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Control ChartsFocuses on prevention of defects rather than detection and rejectionCost can be reduced significantly by applying process control chartsControl charts are based on Normal Distribution curveTells us when to look for troubleCannot tell where to look, or what cause will be foundNayyer KazmiControl Charts X Bar Centerline of the control chart or mean of dataUCL Upper Control Limit (X bar + 3s)LCL Lower Control Limit (X bar 3s)In the normal distribution, 99.73% of all measure lie within UCL and LCL.USL Upper Specification LimitLSL Lower Specification Limit

Nayyer KazmiControl Charts and Normal Distribution

Nayyer KazmiSource: Quality Management, Harold KerznerElements of Control Charts

Nayyer KazmiSource: Quality Management, Harold KerznerControl Chart - Process Run

When several successive points line up on one side of the central lineThe number of points in that run is called the length of the runAs a rule of thumb, if the run has a length of seven points, there is an abnormality in the processNayyer KazmiSource: Quality Management, Harold KerznerControl Chart - Trends

Continuous rise or fallSeven consecutive points rise or fall abnormalityOften points go beyond control limit before reaching sevenNayyer KazmiSource: Quality Management, Harold KerznerControl Charts - Periodicity

Same pattern of change (rise or fall) over equal intervalsNayyer KazmiSource: Quality Management, Harold KerznerHugging the Centerline or Control Limit

Points close to the central line or control limitsDifferent types of data or data from different factors have been mixed into subgroupsChange the subgroups, reassemble the data, redraw control chartsWhether there is hugging of center line?- abnormality if most of the points between these two linesWhether there is hugging of one of control limits? Abnormality if 2 out of 3 points, 3 out of 7 points, 4 out of 10 points lie within outer one third zone.Nayyer KazmiSource: Quality Management, Harold KerznerControl Chart Interpretation

Nayyer KazmiSource: Quality Management, Harold KerznerControl Charts Out of Control

Abnormality when data points exceeds either the upper or lower control limitsNayyer KazmiSource: Quality Management, Harold KerznerControl Charts In Control

Process in Control - No obvious abnormalities appear in the Control ChartsNayyer KazmiSource: Quality Management, Harold KerznerProcess CapabilityAbility to produce a product that conforms to design specificationsMean value plus or minus three standard deviationsCp > 1.33: The process is well within the customer specifications requirements1.33>=Cp>1.0: The process is marginally acceptable. Improvements are needed.Cp