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The purpose of this study is to investigate the effect of the sintering temperature on the microstructural, mechanical and physical properties of Cu-SiC composites.

The powder metallurgy route was used to fabricate the samples. Cold compaction of powders was conducted at 250 MPa which was followed by sintering at 850°C–950°C at the interval of 50 °C in the open atmospheric furnace. SiC was used as a reinforcement and the volumetric fraction of the SiC was varied as 10%, 15% and 20%. The processed samples were metallurgically characterized by the scanning electron microscope (SEM). Mechanical characterization was done using tensile and Vickers’ micro-hardness testing to check the hardness and strength of the samples. Archimedes principle and Four-point collinear probe method were used to measure the density and electrical resistivity of the samples.

SEM micrograph reveals the uniform dispersion of the SiC particles in the Cu matrix element. The results revealed that the Hardness and tensile strength were improved due to the addition of SiC and were maximum for the samples sintered at 950 °C. The addition of SiC has also increased the electrical resistivity of the Cu-SiC composite and was lowest for Cu 100% while the relative density has shown the reverse trend. Further, it was found that the maximum hardness of 91.67 Hv and ultimate tensile strength of 312.93 MPa were found for Cu-20% SiC composite and the lowest electrical resistivity of 2.017 µ- Ω-cm was found for pure Cu sample sintered at 950 °C, and this temperature was concluded as the optimum sintering temperature.

The powder metallurgy route for the fabrication of the composites is a challenging task as the trapping of oxygen cannot be controlled during the compaction process as well as during the sintering process. So, a more intensive study is required to overcome these kinds of limitations.

As of the author’s best knowledge, no work has been reported on the effect of sintering temperature on the properties of the Cu-SiC composites which has huge potential in the industries.

The purpose of this study is to investigate the tribological performance of the developed self-healing Al6061 composite and to optimize the operating conditions for enhanced tribo-performance of the developed material.

A unique procedure has been adopted to convert the sand casted Al6061 into self-healing material by piercing a low melting point solder material with and without MoS₂. Taguchi-based L9 orthogonal array has been used to optimize the number of experiments and analyze the influence of operating parameters such as speed, sliding distance and load on material wear.

The results reveal that the paper shows the self-healing and self-repair is possible in metal through piercing low melting point alloy. Then, the load has a significant influence over other input parameters in predicting the wear behavior of developed material. Moreover, addition of MoS₂ does not affect the tribo-performance of the developed material. The study concludes that the developed self-healing Al6061 has huge potential to be used in mechanical industry.

The concept of self-healing in metals are very challenging task due to very slow diffusion rate of atoms at room temperature. Therefore, researchers are encouraged to explore the other new techniques to create self-healing in metals.

The self-healing materials had shown huge potential to be used in mechanical industry. The current investigation established a structural fabrication and testing procedure to understand the effects of various parameters on wear. The conclusion from the experimentation and optimization helps researchers to developed and create self-healing in metals.

The previous research works were not focused on the study of tribological property of self-healing metal composite. With the best of author’s knowledge, no one has reported tribological study, as well as optimization of parameters such as speed, load and sliding distance on wear in self-healing metals composite.

The purpose of this paper is to based upon the joining and characterization (mechanical and metallurgical) of ferritic stainless steel (SS)-430 using a microwave hybrid heating (MHH) phenomenon.

The preliminary experiments were conducted using nickel-based powder as interface material using a domestic microwave oven at a frequency of 2.45 GHz and 900 W power for 720 s. The processed joint was metallurgically characterized by means of X-ray diffraction, Energy-dispersive X-ray spectroscopy and Field emission scanning electron microscopy. Mechanical characterization was done by means of tensile and Vickers’ microhardness testing to check the hardness and strength of the joint.

The metallurgical study revealed that the microstructure and formation of numerous phases of Fe₂Si₃ accompanied by chromium and nickel carbides. The average hardness of 359 Hv at the center of the joint and 637 Hv around the boundaries of the joint was observed. The tensile strength of the joint was observed to 471 MPa with an elongation of 9.02%. The worn surface of the joint signifies the presence of plastic deformation and it was limited due to the presence of harder phases such as Ni₃Si and Ni₃C.

The concept of microwave joining of metals is a very challenging task as the temperature can not be controlled in the inert atmosphere of the microwave. It has been also observed that at certain elevated temperatures, the material starts absorbing the microwaves; which is unknown. So, a more intensive study is required to overcome these kinds of limitations.

MHH technique can be used to process different materials such as ceramics, composites and polymers. SS-430 joined by microwave heating is highly corrosion resistive and has wide applications in refrigerators cabinet panels, dishwasher linings, chimney liners, lashing wires, etc.

As of the author’s best knowledge, no work has been reported on the joining of SS-430 which has huge potential in the industries. Also, no work has been reported on the characterization of microwave joined SS-430.

