Automating dimensional tolerancing using Ripple Down Rules (RDR)

We propose to use a knowledge based approach to assist in mechanical design focusing on dimensional tolerancing. To illustrate our approach, we capture the knowledge which human designers utilize in order to specify dimensional tolerances on shafts and mating holes in order to meet desired classes of fit as set by relevant engineering standards. The software system we developed would help mechanical designers become more effective in the time-consuming dimensioning and tolerancing process of their designs in the future. In doing this, the paper makes a twofold contribution to the field of knowledge acquisition: firstly, interface was adjusted to receive mathematical functions with their specifications prior and during the KA process to propose an approach to exploit relationships among several classes with respect to certain numerical features of the cases in order to accelerate the convergence of the RDR knowledge acquisition process by generating artificial cases which are likely to trigger the addition of exception rules. Secondly, it introduces the above problem domain of determining suitable tolerances for mechanical parts in a design as a knowledge acquisition problem.