Search results

The purpose of this study is to examine the postprocessed wire tool surface using scanning electron microscopy and find out the streamlined conditions of input process variables using multi-objective optimization techniques to get minimum wire wear values.

A federated mode of response surface methodology (RSM) and artificial neural network (ANN) is used to optimize the process variables during the machining of a nickel-based superalloy.

The study explores that with the rise in spark-off time and spark gap voltage, the rate of wire tool consumption also escalates.

Most of the researchers used the RSM technique for the optimization of process variables. The RSM generates a second-order regression model during the modeling and optimization of a manufacturing process whose major limitation is to fit the collected data to a second-order polynomial. The leading edge of ANN on the RSM is that it has comprehensive approximation capability, i.e. it can approximate virtually all types of nonlinear functions, including quadratic functions also.

In the present study, wire electro-spark machining of Titanium alloy is performed with the machining parameter such as spark-on time, spark-off time, current and servo voltage. The purpose of this study is to model surface roughness using machine learning approach for input/controllable variable. Machined surface examined using scanning electron microscope (SEM) and XRD methods.

Full factorial approach has been used to design the experiments with varying machining parameters into three-level four factors. Obtained surface roughness was modeled using machine learning methods namely Gaussian process regression (GPR) and support vector machine (SVM) methods. These methods were compared for both training and testing data with a coefficient of correlation and root mean square error basis. Machined surface examined using scanned electron microscopy and XRD for surface quality produced and check migration of tool material to workpiece material.

Machine learning algorithms has excellent scope for prediction quality response for the wire electric discharge machining (WEDM) process, resulting in saving of time and cost as it is difficult to find each time experimentally. It has been found that the proposed model with minimum computational time, provides better solution and avoids priority weightage calculation by decision-makers.

The proposed modeling provides better predication about surface produced while machining of Ti6Al7Nb using zinc-coated brass wire electrode during WEDM operation.

The purpose of this paper is to analyze the surface integrity, including recast layer thickness, surface crack density, X-ray diffractions study and microhardness for Ni53.49Ti46.51 shape memory alloy (SMA) during wire-spark erosion machining.

Four persuasive process parameters, that is, spark on time (SON), spark off time (SOFF), wire feed (WF) and spark gap voltage (SV), have been chosen for the current investigation. Efforts have been done to explore the effects of above said parameters on the machined surface of Ni-Ti SMA by embracing box Behnken design of response surface methodology (RSM). Cutting speed and ten-point mean roughness (Rz) has been taken into account as response variables. Analysis of variance test was also performed for both response parameters with the coefficient of determination (R²) 0.9610 for cutting speed and 0.9252 for ten-point mean Rz.

The recast layer thickness from 7.83 to 12.13 µm was developed near the machined surface at different parametric settings. The least surface crack density was found at the lowest value of ten-point mean Rz, while most surface crack density was identified at the highest value of cutting speed. The microhardness near the machined surface was increased by approximately 1.8 times bulk-hardness of Ni53.49Ti46.51 SMA.

Some researchers have done a study on average surface roughness, but very few investigators concentrated on ten-point mean Rz. Surface crack density is an essential aspect of machined parts; other researchers have seldom reported it. The novelty of this research work is that the influence of SON, SV, WF and SOFF on cutting speed, Rz, recast layer thickness, micro-hardness and surface crack density proximate the machined surface while machining workpiece material.

Scarcity of resources, ecological imbalance, global warming, rising energy prices and the ever-changing need for variety have attracted the government and manufacturers for sustainable development of the industries. The integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) provides a solid platform for meeting both the customers’ variety needs and business sustainability requirements. Many organizations opted for ISGLSAMS, but still due to various barriers organizations are not able to fully implement ISGLSAMS. The purpose of this paper is to identify the barriers to the ISGLSAMS, so that a more sustainable industrial manufacturing system and industrial symbiosis can be developed.

A literature review, from the Web of Science and Google Scholar database, has been carried out to identify the various barriers to the implementation of ISGLSAMS in the entire value chain. A total of 168 research papers have been reviewed for identifying the ISGLSAMS barriers.

This paper elaborates the concept of the ISGLSAMS, its attributes and various barriers and contributes to a better understanding and successful implementation of ISGLSAMS to meet business’ sustainability and market performance goals in the entire value chain. The paper also projects the future research framework and directions for the ISGLSAMS, integrated sustainable-green-lean-six sigma-agile (ISGLSA) product and ISGLSA supply and value chain.

The study contributes to a better understanding of ISGLSAMS’ barriers. The government, stakeholders and policymakers may plan the policy, road map and strategies to overcome the ISGLSAMS’ barriers. In-depth knowledge of subclauses of ISGLSAMS’ barriers will help the practitioners to overcome the ISGLSAMS’ barriers strategically. By overcoming the ISGLSAMS barriers, a more sustainable 7 Rs based market focused manufacturing system can be designed. This will also increase the opportunities to enhance the industrial ecology, industrial symbiosis and better recovery of the product, process and supply chain residual value. This will reduce the waste to the ecosystem.

This work has been carried out in search of a more sustainable manufacturing system, i.e. ISGLSAMS (which is 7 Rs based, i.e. 6 Rs of sustainability with 7th R, reconfiguration) to meet the customer variety needs along with sustainability in the ever-changing customer market. This study adds value to the practitioners to identify and prioritize the ISGLSAMS’ industry-specific barriers and design the solution for the more sustainable development of (1) industries, (2) the industrial symbiosis system and (3) the ISGLSA product, process, system and supply value chain with minimum resource consumption and environmental impact. The research also contributes to the (a) ISGLSAMS (b) ISGLSA supply chain (c) reconfigurable, sustainable and modular products and (d) redesign, recovery and refurbishing of the product to increase the product life cycle.

The purpose of this paper is to examine the presence of nostalgic advertising in Indian television and its execution with reference to extent of information disclosure, level of involvement, type of products and stages in product life cycle (PLC).

This research uses a content analysis of 700 TV advertisements aired between January-December 2013 from top five Indian TV channels based on their rank according to Gross Viewership in Thousands.

Humour/happiness was the most commonly used emotional appeal and nostalgic ads constituted 12 per cent of the emotional ads in Indian television. “References to past family experiences” was the most commonly used nostalgic element. As hypothesised, nostalgic ads use low information disclosure strategy (vis-à-vis high/medium information disclosure strategy) and are more commonly used for low involvement products (vis-à-vis high involvement products), experience products (vis-à-vis search products), and non-durables (vis-à-vis durables). Also, nostalgic appeals are more commonly used at maturity stage of PLC (vis-à-vis introduction stage).

This is the first research to analyse the content and execution of nostalgic advertising in India. This study is also one of the first to provide a comprehensive framework on nostalgic advertising. The interrelationships among variables such as product category, process of emotional appeal, degree of information disclosure and stage in PLC has not been investigated earlier, in the context of nostalgic advertising. Moreover, this study is the first attempt to present a snapshot of TV ads in India.