Quality Management

QualityPMIs quality philosophy summarized byDefinition of qualityNo gold-platingPrevention over inspection

PMI Quality DefinitionQUALITY IS CONFORMANCE TO REQUIREMENTS AND FITNESS OF USE

No Gold-platingDont give the customer extrasAdds no-value to the project becauseit is beyond the scope Could cost moreMay be based on impressions not requests

Prevention over inspection

Quality must be planned NOT inspected

Six SigmaOriginally developed by Motorola, Six Sigma refers to an extremely high measure of process capabilityA Six Sigma capable process will return no more than 3.4 defects per million operations (DPMO)Highly structured approach to process improvement

Six sigma

Six SigmaDMAIC Approach

Tools Of TQMCheck SheetsScatter Diagrams Cause-and-Effect DiagramPareto ChartsFlow ChartsHistogramsStatistical Process Control (SPC)

/////////////////////////HourDefect12345678ABC////Seven Tools for TQM(a)Check Sheet: An organized method of recording dataFigure 6.5

Seven Tools for TQM(b)Scatter Diagram: A graph of the value of one variable vs. another variableFigure 6.5

Seven Tools for TQM(c)Cause and Effect Diagram: A tool that identifies process elements (causes) that might effect an outcomeFigure 6.5

Seven Tools for TQM(d)Pareto Charts: A graph to identify and plot problems or defects in descending order of frequencyFigure 6.5

Pareto Chart

Seven Tools for TQM(e)Flow Charts (Process Diagrams): A chart that describes the steps in a processFigure 6.5

Flow Charts

Seven Tools for TQM(f)Histogram: A distribution showing the frequency of occurrence of a variableFigure 6.5

Seven Tools for TQM(g)Statistical Process Control Chart: A chart with time on the horizontal axis to plot values of a statisticFigure 6.5

Variability is inherent in every processNatural or common causesSpecial or assignable causesProvides a statistical signal when assignable causes are presentDetect and eliminate assignable causes of variationStatistical Process Control (SPC)

Natural VariationsAlso called common causesAffect virtually all production processesExpected amount of variationOutput measures follow a probability distributionFor any distribution there is a measure of central tendency and dispersionIf the distribution of outputs falls within acceptable limits, the process is said to be in control

Assignable VariationsAlso called special causes of variationGenerally there is some change in the processVariations that can be traced to a specific reasonThe objective is to discover when assignable causes are presentEliminate the bad causesIncorporate the good causes

SamplesTo measure the process, we take samples and analyze the sample statistics following these steps(a)Samples of the product, say five boxes of cereal taken off the filling machine line, vary from each other in weightFigure S6.1

Samples(b)After enough samples are taken from a stable process, they form a pattern called a distributionFigure S6.1

Samples(c)There are many types of distributions, including the normal (bell-shaped) distribution, but distributions do differ in terms of central tendency (mean), standard deviation or variance, and shapeFigure S6.1

Samples(d)If only natural causes of variation are present, the output of a process forms a distribution that is stable over time and is predictableFigure S6.1

Samples(e)If assignable causes are present, the process output is not stable over time and is not predicableFigure S6.1

Control ChartsConstructed from historical data, the purpose of control charts is to help distinguish between natural variations and variations due to assignable causes

Types of DataCharacteristics that can take any real valueMay be in whole or in fractional numbersContinuous random variablesVariablesAttributesDefect-related characteristics Classify products as either good or bad or count defectsCategorical or discrete random variables

Control Charts for Variables

Control Chart

Patterns in Control ChartsNormal behavior. Process is in control.Figure S6.7

Patterns in Control ChartsOne plot out above (or below). Investigate for cause. Process is out of control.Figure S6.7

Patterns in Control ChartsTrends in either direction, 5 plots. Investigate for cause of progressive change.Figure S6.7

Patterns in Control ChartsTwo plots very near lower (or upper) control. Investigate for cause.Figure S6.7

Patterns in Control ChartsRun of 5 above (or below) central line. Investigate for cause. Figure S6.7

Patterns in Control ChartsErratic behavior. Investigate.Figure S6.7

*********************Points which might be emphasized include: - Statistical process control measures the performance of a process, it does not help to identify a particular specimen produced as being good or bad, in or out of tolerance. - Statistical process control requires the collection and analysis of data - therefore it is not helpful when total production consists of a small number of units - While statistical process control can not help identify a good or bad unit, it can enable one to decide whether or not to accept an entire production lot. If a sample of a production lot contains more than a specified number of defective items, statistical process control can give us a basis for rejecting the entire lot. The issue of rejecting a lot which was actually good can be raised here, but is probably better left to later.********Students should understand both the concepts of natural and assignable variation, and the nature of the efforts required to deal with them.*Once the categories are outlined, students may be asked to provide examples of items for which variable or attribute inspection might be appropriate. They might also be asked to provide examples of products for which both characteristics might be important at different stages of the production process.***Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*Ask the students to imagine a product, and consider what problem might cause each of the graph configurations illustrated.*