DOE
DOE helps to access through the vast amount of data collected as part of the Six Sigma project implementation process and in designing experiments that are required to reduce variations and improve efficiency.
What is DOE?
Design of experiments is a formal statistical tool that helps to ensure that the testing phase of the project produces data that would be beneficial for further improvements to the process. The aim is to maximize return on investment.
It is a systematic method to understand the cause and effect relationship among the different factors that affect the process and the variable results achieved thereby. It even brings out the actual existence of any relation in the cause and effect. Using the advanced statistical tools, it enables to understand the variations and to control them.
This helps to improve the predictability of the business processes.
DOE is based upon factors, levels and responses. A factor in this case is an independent variable, which is given varied values with the purpose to achieve varied results. The level is the state defined for that factor.
The state varies and will bring out varied results. These results are the responses achieved from the experiment at different levels. The results achieved can be numerical or discrete values.
In other words, Six Sigma professionals can select those experiment designs which are best suited to achieve the desired results from such experimentation.
When selecting the factors and the state for experiment, those factors that will generate pertinent data relative to the expected results will be selected. The sequence of the experiment, which runs randomly, will allow all factors to affect all runs of the experiment.
The drawback of a non-random run is the systematic effect the external factors may have on the experiment. Replication can help provide greater amounts of data and greater value to the results. Successfully completed experiments will bring out the effect and the change in levels has on the responses.
This helps to understand the best solution for the process improvement and reduction in variation.
Benefits of DOE
DOE helps to analyze the data to achieve quantifiable results to undertake experiments and make changes to the processes to achieve the Six Sigma level. If Six Sigma concepts and methodologies are not implemented, precisely the expected results would not be achieved and it will hit the bottom line results of the organization adversely.
Being a systematic way to approach the experiments to be undertaken, Six Sigma professionals can ensure the best suited tests, which are conducted and which in turn lead to achieve the expected improvements. As the aim to set up processes is to achieve the same quality of the products and services, the variations have to be identified and eliminated.
DOE helps to understand the root causes of variations. Being well-equipped with the data on variations, Six Sigma professionals can work towards elimination of such variations. This ensures the success of the Six Sigma implementation.
Design of experiments is thus an integral part of the Six Sigma implementation, irrespective of any specific industry.
Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solutions - Six Sigma Online (http://www.sixsigmaonline.org) offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.
Article Source: http://EzineArticles.com/?expert=Tony_Jacowski
Article Source: http://EzineArticles.com/2602694
What is DOE?
Design of experiments is a formal statistical tool that helps to ensure that the testing phase of the project produces data that would be beneficial for further improvements to the process. The aim is to maximize return on investment.
It is a systematic method to understand the cause and effect relationship among the different factors that affect the process and the variable results achieved thereby. It even brings out the actual existence of any relation in the cause and effect. Using the advanced statistical tools, it enables to understand the variations and to control them.
This helps to improve the predictability of the business processes.
DOE is based upon factors, levels and responses. A factor in this case is an independent variable, which is given varied values with the purpose to achieve varied results. The level is the state defined for that factor.
The state varies and will bring out varied results. These results are the responses achieved from the experiment at different levels. The results achieved can be numerical or discrete values.
In other words, Six Sigma professionals can select those experiment designs which are best suited to achieve the desired results from such experimentation.
When selecting the factors and the state for experiment, those factors that will generate pertinent data relative to the expected results will be selected. The sequence of the experiment, which runs randomly, will allow all factors to affect all runs of the experiment.
The drawback of a non-random run is the systematic effect the external factors may have on the experiment. Replication can help provide greater amounts of data and greater value to the results. Successfully completed experiments will bring out the effect and the change in levels has on the responses.
This helps to understand the best solution for the process improvement and reduction in variation.
Benefits of DOE
DOE helps to analyze the data to achieve quantifiable results to undertake experiments and make changes to the processes to achieve the Six Sigma level. If Six Sigma concepts and methodologies are not implemented, precisely the expected results would not be achieved and it will hit the bottom line results of the organization adversely.
Being a systematic way to approach the experiments to be undertaken, Six Sigma professionals can ensure the best suited tests, which are conducted and which in turn lead to achieve the expected improvements. As the aim to set up processes is to achieve the same quality of the products and services, the variations have to be identified and eliminated.
DOE helps to understand the root causes of variations. Being well-equipped with the data on variations, Six Sigma professionals can work towards elimination of such variations. This ensures the success of the Six Sigma implementation.
Design of experiments is thus an integral part of the Six Sigma implementation, irrespective of any specific industry.
Tony Jacowski is a quality analyst for The MBA Journal. Aveta Solutions - Six Sigma Online (http://www.sixsigmaonline.org) offers online six sigma training and certification classes for lean six sigma, black belts, green belts, and yellow belts.
Article Source: http://EzineArticles.com/?expert=Tony_Jacowski
Article Source: http://EzineArticles.com/2602694
