Quality management has three aspects:
1. Quality planning – plan
2. Quality Executing – quality assurance – execute
3. Quality controlling – monitor and control<\/p>\n
Quality planning – plan<\/b>
Identify quality specifications and requirements for the project. Plan hos the quality specifications will be met.<\/p>\n
Output:
Quality management plan
Quality metrics
Quality checklists
Process improvement plans
Quality baseline<\/p>\n
Tools:
Cost benefit analysis
Benchmarking
Cost of quality<\/p>\n
Quality assurance<\/b>
Remember it is not quality control, it is just executing the development in such a way so that the quality requirements are met<\/p>\n
Output:
Requested changes
Requested corrective actions
Modifications to Project management plan<\/p>\n
Input
Quality management plan
Quality metrics
Quality control measurements<\/p>\n
Quality Control<\/b>
Quality Control checks if the quality requirements are met or not. It is done throughout the process\/development\/production life cycle.Quality Control uses statistical sampling<\/p>\n
Tools for Quality Control:
Cause and effect diagram: Shows how different factors relate together and affect the quality<\/p>\n
Control Charts: Uses statistical sampling and known as statistical process control.
Example: take quality mesurements of different samples. Find the avergae quality. Draw a line with the average quality. Plot all the samples’s quality. Draw the line for upper quality limit. Draw the line for lower quality limit. If all\/most points are in between the process may be in control. If seven consecutive samples fall on one side of the avergae line the samples must be inspected.<\/p>\n
Flowcharting:Shows how different components relate and determine where quality problems may occur. Example: Cause and effect diagram<\/p>\n
Histogram:<\/p>\n
Pareto chart: Histogram-shows defects ranked from greatest to least.<\/p>\n
Pareto law: 80% problems come from 20% problems. Pareto chart is used to find the root causes of the problems.<\/p>\n
Run Chart: Displays quality over time. Example: Time\/month on X axis, defects per thousand on y axis.<\/p>\n
Scatter Diagram: Plot all data and try to find the trendsStatistical Sampling: Take a sample randomly and measure quality<\/p>\n
Inspection:<\/p>\n
Defect repair review<\/p>\n
Some Terms<\/b>Total Quality Management: Everyone in the company is responsible for the quality and can influence the quality of the outcome<\/p>\n
ISO 9000: Ensures that companies document what they do and do what they document<\/p>\n
Statistical Independence: Two samples are not dependent on each other<\/p>\n
Mutually Exclusive: One choice excludes the other<\/p>\n
Standard Deviation: Calculate the mean. Then find difference between each data point and the mean. Square each of the differences.std dev = SQRT((sum of the squired differences)\/(count data points – 1)). The higher your standard deviation the more diverse the data points.<\/p>\n
Six Sigma: six sigma standard deviations (99.99966% of the data points) meet customer’s quality limits. <\/p>\n
Prevention vs inspection:<\/p>\n
Attribute sampling: conforms quality or not. binary <\/p>\n
variable sampling: How well something conforms to quality<\/p>\n
Special causes: Unusual and preventable<\/p>\n
Common Causes:normal<\/p>\n
Tolerance:quality limis for product acceptanceControl Limits: Three standard deviation above and below the mean.<\/p>\n
From: http:\/\/sitestree.com\/?p=4773
Categories:PMP – Project Management
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Post Data:2012-02-22 22:14:48<\/p>\n
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