Flexible Tools for Specifying Design Variation

This paper describes flexible tools for specifying design variations that are based on nonuniform profile tolerance definitions. These tools specify bounds of design performance that can be used for negotiation among engineers in a collaborative design process. These specification methods allow for the capture of many different design functions that are not easily described with current tool designs. In addition, these specification methods lend themselves to efficient verification methods. Profile tolerance definitions provide the most general variation controls for complex mechanical surfaces. Common design practices and engineering standards for profile tolerances exhibit many weaknesses and limitations. We present a rationale for a complete specification approach using B-splines [1, 2] for profile tolerances, and illustrate the approach with examples. B-splines can be used to specify both uniform and nonuniform profile tolerance boundaries. Subsequently, algorithms for the evaluation of actual feature deviations and reporting methodologies for such tolerance zones are presented

Evolutionary Algorithm for the Placement of Fluid Power Valves on a Valve Stand

The choice of placement of fluid power valves on a valve stand and routing by pipes has an impact on operational costs. Choosing the right placement that provides optimum routing configuration or determining the optimum routing for a chosen placement are both computationally hard problems. An evolutionary algorithm (EA), to minimize operational costs while optimizing placement and routing of valves, is developed here. The best practices in the industry are abstracted and implemented in the EA. In this paper, the algorithm and its performance for examples with varying complexities are presented. Our results meet or exceed experienced designers’ solutions

Evolutionary Algorithm for the Placement of Fluid Power Valves on a Valve Stand

The choice of placement of fluid power valves on a valve stand and routing by pipes has an impact on operational costs. Choosing the right placement that provides optimum routing configuration or determining the optimum routing for a chosen placement are both computationally hard problems. An evolutionary algorithm (EA), to minimize operational costs while optimizing placement and routing of valves, is developed here. The best practices in the industry are abstracted and implemented in the EA. In this paper, the algorithm and its performance for examples with varying complexities are presented. Our results meet or exceed experienced designers’ solutions