Simulating a virtual machining model in an agent-based model for advanced analytics

Abstract

Monitoring the performance of manufacturing equipment is critical to ensure the efficiency of manufacturing processes. Machine-monitoring data allows measuring manufacturing equipment efficiency. However, acquiring real and useful machine-monitoring data is expensive and time consuming. An alternative method of getting data is to generate machine-monitoring data using simulation. The simulation data mimic operations and operational failure. In addition, the data can also be used to fill in real data sets with missing values from real-time data collection. The mimicking of real manufacturing systems in computer-based systems is called “virtual manufacturing”. The computer-based systems execute the manufacturing system models that represent real manufacturing systems. In this paper, we introduce a virtual machining model of milling operations. We developed a prototype virtual machining model that represents 3-axis milling operations. This model is a digital mock-up of a real milling machine; it can generate machine-monitoring data from a process plan. The prototype model provides energy consumption data based on physics-based equations. The model uses the standard interfaces of Step-compliant data interface for Numeric Controls (STEP-NC) and MTConnect to represent process plan and machine-monitoring data, respectively. With machine-monitoring data for a given process plan, manufacturing engineers can anticipate the impact of a modification in their actual manufacturing systems. This paper describes also how the virtual machining model is integrated into an agent-based model in a simulation environment. While facilitating the use of the virtual machining model, the agent-based model also contributes to the generation of more complex manufacturing system models, such as a virtual shop-floor model. The paper describes initial building steps towards a shop-floor model. Aggregating the data generated during the execution of a virtual shop-floor model allows one to take advantage of data analytics techniques to predict performance at the shop-floor level.

From data to big data in production research: the past and future trends

“…The data collected from production systems can be used as input to process activity models, including virtual models (Lechevalier et al 2017). Experiments with different inputs produce new data for further analysis.…”

Method of Mechanical Fault Diagnosis Under Deep Automatic Encoder Under Support Vector Machine

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Augmented reality in support of intelligent manufacturing – A systematic literature review

“…Within a manufacturing environment, SCADA tasks can be enhanced through AR to, e.g. show real-time virtual copies and simulations (Lechevalier et al 2017)of the physical system (Soete et al 2015), or to preview the outcome of a machining operation during the process (Novak-Marcincin et al 2014) and display relevant production data live on the factory floor (Rechowicz and Garcia 2016). Liu and Cao et al (2017) used AR to simulate and monitor the process by utilising real-time information from a milling machine.…”