Search results

Electric discharge drilling (EDD) is used to drill quality microholes on any conductive materials. EDD process parameters play a crucial role in the drilling. Depending upon the material characteristics, the cost of drilling also changes. Therefore, a suitable method is required to control the process parameters and drill quality microholes.

The input process parameters in the present work are peak current (Ip), pulse on-time (Ton) and pulse off-time (Toff). The trials were intended in accordance to central composite face-centered design of response surface methodology (RSM). The output responses, namely drilling rate (DR) and electrode wear ratio (EWR), were converted into a single response, that is, grade using Grey relational analysis (GRA). The grade value is further modeled by regression analysis. The empirical model was figured out using teaching–learning-based optimization (TLBO). The RSM-Grey-TLBO-based multicriteria decision-making (MCDM) is used to investigate the optimized process parameter setting.

The RSM-Grey-TLBO-based MCDM approach suggests that the optimized setting for DR and EWR is Ip: 3A; Ton: 40 µs; Toff: 42 µs. The percentage errors for the predicted and experimental results are 8.1 and 7.5% in DR and EWR, respectively.

The parametric optimization of EDD using RSM-Grey-TLBO-based MCDM approach while machining commercially pure titanium is still underway. Thus, this MCDM approach will give a path to the researchers working in this direction.

Magnesium alloys are becoming prominent as an alternative to the permanent biomedical implants. In present work, electric discharge drilling (EDD) process has been investigated and optimized for ZM21 Mg alloy that can be used for producing perforated bone implants having geometrically precise micro holes.

Planning of experiments has been carried out in accordance to the Taguchi mixed L18 orthogonal array (OA). The hole overcut (HO), circularity at entrance (Cent) and circularity at exit (Cext) of drilled micro holes were measured as response characteristics during experimentation corresponding to different settings of EDD input parameters. For optimizing multiresponse characteristics, the hybrid approach of grey relational analysis, regression analysis and particle swarm optimization has been implemented.

It is found from hybrid approach that brass electrode along with Ip; 3 Amp, Ton; 50 µs and Toff; 52 µs outperformed over all other parametric settings against the collective result of response characteristics. The experimental values of response characteristics at suggested optimized setting are HO: 93.48 µm; Cent: 0.988 and Cext: 0.992, respectively.

The optimization of EDD process for developing perforated Mg alloy bone implants, using hybrid approach is still missing.

The impact of COVID-19 has caused a recession in economies all over the world. In this context, the current study aims to analyze the prevailing economic scenario using a machine learning approach and suggest sustainable measures to recover the global economy taking the case of Make in India (MII) initiative of developing the economy as a base for the study.

A well-known topic modeling technique – Latent Dirichlet allocation (LDA) algorithm has been employed to extract useful information characterizing the existing state of selected sectors under the MII initiative alongside catalytic policies that have been implemented for the same. The textual data acts as the base of the study upon which suggestions are provided.

The findings obtained suggest that digital transformation will play a key role in concerned sectors to optimize the performance of manufacturing organizations. Additionally, inter-relationship between Key Performance Indicators for the economy's revival is crucial for effective utilization of foreign direct investment resources.

The novel efforts to utilize MII initiative as a case present crucial information which can be used by policy makers and various other stakeholders across the globe to enhance decision-making and draft legislation across different sectors to empower the economy.

The study presents a novel approach to utilize the MII initiative by identifying important measures for crucial sectors and associated policies that have been presented by employing a text mining approach which in itself makes it unique in its contribution to research literature.

Across the architecture, engineering and construction industry, the application of building information modelling (BIM) as a digital technology for architectural heritage is becoming increasingly relevant. However, scholarly research on the application of BIM for architectural heritage is still in its infancy stage and the research gaps and future directions of this research area are still unclear. This paper therefore aims to fill this gap by using a systematic and robust review using a mixed-method approach to show the gaps of research for BIM and architectural heritage and point to new directions for future works.

The study includes a quantitative scientometric analysis and mapping and a qualitative study. A total of 354 articles related to BIM and architectural heritage were analysed using a combination of quantitative and qualitative tools. The qualitative study consists of a systematic literature review supported by data collected from stakeholder and training workshops on digital technologies and BIM for heritage.

Findings from this study reveal the gaps in the field of heritage and BIM research according to retrieved articles from different countries and journals. Furthermore, emerging domains for future research were identified and these included: as-built modelling and 3D reconstruction; conservation, preservation and management; documentation; maintenance and restoration; virtual technology and simulation.

