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This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

This study aims to include the diagnosis of an old concrete deck steel truss rural road bridge in the damaged and retrofitted state through vibration response signals.

The analysis of the vibration response signals is performed in time and time-frequency domains using statistical features-root mean square, impulse factor, crest factor, kurtosis, peak2peak and Stockwell transform. The proposed methodology uses the Hilbert transform in combination with spectral kurtosis and bandpass filtering technique for obtaining robust outcomes of modal frequencies.

The absence or low amplitude of considered mode shape frequencies is observed both before and after retrofitting of bridge indicates the deficient nodes. The kurtosis feature among all statistical approaches is able to reflect significant variation in the amplitude of different nodes of the bridge. The Stockwell transform showed better resolution of present modal frequencies but due to the yield of additional frequency peaks in the vicinity of the first three analytical modal frequencies no decisive conclusions are achieved. The methodology shows promising outcomes in eliminating noise and visualizing distinct modal frequencies of a steel truss bridge.

The findings of the present study help in analyzing noisy vibration signals obtained from various structures (civil or mechanical) and determine vulnerable locations of the structure using mode shape frequencies.

The literature review gave an insight into few experimental investigations related to the combined application of Hilbert transform with spectral kurtosis and bandpass filtering technique in determining mode frequencies of a steel truss bridge.

This research aims to evaluate the impact of barriers experienced by Brazilian companies in adopting Industry 4.0 (I4.0).

As a methodological approach, the survey method was used, adopting the use of the questionnaire for data collection. From the feedback of 99 companies (with an index of 80%), quantitative analyzes of the data were carried out with the aid of factor analysis and linear regression to validate the proposed structural model.

The barriers construct does not impact the I4.0 adoption construct. Directly evaluating the effect of the variables that make up the barriers construct in the I4.0 adoption construct, it was observed that three barriers affect effectively the adoption of I4.0: technological infrastructure; financial constraint and lack of understanding of the benefits of I4.0.

As a limitation, the research was conducted only in the Brazilian context, requiring the development of future studies in other countries that can strengthen the findings of this research.

In addition, the results achieved provide relevant insights into public policymakers and business managers, helping them to deeply understand the barriers that impact the adoption of I4.0. This facilitates the propagation of I4.0 concepts in the context of Brazilian companies and in the formulation of public policies adapted to each sector, allowing a more assertive action in the face of the types of barriers experienced by organizations during the adoption of I4.0.

The findings can help practitioners and policymakers to understand in detail this new industrial model and the difficulties that prevent its implementation.

From an extensive literature review, no studies were identified that statistically validate which barriers effectively affect the adoption of I4.0. This research is a pioneer in proposing a structural model to analyze the barriers experienced by workers during the adoption of I4.0, exploring Brazilian companies, from different economic sectors and sizes. It is noteworthy that the literature still focuses efforts on manufacturing companies.

Industrial wastes such as copper slag and fly ash are being generated in tons every year and disposed mainly by land fillings, resulting in wastage of useful land. Copper slag in itself is a granular cohesionless sand-like material, while fly ash is highly pozzolanic. The purpose of this paper is to investigate copper slag and fly ash mixes with cement as stabilizer for their proper use in road construction.

Different trial mixes of copper slag and fly ash were tested for obtaining the optimum mix having maximum dry density. Cylindrical specimens were prepared using optimum mix with different proportion of cement (3, 6 and 9 per cent) and cured for period of 7, 14 and 28 days in desiccator. Several tests such as proctor test, unconfined compressive strength test, splitting tensile strength test and soaked CBR test were carried out.

After analyzing the variation of test results with varying cement content and curing period, maximum compressive strength of 10 MPa and maximum tensile strength of 1.5 MPa was found for specimen having 9 per cent cement content cured for a period of 28 days. It was concluded that copper slag and fly ash when mixed in optimum proportion and stabilized with 6 and 9 per cent cement can be effectively used as granular material in sub base and base layer of road pavement.

A typical flexible pavement section was designed and checked using IITPAVE software which gave desired results. This paper may add value in the areas of pavement design, waste utilization, etc.

