Showing papers by "YMCA University of Science and Technology published in 2018"

Microstructure and mechanical behavior of AA6082-T6/SiC/B4C-based aluminum hybrid composites

Abstract: The microstructural and mechanical behavior of hybrid metal matrix composite based on aluminum alloy 6082-T6 reinforced with silicon carbide (SiC) and boron carbide (B4C) particles was investigated. For this purpose, the hybrid composites were fabricated using conventional stir casting process by varying weight percentages of 5, 10, 15, and 20 wt% of (SiC + B4C) mixture. Dispersion of the reinforced particles was studied with x-ray diffraction and scanning electron microscopy analyses. Mechanical properties such as micro-hardness, impact strength, ultimate tensile strength, percentage elongation, density, and porosity were investigated on hybrid composites at room temperature. The results revealed that the increase in weight percentage of (SiC + B4C) mixture gives superior hardness and tensile strength with slight decrease in percentage elongation. However, some reduction in both hardness and tensile strength was observed in hybrid composites with 20 wt% of (SiC + B4C) mixture. As compared to the ...

Fabrication of NiTi alloy: A review:

Abstract: Nitinol (NiTi) is categorized as a smart material which is highly recognized material for medical and other engineering applications. The behaviour of NiTi can be modified by altering the composition, modifying the porosity and applying external thermal and mechanical treatment. Due to high composition sensitivity, there are several impediments in fabrication of NiTi with conventional techniques which impel the use of additive manufacturing methods. But due to very high cost of equipments, these processes have not been commercialized till now. This paper presents a review on applications, manufacturing NiTi alloy and its various production routes from conventional to rapid prototyping, porous NiTi, effect of additives on properties of the alloy and its challenges.

ANP-MOORA-based approach for the analysis of selected issues of green supply chain management

Abstract: Purpose Industries start focusing on the green concept in supply chain management (SCM) to reduce waste and emission, preserve the quality of natural resources and decrease the consumption of hazardous/harmful materials for better product life cycle, which not only improve environmental performance but also economic performance. But, for industries, it is still very difficult to understand and analyze the effect of individual activities and their corresponding contribution. The purpose of this paper is to identify and analyze selected issues in green supply chain management for the implementation of the green concept in industries. Design/methodology/approach To fulfill the objectives of this paper, analytical network process-multi-objective optimization using rational analysis (ANP-MOORA) techniques are used. In the proposed methodologies, different issues, sub-issues, and alternatives are identified for the selection of the best supply chain using ANP which is being followed by the MOORA method. Findings Findings of this paper are highly valuable for the Indian manufacturing industries for the management of green supply chain (GSC) issues. Research limitations/implications In this research, only selected issues are identified and analyzed for the management of GSCs. Further, it is believed that an ANP-based framework helps to take up the explicit account of multi-criteria decision making (MCDM) approaches in decision making and for improving and selecting the best supply chain. Other issues in GSC can be analyzed and further extended by other MCDM approaches. Originality/value This paper identified different type of supply chains and their issues. The systematic way of analyzing the green concept in supply chain helps the researchers and managers to implement green management practices for improving economic and environmental performance.

Dry sliding wear behaviour of AA6082-T6/SiC/B4C hybrid metal matrix composites using response surface methodology:

Abstract: In the present work, dry sliding wear behaviour of hybrid aluminum metal matrix composites is carried out. A mixture of silicon carbide and boron carbide is used in equal fraction as reinforcement ...

Parametric study of the dry sliding wear behaviour of AA6082-T6/SiC and AA6082-T6/B4C composites using RSM

