a b s t r a c tCurrently, workflow technology is widely used to facilitate the business process in enterprise information systems (EIS), and it has the potential to reduce design time, enhance product quality and decrease product cost. However, significant limitations still exist: as an important task in the context of workflow, many present resource allocation (also known as ''staff assignment'') operations are still performed manually, which are time-consuming. This paper presents a data mining approach to address the resource allocation problem (RAP) and improve the productivity of workflow resource management. Specifically, an Apriorilike algorithm is used to find the frequent patterns from the event log, and association rules are generated according to predefined resource allocation constraints. Subsequently, a correlation measure named lift is utilized to annotate the negatively correlated resource allocation rules for resource reservation. Finally, the rules are ranked using the confidence measures as resource allocation rules. Comparative experiments are performed using C4.5, SVM, ID3, Naïve Bayes and the presented approach, and the results show that the presented approach is effective in both accuracy and candidate resource recommendations.

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Efficient construction in three-dimensional working procedure model has an important effect on the efficiency and quality of machining process planning. This article proposes an algorithm to mapping machining features to manufacturing feature volumes from B-rep of mechanical part, and then, the working procedure models are generated. The mapping strategy is performed in three steps. In the first step, three types of machining features, such as depression feature, protrusion feature and transition feature, are introduced. In the second step, the edges of the chosen seed face and its neighboring faces are searched in order to generate the machining feature faces. The last step applies a closure to the machining feature faces to generate a compact solid by applying additional neighboring faces and their extensions. Then, the working procedure models are formed by combining the mapped manufacturing feature volumes with the final parts model. Compared with the existing working procedure model's generation methods, this approach can avoid the unnecessary conversions from the engineering drawing to three-dimensional process models and from the machining knowledge to the modeling knowledge, which can greatly reduce the planning time on modeling. To validate the feasibility and validity of this approach, two machined parts with complex machining features are tested in the developed prototype computer-aided process planning system.