The term Taguchi Methods refers to a collection of principles which make up the framework of a continually evolving approach to quality. Taguchi’s approach can be broken down into a few different steps. These steps include problem formulation, experimental planning, experimental results and confirmation of the improvement. This is essentially a closed loop process as shown in figure 2. If the objective is not met, the procedure must begin again with modified parameters.
[pic] Design Process Block DiagramIn Taguchi’s approach, optimum design is determined by using design of experiment principles, and consistency of performance is achieved by carrying out the trial conditions under the influence of the noise factors. 1. BRAINSTORMING This is a necessary first step in any application. The session should include individuals with first hand knowledge of the project. All matters should be decided based on group consensus, (One person — One vote).
– Determine what you are after and how to evaluate it. When there is more than one criterion of evaluation, decide how each criterion is to be weighted and combined for the overall evaluation. Identify all influencing factors and those to be included in the study. – Determine the factor levels. – Determine the noise factor and the condition of repetitions. 2. DESIGNING EXPERIMENTS Using the factors and levels determined in the brainstorming session, the experiments now can be designed and the method carrying them out established.
To design the experiment, implement the following: – Select the appropriate orthogonal array. – Assign factor and interaction to columns. – Describe each trial condition.
– Decide order and repetitions of trial conditions. 3. RUNNING EXPERIMENTRun experiments in random order when possible. 4. ANALYZING RESULTS Before analysis, the raw experimental data might have to be combined into an overall evaluation criterion. This is particularly true when there are multiple criteria of evaluation. Analysis is performed to determine the following: – The optimum design. – Influence of individual factors.
– Performance at the optimum condition ; confidence interval (C. I. ).
– Relative influence of individual factors. etc. 5. RUNNING CONFIRMATION EXPERIMENTS) Running the experiments at the optimum condition is the necessary final step.