This post is in continuation with Stable testing process part one.
For eliminating special causes of variation:
Work to get very timely data so that special causes are signaled quickly – use early
warning indicators throughout your operation.
1.Immediately search for the cause when the control chart gives a signal that a special cause has occurred. Find out what was different on that occasion from other occasions.
2• Do not make fundamental changes in that process.
3• Instead, seek ways to change some higher-level systems to prevent that special cause from recurring.
Common causes of variation are typically due to a large number of small random sources of variation. The sum of these sources of variation determines the magnitude of the process’s inherent variation due to common causes; the process’s control limits and current process
capability can then be determined. Figure illustrates an out of control process.
common causes of variation:
1• Process inputs and conditions that regularly contribute to the variability of process outputs.
2• Common causes contribute to output variability because they themselves vary.
3• Each common cause typically contributes a small portion to the total variation in process outputs.
4• The aggregate variability due to common causes has a “nonsystematic,” randomlooking
appearance.
5• Because common causes are “regular contributors,” the “process” or “system” variability is defined in terms of them.
For reducing common causes of variation:
1• Talk to lots of people including local employees, other managers, and staff from various functions.
2• Improve measurement processes if measuring contributes too much to the observed variation.
3.Identify and rank categories of problems by Pareto analysis (a ranking from high to low of any occurrences by frequency).
4• Stratify and desegregate your observations to compare performance of sub-processes.
5• Investigate cause-and-effect relations. Run experiments (one factor and multifactor).
82.2
For eliminating special causes of variation:
Work to get very timely data so that special causes are signaled quickly – use early
warning indicators throughout your operation.
1.Immediately search for the cause when the control chart gives a signal that a special cause has occurred. Find out what was different on that occasion from other occasions.
2• Do not make fundamental changes in that process.
3• Instead, seek ways to change some higher-level systems to prevent that special cause from recurring.
Common causes of variation are typically due to a large number of small random sources of variation. The sum of these sources of variation determines the magnitude of the process’s inherent variation due to common causes; the process’s control limits and current process
capability can then be determined. Figure illustrates an out of control process.
common causes of variation:
1• Process inputs and conditions that regularly contribute to the variability of process outputs.
2• Common causes contribute to output variability because they themselves vary.
3• Each common cause typically contributes a small portion to the total variation in process outputs.
4• The aggregate variability due to common causes has a “nonsystematic,” randomlooking
appearance.
5• Because common causes are “regular contributors,” the “process” or “system” variability is defined in terms of them.
For reducing common causes of variation:
1• Talk to lots of people including local employees, other managers, and staff from various functions.
2• Improve measurement processes if measuring contributes too much to the observed variation.
3.Identify and rank categories of problems by Pareto analysis (a ranking from high to low of any occurrences by frequency).
4• Stratify and desegregate your observations to compare performance of sub-processes.
5• Investigate cause-and-effect relations. Run experiments (one factor and multifactor).
82.2
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