Taguchi: 'Design it in'

Taguchi methods belong to the class of approaches that attempt to ensure quality of products through design, in this case through the identification and control of critical variables (or noises) that cause deviations to occur in the process/product quality.

Taguchi methods, developed by Dr. Genichi Taguchi, refer to techniques of quality engineering that embody both statistical process control (SPC) and new quality related management techniques. Most of the attention and discussion on Taguchi methods has been focused on the statistical aspects of the procedure; it is the conceptual framework of a methodology for quality improvement and process robustness that needs to be emphasized. The entire concept can be described in two basic ideas:

  1. Quality should be measured by the deviation from a specified target value, rather than by conformance to preset tolerance limits
  2. Quality cannot be ensured through inspection and rework, but must be built in through the appropriate design of the process and product

Figure 1. The Evolution of Quality Control

The first concept underlines the basic difference between Taguchi methods and the SPC methodology. Whereas SPC methods emphasize the attainment of an attribute within a tolerance range and are used to check product/process quality, Taguchi methods emphasize the attainment of the specified target value and the elimination of variation (Figure 2). In conjunction with the second concept, this assumes great significance for composites manufacturing since Taguchi methods emphasize that control factors must be optimized to make them insensitive to manufacturing transients through design, rather than by trial and error. SPC allows for faults and defects to be eliminated (if detected) after manufacture, whereas what is really needed is a methodology that prevents their occurrence. In this case, the methodology is the use of Taguchi methods. This then presents a powerful tool for composites processing within which there is an inherent variability due to raw material quality and/or noise in the process environment itself.Through the proper design of a system, the process can be made insensitive to variations, thus avoiding the costly eventualities of rejection and/or rework. In order to determine and subsequently minimize the effect of factors that cause variation, the design cycle is divided into three phases of System Design, Parameter Design, and Tolerance Design, as depicted in Figure 3.

Figure 2. A Comparison of Methodologies

Figure 3. Stages in the Design Cycle