The common research challenges were identified as an integrated outcome of the findings revealed from the scientometric mapping and qualitative review and resulted in key BIM and heritage research priority recommendations relevant to researchers within this field.

In the twenty-first century, the use of fossil fuels has increased drastically because the necessity of energy is increasing day by day which affects the world’s economy. The solar energy (photo-thermal energy conversion) system is the most economical and eco-friendly alternative source. To increase the use of domestic as well as commercialization purpose, the authors have reviewed this paper on the solar water heater along with its structural mechanism for energy enhancement and to create easier stair steps for climbing on the green world dream.

In this study, nanotechnology has remarkably built its own use for extending thermal efficiency by using some gradual experiments. It is a phenomenon, like nanofluid (as a working fluid for a direct solar collector), nanocoating (on the surface of a solar-evacuated tube by using the chemical vapor deposition/physical vacuum deposition/sol–gel technique) and nanorod-based solar collector tube.

This invention gives greater efficiency rather than the conventional systems, but also this advancement is not too much supported in a low- temperature environment also, we can consider the poor light absorption characteristics of the pure water (Bencic, et al., 2000).

The basic idea and understanding of this phenomenon to improve solar collecting performance for obtaining a high working-fluid temperature are discussed in this paper.

The purpose of this study is to identify the capacity needs of building professionals to deliver environmentally sustainable buildings (ESBs) globally, from a unique systems approach. Through a review of extant literature, this study contributes to knowledge of the global delivery of ESBs by identifying research trends and gaps that can be tackled in future research, and current hotspots in capacity building (CB) research within the built environment (BE). The adopted systems approach to CB postulates that the construction industry is systemized in nature, and thus, CB solutions within the industry should be approached from a systems approach.

A literature search was conducted using the Scopus search engine, augmented by Google Scholar and Web of Science, to produce 54 relevant articles for analysis. The scientometric analysis was undertaken with the use of VOSViewer to better understand the broad literature on CB in the construction industry which would not have been possible with traditional data analysis. The content analysis allowed, for a systematic review of selected articles, to reveal key themes in this study.

Through a content analysis, four levels of CB were identified within the construction industry; individual level, organizational level, industry level and state level. Nine sub-capacities were subsumed under the four identified levels adopted from Potter and Brough (2004), including but not limited to Performance capacity, Workload capacity, Supervisory capacity, Industry Role capacity and Systems capacity. Under each sub-capacity, key questions were posed to aid identify the capacity needs of BE professionals. A framework for identifying capacity needs in the BE is proposed.

The findings of this study serve as a useful reference for practitioners and policymakers to assess their level of commitment to CB efforts for ESB delivery. The findings of this study have revealed that building the capacities of BE professionals to deliver ESBs should be addressed as part of a broader framework, interdependent on the other levels of CB in the systemic construction industry.

As a review study identifying capacity needs for BE professionals to deliver ESBs, this study enhances knowledge of CB within the construction industry.

The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility.

The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz.

The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm³/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm.

The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

The purpose of this paper is to propose an interpretive structural modeling (ISM) model which highlights the relationships between the identified just-in-time (JIT) elements useful for the implementation of JIT in maintenance and understand mutual influences of these identified JIT elements on JIT implementation in maintenance. Further, this paper seeks to identify dependence power and driving power of identified JIT elements using an ISM and Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis.

The methodology used in the paper is ISM with a view to evolving mutual relationships among JIT elements. The identified JIT elements have been further classified, based on their dependence power and driving power using MICMAC analysis.

This paper has developed the relationships among 16 identified JIT elements using the ISM methodology. Further, this paper analyses the driving power and dependence power of identified JIT elements with the help of MICMAC analysis. The incorporated approach is developed here, as the ISM provides only binary correlation among identified JIT elements. The MICMAC analysis is adopted here as it is useful in specific examination related to driving and the dependence power of identified JIT elements. The ISM developed model and MICMAC analysis finding are validated with the help of industrial experts.

The weightage and validation for the ISM and MICMAC analysis are obtained throughout the opinion of academics and industry experts. Further hypothesis may be conducted to examine the validity of the planned model, and structural model may also be validated statistically with the help of structural equation modeling.

The ISM model development and MICMAC analysis of identified JIT elements provide academics and maintenance managers a macro picture of the profits gained by the organizations by the implementation of JIT in maintenance of an organization.

The results will be useful for maintenance managers to understand the process of implementation of JIT in maintenance and to gain benefits after the implementation of JIT in maintenance of an organization.