal information into a visual one, generally by writing down on separate pieces of paper AFFINITY DIAGRAM A sequenced plan.
The field of statistics deals with the collection,
Lean Six Sigma: Process Improvement Tools and Techniques Donna C. Summers © 2011 Pearson Higher Education, Upper Saddle River, NJ All Rights Reserved.
Math 310 Section 8.1 & 8.2 Statistics. Centers and Spread A goal in statistics is to determine how data is centered and spread. There are many different.
Standardized Testing. Basic Terminology Evaluation: a judgment Measurement: a number Assessment: procedure to gather information.
Lesson 25 Finding measures of central tendency and dispersion.
The seven traditional tools of quality I - Pareto chart II – Flowchart III - Cause-and-Effect Diagrams IV - Check Sheets V- Histograms VI - Scatter Diagrams.
Why do we analyze data?  It is important to analyze data because you need to determine the extent to which the hypothesized relationship does or does.
Measurements and Their Analysis. Introduction Note that in this chapter, we are talking about multiple measurements of the same quantity Numerical analysis.
Statistics Josée L. Jarry, Ph.D., C.Psych. Introduction to Psychology Department of Psychology University of Toronto June 9, 2003.
Chapter 3 EXPLORATION DATA ANALYSIS 3.1 GRAPHICAL DISPLAY OF DATA 3.2 MEASURES OF CENTRAL TENDENCY 3.3 MEASURES OF DISPERSION.
Ms. Drake 7th grade Math Measures of Central Tendency Lesson 2 Mean, Median, Mode and Range.
Welcome to MM305 Unit 2 Seminar Dr. Bob Statistical Foundations for Quantitative Analysis.
8.1 Plan Quality Management
Methods for Describing Sets of Data
QUALITY CONTROL CHAPTER 8.
STATISTICS AND PROBABILITY IN CIVIL ENGINEERING
Module 6: Descriptive Statistics
Statistical significance & the Normal Curve
Central Tendency.
Notes Over 7.7 Finding Measures of Central Tendency
Collecting & Displaying Data
Introduction to the Use of Classic Quality Tools
Psychology Statistics
2-1 Data Summary and Display 2-1 Data Summary and Display.
Statistics: The Interpretation of Data
Warm Up # 3: Answer each question to the best of your knowledge.
Review for Exam 1 Ch 1-5 Ch 1-3 Descriptive Statistics
DESIGN OF EXPERIMENT (DOE)
Presentation transcript:

QUALITY MANAGEMENT TOOLS

COMPREHENSIVE QUALITY MANAGEMENT PROGRAM EQUIPMENT QUALITY CONTROL ADMINISTRATIVE RESPONSIBILITIES RISK MANAGEMENT RADIATION SAFETY PROGRAM

INFORMATION ANALYSIS POPULATION SAMPLE DATA SET FREQUENCY CONTINUOUS VARIABLES DICHOTOMOUS VARIABLES CENTRAL TENDENCY RELIABILITY STANDARD DEVIATION VARIANCE

POPULATION SET OR GROUP OF ITEMS UNDER MEASUREMENT

SAMPLE NUMBER OF ITEMS MEASURED FROM POPULATION.

DATA SET INFO ACQUIRED BY EVALUATING PARTICULAR SAMPLE.

CONTINUOUS VARIABLES HAVE AN INFINITE RANGE OF MATHEMATICAL VALUES THAT ARE POSSIBLE.

DICHOTOMOUS VARIABLE HAVE ONLY TWO POSSIBLE CHOICES: (ON OR OFF, ETC.)

CENTRAL TENDENCY MEAN MEDIAN MODE

RELIABILITY ACCURACY, DEPENDABILITY OF THE COLLECTED DATA

STANDARD DEVIATION THE RANGE OF VARIATIONS SURROUNDING THE MEAN

VARIANCE THE SQUARE OF STANDARD DEVIATION.

INFO. ANALYSIS TOOLS FLOWCHART CAUSE AND EFFECT DIAGRAM ( ISHIKAWA OR FISHBONE DIAGRAM) HISTOGRAM PARETO CHART SCATTER PLOT TREND CHART CONTROL CHART

FLOWCHART PICTORIAL REPRESENTATION OF THE INDIVIDUAL STEPS IN THE PROCESS

CAUSE AND EFFECT DIAGRAM DEMONSTRATES CAUSE AND EFFECT OF DIFFERENT VARIABLES.

HISTOGRAM DISPLAY IN THE FORM OF BAR GRAPH WITH THE MOST FREQUENT OCCURRENCE IN THE CENTER.

PARETO CHART VARIATION OF BAR GRAPH. PRIORITIZES OCCURRENCE IN THE DECREASING ORDER TO THE RIGHT.

SCATTER PLOT DESIGNED TO DETERMINE IF RELATIONSHIP EXIST BETWEEN TWO DIFFERENT VARIABLES IN A PROCESS

TREND CHART WHAT INDICATORS ARE MOVING UP OR DOWN IN A GIVEN PERIOD.

CONTROL CHART TREND CHART MODIFICATION. HAS LOWER AND UPPER LIMITS WITH CENTRAL LINE THAT INDICATES AN ACCEPTED NORM.