Computer-aided process planning is the link between design and manufacturing in a computer-integrated manufacturing (CIM) environment. The process-planning problem comes out as a rigid hierarchical structure of tasks where the lowest levels are well-defined tasks, such as determination of machine and cutting parameters, while the top levels control, coordinate, and manage the entire system. Such a top-down manner of coordination makes it a tightly coupled distributed decision-making situation. The complexity of CIM systems with hierarchical structures grows rapidly with the size of the system making them very expensive. Also, assimilating a large array of knowledge sources to plan the activities is a major hurdle.Cooperative distributed problem-solving (CDPS) is concerned with the cooperative solution of problems by a decentralized group of cooperating intelligent agents. CDPS techniques have good adaptive capability, make the system modular, are faster due to parallel operation of subsystems, possess greater reliability through redundancy, can over-ride limited resources, and can collect knowledge. This paper describes a conceptual framework of applying CDPS to CAPP for general-purpose process modeling. The problem in process planning has been mapped onto a CDPS architecture based on multistage negotiation. The needed agents are defined, and their roles in the architecture and the knowledge that each agent would need are described at the conceptual level. Potential benefits of the framework in solving process planning problems in an intelligent and distributed manner have been discussed.