This study investigates the role of consumer cosmopolitanism on consumer attitudes and purchase intentions (PIs) towards foreign and local brands.

The responses were collected on a structured questionnaire through a consumer survey. The data were then analysed through structural equation modelling (SEM).

The results depict the positive influence of consumer cosmopolitanism on consumer attitudes towards foreign brands, which positively influences PIs towards foreign brands and negatively influences the PIs of local brands. Further, the mediating role of perceived quality was observed in explaining the consumer preference towards foreign and domestic brands.

Finally, the study concludes by providing implications for marketing scholars and managers of global and local brands.

The paper examines the underlying mechanisms related to consumer cosmopolitanism and its role in influencing the foreign and local brand purchase.

The mobile phone industry in India is highly competitive, fast paced and technology-driven. In such a hyper competitive era, effective advertising is considered a key success driver for a mobile phone brand. The purpose of this paper is to identify advertisement effectiveness dimensions for Indian mobile phone industry and to develop hierarchical interrelationships among these dimensions in the Indian print context.

Structured Delphi approach is used to derive the set of dimensions for advertisement effectiveness. Further, techniques such as interpretive structural modeling and MICMAC analysis are used to establish hierarchical linkages among identified dimensions.

On the basis of experts’ opinion, refinement through structured Delphi resulted in the identification of 14 advertisement effectiveness dimensions specific to Indian mobile phone industry. Interpretive structural modeling assisted in the development of linkages among these identified dimensions based on their interrelations. Further, attention, relevance, excitability, liking and consumer preference, etc., turned out to be the dimensions of utmost importance for measuring advertisement effectiveness for the Indian mobile phone industry.

The present research work is limited to the recognition and development of hierarchical interrelationships among advertisement effectiveness dimensions specific to mobile phone business in the Indian print context only. Further studies may be carried out for other product or service category in some different media context.

The present research has several significant implications for academics and advertising practitioners involved in designing and developing promotional campaigns for mobile phone brands in India. The identified 14 dimensions and developed hierarchical model provide valuable insights for improving advertisement effectiveness.

This paper demonstrated successful implementation of Delphi and interpretive structural modeling technique to explore the research area of advertisement effectiveness.

Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.

In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.

The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.

The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.

The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.

The enormous amount of waste generated and the scarcity of natural resources worldwide have encouraged societies and industries to adopt the Circular Supply Chain (CSC) concept. With a focus on zero-waste generation, Circular Economy (CE) mimics the ecosystem cycle as an alternative to the traditional linear economic model. This paper aims to investigate the evolution of research themes in this research area, hence, trace the trajectory of development in the field of CSC.

The authors conduct scientometric analysis using Pajek and VOSviewer software to identify key themes in the Circular Supply Chain Management (CSCM) field. The Citation Path Analysis (CPA), including Main Path and Local Path analysis, has been followed by a critical review of the papers. This paper includes highlighting the interrelationships between the information flows in the topic of study as well as an analysis of keywords co-occurrence.

The analysis of keywords co-occurrence revealed that the earlier years of research in CSC were more inclined toward value chain, stakeholders and green supply chains, whereas, in recent years, topics like logistics, Industry 4.0 and food supply chain have been more focused upon. Further, the Main Path Analysis (MPA) revealed an evolving trajectory that examines challenges and opportunities in CSC, the economic aspects of implementing CSC, the impact on the firm's revenue growth and collaboration between multiple echelons of a supply chain and Industry 4.0.

The adoption of scientometrics analysis unveils the hidden flow of information, various themes of research and their interconnections. The development of research trajectories and progressive attention paid to certain topics is also discovered. The research findings could be used by researchers for further theoretical and research development.

This paper traces the path of development in the field of CSC and its emerging trends and provides a thorough understanding of the same. It enables research scholars to conduct an in-depth study in the CSC domain, adding to the body of literature.

Block chain technology (BCT) has apparent capability of handling information in digital format, which has dragged attention of the practitioners for its utility in industrial and manufacturing practices. Conversely, the managerial adoption of BCT is relatively limited, which motivated the authors to identify crucial dimensions that can persuade the acceptance of BCT from an executive perspective. Thus, the present study is aimed to conduct to understand crucial barriers under BCT for managerial implementation in supply chain management (SCM) of small and medium enterprises (SMEs).

The present study investigated evident barriers to understand implementation of BCT. A questionnaire based survey is performed to collect primary data from service and manufacturing based companies in India. Survey responses are received online and the data is analyzed in a scorecard. The scorecard embedded the scribed entries of Likert scale to determine the relative score.

