Design of fixture elements from the aspect of fixture-workpiece inteface load capacity and compliance

U doktorskoj disertaciji je prikazana nova metodologija za projektovanje i optimizaciju konstrukcije elemenata pribora. Projektovani su i realizovani uređaji koji omogućavaju ispitivanje nosivosti i popustljivosti kontakta između elemenata pribora i radnog predmeta u statičkim i dinamičkim uslovima opterećenja. U istraživanjima je simuliran proces stezanja elementima sa specijalno projektovanim završetkom i praćena je nosivost i popustljivost spoja između elemenata pribora i radnog predmeta. Utvrđeno je da standardni elementi za stezanje sa ravnim čelom u odnosu na specijano projektovane elemente imaju značajno manju nosivost i popustljivost. Pozitivni efekti primene elemenata za stezanje sa specijalno projektovanim završetkom ogledaju se u povećanju pouzdanosti, tačnosti i produktivnosti mašinske obrade.Presented in this doctoral dissertation is a new methodology for the design and optimization of fixture elements. Special device is designed and manufactured to test load capacity and interface compliance between fixture elements and workpiece under static and dynamic loads during machining. The research process is simulated by specially designed clamping elements and monitored for load capacity and interface compliance between fixture elements and workpiece. It was found that the standard clamping elements with flat clamping surface have a significantly lower load capacity and interface compliance in comparison with the specially designed clamping elements. Application of the specially designed clamping elements results in increased reliability, accuracy and machining productivity

Combined Additive Manufacturing and Machining for Large-Scale Prototyping for Minimising Material Wastage

This research project aimed to develop a combined additive and subtractive manufacturing platform capable of rapidly producing large-scale prototypes for minimising material wastage. A design conceptualisation process led to the design and development of a system to deposit the additive material. The developed system was mounted to a large-scale CNC milling machine. This combination of additive and subtractive manufacturing into a single system integrated the separate benefits of the two independent technologies. Mastercam was selected as the preferred CAD/CAM software package to generate toolpaths for the additive and subtractive processes. The Beckhoff HMI provided a user-friendly interface to interpret the generated G-code files, set the Work Coordinate System, and control user-defined parameters such as the feed rate. An in-depth statistical analysis of the developed platform's dimensional accuracy, repeatability, stability, and material wastage was performed. In addition, the effects of the independent adjustment of the subtractive manufacturing process parameters such as the spindle speed, feed rate, depth of cut and stepover distance were considered. Finally, a cycle time comparison was performed in producing a working prototype between the developed HM system and a commercially available 3D printer. This research provided a platform for further investigation into the ever-expanding applications and benefits of rapid prototyping.Thesis (MA) -- Faculty of Engineering, the Built Environment, and Technology, 202

Combined Additive Manufacturing and Machining for Large-Scale Prototyping for Minimising Material Wastage

This research project aimed to develop a combined additive and subtractive manufacturing platform capable of rapidly producing large-scale prototypes for minimising material wastage. A design conceptualisation process led to the design and development of a system to deposit the additive material. The developed system was mounted to a large-scale CNC milling machine. This combination of additive and subtractive manufacturing into a single system integrated the separate benefits of the two independent technologies. Mastercam was selected as the preferred CAD/CAM software package to generate toolpaths for the additive and subtractive processes. The Beckhoff HMI provided a user-friendly interface to interpret the generated G-code files, set the Work Coordinate System, and control user-defined parameters such as the feed rate. An in-depth statistical analysis of the developed platform's dimensional accuracy, repeatability, stability, and material wastage was performed. In addition, the effects of the independent adjustment of the subtractive manufacturing process parameters such as the spindle speed, feed rate, depth of cut and stepover distance were considered. Finally, a cycle time comparison was performed in producing a working prototype between the developed HM system and a commercially available 3D printer. This research provided a platform for further investigation into the ever-expanding applications and benefits of rapid prototyping.Thesis (MA) -- Faculty of Engineering, the Built Environment, and Technology, 202

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Neural Extended Kalman Filter for State Estimation of Automated Guided Vehicle in Manufacturing Environment

To navigate autonomously in a manufacturing environment Automated Guided Vehicle (AGV) needs the ability to infer its pose. This paper presents the implementation of the Extended Kalman Filter (EKF) coupled with a feedforward neural network for the Visual Simultaneous Localization and Mapping (VSLAM). The neural extended Kalman filter (NEKF) is applied on-line to model error between real and estimated robot motion. Implementation of the NEKF is achieved by using mobile robot, an experimental environment and a simple camera. By introducing neural network into the EKF estimation procedure, the quality of performance can be improved

Prediction of Robot Execution Failures Using Neural Networks

In recent years, the industrial robotic systems are designed with abilities to adapt and to learn in a structured or unstructured environment. They are able to predict and to react to the undesirable and uncontrollable disturbances which frequently interfere in mission accomplishment. In order to prevent system failure and/or unwanted robot behaviour, various techniques have been addressed. In this study, a novel approach based on the neural networks (NNs) is employed for prediction of robot execution failures. The training and testing dataset used in the experiment consists of forces and torques memorized immediately after the real robot failed in assignment execution. Two types of networks are utilized in order to find best prediction method - recurrent NNs and feedforward NNs. Moreover, we investigated 24 neural architectures implemented in Matlab software package. The experimental results confirm that this approach can be successfully applied to the failures prediction problem, and that the NNs outperform other artificial intelligence techniques in this domain. To further validate a novel method, real world experiments are conducted on a Khepera II mobile robot in an indoor structured environment. The obtained results for trajectory tracking problem proved usefulness and the applicability of the proposed solution