Abstract: In this paper a parametric study of the wear behaviour of Aluminum matrix composites has been carried out. AA6082-T6/SiC and AA6082-T6/B4C composites were fabricated using stir casting technique. The percentage of reinforcement was taken as 5, 10, 15 and 20 wt.% for both SiC and B4C particulates. Dry sliding wear tests were conducted using pin-on-disc apparatus at room temperature and process optimization was done using Response surface methodology (RSM). Weight percentage (wt.%) of reinforcement, sliding speed, load and sliding distance were the four process parameters considered to analyse these composites wear behaviour. Analysis of variance (ANOVA) showed that sliding distance exerted the highest contribution (60.24 %) to AA6082-T6/SiC wear, followed by sliding speed (14.28 %), load (11.88 %) and reinforcement content (4.31 %). The same trend was found in AA6082-T6/B4C composites with slightly different contribution values, namely sliding distance (63.28 %), sliding speed (14.02 %), load (10.10 %) and reinforcement content (4.05 %). RSM analysis revealed that increases in the reinforcement content and sliding speed reduce the wear rate in both composites. On the other hand, increases in load and sliding distance led to higher AA6082-T6/SiC and AA6082-T6/B4C composites wear. The two predictive models were validated by conducting confirmation tests and certified that the developed wear predictive models are accurate and can be used as predictive tools for wear apllications.

Effect of hybrid wire EDM conditions on generation of residual stresses in machining of HCHCr D2 tool steel under ultrasonic vibration

Abstract: This experimental examination exhibit a novel Hybrid Wire electrical discharge machining (H-WEDM) process of ultrasonic vibration combined with traditional Wire-EDM. The metal cutting for form tool and extrusion die with WEDM is liked to give better surface morphology. The effect of residual stresses has been dissected for H-WEDMed machined surface alongside the surface roughness and erosion rate to enhance surface integrity and longer service life of High Carbon High Chromium D2 tool steel. The process parameters chose for this investigation are type of vibration continuous/discontinues, amplitude of vibration, workpiece dimension, duty cycle, peek current and wire feed rate with objective to optimize the residual stresses and erosion rate. Portable X-ray Residual Stress Analyzer, a non-destructive X-ray analyzer is used to measure the residual stress efficiently by detecting the full Debye ring data from a single incident X-ray angle and Non goniometer stage influence on the measurements. An endeavor was made to compare the residual stresses for continuous/discontinues vibration and without vibration. The impacts of amplitude of vibration, peak current, duty cycle and wire feed rate variations on erosion rate was study using Taguchi method. From experimental study, it was observed that discontinuous vibration enhances the erosion rate and diminishes the resultant stresses. High Peak current and duty cycle altogether deteriorate the surface texture, which creates high tensile residual stresses because of debris and micro cracks. The optimum value of residual stresses 86.53 MPa and material erosion rate 6.45 mm/min was achieved using H-WEDM.

A Novel Image Encryption Scheme Based on Intertwining Chaotic Maps and RC4 Stream Cipher

Abstract: As the systems are enabling us to transmit large chunks of data, both in the form of texts and images, there is a need to explore algorithms which can provide a higher security without increasing the time complexity significantly. This paper proposes an image encryption scheme which uses intertwining chaotic maps and RC4 stream cipher to encrypt/decrypt the images. The scheme employs chaotic map for the confusion stage and for generation of key for the RC4 cipher. The RC4 cipher uses this key to generate random sequences which are used to implement an efficient diffusion process. The algorithm is implemented in MATLAB-2016b and various performance metrics are used to evaluate its efficacy. The proposed scheme provides highly scrambled encrypted images and can resist statistical, differential and brute-force search attacks. The peak signal-to-noise ratio values are quite similar to other schemes, the entropy values are close to ideal. In addition, the scheme is very much practical since having lowest time complexity then its counterparts.

GA-based optimisation using RSM in WEDM of Nimonic-90: a nickel-based super alloy

Abstract: The present research work is focused on optimisation of WEDM process parameters for machining of Nimonic-90. It is a nickel-based alloy possessing creep resistance and high rupture strength at high temperature (up to 950°C). Genetic algorithm (GA) and response surface methodology (RSM) incorporated with each other to optimise the process parameters. Four input process parameters viz. discharge current (Ip), pulse-off time (Toff), pulse-on time (Ton), and servo voltage (SV) have been investigated and modelled for surface roughness (SR) utilising RSM. In present experimentation, quadratic model has been suggested for surface roughness. Pulse-on time is most significant effect on surface roughness as compared to other parameters. Finally, genetic algorithm, a popular evolutionary approach is used to optimise the process parameters. Using SEM micrographs and micro-hardness profile, effect of discharge energy on surface morphology has been examined.

