CONTROL CHARTS | 7 QC Tools | Quality Control Tools | Lean Six Sigma Tools | Quality Management

CONTROL CHARTS: Mean Chart, Range Chart, P-Chart, C-Chart | 7 QC Tools | Quality Control Tools | Lean Six Sigma Tools | Quality Management

CHAPTERS
0:00 Introduction to control chart
0:24 Control chart as QC tool
0:50 Types of control chart
1:34 Mean chart for accuracy
3:19 Range chart for precision
4:32 P-chart for proportion defective.
5:34 C-chart for attribute data.

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CONTROL CHART
The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has the central line for the average, an upper line for the upper control limit (UCL), and a lower line for the lower control limit (LCL). These lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or unpredictable (out of control, affected by special causes of variation). This versatile data collection and analysis tool can be used by a variety of industries and is considered one of the seven basic quality tools.

WHEN TO USE A CONTROL CHART
• When controlling ongoing processes by finding and correcting problems as they occur.
• When predicting the expected range of outcomes from a process.
• When determining whether a process is stable (in statistical control).
• When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process).
• When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.

TYPES OF CONTROL CHARTS
• Control charts for variables: Mean chart and Range chart.
• Control charts for attributes: P-chart and C-chart

BASIC PROCEDURE
1) Choose the appropriate control chart for your data.
2) Determine the appropriate time period for collecting and plotting data.
3) Collect data, construct your chart and analyze the data.
4) Look for "out-of-control signals" on the control chart. When one is identified, mark it on the chart and investigate the cause. Document how you investigated, what you learned, the cause, and how it was corrected.
Out-of-control signals
• A single point outside the control limits.
• Two out of three successive points are on the same side of the centerline and farther than 2σ from it.
• Four out of five successive points are on the same side of the centerline and farther than 1σ from it.
• A run of eight in a row is on the same side of the centerline. Or 10 out of 11, 12 out of 14, or 16 out of 20.
• Obvious consistent or persistent patterns that suggest something unusual about your data and your process.
• Continue to plot data as they are generated. As each new data point is plotted, check for new out-of-control signals.
• When you start a new control chart, the process may be out of control. If so, the control limits, calculated from the first 20 points are conditional limits. When you have at least 20 sequential points from a period when the process is operating in control, recalculate control limits.

Related Videos and Playlists:-
• Control Charts Explained in Hindi https://www.youtube.com/watch?v=FgEs-ZY9-tI&t=1933s

•https://www.youtube.com/watch?v=DmrI4WaLULE&t=524s

• 7 QC Tools in a Nutshell in English https://www.youtube.com/watch?v=VmMN583M8n0&t=1s

• 7 QC Tools in a Nutshell in Hindi https://www.youtube.com/watch?v=MqnzFtljjyI&t=4s

• 7 QC Tools Vs New 7 QC Tools https://www.youtube.com/watch?v=v5rR-AY5gNE

• 7 QC Tools Master Class in English https://www.youtube.com/watch?v=OHrUZB5NXtk&list=PL2H1lLi34F7gaX_nR8FDCHvXSxHOscWOu

• 7 QC Tools Master Class in Hindi https://www.youtube.com/watch?v=FgEs-ZY9-tI&list=PL2H1lLi34F7ilS4W4DVDxiG0swmAf9V5U

• New 7 QC Tools English Lectures: https://www.youtube.com/watch?v=nk73ctFXWsI&list=PL2H1lLi34F7g9QK3RMkETeoDbY5rI0jXw

• New 7 QC Tools Hindi Lectures: https://www.youtube.com/watch?v=UKb3Bb45cn4&list=PL2H1lLi34F7hfmjbftiQ-Uo6WupcgjpnC
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