An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Evaluation of an Injection Molding Process Model Using the Calculus of Imprecision to Simultaneously Specify Tolerances and Process Parameters
Published
Author(s)
Ronald Giachetti
Abstract
The strong interrelationship between part geometry, material properties, tolerances, and process parameters for injection molded parts hinders tolerance allocation and process specification. The traditional design process of first optimizing tolerances and then setting process parameters to achieve these tolerances has the potential for sub-optimization. Rather simultaneous tolerance allocation and process specification is required. Unfortunately the injection molding modeling uncertainty hampers optimal tolerance and process specification. Consequently methods are needed for directly incorporating imprecision into these models. This paper advocates the use of imprecise quantities in existing analytical process models to simultaneously allocate tolerances and process specification for minimum manufacturing cost. A set mathematical approach called the Calculus of Imprecision (CoI) is developed to provide a general framework for including imprecision directly in existing process models. The CoI is a refinement of a worst-case interval approach but at various levels of plausibility with a reduced computational load.
concurrent engineering, Design for manufacturing, fuzzy set theory, injection molding, manufacturing process modeling, model uncertainty, optimization, tolerance allocation
Citation
Giachetti, R.
(1997),
Evaluation of an Injection Molding Process Model Using the Calculus of Imprecision to Simultaneously Specify Tolerances and Process Parameters, NIST IR, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822342
(Accessed February 11, 2025)