Applied Mechanics and Materials Vol. 761

Abstract: Most rapid prototyping models are fabricated by additive manufacturing (AM) devices, which are usually called as 3D-printers. The AM models are expected to be used as practical parts for small batch manufacturing and maintenance parts supply. The main problem of AM for practical parts depends on processing accuracy and productivity. To compete with these problems, the parallel fabrication is considered. In this paper, after the concept of the parallel fabrication is introduced, the geometric accuracy of AM parts is evaluated and discussed from viewpoints of shape and processing. Two primitive shapes, which are a cube and a cylinder, are chosen as evaluation objects. These models are fabricated by two different type AM processing, which are Stereo Lithography (SL) and Fused Deposition Modeling (FDM). The geometry of objects is measured by a contact type 3D measurement system. As a result, characteristics of geometric error, which depend on shape features and AM processing, were found. The design guideline for contact surfaces between segmented parts is discussed.

Abstract: In Line Balancing principles, the total workload in the assembly process is divided as evenly as possible among the workstations, without violating the sequences and relations in the assembly operations. Line balancing is important in an assembly system as it balances the line and increases the efficiency, as well as the productivity of a system. A case study was conducted in the assembly line of an electrical accessories manufacturer in Malaysia. The cycle time for each station was recorded, and the standard cycle time was estimated. The productivity, as well as the efficiency of the current assembly line, were studied. In terms of the productivity, the performance of the current systems was 500 units/worker/day, while the expected productivity was 600 units/worker/day. An assembly line setting was proposed based on the Line Balancing Method; the productivity for the proposed line increased to 671 units/worker/day, or in rough additional increase around 34%.

Abstract: This paper reports a new approach for recognizing objects by using combination of texture, color and shape features. Texture features were generated by applying statistical calculation on the image histogram. Color features were computed by using mean, standard deviation, skewness and kurtosis. Shape features were generated using combination of Shen features and basic shapes such as eccentricity and dispersion. The total features were used much less compared to approaches that involve orthogonal moments such as Krawtchouk moments, Zernike moments, or Tchebichef moments. Testing was done by using a dataset that contains 53 kinds of objects. All objects contained in the dataset were various things that can be found in supermarkets or produced by manufacturing. The result shows that the system gave 98.11% of accuracy rate.

Abstract: Multiple video streaming can be used for many functions and there are two techniques that can be used for streaming. The first is the use of the on-the shelf software which is ready-made and can be downloaded. The second technique is a self-programming technique using open source software. In this paper, both techniques were compared to investigate their capabilities in the manufacturing process. Some experiments were conducted to verify the affordability of the techniques. The focus of comparison for both techniques is to detect the image of real-time motion and generate report of the motion. In this research, the capabilities and differences between the two techniques are also identified.

Abstract: This paper presents a product identification using image processing and radial basis function neural networks. The system identified a specific product based on the shape of the product. An image processing had been applied to the acquired image and the product was recognized using the Radial Basis Function Neural Network (RBFNN). The RBF Neural Networks offer several advantages compared to other neural network architecture such as they can be trained using a fast two-stage training algorithm and the network possesses the property of best approximation. The output of the network can be optimized by setting suitable values of the center and the spread of RBF. In this paper, fixed spread value was used for every cluster. The system can detect all the four products with 100% successful rate using ±0.2 tolerance.

Abstract: Nowadays, the utilization of cameras as an inspection tool has been increasing. The flexibility functions of camera fits to get different kind of information. This research is focusing on developing a robust visual inspection system for corrosion detection that is able to detect corrosion in any environment, and the corrosion detection will be using visual data as primary tools. A review on current pipeline inspection would give a brief detail on the improvement of the proposed inspection system. Furthermore, the inadequacies of the proposed visual corrosion detection are identified and discussed from the reviewing process on existing researches and analysis on preliminary data obtained. It is expected that the output of the proposed system will be a new method of corrosion detection and pioneer for the inspection system on robust environment.

