Manufacturing Technology Today

S. J. Vaghela ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, IN

Abstract

Weld distortion is one of the important quality measures and due to non-linearity of influencing variables it is difficult to predict its behavior. A three dimensional Thermo Mechanical Finite Element Analysis is proposed to estimate the angular distortion in combined butt and fillet weld joint. Different weld sequences are considered to study their effects on distortion. The geometry is modeled using SYSWELD and simulated using Visual Weld. Temperature dependent material properties and nonlinear stress-strain behavior are considered. Moving heat source is modeled as double ellipsoidal volumetric source. The effect of different sequences on angular distortion is reported.

Keywords

Finite Element Method, Weld Distortion, Gas Metal Arc Welding.

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S. P. Leo Kumar ¹, J. Jerald ¹, S. Kumanan ¹, R. Nargundkar Aniket ¹

Affiliations
1 Department of Production Engineering, National institute of Technology, Tiruchirappalli, IN

Abstract

This paper presents an experimental study on effect of micro end milling process parameters on surface roughness with PMMA (Poly methyl methacrylate) as work piece material. It has wide applications in micro features and micro parts fabrication for automobile, aerospace, biomedical industries. Effect on surface finish during micro end milling on PMMA with 0.7mm carbide end mill tool was analyzed in this work. Response Surface Methodology (RSM) technique used for design of experiments for the factors feed rate and spindle speed. Experiments were carried out using multipurpose micro machine tool. Analysis was carried out with surface roughness value measured using surface roughness tester and inferences were made.

Keywords

Micro End Milling, PMMA, Response Surface Methodology, Surface Roughness.

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S. P. Leo Kumar ¹, J. Jerald ¹, S. Kumanan ¹, Shashank Pansari ¹

Affiliations
1 Dept of Production Engg, National Institute of Technology, Tiruchirappalli, IN

Abstract

This paper presents an experimental study on effect of micro drilling parameters on burr formation in C360 brass. Burr formation during machining is unacceptable in nature. Hence its dominant parameters are studied in this work. Micro drilling with 0.8mm HSS drill on C360 brass was performed. Response Surface Methodology (RSM) is used for design of experiments for the factors such as feed rate and spindle speed and experiments were carried out using multipurpose micro machine tool. Burr formation analysis was carried out using Scanning Electron Microscope (SEM) and inferences were made.

Keywords

Micro Drilling, Burr Formation, Response Surface Methodology, Scanning Electron Microscope.

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C. P. Jesuthanam ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirapalli-620015, IN

Abstract

Surface roughness is an important aspect in evaluating the quality of a machined product and it is influenced by the machining conditions. Conventional surface roughness measuring instruments are of contact type, offline and post processing in nature. Presently there is an increase in the demand for the use of intelligent techniques in manufacturing applications. In this paper a hybrid intelligent technique is presented by combining Radial Basis Function Neural Network (RBFNN) and Fuzzy Logic (FL) for the prediction of surface roughness in turning operations to achieve effective automation. A comparison is made between the use of RBFNN and hybrid RBFNN-FL technique.

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M. Dev Anand ¹, T. Selvaraj ¹, S. Kumanan ¹

Affiliations
1 Dept of Production Engg., National Institute of Technology, Tiruchirappalli, IN

Abstract

A high degree of automation in flexible production units demands powerful tools for supervision and fault detection. This paper outlines recent advances on the theory of model-based fault diagnosis in dynamic systems. Robot manipulator fault detection and diagnosis involves processing of huge information about the robot system. A fuzzy logic based threshold for residual evaluation is suggested here. The proposed fuzzy logic control scheme has been applied to trajectory control of a five-degree of freedom robot manipulator. The proposed method is capable to address unstructured and unknown disturbances. Simulated results are presented in terms of fault detection accuracy and knowledge extraction feasibility.

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C. A. Shajahan ¹, S. Kumanan ¹

Affiliations
1 Dept. of Production Engg., National Institute of Technology, Tiruchirappalli, IN

Abstract

Product developinent is the process of managing activities to bring a new product or service to market that meets customer needs. It involves different set of interrelated dynamic tasks with randomness of duration, uncertainty of interruptions and complexity of iteration. Increased pressure to bring down the 'time to market' of the product, maintaining increased level of customization makes product development process complex. Modeling and simulation proved to be an effective tool in dealing with this kind of problems. This paper proposes the use of 'SIMQUICK' in modeling and simulation of PD process.

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R. Christu Paul ¹, P. Asokan ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engg., National Institute of Technology, Tiruchirappalli-620015, IN

Abstract

The facility layout design problem is concerned with determining the arrangement and configuration of facilities, which optimizes a prescribed objective such as profit, cost, or distance, and which satisfies various prescribed constraints pertaining to available resources. In industry, facility layout design problems arise in manufacturing, in warehousing, and in various assignment type situations. The solution of this problem has impacts on the viability of the industry. For example, using the optimization methods associated with the facility layout design can reduce material-handling costs, which can comprise between 30 and 75% of the total manufacturing costs. This paper is concerned with the application of the Particle Swarm Optimization algorithm to solve the problem of optimal facility layout in manufacturing system design. The general mathematical model available in literature is followed. The production flow data for varying number of products, machines and flow line are adapted for extensive application. The paper considers the different types of material flow patterns for the generalization of proposed method. The effectiveness of Particle Swarm Optimization is evaluated and compared with the benchmarked problems.

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J. Edwin Raja Dhas ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirapalli, IN

Abstract

Submerged Arc Welding (SAW) is a metal joining technique widely used in heavy fabrication industries due to its inherent properties. The welding quality and productivity is controlled by the process parameters. The process planners use different techniques to estimate the influence of the welding parameters (welding current, arc voltage, welding speed and electrode stickout) on bead geometry. This paper discusses about the design of experiments and the development of Multiregression model to predict the weld bead geometry. The developed model determines those variables which will give the desired set of bead geometry (weld bead width, weld reinforcement, weld bead penetration, reinforcement area, and area of penetration and bead dilution).

