Virtual Machining (VM) allows simulation of the machining process by realistically representing kinematic, static and dynamic behaviour of the intended machine tools. Using this method, manufacturing related issues can be brought to light and corrected before the product is physically manufactured. Machining systems utilised in the manufacturing processes are represented in the VM environment and there is a plethora of commercial VM software used in the industry. Each software system has a different focus and approach towards virtual machining; more than one system may be needed to complete machining verification. Thus, the significant increase in the use of virtual machining systems in industry has increased the need for information reusability. Substantial time and money has been put into the research of virtual machining systems. However, very little of this research has been deployed within industrial best practice and its acceptance by the end user remains unclear. This paper reviews current research trends in the domain of VM and also discusses how much of this research has been taken on board by software venders in order to facilitate machine tool information reusability. The authors present a use cases which utilises the novel concept of Machining Capability Profile (MCP) and the emerging STEP-NC compliant process planning framework for resource allocation. The use cases clearly demonstrate the benefits of using a neutral file format for representing MCPs, as opposed to remodelling and or reconfiguring of this information multiple times for different scenarios. The paper has shown through the use cases that MCPs are critical for representing recourse information from a kinematic, static and dynamic perspective that commercial software vendors can subsequently use. The impact of this on mainstream manufacturing industry is potentially significant as it will enable a true realisation of interoperability.
|Journal||Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture|
|Early online date||17 May 2017|
|Publication status||Published - 1 Mar 2018|