Abstract: . The minimum cost and high productivity of the recent industrial renaissance are its main challengers. Selecting the optimum cutting parameters play a significant role in achieving these aims. Heat generated in the cutting zone area is an important factor affecting workpiece and cutting tool properties. The surface finish quality specifies product success and integrity. In this paper, the temperature generated in the cutting zone (shear zone and chip-tool interface zone) and workpiece surface roughness is optimized using an artificial immune system (AIS) intelligent algorithm. A mild steel type (S45C) workpiece and a tungsten insert cutting tool type (SPG 422) is subjected to dry CNC turning operation are used in experiments. Optimum cutting parameters (cutting velocity, depth of cut, and feed rate) calculated by the (AIS) algorithm are used to obtain the simulated and ideal cutting temperature and surface roughness. An infrared camera type (Flir E60) is used for temperature measurement, and a portable surface roughness device is used for roughness measurement. Experimental results show that the ideal cutting temperature (110°C) and surface roughness (0.49 μm) occur at (0.3 mm) cut depth, (0.06 mm) feed rate, and (60 m/min) cutting velocity. The AIS accuracy rates in finding the ideal cutting temperature and surface roughness are (91.70 %) and (90.37 %) respectively. Analysis shows that the predicted results are close to the experimental ones, indicating that this intelligent system can be used to estimate cutting temperature and surface roughness during the turning operation of mild steel.

Abstract: A two-degree-of-freedom (2-DOF) PID controller is designed for an AC servo ball screw driven XY table. XY table is widely used in manufacturing industry especially in CNC machineries. The most commonly used controller in industries is conventional PID controller. This controller has satisfactory performance, simple structure, and is one-degree-of-freedom (1DOF). Nonetheless, PID controller can only achieve either good set-point response or good disturbance response. This leads to introduction of 2-DOF PID controller which can achieve both good set-point response and disturbance response. In this project, 2-DOF PID is used for accurate tracking purpose. 2-DOF PID controller is designed using two-steps-tuning-method. Disturbance response is optimized by tuning parameters of KP, Ti, and TD using Ziegler-Nichols 2^nd method, followed by optimization of set-point response by tuning of 2-DOF parameters, α and β. Tracking performance of 2-DOF PID controller is compared with conventional PI and 1-DOF PID. Maximum absolute error, sum of absolute error, and mean square error are analyzed for all tracking performance of compensated system. Result shows that tracking error compensation (set-point response) of 1-DOF PID controller is better than 2-DOF PID controller. However, this is due to tuning of α and β parameters in simulation in this project. α and β values should be tuned experimentally. Disturbance response of 1-DOF PID and 2-DOF PID are almost similar due to same KP, Ti, and TD values are used in both controllers.

Abstract: This paper presents the comparison of positioning control between conventional PID controller and fuzzy PID controller. The controllers are applying into the ball screw system driven by DC motor to observe and analyze the change of the positioning output responses. The DC motor is used because it is easy to setup and control, has precise rotation and most importantly is low cost. As for ball screw mechanism itself, has smooth motion, not easy to wear out and high mechanical efficiency. The problem is arise when the used of conventional PID controller in the ball screw system driven by DC motor shows less adaptability to the changes of system parameter. Therefore, the objective of this project is to design an adaptive fuzzy PID controller to overcome the limitation of conventional PID controller. The performances between the conventional PID controller and fuzzy PID controller will be compared in order to validate the robustness of the fuzzy PID controller. So this project is to compare the robustness of two proposed controllers by comparing the results of ball screw table position when the parameter mass of load is set to vary. The experiment is started with designing the algorithms of fuzzy PID control and conventional PID controller, then the designed algorithm is applied onto the experimental that has been setup. The performances especially the transient response and steady state error between the controllers will be collected and compared by conducting the point to point positioning, tracking and variation of load weight experiments.

Abstract: In milling process, the quality of tracking performance is influenced by the characteristics of the cutting forces generated during the material removal process. The undesired frequency harmonics of the cutting force contributes negatively to the positioning accuracy. An effective compensation of these harmonics is desired. This paper presents and discusses a disturbance force observer as an approach to estimate and compensate effect of external disturbance forces on system performance. Knowledge of the properties of the disturbance signal is essential for the design of an observer. A Fast Fourier Transform analysis of the disturbance force reveals the harmonics content of the signal. The frequency harmonics is a function of the spindle rotational speeds. The results show effective compensation of the cutting force with reduced amplitudes of the harmonics frequency content.