T20-02 Mean Chart (Unknown Variation) CL Calculations

Slides:



Advertisements
Similar presentations
Control Charts for Variables
Advertisements

Statistical Process Control
Quality Assurance (Quality Control)
1 © The McGraw-Hill Companies, Inc., 2006 McGraw-Hill/Irwin Technical Note 9 Process Capability and Statistical Quality Control.
Nursing Home Falls Control Chart Problem Statement: Assume that following data were obtained about number of falls in a Nursing Home facility. Produce.
Statistical Process Control. Overview Variation Control charts – R charts – X-bar charts – P charts.
Agenda Review homework Lecture/discussion Week 10 assignment
T T06-02 Normal & Standard Normal Templates Purpose T06-02 is an all in one template combining the features of the two templates T06-02.N and.
T T18-03 Exponential Smoothing Forecast Purpose Allows the analyst to create and analyze the "Exponential Smoothing Average" forecast. The MAD.
T T20-01 Mean Chart (Known Variation) CL Calculations Purpose Allows the analyst calculate the "Mean Chart" for known variation 3-sigma control.
Quality Control Ross L. Fink. Quality Control n Quality control involves controlling the delivery processes to adhere to the specifications (or product.
T T02-06 Histogram (6 SD) Purpose Allows the analyst to analyze quantitative data by summarizing it in sorted format, scattergram by observation,
T T Population Sampling Distribution Purpose Allows the analyst to determine the mean and standard deviation of a sampling distribution.
T T20-05 Forecast Control Limit Calculations Purpose Allows the analyst to calculate the “Forecast Control Chart” 3-sigma control limits based.
T T18-04 Linear Trend Forecast Purpose Allows the analyst to create and analyze the "Linear Trend" forecast. The MAD and MSE for the forecast.
T T18-05 Trend Adjusted Exponential Smoothing Forecast Purpose Allows the analyst to create and analyze the "Trend Adjusted Exponential Smoothing"
ESAP T T02-00 Qualitative (Tabular Summary, Bar Graph, Pie Chart) Purpose Allows the analyst to analyze qualitative data by summarizing it in.
T T20-03 P Chart Control Limit Calculations Purpose Allows the analyst to calculate the proportion "P-Chart" 3-sigma control limits. Inputs Sample.
ESAP T T02-01 Quick Graphs (Line Plot, Bar Graph, Pie Chart) Purpose Allows the analyst to create line plots, bar graphs and pie charts from data,
T T07-01 Sample Size Effect – Normal Distribution Purpose Allows the analyst to analyze the effect that sample size has on a sampling distribution.
T T02-04 Histogram (User Selected Classes) Purpose Allows the analyst to analyze quantitative data by summarizing it in sorted format, scattergram.
T T20-06 Control Chart (with Runs Tests) Purpose Allows the analyst create and analyze a "Control Chart". A visual analysis of the control time.
5 – 1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall. Quality And Performance 5.
Control Charts.
T T Population Variance Confidence Intervals Purpose Allows the analyst to analyze the population confidence interval for the variance.
T T18-09 Line Plot (by Observation) Purpose Allows the analyst to visually analyze up to 5 time series plots on a single graph data samples by.
Rev. 09/06/01SJSU Bus David Bentley1 Chapter 10 – Quality Control Control process, statistical process control (SPC): X-bar, R, p, c, process capability.
T T20-00 Range Chart Control Limit Calculations Purpose Allows the analyst to calculate the "Range Chart" 3- sigma control limits based on table.
T T18-06 Seasonal Relatives Purpose Allows the analyst to create and analyze the "Seasonal Relatives" for a time series. A graphical display of.
1 Doing Statistics for Business Doing Statistics for Business Data, Inference, and Decision Making Marilyn K. Pelosi Theresa M. Sandifer Chapter 16 Improving.
Statistical Process Control (SPC) Chapter 6. MGMT 326 Foundations of Operations Introduction Strategy Quality Assurance Capacity, Facilities, & Work Design.
Guide to Using Excel 2007 For Basic Statistical Applications To Accompany Business Statistics: A Decision Making Approach, 8th Ed. Chapter 8: Estimating.
T T20-04 C Chart Control Limit Calculations Purpose Allows the analyst to calculate the defectives per unit "C-Chart" 3-sigma control limits.
T T03-01 Calculate Descriptive Statistics Purpose Allows the analyst to analyze quantitative data by summarizing it in sorted format, scattergram.