Analyzing and modeling the performance index of ultrasonic vibration assisted EDM using graph theory and matrix approach

Abstract: This paper is an endeavor to comprehend an interactive learning process of ultrasonic vibration assisted Electrical Discharge Machining (USEDM) process performance index. The factors influencing the USEDM process are identified and analyzed, through a logical and systematic framework of graph theory and matrix approach. The interdependency of factors are distinguished and examined. A systematic model of USEDM performance index is proposed to utilize graph theoretic approach (GTA). The performance index for USEDM is obtained so from the matrix model and digraphs to comprehend the power of subjective factors affecting. Factors and sub-factors impacting the performance are perceived and collected into five essential groups e.g. flushing, cavitation, abnormal discharge, dimensional accuracy and surface morphology. GTA framework reveals that the flushing, surface morphology and dimensional accuracy impact the basically ascertains, however cavitation effect can in like manner be unequivocal variables for USEDM performance index regard.

Prioritising the performance measures of FMS using multi-criteria decision making approaches

Abstract: The evaluation of the most appropriate performance measures in the manufacturing sector is one of the strategic issues that may affect the flexible manufacturing system (FMS). In this paper, five areas of performance measures, i.e., measures related to finance, measures related to customers, measures related to innovation and knowledge, measures related to internal business and miscellaneous measures with their sub-measures are considered. The purpose of this paper is to provide a framework to proactively manage performance measures. For this purpose, a comparative study of multi criteria decision making approaches, simple additive weighting (SAW) and weighted product method (WPM) are integrated with analytic hierarchy process (AHP) in order to get the best solution. AHP is used to determine the weights of the measures which are used in SAW and WPM approaches, for prioritising the performance measures so that management could take the decision regarding improvement. Here, fuzzy logic is used to change the qualitative measures into the quantitative measures.

Leagile manufacturing: a review paper

Abstract: Leagile manufacturing is one of the recent dominant research areas in the field of operations management in the current scenario. However, there is a lack of research focusing on leagile in manufacturing industries. The leagile system combines the advantages of both lean as well as agile system. The purpose of the paper is to make the industries and academicians aware of the leagile concept and its tools so as to meet the fluctuating needs of customers in short duration of time. It provides industries to remove all different types of wastes and at the same time concurrently meeting the changing needs of customers and hence helps in achieving better customer satisfaction. Both lean and agile systems can be incorporated simultaneously in the system by proper positioning of de-coupling point in the supply chain. In the upstream of the supply chain, lean system is adopted while in downstream, agile system is best suited.

Critical Path Problem for Scheduling Using Genetic Algorithm

Abstract: The critical path problem, in Software Project Management, finds the longest path in a Directed Acyclic Graph. The problem is immensely important for scheduling the critical activities. The problem reduces to the longest path problem, which is NP as against the shortest path problem. The longest path is an important NP-hard problem, which finds its applications in many other areas like graph drawing, sequence alignment algorithms, etc. The problem has been dealt with using Computational Intelligence. The paper presents the state of the art. The applicability of Genetic Algorithms in longest path problem has also been discussed. This paper proposes a novel Genetic Algorithm-based solution to the problem. This algorithm has been implemented and verified using benchmarks. The results are encouraging.

Evaluating key performance indicators of leagile manufacturing using fuzzy TISM approach

Abstract: Leagile manufacturing strategy has emerged as one of the important strategy adopted by most of manufacturing organizations now a days. It has advantages of both lean as well as agile manufacturing system. Lean manufacturing tries to eliminate all different types of wastages like overproduction, inventory, unnecessary motion etc., while agile manufacturing focus on changing the production system as per the requirements of the customer and provide customized products within short span of time. Lean manufacturing focuses on no inventory and try to implement Just in Time methodology but for the system to be agile, there should be at least some inventory in store so that production can be started as soon as customer order is achieved. In this paper, key performance indicators (KPI) of leagile manufacturing are found by literature review and in consultation of experts and academicians working in the concerned field. Fuzzy TISM approach has been applied to find levels of different KPI’S. MICMAC analysis has been made to analyze the KPI’S and categorize them as autonomous, dependent, linkage, independent etc. on the basis of driving and dependence power. Finally, digraph is drawn to show relationship between various KPI’s.

