Optimal measurement planning using fuzzy-set theory

In precision measurement, it is known that a measurement process involves errors or factors of different kinds and types. Using the prior knowledge on the relationship between the measured variables and the factors, the best measurement plan may be obtainable if a target function on the errors is minimized. In many cases, however, the relationship may not be clear since non-quantitative factors are involved, making the finding of the best plan using methods such as the statistics method quite difficult. A new method based the fuzzy-set theory is proposed to solve this problem. In this method, the membership grade is maximized. The concept of quasi-perfect plan is presented. Mathematical modes are established and case studies are presented in order to demonstrate the feasibility of the proposed method.