Stable Process Software Testing part TWo

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).

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Stable Process Software Testing part one

The amount of variation in a process is quantified with summary statistics; typically, the standard deviation is used. A process is defined as stable if its parameters (i.e., mean and standard deviation) remain constant over time; it is then said to be in a state of statistical control. Figure illustrates a stable process. Such a process is predictable, i.e., we can predict, within known limits and with a stated degree of belief, future process values.

Accepted practice uses a prediction interval three standard deviation distances in width around the population mean (µ ± 3) in establishing the control limits.

Continuous process improvement through the use of quantitative methods and employee involvement sets quality management apart from other attempts to improve productivity.

Continuous process improvement is accomplished by activating teams and providing them with quantitative methods such as SPC techniques and supporting them as they apply these tools. We will further discuss the concept of variation, common and special causes of variation, and QAI’s Continuous Improvement Strategy.

The natural change occurring in organizational life moves systems and processes towards increasing variation. Statistical methods help us collect and present data in ways that facilitate the evaluation of current theories and the formation of new theories. These tools are the only methods available for quantifying variation. Since the key to quality is process consistency, variation (the lack of consistency) must be understood before any process can be improved.

Statistical methods are the only way to objectively measure variability. There is no other way!

Variation is present in all processes.

The cumulative effect of sources of variation in a production process is shown in the table.

One of the challenges in implementing quality management is to get those working in the process thinking in terms of sources of variation. How much of the observed variation can be attributed to measurements, material, machines, methods, people and the environment?

Consistency in all the processes from conception through delivery of a product or service is the cornerstone of quality. Paradoxically, the route to quality is not just the application of SPC and the resulting control charts. Managers must change the way they manage. They must use statistical methods in making improvements to management processes as well as all other processes in the organization.

Special causes of variation are not typically present in the process. They occur because of special or unique circumstances. If special causes of variation exist, the process is unstable or unpredictable. Special causes must be eliminated to bring a process into a state of statistical control. A state of statistical control is established when all special causes of variation have been eliminated.

SUMMARY:

Process inputs and conditions that sporadically contribute to the variability of process outputs.

1• Special causes contribute to output variability because they themselves vary.

2.Each special cause may contribute a “small” or “large” amount to the total variation in process outputs.

3• The variability due to one or more special causes can be identified by the use of control charts.
• Because special causes are “sporadic contributors,” due to some specific circumstances, the “process” or “system” variability is defined without them.

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