An adaptive neuro-fuzzy inference system for makespan estimation of flexible manufacturing system assembly shop: a case study

Abstract: This paper considers the use of combination of neural networks and fuzzy system i.e. adaptive neuro-fuzzy inference system (ANFIS) applied to the n job, m machine real flexible manufacturing system assembly shop problem with the objective of prediction of makespan. Assembly shop makespan is calculated by Nawaz, Enscor, and Ham (NEH) algorithm. On the basis of this algorithm, adaptive neuro-fuzzy inference system model is made to predict the makespan of the jobs. The purpose of this study is to find the makespan estimation in advance if processing time of machines is known. The purpose of this research is to gain the advantage of the capabilities of both Fuzzy systems, which is a rule-based approach and neural network which focus on the network training. This model has been verified by testing and actual data set with the average percentage accuracy achieved is 95.97%. Coefficient of determination and Correlation coefficient is 0.9310 and 0.9649 respectively. The derived values of ANFIS model output are found within the range after being verified practically. Therefore, it can be concluded that makespan calculation of the production system, by the proposed adaptive neuro-fuzzy inference system, can be used as a reliable approach in estimating the makespan of flexible manufacturing system assembly shop.

Prediction of cutting force by using ANFIS

Abstract: The aim of this research is to develop a model to predict the cutting forces of a turning operation. This paper focuses on to design a monitoring system that can recognize cutting force on the basis of cutting parameters like spindle speed, feed and depth of cut by using adaptive neuro-fuzzy inference system (ANFIS). Cutting force is one of the important characteristic variables to be watched and controlled in the cutting processes to determine tool life and surface roughness of the work piece. The principal assumption was that the cutting forces increase due to the wearing of the tool. So, ANFIS model is used to express the cutting force signal. In this paper, ANFIS is used to predict the cutting force. The correlation coefficient (R) and average percentage error found in this modeling are 0.9976 and 2.59% respectively. The predicted cutting force values derived from ANFIS were compared with experimental data. The comparison indicates that the ANFIS achieved very satisfactory accuracy. The correlation coefficient (R) and average percentage error found in this modeling are 0.9976 and 2.59% respectively. The prediction accuracy of ANFIS reached is as high as 97%.

A Survey of IPv6 Addressing Schemes for Internet of Things

Abstract: As IPv4 addresses are already exhausted before the beginning of Internet of Thing (IoT), IPv6 is widely used to assign unique identity to IoT nodes. In this article, the analysis of different components required in assigning IPv6 addresses to IoT nodes, a survey of IPv6 address assignment schemes and an examination of the different kinds of IPv6 addresses are presented. This article highlights the architectural complexity of IoT technologies, protocol stacks, limitations of IoT nodes, renumbering, multihoming, the merging of IoT network and other challenges towards assigning of IPv6 address to IoT nodes. A comprehensive survey on recent addressing schemes with classification based on allocation tables and spatial information are presented. This survey describes the address allocation mechanism, performance on different metrics, the area of applicability, and the merits and demerits of different addressing schemes. It also describes the future research options addressing IoT.

Sentiment Analysis and Mining of Opinions

Abstract: Now days the way of expressing opinions on certain products that people purchase and the services that they receive in the various industries has been transformed considerably because of World Wide Web. Social Networking sites fascinate people to post feedbacks and reviews online on blogs, Internet forums, review portals and much more. These opinions play a very important role for customers and product manufacturers as they tend to give better knowledge of buying and selling by setting positive and negative comments on products and other information which can improve their decision making policies. Mining of such opinions have focused the researchers to pay a keen intention in developing such a system which can not only collect useful and relevant reviews online in a ranked manner and also produce an effective summary of such reviews collected on different products according to their respective domains. However, there is little evidence that researchers have approached this issue in opinion mining with the intent of developing such a system. Our work will focus on what opinion mining is the existing works on opinion mining, the challenges in the existing techniques and the workflow of mining opinions. Consequently, the aim of this chapter is to discuss the overall novel architecture of developing an opinion system that will address the remaining challenges and provide an overview of how to mine opinions. Existing research in sentiment analysis tend to focus on finding out how to classify the opinions and produce a collaborative summary in their respective domains, despite an increase in the field of opinion mining and its research, many challenges remain in designing a more comprehensive way of building a system to mine opinions. This chapter addresses the problem of how to classify sentiments and develop the opinion system by combining theories of supervised learning.

