Tolerance Specification Across Sensing, Design, and Manufacturing



Faculty


A Consistent Framework for Tolerance Specification Across Sensing, Design, and Manufacturing

In this project we address the problem of tolerance representation and analysis across the domains of industrial inspection using sensed data, CAD design, and manufacturing. Instead of using geometric primitives in CAD models to define and represent tolerances, we propose the use of stronger methods that are completely based on the manufacturing knowledge for the objects to be inspected. We guide our sensing strategies based on the manufacturing process plans for the parts that are to be inspected and define, compute, and analyze the tolerances of the parts based on the uncertainty in the sensed data along the different toolpaths of the sensed part. We believe that our new approach is the best way to unify tolerances across sensing, CAD, and CAM, as it captures the manufacturing knowledge of the parts to be inspected, as opposed to just CAD geometric representations.

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_1 system, 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:

The keys to our approach are:

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:

We are working with the Alpha_1 Computer 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.


Selected Publications:

Books and Book Chapters:

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T. M. Sobh, ``Techniques in Reverse Engineering of Machined Parts in Manufacturing Systems,'' in Computer Aided and Integrated Manufacturing Systems Techniques and Applications. Gordon and Breach International Series in Engineering, Technology and Applied Science, to appear in 1997.


Journal Papers

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T. M. Sobh, X. Zhu, and B. Bruderlin, ``Analysis of Tolerance for Manufacturing Geometric Objects from Sensed Data'', Accepted for publicaton in Applied Mathematics and Computer Science, October 1995, In the Journal of Intelligent and Robotic Systems, 30: 143-153, 2001.

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T. M. Sobh, T. C. Henderson, and F. Zana, ``A Consistent Framework for Tolerance Specification across Sensing, Design, and Manufacturing.'' Under Revision, IEEE Transactions on Robotics and Automation.


Conference Papers

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M. Dekhil and T. M. Sobh, ``Embedded Tolerance Analysis for Sonar Sensors.'' Invited paper to the special session of the 1997 Measurement Science Conference: Measuring Sensed Data for Robotics and Automation, Pasadena, California, January 1997.

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T. M. Sobh, T. C. Henderson, and F. Zana, ``A Unifying Framework for Tolerance Analysis in Sensing, Design, and Manufacturing''. In proceedings of the IEEE International Conference on Robotics and Automation, Nagoya, Japan, May 1995.

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T. C. Henderson, T. M. Sobh, F. Zana, B. Bruderlin, and C. Hsu, ``Sensing Strategies Based on Manufacturing Knowledge'', In Proceedings of the ARPA Image Understanding Workshop, September 1994.


Technical Reports

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T. M. Sobh, ``Tolerance Analysis for Sensing, Design, and Manufacturing,'' Technical Report UBCSE-96-004, Department of Computer Science and Engineering, University of Bridgeport, November 1996.






sobh@bridgeport.edu