Search

'Laser Beam Welding (LBW) is a welding technique used to join pieces of metal or thermoplastics with the aid of laser'. The beam offers a concerted heat source, which enabled higher, deeper welds and narrower welding rates. The procedure is commonly exploited in higher volume appliances using mechanization. It is dependent on penetration or keyhole mode welding. This paper intends to design a novel prediction model on LBW using the Optimized Neural Network (NN) framework. The input to the optimized NN is the welding properties like 'Laser power, welding speed, offset, shielding gas, flow/pressure, focal distance and frequency (where power, speed and offset gets varied)' that directly predict the hardness and tensile strength of welds since the NN is already trained with the provided data. In order to make the prediction model more accurate, this paper aims to train the NN using a new improved Trial Integer-based Whale Optimization Algorithm (TI-WOA) via updating the weight. Finally, the betterment of the suggested scheme is validated with respect to error analysis. Accordingly, from the analysis, it is observed that the proposed methods are 50%, 13.33%, 6.67% and 4% better than ANN-BP, RBF, ANN-GA and NN-WOA models, respectively, at 70th learning percentage. [ABSTRACT FROM AUTHOR]

Electron beam welding plays an important role in joining dissimilar metals. This paper describes a numerical method to find the temperature distribution in dissimilar metals during Electron Beam Welding. Copper and SS304 are considered as dissimilar metals for this study. When the high beam of electrons hits the metals, heat transfer is accomplished by a phase change due to the heat absorption in the active zone and thus the metals melts. A moving interface exists as a function of time which separates two regions of different properties. Due to the difference in physical properties of both copper and stainless steel the distribution of temperature varies in both the metal. Numerical calculations have been done to find the temperature travelled in both metals when a moving heat source acts on it. [ABSTRACT FROM AUTHOR]

Byline: M. Dev Anand, T. Selvaraj, S. Kumanan, T. Ajitha Fault tolerance is increasingly important in industrial robots. The ability to detect and tolerate failures allows robots to effectively cope with internal failures and continue performing designated tasks without the need for immediate human intervention. To tolerate hardware failures, a set of fault tolerance algorithms are written for each component. These processes are responsible for detecting faults in their respective component and minimising the impact of the failure on the robot's performance. This work presents new intelligent neuro-fuzzy fault detection algorithms, which detect failures in robot components using analytical redundancy relations. An intelligent fault tolerance framework is proposed in which a fault component database or rule base and the detection algorithms work together to detect and tolerate sensor or motor failures in a robot system. Motor faults as well as sensor faults are considered. The Scorbot ER 5u plus model was simulated in robotics toolbox for MATLAB using the neuro-fuzzy algorithms.

Byline: M. Dev Anand, T. Selvaraj, S. Kumanan, J. Janarthanan The adoption of an efficient online Fault Detection and Isolation (FDI) tool is becoming utmost importance for robots, especially for those operating in remote or hazardous environments, where a high degree of safety and self-diagnostics capabilities are required. This saves time and cost in repairing the robot. A number of researchers have proposed Fault Diagnosis (FD) architectures for robotic manipulators using the model-based analytical and redundancy approach. One of the main issues in the design of fault detection system is to model the rigid link robotic manipulators with modelling uncertainties. In this paper, a new approach neuro fuzzy-based FDI for robot manipulators is discussed. A learning architecture, with neural network as online approximates the off-nominal system behaviour, which is used for monitoring the robotic system for the faults. This generates the residual by comparing the actual output from robot. Fuzzy inference system is applied to identify and isolate the faults which provide the adaptive threshold under the varying conditions. The concepts discussed were validated through simulation study using a Scorbot-ER 5 plus manipulator to illustrate the ability of the neuro fuzzy-based FD scheme to detect and isolate fault. Although a robotic manipulator is used to illustrate the effectiveness of this approach, it can also be applied to the non-linear systems.

Byline: M. Dev Anand, T. Selvaraj, S. Kumanan, M. Austin Johnny Selection of a robotic system is an important task for the dynamic scenario. Improper selection may adversely affect a firm's production by reducing the quality of the product, thereby reducing productivity as well as profitability. In order to select a suitable robotic system for a specified job, several factors have to be considered. Investment decisions for robotic system are capital intensive and are usually made by a committee of experts from different functional backgrounds within a company. Ignoring this factor, most models for robot or robotic system selection assume that there is only a single decision maker. This paper discuss, a robotic system selection model incorporating the inputs from multiple decision makers. This model is based on the Fuzzy Analytic Hierarchy Process (FAHP) method and both the subjective and objective criteria for robotics system selection are used. It does not assume the consensus of the decision makers; that is, they may not agree on evaluations of the system with respect to each of the criteria. The objective of this work is to explain how, the FAHP model is used in the selection of robotics system. Some technical requirement factors also have been considered for the case study.

The objective of this work is to find out the stress intensity and load confrontation of the axially cracked ASME pressure vessels so that the condition of the vessel will be branded how much more the life of the vessel wall would come if the crack is generated during operating conditions. The background of this work is based on the failures often occurring in the oil, gas and chemical plant industries. Process equipments are having its own standard design procedures and operating life's according to its material properties. Some of the equipments need frequent refurbishment as well as proper maintenance during operations due to the various working conditions. The code practices that process equipments need to be designed for time span of 20 to 25 years. However failures occurring during operations are unpredictable but it is diagnosable. It may be due to various reasons such as malfunctioning of components and wrong operations. In this paper the work is such that if the crack is generated axially inside due to load or corrosion, how much more operation the vessel would sustain. If the cracks grow continuously due to frequent loads how long the un-cracked thicknesses would withstand the internal pressure loads. ASME based designed pressure vessel has been considered for this study. The typical pressure vessel crack has been modeled internally in axial directions. The operating load has been applied and the behavior of cracks and its load confrontations were simulated using finite element technology and the results were presented. [ABSTRACT FROM AUTHOR]

Closure used to close and open the pressure vessel comes in special type of vessels instead of the fixed dish heads. This type of vessel design purely depends on the process and maintenance requirements. Closures may be in different thicknesses, dimensions and materials according to the requirements. The design of closure in the vessel head area is subjected to mechanical and hydrostatic loads. Need of this work accounts to the often failures of closures in the oil, gas, natural chemical product production industries due to the insufficient design, over pressure loading during hydro test and over mechanical loading during operation. Estimates of fatigue and brinelling were obtained from the finite element analysis from the range of work hardening plasticity. Comparisons were made with the outputs taken from the finite element analysis for the range of loading conditions, vessel and closure geometry and its shape. Generally it is found that although there are significant variations between the different finite element solutions, satisfactory estimates of fatigue and brinelling that are most conservative are obtained when the reference stress produced is adopted. In this paper the evaluation of fatigue and brinelling for 300 Liter High Strength Steel TYPE-17-4PH pressure vessel closure with locking ring is discussed. The reasons for the failures were studied. New design methodology and recommendations are suggested based on the analysis with respect to the requirements of ASME. [ABSTRACT FROM AUTHOR]