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    In this paper, another popular AI technique, blackboard architecture, is adopted to develop a blackboard-based stamping process planning system. In the last two decades, blackboard architecture has been successfully used in a wide variety of areas, such as speech recognition, signal processing, engineering design and process planning. Thompson and Lu [17] used blackboard architecture to provide a cooperative decision making environment that is suitable for concurrent product and process design. Srihari et al. [18] developed a real-time CAPP system for printed circuit board (PCB) assembly by integrating multiple KSs, including planning expert and dynamic information processing modules in the blackboard architecture. Chen et al. [19] developed a concurrent product design evaluation system, using blackboard architecture to classify knowledge into perse KSs suitable for qualitative and quantitative evaluation, respectively.
    In the past few years, blackboard architecture has proven to be suitable for tooling design such as fixture design [20] and injection molding design [21], though this kind of application is still in its infancy stage. Roy and Liao [20] report the preliminary work that investigates the suitability of using a blackboard architecture as a [K1] problem solving model for fixture design. It describes the creation of various functional KSs for fixture design and their organization in a cooperative problem solving environment. K wong et al. [21] proposes a blackboard-based system for concurrent process design of injection moulding, which facilitates the simultaneous considerations of moulding part design, tool design, machine-selection, production scheduling, and cost as early as possible in the conceptual design stage. However, we have not found in the literature any attempt to apply the blackboard architecture to stamping process planning for sheet metal parts. It has been mentioned in our earlier work [22] that a blackboard architecture is well suited for constructive problem solving, like process planning of stamping operations, where the problem space is large and knowledge from many different sources must be integrated to achieve a solution. This topic is now to be extensively elaborated in the present paper.
    3 Blackboard frameworks for stamping process planning
    Cooperative decision making for knowledge-based stamping process planning involves a variety of KSs such as unfolding knowledge to produce flat pattern, nesting knowledge to produce blank layout, mapping knowledge to transform stamping features into stamping operations, and staging knowledge to sequence the stamping operations. These KSs may be expressed in different representation schemes such as procedures, rules, and objects. This justifies the use of a blackboard framework that can manage heterogeneous KSs effectively. The KSs interact through the blackboard to develop a solution incrementally.
    The proposed blackboard framework consists of three major components: the blackboard data structure, KSs, and a control module (Fig. 1), and was developed using object-oriented expert system shell CLIPS. The different components of the blackboard framework are described as follows.
    3.1 Object-oriented blackboard data structure
    The blackboard is a globally accessible database, which contains the data and partial solutions and is shared by a number of independent KSs. The KSs contribute their partial solutions to the blackboard, which lead to a final solution incrementally. The blackboard is structured as a hierarchy of solution partition levels, which represent different aspects or stages of the solution process. Partial solutions are associated with each level and may be linked to information on other levels using algorithmic procedures or heuristic rules. Each level contains planning objects that are used to represent the solution space in an object oriented manner. This leads to the added advantage in knowledge system development because object-oriented approach supports software modularity, reusability, and scalability.
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