In present study, sixteen barriers from three categories named as technological, organizational and environmental are evaluated, where, five sub-barriers from technological domain, seven sub-barriers from organizational domain and four sub-barriers from environmental domain are evaluated. The findings of the study determined that the three factors, i.e. “complexity in setup/use”, “Security and privacy concern” and “Technological awareness” mostly affect the adaptation of BCT in SCM. Conversely, “Market dynamics”, “Scalability” and “Cost” do not influence the intention to adopt the technology.

Only few studies have endeavored to ascertain the BCT adoption in SCM of SMEs in developing country like India. Thus, the study is filling a momentous gap of mapping BCT dimensions in the scholastic literature. The findings are expected to enable SMEs to understand important factors to be considered for adopting BCT in their curriculum. Furthermore, the study may benefit the BCT developers and suppliers to endure customized solutions based on the findings.

Today, proficient practices are required to stimulate along various boundaries of the supply chain (SC) to exploit manufacturing resources economically, effectually and gracefully for retaining operational excellence. Accordingly, varieties of paramount practices, i.e. Lean, Agile, Resilient and Green practices, are integrated in present study with the objective to develop a Decision Support Framework (DSF) to select robust supplier under the extent of Lean-Agile-Resilient-Green (LARG) practices for a manufacturing firm. The framework is developed and validated in the Indian automotive sector, where the primary data is collected based on perceptions of the respondents working in an automotive company.

LARG metrics can ponder ecological balance, customer satisfaction, associations, effectiveness and sustainability and thus, the study consolidated LARG practices in one umbrella to develop a DSF. The analytical approach under DSF is developed by the integration AHP, DEMATEL, ANP, Extended MOORA and SAW techniques in present study to evaluate a robust supplier under the aegis of LARG practices in SC. DSF is developed by scrutinizing and categorizing LARG characteristics, where the selected LARG characteristics are handled by fuzzy sets theory to deal with the impreciseness and uncertainty in decision making.

The study has identified 63 measures (15 for Lean, 15 for Agile, 14 for resilient and 19 for Green) to support the robust supplier selection process for manufacturing firms. The findings of study explicate “Internal communication agility”, “Interchangeability to personnel resources”, “Manufacturing flexibility”, “degree of online solution”, “Quickness to resource up-gradation”, “Manageability to demand and supply change”, “Overstocking inventory practices” as significant metrics in ranking order. Additionally, “Transparency to share information”, “Internal communication agility”, “Manufacturing Flexibility”, “Green product (outgoing)” are found as influential metrics under LARG practices respectively.

A technical DSF to utilize by the managers is developed, which is connected with knowledge-based theory and a case of an automobile manufacturing firm is presented to illustrate its implementation. The companies can utilize presented DSF to impose service excellence, societal performance, agility and green surroundings in SC for achieving sustainable outcomes to be welcomed by the legislations, society and rivals. The framework represents an important decision support tool to enable managers to overcome imprecise SC information sources.

The study presented a proficient platform to review the most significant LARG alternative in the SC. The study suggested a cluster of LARG metrics to support operational improvement in manufacturing firms for shifting gear toward sustainable SC practices. The present study embraces its existence in enrolling a high extent of collaboration amongst clients, project teams and LARG practices to virtually eradicate the likelihood of absolute project failure.

Advanced manufacturing machines (AMMs) are searched as a momentous asset across the manufacturing societies for quenching and addressing the production units under economical circumstances, i.e. production of high-quality of goods under feasible cost. AMMs are significant in holding the managers against their rivals and competitors with high profit margins. The authors developed the decision support mechanism/portfolio (DSM-P) consist of knowledge-based cluster approach with a dynamic model. The purpose of research work is to measure overall economic worth of AMMs under objective and grey-imperfect (mixed) data by exploring the proposed DSM-P.

The authors developed the DSM-P that consist of knowledge-based cluster, three multi-criteria decision-making (MCDM) techniques-1-2-3 with complementary grey relational analysis-4(GRA), approach with a dynamic model (complied by technical plus cost and agility measures of AMMs). The proposed DSM-P enables the manager to map the overall economic worth of candidate AMMs under objective and grey-mixed data.

The presented DSM-P assist the managers for handling the selection problem of AMMs, i.e. CNCs, robots, automatic-guided vehicle, etc under mixed (objective cum grey) data. To enable the readers for intensely understand the work, the utility of proposed approach is displayed by illustrating a polar robot evaluation and selection problem. It is ascertained that the robot candidate-11 alternative is fulfilling the entire technical cum cost and agility measures.

The DSM-P provides more precise and reliable outcomes due to a usage of the dominance theory. Under the dominance theory, the ranks are obtained by MCDM techniques-1-2-3 are compared with ranks gathered by the GRA-4 under objective cum grey data, formed the novelties in presented research work. From a future perspective, the grey-based models in DSM-P can be built/extended/constructed more extensive and can be simulated by the same approach.