Feasibility analysis of FMS in small and medium scale Indian industries with a hybrid approach using ISM and TOPSIS

Abstract: Small and medium scale industries play an important role in Indian economy and their strength lays in the competitiveness of their products in the world market. Backed by a strong government support in India, they continue to improve their growth rate. Despite this high growth rate, huge potential amongst the Indian small and medium scale industries still remains untapped. So there is a need to upgrade these industries so that they bloom to their full potential. For achieving increased competitiveness, the manufacturing SMEs need to replace or supplement their previous methods of production with more flexible and dynamic production systems like, flexible manufacturing system (FMS) which is characterised by shorter product development and manufacturing lead-time, better quality and flexibility, team-based work organisations, low setup/changeover times, multifunctional workers. FMS as a manufacturing strategy can help a SME to improve its processes and align it to the requirements of its customers. So this paper discusses the issues of SMEs and presents the major attributes for the adoption of FMS in SMEs and further these attributes are modelled to give a structure amongst them by using two distinct, well established modelling techniques, ISM and TOPSIS.

Performance analysis of magnetorheological fluid-assisted electrical discharge machining

Abstract: In this study, a newly developed method of electric discharge machining has been proposed, which uses magnetorheological (MR) fluid instead of conventional oil like kerosene. The paper aims...

Synthesis of Er doped ZnO cone-like nanostructures with enhanced structural, optical and magnetic properties

Abstract: In this report, undoped ZnO and Er doped ZnO nanostructures [Zn1−xErxO, where x = 1, 3, 5 and 7 at.%] were synthesized by chemical precipitation technique. The chemical precipitation route for the preparation of undoped ZnO and Er doped ZnO nanostructures at different concentrations represents an easy, fast and efficient method. The synthesized nanostructures were characterized to analyze their crystal structure, crystal morphology, optical and magnetic properties using X-ray diffraction (XRD), Energy dispersive X-ray (EDX), High resolution scanning electron microscopy (HRSEM), Ultraviolet–Visible spectroscopy (UV–Visible), Photoluminescence spectroscopy (PL) and Vibrating sample magnetometer (VSM) respectively. The XRD studies exposed that undoped ZnO and all Er doped ZnO samples have a hexagonal wurtzite crystal structure. The XRD results showed that Er3+ ions were successfully doped into ZnO nanostructures as no diffraction peaks of Er or erbium oxide were observed in the pattern. EDX results also confirmed that Er ions were successfully incorporated into the lattice position of Zn ions in ZnO. HRSEM characterization showed that presence of Er3+ ions in crystal structure of ZnO can change the morphology i.e. the transformation of nanorods to nanocones. Nanorods-like structure obtained with 1 at.% Er extend to nanocones-like for 3–7 at.% Er doped ZnO with changes in length and thickness in nm range. In UV–Visible absorbance spectra, a red shift was observed in the band gap of undoped ZnO and Er doped nanostructures with increasing Er concentration. PL measurements also revealed that the undoped ZnO and Er doped ZnO nanostructures had an UV emission, a defect emission and the Er ions doping induced a red shift in the UV emission with a small enhancement in the defect emission. The VSM study revealed that the undoped ZnO and Er doped ZnO nanostructures exhibit paramagnetic and ferromagnetic behaviour at room temperature respectively.

