@article {18812, title = {Algorithms for selecting cutters in multi-part milling problems}, journal = {Computer-Aided Design}, volume = {35}, year = {2003}, month = {2003/08//}, pages = {825 - 839}, abstract = {This paper describes geometric algorithms for automatically selecting an optimal sequence of cutters for machining a set of 2.5-D parts. In milling operations, cutter size affects the machining time significantly. Meanwhile, if the batch size is small, it is also important to shorten the time spent on loading tools into the tool magazine and establishing z-length compensation values. Therefore, in small-batch manufacturing, if we can select a set of milling tools that will produce good machining time on more than one type of parts, then several unnecessary machine-tool reconfiguration operations can be eliminated. In selecting milling cutters we consider both the tool loading time and the machining time and generate solutions that allow us to minimize the total machining time. In this paper we first present algorithms for finding the area that can be cut by a given cutter. Then we describe a graph search formulation for the tool selection problem. Finally, the optimal sequence of cutters is selected by using Dijkstra{\textquoteright}s shortest path planning algorithm.}, keywords = {2.5-D Milling, cutter selection, Geometric Algorithms}, isbn = {0010-4485}, doi = {10.1016/S0010-4485(02)00110-0}, url = {http://www.sciencedirect.com/science/article/pii/S0010448502001100}, author = {Yao,Zhiyang and Gupta, Satyandra K. and Nau, Dana S.} } @article {18800, title = {A Geometric Algorithm for Finding the Largest Milling Cutter}, volume = {ISR; TR 2000-40}, year = {2000}, month = {2000///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {In this paper, we describe a new geometric algorithm to determine the largest feasible cutter size for2-D milling operations to be performed using a single cutter. In particular:

1. We give a general definition of the problem as the task of covering a target region without interfering with anobstruction region. This definition encompasses the task of milling a general 2-D profile that includes bothopen and closed edges.

2. We discuss three alternative definitions of what it means for a cutter to be feasible, and explain which of thesedefinitions is most appropriate for the above problem.

3. We present a geometric algorithm for finding the maximal cutter for 2-D milling operations, and we show thatour algorithm is correct.}, keywords = {algorithms, computational geometry, computer aided manufacturing CAM, cutter selection, Manufacturing, Next-Generation Product Realization Systems, path planning}, url = {http://drum.lib.umd.edu//handle/1903/6137}, author = {Yao,Zhiyang and Gupta, Satyandra K. and Nau, Dana S.} } @article {18801, title = {A Geometric Algorithm for Multi-Part Milling Cutter Selection}, volume = {ISR; TR 2000-42}, year = {2000}, month = {2000///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {Mass customization results in smaller batch sizes in manufacturing that require large numbers of setup and tool changes. The traditional process planning that generates plans for one part at a time is no longer applicable.

In this paper, we propose the idea of process planning for small batch manufacturing, i.e., we simultaneously consider multiple parts and exploit opportunities for sharing manufacturing resources such that the process plan will be optimized over the entire set of parts. In particular, we discuss a geometric algorithm for multiple part cutter selection in 2-1/2D milling operations.

We define the 2-1/2D milling operations as covering the target region without intersecting with the obstruction region. This definition allows us to handle the open edge problem. Based on this definition, we first discuss the lower and upper bond of cutter sizes that are feasible for given parts. Then we introduce the geometric algorithm to find the coverable area for a given cutter. Following that, we discuss the approach of considering cutter loading time and changing time in multiple cutter selection for multiple parts. We represent the cutter selection problem as shortest path problem and use Dijkstra{\textquoteright}s algorithm to solve it. By using this algorithm, a set of cutters is selected to achieve the optimum machining cost for multiple parts.

Our research illustrates the multiple parts process planning approach that is suitable for small batch manufacturing. At the same time, the algorithm given in this paper clarifies the 2-1/2D milling problem and can also help in cutter path planning problem.}, keywords = {algorithms, computer aided manufacturing CAM, cutter selection, Manufacturing, multi-part process planning, Next-Generation Product Realization Systems, OPTIMIZATION}, url = {http://drum.lib.umd.edu//handle/1903/6139}, author = {Yao,Zhiyang and Gupta, Satyandra K. and Nau, Dana S.} } @article {18863, title = {Selecting Flat End Mills for 2-1/2D Milling Operations}, volume = {ISR; TR 2000-41}, year = {2000}, month = {2000///}, institution = {Institute for Systems Research, University of Maryland, College Park}, abstract = {The size of milling cutter significantly affects the machining time. Therefore, in order to perform milling operations efficiently, we need to select a set of milling cutters with optimal sizes. It is difficult for human process planners to select the optimal or near optimal set of milling cutters due to complex geometric interactions among tools size, part shapes, and tool trajectories.

In this paper, we give a geometric algorithm to find the optimal cutters for 2-1/2D milling operations. We define the 2-1/2D milling operations as covering the target region without intersecting with the obstruction region. This definition allows us to handle the open edge problem. Based on this definition, we introduced the offsetting and inverse-offsetting algorithm to find the coverable area for a given cutter. Following that, we represent the cutter selection problem as shortest path problem and discuss the lower and upper bond of cutter sizes that are feasible for given parts. The Dijkstra{\textquoteright}s algorithm is used to solve the problem and thus a set of cutters is selected in order to achieve the optimum machining cost.

We believe the selection of optimum cutter combination can not only save manufacturing time but also help automatic process planning.}, keywords = {algorithms, computer aided manufacturing CAM, cutter selection, Manufacturing, Next-Generation Product Realization Systems}, url = {http://drum.lib.umd.edu//handle/1903/6138}, author = {Yao,Zhiyang and Gupta, Satyandra K. and Nau, Dana S.} }