Institute for Systems Research

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.

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.

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.

In this paper, we describe our current work towards the integration and enhancement of the capabilities of EDAPS and EXTRA. We integrate EXTRA's functionality with the initial design step of EDAPS. in the resultant system, the user, supported by an enhanced tradeoff analysis capability, can select and describe a promising preliminary design and process plan based on the analysis of a variety of alternatives from both an electrical and mechanical perspective. This preliminary design is then subjected top further analysis and refinement using existing EDAPS capabilities. In addition to the integration of these two systems, specific new functions have been developed, including tradeoff analysis over a much broader set of criteria, and the ability of the tradeoff module to query the process planner to determine costs of individual options.

Given an interpretation of the design as a collection of machinable features, our approach is to generate alternate machining features by making geometric changes to the original features, and add them to the feature set of the original part to create an extended feature set. The designer may provide restrictions on the design indicating the type and extent of modifications allowed on certain faces and volumes, in which case all redesign suggestions generated by our approach honor those restrictions.

By taking combinations of features from the extended feature set generated above, we can generate modified versions of the original design that still satisfy the designer's intent. By considering precedence constraints and approach directions for the machining operations as well as simple fixturability constraints, we can estimate the setup time that will be required for each design. Any modified design whose setup time is less than that of the original design can be presented to the designer as a possible way to modify the original design.

In this paper, we survey of current state of the art in automated manufacturability analysis. We describe the two dominant approaches to automated manufacturability analysis and overview representative systems based on their application domain. Finally, we attempt to expose some of the existing research challenges and future directions.

In this paper, we provide a survey of current state of the art in automated manufacturability analysis. We present the historical context in which this area has emerged and outline characteristics to compare and classify various systems. We describe the two dominant approaches to automated manufacturability analysis and overview representative systems based on their application domain. We describe support tools that enhance the effectiveness of manufacturability analysis systems. Finally, we attempt to expose some of the existing research challenges and future directions.

To achieve any improvement in setup time, first we need to estimate the setup time accurately. In this paper we propose a methodology to estimate the setup time for machining prismatic parts in a three axis vertical machining center. We consider three major factors in estimating the number of setups, namely---the precedence constraints among machining operations, the feasibility of work holding using vise clamping, and the availability of datum faces for locating the workpiece.