Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T17:32:02.037Z Has data issue: false hasContentIssue false

Precision machine design assistant: A constraint-based tool for the design and evaluation of precision machine tool concepts

Published online by Cambridge University Press:  01 November 1998

BRADLEY S. HOMANN
Affiliation:
Mechanical Engineering Department, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, U.S.A.
ANNA C. THORNTON
Affiliation:
Mechanical Engineering Department, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, U.S.A.

Abstract

Precision machines are necessary to manufacture parts and subassemblies that require tight tolerances. During the design of precision machines, like any design, it is critical that the best concept is chosen in the early stages of the design process because 80% of the final cost and quality of a product are designed in at this phase. In addition, changes and optimization late in the design process have limited impact on cost and quality. Typically, during the design of precision machines, engineers and skilled machinists develop several machine concepts and down select based on heuristics and past design experience rather than quantitative measures. This paper describes a computation tool, Precision Machine Design Assistant (PMDA), which automates basic machine error simulation and concept evaluation. The tool uses a combination of machine error motion modelling and constraint-based design methods. By combining these methods in a computational environment, multiple machine concepts may be rapidly modeled, analyzed, and compared. The goal of the program is to assist the designer in the selection of a superior concept for detail design. The PMDA methods and implementation are demonstrated in an example.

Type
Research Article
Copyright
1998 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)