DEVELOPMENT OF AN INTELLIGENT PC-BASED SYSTEM FOR CNC NIBBLING

Abstract

Nibbling, a progressive punching process, uses combinations of standard punches which may be square, rectangular or circular in shape, to create complex 2-D sheet metal parts. Much time is required to select suitable standard punches, compute feeds to achieve the required surface roughness, sequence the selected punches and program the NC codes. To overcome these shortcomings, a PC-based software system has been developed within the AutoCAD environment using AutoLISP and C language to aid the development of process plans. A hybrid nibbling and laser cutting approach is also considered. The system was implemented in three modules. Technical data of the nibbling machine, requirements of the job and information of available punches are managed in Module 1. Geometrical data of the part are also processed in Module 1 and details are presented in Chapter 5. Processed data are used in Module 2 for automatic and manual punch selections. The automatic punch selection algorithm is divided into two stages. In the primary selection, punches are selected based on the geometry, availability of punches and technological rules of a nibbling machine. Square, rectangular, circular, fillet and triangular punches are the five types of standard punches considered. Other types of punches are classified as special punches. In the secondary punch selection, the primary selections are refined based on the selected machine configurations to achieve one tool set-up. Three types of machines considered are: AMADA Pega 375, TRUMPF Laserpress 240 and TRUMPF Rotation 240. The algorithm developed is suitable for other nibbling machines with similar features. Module 2 is discussed h1 detail in Chapter 6. In Module 3, generated tool paths are processed to remove duplicate strokes. They are then sequenced and optimised, followed by simulation and verification by users. Auxiliary information and NC codes can also be generated. Chapter 7 discusses these in details. Chapter 8 presents two case studies to illustrate the algorithms developed. Case I compares three set of different solutions generated for the three different machines mentioned previously. Case II highlights some shortcomings of the program, the method to eliminate such shortcomings and some important features of the developed system.