Smart Machining Simulation Based on High-Level Data

Abstract

The main objective of any machining simulation system is to produce a model that can reveal or mimic the real machining process as accurately as possible. Current simulation systems often use G-code or CL data as input that has inherent drawbacks such as vendor-specific nature, incomplete data, irreversible data conversions and lack of accuracy. These limitations hinder the development of a ‘trustworthy’ simulation system. Hence, there is a need for higher-level input data that can assist with accurate simulation for machining processes. There is also a need to take into account of true behaviour and real-time data of a machine tool. The paper presents a ‘near-real simulation’ solution for more accurate results. STEP-NC is used as the input data as it provides a more complete data model for machining simulations. Data from the machine tool is captured by means of sensors to provide true values for machining simulation purposes. The outcome of the research provides a smart and better informed simulation environment. The paper reviewed some of the current simulation approaches, discussed input data sources for smart simulation system and proposed near-real simulation system architecture.