By: Samah Tout and Bing Liu Team Potassium Sigma Nov. 20,2007.
Statistical Process Control
Statistical Quality Control/Statistical Process Control
T06-02.S - 1 T06-02.S Standard Normal Distribution Graphical Purpose Allows the analyst to analyze the Standard Normal Probability Distribution. Probability.
T T Population Confidence Intervals Purpose Allows the analyst to analyze the difference of 2 population means and proportions for sample.
1 Six Sigma Green Belt Introduction to Control Charts Sigma Quality Management.
T T Population Sample Size Calculations Purpose Allows the analyst to analyze the sample size necessary to conduct "statistically significant"
Statistical Process Control. Overview Variation Control charts – R charts – X-bar charts – P charts.
T T18-07 Seasonally Adjusted Linear Trend Forecast Purpose Allows the analyst to create and analyze a "Seasonally Adjusted Linear Trend" forecast.
SPC (Statistical Process Control)
Individuals Chart Due to High Costs (e.g., destructive testing/measurement) or a lack of data gathering opportunities there may be only one measurement.
Dr. Dipayan Das Assistant Professor Dept. of Textile Technology Indian Institute of Technology Delhi Phone:
I NDUSTRIAL Q UALITY M ANAGEMENT Exponentially Weighted Moving Average Control Charts January 16, 2012.
Route 44 Soft Drink AN ANALYSIS ON PROCESS CAPABILITY, AND CONTROLS.
1 Statistical Process Control Is a tool for achieving process stability improving capability by reducing variability Variability can be due to chance causes.
T T Population Hypothesis Tests Purpose Allows the analyst to analyze the results of hypothesis testing of the difference of 2 population.
T T05-01 Binomial Distribution Purpose Allows the analyst to analyze a Binomial Distribution with up to 50 trials. Probability Scenario's, Expected.
T T05-02 Poisson Distribution Purpose Allows the analyst to analyze a Poisson Distribution. Probability Scenario's, Expected Value, Variance and.
Quality Control Chapter 6. Transformation Process Inputs Facilities Equipment Materials Energy Outputs Goods & Services Variation in inputs create variation.
Process Control Charts By: Brian Murphy. Control Charts are an on-line process- monitoring technique. Used to determine if a process is capable or out.
T T18-02 Weighted Moving Average Forecast Purpose Allows the analyst to create and analyze the "Weighted Moving Average" forecast for up to 5.
Tech 31: Unit 3 Control Charts for Variables
Quality Control İST 252 EMRE KAÇMAZ B4 /
Microsoft EXCEL Basics
X AND R CHART EXAMPLE IN-CLASS EXERCISE
Agenda Review homework Lecture/discussion Week 10 assignment
Variable Control Charts
What is the point of these sports?
Control Charts - SPC Types of Control Charts:
Development and Interpretation of Control Charts
Determine the central line and control limit
Statistics for Business and Economics
Hypothesis Testing and Confidence Intervals
T18-08 Calculate MAD, MSE Purpose Allows the analyst to create and analyze the MAD and MSE for a forecast. A graphical representation of history and.
Basic Training for Statistical Process Control
SPC (Statistical Process Control)
Presentation transcript:

T20-02 Mean Chart (Unknown Variation) CL Calculations Purpose Allows the analyst to calculate the "Mean Chart" for unknown variation 3-sigma control limits based on table lookup. Inputs Sample Size Centerline (Grand Average) Average Range Outputs Mean Control Chart LCL & UCL

Mean Chart ( Chart) - Unknown Variation The Mean Chart Centerline, UCL and LCL (3 sigma limits) are calculated by the following when the variation of the process is unknown.

3 Sigma Control Chart Table

Example The mean of 20 samples each containing 5 observations are shown here. They have been taken from a process with unknown variance. The grand average can now be calculated. This can be done by using the Descriptive Statistics Template or more quickly by using the EXCEL built in AVERAGE function on this set of numbers. Grand Average

Example The range of the 20 samples are shown here. The average range can now be calculated. This can be done by using the Descriptive Statistics Template or more quickly by using the EXCEL built in AVERAGE function on this set of numbers. Calculate the Control Limits for the Mean Control Chart. Average Range

Input the Sample Size, Centerline (Grand Average), and Average Range in the light green cells. The LCL, UCL are automatically calculated