Search for Prioritized Test Cases in Multi-Objective Environment During Web Application Testing

Abstract: Regression testing is an expensive procedure that is implemented during maintenance phase of the Software Development Life Cycle of evolving software. During this process, test case prioritization is one of the strategies followed in which test cases are organized in a fashion so as to enhance efficiency in achieving some performance goal. During the process, there could be several aspects to be kept in mind due to resources constraints such as fault severity detected per unit of test cost, severity detection per test case execution, and execution time of test cases to detect all the faults. Keeping all such constraints in mind, the test case prioritization problem becomes a multi-objective problem where some of the objectives have to be maximized and the remaining ones minimized. In this study, experiments were performed on different versions of five web applications. The problem instance was found to vary from 5 $$\times $$ 5 test cases versus fault matrix, to 125 $$\times $$ 125 matrix. Random approach, 2-opt algorithm, improved 2-opt algorithm, greedy approach, additional greedy approach, Weighted Genetic Algorithm and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were applied to a generate prioritized test sequence which maximizes the Cost Cognizant Average Percentage of Fault Detection value, severity detection and minimizes test case execution cost to expose all the faults. The performances of these algorithms are compared, keeping these parameters in mind, and it is concluded that the performance of NSGA-II algorithm is better than that of all the other tested algorithms throughout all the experiments.

Conceptual design and development of pneumatically controlled flexible fixture and pallets

Abstract: Fixture performance influences the product manufacturing quality, productivity and cost. Flexible fixtures (FF) provide solution to the problem of costly redesign of fixtures due to changes in dimensions/geometry of parts to be manufactured. Various areas related to design of FFs have already been very well described by various renowned authors. This paper carries out the conceptual designing of pneumatically controlled FF and pallets for machining (drilling and milling) operations. Pneumatic cylinders and electric motors were used as actuators. The first part considers introduction and literature review with significant researches and requirements of fixtures over time. After that, different aspects related to fixture design have been presented to give a deep and quick understanding of fixture design and its criteria for drilling and milling heads. Then, conceptual designing of pneumatically controlled FF and pallets has been discussed. The shortcomings of the existing studies are stated and future directions are proposed.

Investigating the benefits and challenges of the implementation of ISO 9001 and ISO 14001 in the aerospace industry

Abstract: Aerospace companies implement certain quality management and environmental standards, e.g. ISO 9001 and ISO 14001 requirements specific to the aerospace industry. The big question is whether the implementation of the ISO standards has provided its hope for returns. The aim of this research is therefore to analyze the benefits and challenges of the implementation of ISO 9001 and ISO 14001 in the aerospace industry. This study aims to investigate two underlying subjects – quality management and environmental management, and explore how they influence firm performance and how they are implemented in the aerospace industry. Nine participants from different aerospace companies were interviewed. The results suggest that these companies were put under pressure internally and externally by the customers for pursuing the certification. Major factors that affect the implementation include size of company, employee participation, and company commitment. It also discovered that ISO 14001 seems to mainly impact the managers and employees related to environmental work. This study found that the larger the company size, the more sensitive it becomes toward customer pressure on commitment to sustainability.

Dynamic priority-based packet handling protocol for healthcare wireless body area network system

Abstract: The vision of wireless body area network (WBAN) is to facilitate, improve, and have an immense impact on the healthcare system in terms of identifying the risk level or severity factor of a patient in various emergencies. Modern and technical advances in WBAN revolutionise this area for autonomous monitoring of vital signals for a longer duration as well as from a remote place. However, handling of heterogeneous packets in a fast changing healthcare scenario has continued to be an opportunity for exploration. We present a novel concept of dynamic priority-based packet handling (DPPH) which promises to add exciting capabilities to the world of WBANs. DPPH uses the principles of accurate identification and classification of heterogeneous packets to effectively determine patient's critical condition and alerts the medical person if required. In this paper, we have focused on dynamic prioritisation-based queuing, scheduling, alerting and resource sharing policies for performance enhancement. The proposed approach is validated through a comparison with existing approaches. The effectiveness of the proposed protocol is evaluated under various scenarios using a network simulator 'NS-2.35' and its performance is judged on the basis of packet delivery ratio, loss ratio, end-to-end delay, and throughput.

