No abstract

No abstract

A broadly applicable approach for numerical analysis of the kinematic working capability of mechanisms is presented. Composite workspaces are introduced to represent position and orientation capabilities of mechanisms, both individually and together. Numerical methods for solving systems of kinematic constraint equations, using a moving-frame algorithm and equations that characterize the workspace boundary are developed. Two analytic methodologies, comparison and incorporation methods, are presented to determine whether the workspace of a mechanism satisfies design requirements. An experimental computer program for workspace analysis that incorporates a numerical solver and computer graphics for visualization on a high speed graphics workstation is outlined. The feasible positioning space of a Stewart platform that is subject to orientation constraints is computed, to illustrate the use of this approach.

A general approach to numerical analysis of the kinematic dexterity of mechanisms is presented. Dextrous workspace problems are first defined and illustrated with examples. Composite workspaces are introduced to characterize both positioning and orienting capabilities of mechanisms. A numerical formulation and computer implementation that incorporates computer graphics and a numerical algorithm for solving systems of nonlinear equations are presented. Using the composite workspace formulation and the computer implementation, numerical techniques for dextrous workspace analysis are presented. Examples are given to illustrate the techniques developed.

No abstract

In this paper, an online grey forecasting run-to-run control system was proposed with the integration of run-to-run control system, recursive least-squares (RLS) algorithm, and grey forecasting model (GFM). One of the objectives of this study is to explore the possibility and feasibility of applying GFM to run-to-run control system in copper chemical mechanical polishing. Under the condition of limited experiment data, GFM is excellent at estimating and forecasting error of the next batch online. To keep the process under control, the controllers are then employed to adjust the process parameters in order to compensate the error. In addition, the RLS algorithm is used to construct dynamically a system estimation matrix for the purpose of stating precisely the relationship between process quality and process parameters, and to consequently improve processing performances. From the computer simulation and the experiment results, the proposed new method developed in this study was able not only to confine the processing performances' error within the range of 5% but also to supplement, when the process parameters are saturated, the control capability through adjusting other unsaturated process parameters, thus maintaining good processing performances

No abstract

No abstract