Allen G Jackson

US Patent:

6643628, Nov 4, 2003

Filed:

Jul 14, 1999

Appl. No.:

09/353697

Inventors:

Allen G. Jackson - Kettering OH
Mark D. Benedict - Worthington OH
Steven R. LeClair - Springboro OH

Assignee:

The United States of America as represented by the Secretary of the Air Force - Washington DC

International Classification:

G06F 1518

US Classification:

706 25

Abstract:

A cellular automata neural network method for process modeling of film-substrate interactions utilizes a cellular automaton system having variable rules for each cell. The variable rules describe a state change algorithm for atoms or other objects near a substrate. The state change algorithm is used to create a training set of solutions for training a neural network. The cellular automaton system is run to model the film-substrate interactions with the neural network providing the state change solutions in place of the more computationally complex state change algorithm to achieve real-time or near real-time simulations.

US Patent:

54853907, Jan 16, 1996

Filed:

Nov 30, 1993

Appl. No.:

8/159968

Inventors:

Steven R. LeClair - Spring Valley OH
Timothy E. Westhoven - Huntington Beach CA
Hilmi N. Al-Kamhawi - Columbus OH
C. L. Philip Chen - Kettering OH
Allen G. Jackson - Kettering OH
Adel C. Chemaly - Cincinnati OH

Assignee:

The United States of America as represented by the Secrectary of the Air
Force - Washington DC

International Classification:

G06F 1900

US Classification:

36447424

Abstract:

In the design of the process to machine discrete mechanical parts, the sequence of removing material is arrived at to ensure that the resulting part is of the correct geometry and finish, and the process is safe, feasible and accomplished in minimum time. For complex parts, an experienced machinist makes use of inductive methods to relate similar part material, geometries together with interdependencies and their associated machining sequences which have produced quality parts in the past with minimum time expended, or deductive methods to generate a sequence by relating feature attributes (relative size and position) and relations (intersections and common tooling). Of interest is the interaction between the two methods because their coupling enables a self-improving design system to be realized. A feature-based solid modelling software environment provides the elements of a symbolic language for describing a discrete mechanical part in terms of its product and process design. The language is based on the use of features which the designer and/or machinist uses to associate and reason about the part and interaction between the machine, tool, fixture and starting raw stock for the various process design options involving the milling and drilling sequence for removing material.