@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 The traditional process planning that generates plans for one part at a time is no longer applicable.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.} }