Machining Process Models for Product and Process Design

1988 ◽  
Author(s):  
J. W. Sutherland ◽  
R. E. DeVor ◽  
S. G. Kapoor ◽  
P. M. Ferreira
2012 ◽  
Vol 271-272 ◽  
pp. 1006-1011
Author(s):  
Neng Wan ◽  
Zhi Yong Chang

To tackle process knowledge discovery difficulty in machining process, this paper studies knowledge discovery method of 2.5–dimensional machining characteristics based on process model with model based definition technology, and finds out machining process design knowledge with the natural structured process description ability of MBD process model. Firstly, the composition of machining geometry ontology and process ontology is analyzed. Secondly, decision tree between ontology are obtained by analyzing abundant samples of MBD process model. Thus, the process and method of reasoning from geometry ontology to process ontology is achieved. Finally, the validity of process knowledge discovery method is exemplified with a group of MBD process models.


Author(s):  
Karl R. Haapala ◽  
Adrian V. Catalina ◽  
Michael L. Johnson ◽  
John W. Sutherland

Growing interest in sustainability is driving manufacturers to improve the environmental performance of their products and processes. The production of steel and steel products consumes materials and energy resources, and creates wastes and emissions. Industry leaders and policy makers have identified iron/steel and metal casting as areas of concern from an environmental perspective. By evaluating steel product manufacturing processes commonly employed in the heavy equipment industry, environmental impacts can be mitigated during product and process design. A process modeling approach that is focused on improving the environmental performance of steel product manufacturing is developed and demonstrated. The process models focus on part production employing electric arc furnace (EAF) steelmaking and sand casting with chemical binders, and relate process energy and material inputs and outputs to product and process design characteristics. The models are based on scientific principles, as well as empirical data reported in the literature. Models of the two processes are applied to assess the production of a representative ground engaging tool (GET) component. It is found that EAF electricity use can be reduced by more than 30% and process-related CO2 emissions by nearly 20% over initial settings. Replacing the polyurethane nobake sand mold binder with a low nitrogen furan binder is predicted to reduce casting emissions by more than 50%, and sulfur dioxide emissions by over 90%. Thus, the models are capable of estimating changes in environmental performance due to modifications in material type, part geometry, and process parameters. This process modeling approach demonstrates improvements in environmental performance for the production of a GET component, and can be extended to assess and compare other steel alloys and components.


2013 ◽  
Vol 770 ◽  
pp. 361-365
Author(s):  
Yu Peng Xin ◽  
Xi Tian Tian ◽  
Li Jiang Huang ◽  
Jun Hao Geng

In order to improve the efficiency of NC machining programming, and realize the rapid establishment of blank model or middle blank model, a geometrical modeling method of process driven by typical process model was put forward. This method is based on the typical process for the establishment of typical process model, to establish a mapping between modeling operation and machining process ontology, and format model mapping rules. In the process geometrical modeling of the high similarity parts, by calling the typical process model mapping rules, can generate process models automatically. A enterprise disc type parts typical process as an example is used to verify the proposed method.


Author(s):  
Jesse D. Peplinski ◽  
Janet K. Allen ◽  
Farrokh Mistree

Abstract How can the manufacturability of different product design alternatives be evaluated efficiently during the early stages of concept exploration? The benefits of such integrated product and manufacturing process design are widely recognized and include faster time to market, reduced development costs and production costs, and increased product quality. To reap these benefits fully, however, one must examine product/process trade-offs and cost/schedule/performance trade-offs in the early stages of design. Evaluating production cost and lead time requires detailed simulation or other analysis packages which 1) would be computationally expensive to run for every alternative, and 2) require detailed information that may or may not be available in these early design stages. Our approach is to generate response surfaces that serve as approximations to the analyses packages and use these approximations to identify robust regions of the design space for further exploration. In this paper we present a method for robust product and process exploration and illustrate this method using a simplified example of a machining center processing a single component. We close by discussing the implications of this work for manufacturing outsourcing, designing robust supplier chains, and ultimately designing the manufacturing enterprise itself.


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