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P. Udhayakumar ¹, S. Kumanan ¹, P. Asokan ¹

Affiliations
1 Dept. of Production Engg., National Institute of Technology, Tiruchirappalli - 620 015, Tamilnadu, IN

Abstract

Flexible Manufacturing Systems (FMS) that are equipped with several automated machine tools, automated material handling, and automated storage and automated retrieval systems are designed and implemented to gain the flexibility and efficiency of production. Effective sequencing and scheduling of the Material Handling Systems (MHS) can have a major impact on the productivity of the manufacturing system. Automated Guided Vehicles (AGVs) are widely used for material handling in such a manufacturing systems. AGVs are much more flexible than other automated material handling devices such as conveyor systems. When products change or production processes change, the reconfiguration of AGVs is much easier than that of a conveyor system. The objective of this paper is to minimize the total distance travel time of AGV in a network with bi-directional paths. In this context, different dispatching strategies such as First in first serve (FIFS), random call stations are simulated. The random call stations are simulated by using non-traditional optimization technique as Simulated Annealing Algorithm (SAA). The computer simulation algorithm is developed using C language. The outputs of the FIFS system and the random call stations using SAA are compared based on the shortest route and minimum total distance traveled and the results are presented.

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P. Asokan ¹, S. Kumanan ¹, S. Satish Kumar ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, IN

Abstract

The examination of the economics of multi-pass machining operations has significant practical importance. Determination of optimal cutting parameters like the number of passes, depth of cut for each pass, speed and feed is considered as a crucial stage in multi-pass machining. The effective optimization of these parameters affects dramatically the cost and production time of machining components as well as quality of final products. This paper outlines the development of an optimization strategy to determine the optimum cutting parameters. Total production cost model is presented in this paper for multi-pass face milling process. The developed strategy is based on the "minimization of production cost" criterion and incorporates eight technological constraints. The optimal number of passes and optimal values of cutting conditions is determined using Simulated Annealing.

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R. Ravi Kumar ¹, P. Narendar Singh ², P. Asokan ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli-620015, IN
2 Department of Manufacturing Engineering, Annamalai University, Chidambaram-608002, IN

Abstract

This paper deals with the development of mathematical models for electrical discharge machining process (EDM) and also an attempt has been made to optimize the machining parameters of EDM processes. Through hole drilling experiment has been conducted on mild steel and mathematical models are formulated for maximizing the metal removal rate and minimizing the surface roughness. SPSS and 'C' programming have been used to optimize the machining parameters for EDM.

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V. Srinivasa Raman ¹, K. Barathi Raja ¹, P. Asokan ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, IN

Abstract

This paper presents the application of particle swarm optimization (PSO) technique and its variants to gearbox design problem. The gearbox design problem is a highly constrained, multi-objective optimization problem. PSO is one of the swarm intelligence (SI) techniques, which use the group intelligence behavior along with individual intelligence to solve the combinatorial optimization problem. In this work a multi-speed gearbox is designed for the HMT high speed lathe, LB-17, which is available in the Production Engineering Department, National Institute of Technology, Trichy. This work focuses on the design improvement of existing gearbox so as to increase the power output and to reduce the size, using non-traditional optimization techniques. This paper presents particle swarm optimization algorithm for finding the gearbox parameters with reasonable time.

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R. Siva Sankar ¹, P. Asokan ¹, S. Kumanan ¹, T. Selvaraj ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, Tamilnadu - 620 015, IN

Abstract

This paper proposes a new optimization technique based on Adaptive Genetic Algorithm (AGA) to solve multi-pass turning optimization problems. The objective function is to determine machining parameters by minimizing the unit production cost subjected to various practical machining constraints. The proposed Adaptive Genetic Algorithm scheme for optimization of multi-pass turning operation proves p be competent with Genetic Algorithm and Simulated Annealing.

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S. Jagadeesh ¹, S. Kumanan ¹

Affiliations
1 Department of Production Engineering, National Institute of Technology, Tiruchirappalli, IN

Abstract

Cladding is process of coating of low alloy base with high alloy overlay to safeguard the base metal from corrosive fluids and fumes. Conventional ultrasonic testing is used to detect flaws in cladding and to enhance the quality of the product during the manufacturing stage. When the component is put to operation, miniscule flaws could propagate due to high working temperatures and pressures thereby reducing the service life of the product. Process plants and nuclear power plants undergo periodic in-service inspection to verify the integrity of components using NDE technique. Conventional ultrasonic testing is limited in application and Phased array ultrasonic testing (PAUT) as an advanced NDE technique could be a viable alternative. This paper details about the application of PAUT to detect a variety of bonding layer flaws in in-service inspection of cladded components.

Keywords

Cladding, NDE, UT, PAUT.

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A. Andrew ¹, S. Kumanan ¹

Affiliations
1 National Institute of Technology, Tiruchirappalli, Tamilnadu, IN

Abstract

Spares inventory is the key function in maintenance management and is a great challenge to estimate the current quantity with cost effectiveness. Modern manufacturing management invokes artificial intelligent techniques to enable faster and accurate decision making. This paper presents a novel method for machine spares inventory prediction using back propagation neural network. Traditional techniques have shown inadequacy in handling large data and limits the spares inventory prediction. This paper details on a back propagation neural network based spares inventory prediction for welding system. The results of the proposed system show that the developed model will be worth implementing in industries for quick breakdown resolution and for financial savings.

Keywords

Spares Inventory, BPNN, Prediction, Artificial Intelligence, Neural Networks.

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