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Developing a virtual machining model to generate MTConnect machine monitoring data from STEP-NC
Published
Author(s)
Seungjun Shin, Jungyub Woo, Duck B. Kim, FNU Kumaraguru, Sudarsan Rachuri
Abstract
The ability to predict performance of manufacturing equipment during early stages of process planning is vital for improving efficiency of manufacturing processes. In the metal cutting industry, measurement of machining performance is usually carried out by collecting machine monitoring data that record the machine tools actions (e.g., coordinates of axis location and power consumption). Understanding the impacts of process planning decisions is central to the enhancement of the machining performance. However, current methodologies lack the necessary models and tools to predict impacts of process planning decisions on the machining performance. This paper presents the development of a virtual machining model (called STEP2M model) that generates machine monitoring data from process planning data. The STEP2M model adopts STEP-NC and MTConnect standardized interfaces to represent process planning and machine monitoring data. We have developed a prototype system for 2-axis turning operation and validated the system by conducting an experiment using a CNC lathe. The virtual machining model presented in this paper enables process planners to analyze machining performance through virtual measurement and to perform interoperable data communication through standardized interfaces.
Shin, S.
, Woo, J.
, Kim, D.
, Kumaraguru, F.
and Rachuri, S.
(2015),
Developing a virtual machining model to generate MTConnect machine monitoring data from STEP-NC, International Journal of Production Research, [online], https://doi.org/10.1080/00207543.2015.1064182
(Accessed October 18, 2025)