A new decision support method for the selection of RP process: knowledge value measuring

Many RP processes (rapid prototyping) have now been perfected and play an important role in creating prototypes as a support to the product development and in producing functional parts for direct applications. However, the selection of the right RP process or system for specific applications is becoming more difficult due to the expanding alternatives and their conflicting manufacturing properties, which form a classical multi-attribute decision-making (MADM) problem. To deal with the problem, this paper introduces a new method based on measuring manufacturing knowledge value extracted from RP processes. Knowledge unit and explicit knowledge value are redefined within the RP application context so as to apply an improved knowledge value measuring model which measures explicit knowledge value directly based on the deviation extent between knowledge units and the aspired application goals or preferences. The new method has some advantages when compared to former methods due to its simplicity and efficiency of using structured expert knowledge or production experience. It also has the potential to be widely applied in other fields where MADM problems exist, and to improve the efficiency of the present knowledge-based systems.