This paper presents an overview of our DPP (distributed process planning) approach, covering DPP concept, generic machining process sequencing using enriched machining features, process plan encapsulation in function blocks, and process monitoring enabled by the function blocks. A two-layer structure of Supervisory Planning and Operation Planning is proposed in DPP to separate generic data from machine-specific ones. The supervisory planning is only performed once, in advance, at shop level, whereas the operation planning is carried out at runtime at machine level. This dynamic decision-making is facilitated by a set of resource-driven algorithms embedded in the function blocks. The internal structures of typical function blocks are also introduced in the paper. The DPP approach and algorithms are further verified through a case study before drawing conclusions. It is expected that the new approach can largely enhance the dynamism of fluctuating job shop operations.
A machining process planning activity model for systems integration
