A Unifying Framework Previous:

A Unifying Framework

Introduction

In this work we address the problem of recovering manufacturing tolerances and deformations from the uncertainty in sensing machine parts. In particular, we utilize the sensor uncertainty to recover robust models of machine parts, based on the probabilistic measurements recovered, for inspection applications. We design and implement a spline-based model that captures manufacturing tolerancing based on uncertain sensed data and knowledge of possible manufacturing process plans.

We design and implement our sensing strategies and tolerance determination algorithms based on interval splines. We believe this is the best way to define a unifying framework, as it captures both parameterizable manufacturing tolerancing errors, and non-easily-parameterizable ones (toolpaths that produce a surface definition, for example). This method is also suitable for our purposes as our CAD modeler (The Alpha_1system, designed at the University of Utah) is based on spline representation, and it is used to produce process plans and toolpaths for NC milling machines to manufacture the actual parts from CAD models. Our tolerancing method captures the mechanical way in which the manufacturing tool moves and actually makes a feature, surface or curve in a manufacturing process.

The standard representations for Computer Aided Design include volumetric, boundary and CSG models. Current advanced modelers, can produce process plans for specific machines in order to manufacture the object. We believe that the process plan and associated information (e.g., the tool path, the tool to be used, its speed, etc.) provide a strong basis for analyzing the manufacturing and inspection steps with respect to tolerances.

A tolerance specification on the shape geometry must be transformed into the corresponding tolerance on the machining operation and vice versa. This in turn can be used to select an appropriate manufacturing process, given knowledge of the manufacturing accuracy of the process. This yields direct methods for deciding on sensing strategies both to monitor the manufacture of the part, as well as for post-manufacturing inspection. These sensing strategies are derived from an analysis of where the toolpath is most likely to deviate from the tolerance specification.

These must all be done as efficiently as possible; in particular, it must be:

• straightforward to choose the cheapest manufacturing process, to go as fast as possible on that machine,
• to make as few sensed measurements as possible, and
• to perform as little computation as possible.

The keys to our approach are:

• have/use knowledge about each feature and machining process for that feature, and
• exploit the tool path representation to guide analysis and sensing strategies.

The usual approach to validation is to simply measure the geometry resulting from the manufacturing process and compare it to the nominal geometry from the CAD model. We believe that a stronger approach, exploiting knowledge of the process plan and the particular manufacturing process, is possible, and that this approach permits the automatic synthesis of sensing strategies.

To achieve this requires a tolerance specification which:

• specifies design geometry tolerance as well as toolpath tolerances, and

• helps locate high payoff (i.e., maximal information gain) inspection regions.

We are working with the Alpha_1Computer Aided Geometric Design system and exploiting its ability to generate process plans for 3 and 5-axis NC milling machines. For these machines, the process is a set of toolpaths with appropriate tools, speeds, etc., specified. Thus, a sensing strategy is a set of sensing operations carried out at particularly high risk parts of the toolpath or places on the completed part.

A Unifying Framework Previous:

A Unifying Framework