Xianzhi Zhang

A meta-model of computer numerical controlled part programming languages

Over the last 50 years, the development of computer numerical controlled machines has seen a plethora of part programming languages being developed. The large majority of these languages are based on the ISO 6983 standard which is commonly known as G&M codes, but other languages from machine tool suppliers are also used for programming machine tools. These programming languages have provided major barriers for the interoperability of such information between computer numerical controlled machines and also from computer numerical controlled machines to computer-aided systems. Thus, the process knowledge in existing part programs cannot be recycled and reused easily, due to an inability to interpret these forms of data. In this article, a new meta-model of computer numerical controlled part programming languages has been proposed. The meta-model aims to abstract the characteristics of computer numerical controlled machine activities and interpret/represent process information within computer numerical controlled part programs written in different languages or dialects. Realising the translation between the meta-model and different part programming languages, it is possible to capture the shopfloor knowledge from computer numerical controlled machines without the need to develop individual interpreting interfaces for each programming language. The valuable process knowledge can thus be captured from the part programs and represented in a neutral presentation to facilitate the knowledge accumulation and management, which is vital for manufacturing companies to gain competitive advantages in the globalised market.

Development of a data model and a prototype information sharing platform for DEMAT machine tools

The design of typical CNC machine tools has remained relatively static over the last thirty years, and gradual improvements can be classified as being evolutionary. The emerging concept of a dematerialised CNC machine tool extenuates from the need to reduce machine tool raw material use in terms of mass by up to 60%. An important requirement for this concept is a detailed catalogue of machine tool parts that links individual components, their attributes and functionalities to ensure that all mass in a machine tool adds value. This article describes DEMAT machine tools and presents research pertaining to the development of a data model and a novel information-sharing platform (ISP) that supports and enables the design of a dematerialised machine tool. It provides a unique approach to design and life cycle monitoring of machines. An experimental software system has been developed using UML machine tool data models implemented as Java classes, and an SQL database is used to store machine tool component data. The database has been populated with typical machine tool components to demonstrate the functionality of the prototype ISP, when developing DEMAT machine tools.

Computer numerical control machine tool information reusability within virtual machining systems

Virtual machining 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 virtual machining environment, and there is a plethora of commercial virtual machining 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 the 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 article reviews current research trends in the domain of virtual machining and also discusses how much of this research has been taken on board by software vendors in order to facilitate machine tool information reusability. The authors present use cases which utilise the novel concept of machining capability profile 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 machining capability profiles, as opposed to remodelling and/or reconfiguring of this information multiple times for different scenarios. This article has shown through the use cases that machining capability profiles 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.

Positioning variation modeling for aircraft panels assembly based on elastic deformation theory

Dimensional variation in aircraft panel assembly is one of the most critical issues that affect the aerodynamic performance of aircraft, due to elastic deformation of parts during the positioning and clamping process. This article proposes an assembly deformation prediction model and a variation propagation model to predict the assembly variation of aircraft panels, and it derives consecutive three-dimensional deformation expressions which explicitly describe the nonlinear behavior of physical interaction occurring in compliant components assembly. An assembly deformation prediction model is derived from equations of statics of elastic beam to calculate the elastic deformation of panel component resulted from positioning error and clamping force. A variation propagation model is used to describe the relationship between local variations and overall assembly variations. Assembly variations of aircraft panels due to positioning error are obtained by solving differential equations of statics and operating spatial transformations of the coordinate. The calculated results show a good prediction of variation in the experiment. The proposed method provides a better understanding of the panel assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.