In this paper, we will describe a new approach to handle the combinatorics of the search space of process plans and generate a satisfying process plan through interaction with the user. In our planning system, a satisfying plan is either a plan which minimizes the penalty cost associated with evaluation criteria violations, or one that satisfies the expert user. Knowledge about process plans is obtained from the Arizona State University Features Test Bed(ASUFTB), a comprehensive and systematic framework for recognizing and reasoning with features of machinable parts. Our approach can be seen as searching the space of interpretations for a design part as plans set up by ASUFTB. We will discuss the detailed algorithms and experimental results for satisfying process plan generation.