Modeling manufacturing process variation for design and test

2011 ◽  
Author(s):  
S Kundu ◽  
A Sreedhar
Keyword(s):  
Manufacturing Process ◽  
Process Variation

Quantifying Design and Manufacturing Robustness Through Stochastic Optimization Techniques

1996 ◽  
Author(s):  
David Kazmer ◽  
Philip Barkan ◽  
Kosuke Ishii
Keyword(s):  
Manufacturing Process ◽  
Process Variation ◽  
Optimization Techniques ◽  
Design Stage ◽  
Tool Geometry ◽  
Detailed Design ◽  
Process Dynamics ◽  
Molded Parts ◽  
Industry Practice ◽  
End Use

Abstract Critical design decisions are often made during the detailed design stage assuming known material and process behavior. However, in net shape manufacturing processes such as stamping, injection molding, and metals casting, the final part properties depend upon the specific tool geometry, material properties, and process dynamics encountered during production. As such, the end-use performance can not be accurately known in the detailed design stage. Moreover, slight random variations during manufacture can inadvertently result in inferior or unacceptable product performance and reduced production yields. These characteristics make it difficult for the designer to select the tooling, material, and processing details which will deliver the desired functional properties, let alone achieve a robust design which is tolerant to process variation. This paper describes a methodology for assessing the design/manufacturing robustness of candidate designs at the detailed design stage. In the design evaluation, the fundamental sources of variation are explicitly modeled and the effects conveyed through the manufacturing process to predict the distribution of end-use part properties. This is accomplished by utilizing optimization of manufacturing process variables within Monte Carlo simulation of stochastic process variation, which effectively parallels the industry practice of tuning and optimizing the process once the tool reaches the production floor. The resulting estimates can be used to evaluate the robustness of the candidate design relative to the product requirements and provide guidance for design and process modifications before tool steel is cut, as demonstrated by the application of the methodology for dimensional control of injection molded parts.

Accuracy of Additive Manufactured Parts

2015 ◽  
Vol 661 ◽  
pp. 113-118 ◽  
Author(s):  
Thomas Rainer Neitzert
Keyword(s):  
Heat Transfer ◽  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Process Variation ◽  
Constant Volume ◽  
Manufacturing Processes ◽  
Important Criterion ◽  
Machine Material ◽  
The Future ◽  
Build Environment

Additive manufacturing processes and materials are described with respect to their ability to generate finished products. The accuracy of produced parts is seen as an important criterion for this technology to compete with subtractive or constant volume technologies. From the existing literature can be concluded process variation is high and part accuracy is not better then IT grade 9. The manufacturing process itself is complex and dependent on a number of machine, material and geometry parameters. A better understanding of the heat transfer within the product build environment will assist in the future to improve the process and therefore the resulting parts’ accuracy.

Identifying groups of airborne particles by ordination

1994 ◽  
Vol 52 ◽  
pp. 856-857
Author(s):  
M. Shlepr ◽  
C. M. Vicroy
Keyword(s):  
Elemental Analysis ◽  
Energy Dispersive Spectroscopy ◽  
Manufacturing Process ◽  
Spatial Representation ◽  
Airborne Particles ◽  
Common Source ◽  
Data Set ◽  
Microelectronics Industry ◽  
Induced Changes ◽  
Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

Sign in / Sign up

Export Citation Format

Share Document