Optimizing the Improvement

Design of Experiment and Response Surface Methodologies is the power tools to get the optimal solution based the observation and experiment data. Many tools in this world can be applied in this phase; you can choose what tools that proper with the project. In this site, you will learn how to optimize the solution use the Design of Experiment and Response Surface Methodology. Both methods are experiment base.

In the term of experiment, we will often talk about response, factor and level. Response is a measurable variable from the output which provides useful information about the process. Or we can say response is the Y of our project. Through the experiment, we will find the optimal factors (vital factor value) to gain the optimal of Y value. While factor selected controllable variable and important independent variables for an experiment. Each factor will be detailed in the levels. Levels mean values of factor. To conduct the experiment, we will do a treatment which combine the each level each factor.

The basic to get the success of an experiment, we must follow the basic way of the experiment rules. Experiment must be no ordered. Its mean, the experiment must be follow randomization rule to guarantee the objective and reproducibility of the result. Also, the project must be run more than one. Often this rule we call Replication. By using this rule in our experiment, we get more precision and better result of the experiment. Besides that, the experiment also contains blocking rules. Blocking is means grouping experimental units into the homogeneous sets. Blocking very effective way to minimize the experimental error and guarantee the better precision result.

Experimental should be use Randomization Rule which experimental unit are randomly assigned to the treatment and randomly execute the order of the treatment. Besides get better objectivity and reproducibility of experimental, this way also able to minimize the bias from the external sources of experimental.

Replication Rule consists of Repetition and Replication in the term itself. Repetition mean action of repeating experimental units while replication is repetition of the basic experimental. Its mean that the experimental units will be executed more than one in the same treatment. By doing this rule, the experimental will provide more accurate and precise set of observation. This way able to estimate an experimental error.

Blocking Rule aim to compare experiment that being done in one environment with another one within the group. Blocking will provide local control of the environmental error and effective to minimize the experimental error.

Picture I.3 Experimental Steps Process

The experimental steps consist of Design Step, Execution and Analyze. In the design step, we must clearly determine what the purposes of our experiment (must be clear – use SMART concept), response (Y), Factors (X’s) and Levels. After we can construct the components of experimental, we can decide what design of experimental that should be chosen.

In Execution steps, we execute the design that has been built. This step is equal Process step in SIPOC tools. The entire rule must be applied in this step. So, we can collect the data from this step correctly.

In the analyze step, we can analyze the data experimental based on the design. The properly tool of analyzing will determine the properly result of our experimental and get the right conclusion. The conclusion has been made, will be used to the implementation or application of the process of improvement. Better we run additional experimental to verify the reproducibility of derived optimal solution. This final conclusion may better than the first conclusion.

The detail of this tool, you can learn in Tool Categories in this site. (Design of Experiment and Response Surface Methodology)