### Browsing by Author "Yao, Zhiyang"

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Item A Geometric Algorithm for Finding the Largest Milling Cutter(2001) Yao, Zhiyang; Gupta, Satyandra K.; Nau, Dana S.; ISRIn this paper, we describe a new geometric algorithm to determine the largest feasible cutter size for 2-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 an obstruction region. This definition encompasses the task of milling a general 2-D profile that includes both open and closed edges.2. We discuss three alternative definitions of what it means for a cutter to be feasible, and explain which of these definitions 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 that our algorithm is correct.Item A Geometric Algorithm for Finding the Largest Milling Cutter(2000) Yao, Zhiyang; Gupta, Satyandra K.; Nau, Dana S.; ISRIn 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.

Item A Geometric Algorithm for Multi-Part Milling Cutter Selection(2000) Yao, Zhiyang; Gupta, Satyandra K.; Nau, Dana S.; ISRMass 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 The traditional process planning that generates plans for one part at a time is no longer applicable.In this paper, we propose the idea of process planning for small batch manufacturing, i.e., we simultaneously consider multiple parts and exploit opportunities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'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.

Item Selecting Flat End Mills for 2-1/2D Milling Operations(2000) Yao, Zhiyang; Gupta, Satyandra K.; Nau, Dana S.; ISRThe 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'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.