A method for automatic generation of optimized 3-axis nc programs for pocketing operations is described that relies on the use of boundary files for geometric and topological information about the workpiece. A boundary file of the part is first created by a solids modeller and then input to the system along with machining parameters. After the user indicates those areas of the part to be machined, a cutter path of minimum length is generated consisting of two cut-sequences: a rough-cut and a finishing-cut. To implement the procedure, an APT code generator has been developed and tested on several parts.

Many database maintenance operations are performed periodically in batches, even in real-time systems. The purpose of this paper is to present a general model for determining the optimal frequency of these batch operations. Specifically, optimal backup, checkpointing, batch updating, and reorganization policies are derived. The approach used exploits inventory parallels, by seeking the optimal number of items --- rather than a time interval --- to trigger a batch. The Renewal Reward Theorem is used to find the average long run costs for backup, recovery, and item storage, per unit time, which is then minimized to find the optimal backup policy. This approach permits far less restrictive assumptions about the update arrival process than did previous models, as well as inclusion of storage costs for the updates. The optimal checkpointing, batch updating, and reorganization policies are shown to be special cases of this optimal backup policy. The derivation of previous results as special cases of this model, and an example, demonstrate the generality of the methodology developed.

Many database maintenance operations are performed periodically in batches, even in realtime systems. The purpose of this paper is to present a general model for determining the optimal frequency of these batch operations. Specifically, optimal backup, checkpointing, batch updating, and reorganization policies are derived. The approach used exploits inventory parallels by seeking the optimal number of items—rather than a time interval—to trigger a batch. The Renewal Reward Theorem is used to find the average long run costs for backup, recovery, and item storage, per unit time, which is then minimized to find the optimal backup policy. This approach permits far less restrictive assumptions about the update arrival process than did previous models, as well as inclusion of storage costs for the updates. The optimal checkpointing, batch updating, and reorganization policies are shown to be special cases of this optimal backup policy. The derivation of previous results as special cases of this model, and an example, demonstrate the generality of the methodology developed.