COVID-19 lockdown imposed by the government in India affected markets, factories, industries, construction sites, restaurants, transport services, etc. in which migrant workers were engaged. Migrant workers expected that after the imposition of the lockdown government will facilitate transportation facilities to their hometowns as they lost their jobs. But due to negligence from both the central and the state governments, neither transportation was arranged nor food, shelter or health facilities were arranged. This paper aims to investigate the causes of the death of migrant workers under the theoretical framework of negligence theory.

The authors have applied the content analysis method and collected 926 death cases of migrant workers from 28 Indian states. The researchers applied this technique as the newspapers in India are one of the largest and most useful sources to generate a report/record on migrant workers causes during the COVID-19 lockdown. During the lockdown period, due to lack of attention from the government, police atrocities, hunger and accidental cases increased which resulted in the death of migrant workers.

The finding of the study proves that during the first phase of COVID-19 lockdown the death cases of migrant workers increased due to negligence by the governments. The number of death cases of migrant workers has been analysed through applying negligence theory which included duty, breach, cause, in fact, proximate cause and harm which increased the death cases. It has been noticed that the central government without any prior notice-imposed lockdown all over India, in which all the states were not received any guidelines or communication which indicate what they have to do or how to handle the Covid-19 situation.

To the best of the authors’ knowledge, this is an original work of researchers which is basically based on negligence theory.

This paper aims to examine the traditional business communities and family businesses of India, their emergence and sustained growth.

The authors analyze the role of business communities in family businesses of India and identify business communities that have still sustained and marked a global presence.

Business communities such as Marwaris have the knack for business activities and are leaders of family businesses in India today, who have sustained their past success and continue to create new histories. Other traditional business communities such as Parsis, Sindhis, Chettiars and Gujarati banias have not been able to sustain much. Possible reasons were switching to white-collar jobs, taking up diplomacy and other professions, inter caste marriages, international migration in search of business and Indian government policies.

This study provides a useful source of information for academics, policy-makers and economists.

Traditional business communities populate the list of family businesses that have marked their global presence. This paper identifies various factors that are responsible for the growth and sustainability of these business communities.

The study clarifies the role of business communities in domestic economic development.

The paper explored traditional business communities of India and assessed their role in family businesses of India that currently mark a global presence.

This paper aims to analyze the agile manufacturing practices in small and medium enterprises (SMEs) within the auto-ancillary sector spread across eastern India. Using statistical method, a number of crucial insights have been captured and discussed in detail.

A structural equation model (SEM) encapsulating pertinent agile manufacturing attributes and enablers as the focal construct is conceptualized and validated in this research. The SEM model is evolved in a manner that agile attributes and agile enablers are modeled as latent dependent and manifest variable, respectively.

A number of key hypothesis entailing interactions of key agility enablers, i.e. manufacturing responsiveness agility, manufacturing strategy agility, workforce agility, technology agility, manufacturing management agility, etc. are conceptualized and validated.

The authors specifically focus on evolving agile manufacturing framework (characterized by agility enablers and attributes) that lies at the intersection of SMEs, automotive sector and an emerging economy.

The purpose of this paper is to investigate the existing literature on agile manufacturing (AM) to pinpoint critical success factors (CSFs) affecting the successful implementation of agile manufacturing systems.

The study focused on empirical articles published in peer-reviewed journals from 1991 to 2019 (July). In total, 37 empirical studies were shortlisted for analysis as the reliability and validity of the constructs were critically tested using various statistical methods. Further, “Pareto analysis” tool was employed to sort and arrange the factors critical for smoother and effective implementation of AM, in descending order according to their frequency of occurrence.

The present work scrutinizes 37 research papers, resulting in 33 CSFs that affect AM implementation. Using Pareto analysis, 8 CSFs are regarded as “vital few,” which account for 82.66 percent of occurrence, and the remaining 25 CSFs are regarded as “useful many,” which account for 17.34 percent of occurrence. The managers must focus on successful deployment of “vital few” CSFs, as they are more critical in achieving business excellence through the successful implementation of AM, in comparison to other 25 “useful many” CSFs.

To the best knowledge of authors, this work is the first attempt to employ Pareto analysis for critically analyzing a wide range of AM CSFs studies. The findings of this study will assist researchers and managers in AM implementation in a more smoother and effective way in manufacturing industries.