Work culture enablers: hierarchical design for effectiveness and efficiency

Abstract: The manufacturing process also referred to as the transformation process (converting raw material into finished products) consumes huge amount of resources (Gupta et al., 2012), which severely affects sustainability. Extensive initiatives are sought to stand to the 'Make in India' proposal of the Indian Prime Minister, which are primarily people dependent. The present work seeks to investigate the enablers of people's work culture to implement the PM's commandments along with their interdependence and hierarchy levels in the Indian manufacturing sector for which the interpretive structural modelling (ISM) has been used. While understanding the contextual relationships among the identified enablers MICMAC analysis is used to categorise the identified enablers according to their importance in the organisation. The investigations reported that a twin enabler compettitude (competence + attitude) (Thareja, 2012) is the driving enabler for a zero waste culture paradigm to sustainable progression of the PM's initiative. Consistency is next reported as the dependent enabler for a healthy work culture on all other enablers.

Experimental Investigation and optimization of Process Parameters for Shear Strength of Compound Cast Bimetallic Joints

Abstract: Joining of A356 alloy and magnesium was carried out by vacuum assisted sand mold compound casting process. Microstructure at the joint interface was studied by using optical microscope, scanning electron microscope, energy dispersive X-ray spectroscopy and X-ray diffractometer. Characterization indicated that a relatively uniform joint interface was obtained. The joint interface was composed of three distinct layers containing Mg2Al3 on aluminum side, Mg17Al12 + δ eutectic structure on magnesium side and Mg17Al12 as middle layer. As a result of interaction between silicon, present in A356 with magnesium, Mg2Si compound was formed. Push out test was conducted on electronics universal testing machine to measure the shear strength across the joint interface. The important process parameters (grit size of sand paper, insert temperature, pouring temperature and vacuum pressure) were optimized to maximize the shear strength. Optimization was carried out by using response surface methodology, desirability analysis and genetic algorithm (GA) techniques. It was observed that the shear strength increased by 14.21, 8.60 and 4.80% with genetic algorithm, desirability analysis and regression model respectively. GA reported the optimal value of shear strength.

Profile-Based Ad Hoc Social Networking Using Wi-Fi Direct on the Top of Android

Abstract: Ad-hoc Social Networks have become popular to support novel applications related to location-based mobile services that are of great importance to users and businesses. Unlike traditional social services using a centralized server to fetch location, ad-hoc social network services support infrastructure less real-time social networking. It allows users to collaborate and share views anytime anywhere. However, current ad-hoc social network applications are either not available without rooting the mobile phones or don't filter the nearby users based on common interests without a centralized server. This paper presents an architecture and implementation of social networks on commercially available mobile devices that allow broadcasting name and a limited number of keywords representing users' interests without any connection in a nearby region to facilitate matching of interests. The broadcasting region creates a digital aura and is limited by WiFi region that is around 200 meters. The application connects users to form a group based on their profile or interests using peer-to-peer communication mode without using any centralized networking or profile matching infrastructure. The peer-to-peer group can be used for private communication when the network is not available.

Analysis of quality enabled factors in the product design stage of a production system life cycle: a relationship modelling approach

Abstract: The product design stage is the most vital stage of a production system life cycle (PSLC) as it forms the foundation of the production system. The success of a production system relies on efficient...

An Agent-Based Solution to Energy Sink-Hole Problem in Flat Wireless Sensor Networks

Abstract: Repeated and continuous transmission of data to the sink leads to energy loss in all the nodes in case of flat WSN. Especially, depletion of energy is highly acute in case of nodes that are near to the sink. Conventionally known as energy sink-hole problem, it causes early failure of the network even when there is a substantial amount of residual energy left in it. Though the research fraternity has been continuously addressing this problem and even has provided various solutions to deal with it, the use of mobile agents to meet the above-stated problem is still in its infancy. The paper proposes a mobile agent-based solution for solving energy sink-hole problem. The proposed solution aims to extend the network life by reducing redundant data being passed to the nodes near to the sink thereby reducing the load and saving battery life. The algorithm is implemented using aglets and the analytical results show significant improvement in the network lifetime.