A Bending-Machining Hybrid Process for Angular Dimensional Accuracy Enhancement

Bending is a fundamental manufacturing process to form sheet metals into intended angular geometries. Although the process has been extensively studied, predicting its accuracy is still challenging due to the Springback phenomenon inherent to the process. This research intends to combine bending and machining processes to improve bent workpiece angular dimensional accuracy. A minimum enclosing CAD model is first obtained by determining optimum thickness from the bend part CAD model to accommodate the estimated Springback in order to guide the selection of blank workpiece dimension for this bending/machining strategy. Then the machining areas are determined and the cutting forces are predicted to estimate the deformation in the machining process. Toolpath is planned on the surface profile considering both the cutter deflection and the incurred workpiece deformation during machining. This project aims to produce a bending part with the desired dimensional accuracy through a hybrid manufacturing approach. More importantly, it also provides a technological foundation to prototype angled parts at a low cost by avoiding high expenses in making new die.

THE DESIGN AND DEVELOPMENT OF G-CODE CHECKER AND CUTTING SIMULATOR FOR CNC TURNING

CNC machines have become popular in the manufacturing sector in the last three decades. It is still expensive to afford all aspects related to the operations of these machines. One important aspect is the programming stage, which requires a skilful programmer and an appropriate programming media. Hiring a good programmer is not the cheap and the best solution, while having a commercial programming media is also not affordable for SME in Indonesia. This research is focusing on the design and development of a program checker to see whether the program for a CNC turning machine is correct and ready to be fed to the machine. At once, this program is also capable of displaying cutting simulation of how the product is to be cut in the machine. Therefore, this program will help a small manufacturing company to avoid hiring an expensive expert or buying special programming media. This program is specifically developed for a CNC Okuma Howa ACT 3 turning machine. Some results show that the program can easily point out error location if there is a logical or syntax error in the NC program. Moreover, the simulation can be executed only if all errors have been corrected. This feature ensures that the simulation can run properly. To run the simulation, one has to set up some variables such as workpiece dimension, tool position with respect to the machine, and cutter dimension.

Intelligent Error Compensation in CNC Machining through Synergistic Interactions Among Modeling, Sensing and Learning

Industry is looking for practical means to improve the accuracy of the parts machined on CNC machines. Some artificial intelligence (AI) systems have been applied in modeling and compensating manufacturing process errors in CNC machining. However, these systems are not capable of predicting the results of a new operation if no sufficient data on a number of similar operations is available. A generalized AI approach named synergistic interactions amongst modeling, sensing and learning is proposed in this paper. Based on the AI approach, a new strategy of error compensation of workpiece dimension in CNC machining is developed and applied in a CNC turning center. Error compensation results are illustrated the effectiveness of the error compensation strategy. The learning curve shows that the error compensation confidence gradually progresses towards 100% confidence from zero along with the CNC machine operation time increasing.