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The purpose of this paper is to implement new concept of mobile maintenance in manufacturing industry of Northern India. This study tries to introduce the new concept of total productive maintenance program in the case company.

The approach is to study the role of mobile maintenance in the context of Indian industry through significant improvement in overall equipment effectiveness (OEE).

This industry adopted the mobile maintenance strategy and improved their productivity by decreasing breakdown time. This mobile maintenance strategy can reduce major breakdowns, setup and adjustment losses and improve productivity, product quality and OEE of equipment. Results indicate an average increase in production of 15.63 percent, average reduction in breakdown time of 23.14 percent, average reduction in rejection rate of 17.94 percent and average increase in OEE of 17.08 percent. Moreover, the results of improvements in parameters are validated by using multi-criteria decision-making approaches.

Maintenance is of great importance in modern era of manufacturing systems for those organizations who consider maintenance as a profit-generating factor. In the dynamic and highly challenging environment, reliable manufacturing equipment is regarded as the major contributor to the performance and profitability of manufacturing systems. Moreover, the selection of manufacturing industry is done on the basis of convenience sampling technique.

Industry can improve machine availability and OEE by implementing this mobile maintenance concept especially in the Indian context and is very beneficially for the case company under study.

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.

Because of the extensive user coverage of news sites and apps, greater social and commercial value can be realized if users can access their favourite news as easily as possible. However, news has a timeliness factor; there are serious cold start and data sparsity in news recommendation, and news users are more susceptible to recent topical news. Therefore, this study aims to propose a personalized news recommendation approach based on topic model and restricted Boltzmann machine (RBM).

Firstly, the model extracts the news topic information based on the LDA2vec topic model. Then, the implicit behaviour data are analysed and converted into explicit rating data according to the rules. The highest weight is assigned to recent hot news stories. Finally, the topic information and the rating data are regarded as the conditional layer and visual layer of the conditional RBM (CRBM) model, respectively, to implement news recommendations.

The experimental results show that using LDA2vec-based news topic as a conditional layer in the CRBM model provides a higher prediction rating and improves the effectiveness of news recommendations.

This study proposes a personalized news recommendation approach based on an improved CRBM. Topic model is applied to news topic extraction and used as the conditional layer of the CRBM. It not only alleviates the sparseness of rating data to improve the efficient in CRBM but also considers that readers are more susceptible to popular or trending news.

Accurate prediction of temperature and heat is crucial for the design of various nano/micro devices in engineering. Recently, investigation has been carried out for calculating the heat flux of gas flow using the concept of sliding friction because of the slip velocity at the surface. The purpose of this study is to exetend the concept of sliding friction for various types of nano/micro flows.

A new type of Smoluchowski temperature jump considering the viscous heat generation (sliding friction) has recently been proposed (Le and Vu, 2016b) as an alternative jump condition for the prediction of the surface gas temperature at solid interfaces for high-speed non-equilibrium gas flows. This paper investigated the proposed jump condition for the nano/microflows which has not been done earlier using four cases: 90° bend microchannel pressure-driven flow, nanochannel backward facing step with a pressure-driven flow, nanoscale flat plate and NACA 0012 micro-airfoil. The results are compared with the available direct simulation Monte Carlo results. Also, this paper has demonstrated low-speed preconditioned density-based algorithm for the rarefied gas flows. The algorithm captured even very low Mach numbers of 2.12 × 10⁻⁵.

Based on this study, this paper concludes that the effect of inclusion of sliding friction in improving the thermodynamic prediction is case-dependent. It is shown that its performance depends not only on the slip velocity at the surface but also on the mean free path of the gas molecule and the shear stress at the surface. A pressure jump condition was used along with the new temperature jump condition and it has been found to often improve the prediction of surface flow properties significantly.

This paper extends the concept of using sliding friction at the wall for micro/nano flows. The pressure jump condition was used which has been generally ignored by researchers and has been found to often improve the prediction of surface flow properties. Different flow properties have been studied at the wall apart from only temperature and heat flux, which was not done earlier.

This paper aims to conduct, a detailed investigation of various Reynolds averaged Navier–Stokes (RANS) models to study their performance in attached and separated flows. The turbulent flow over two airfoils, namely, National Advisory Committee for Aeronautics (NACA)-0012 and National Aeronautics and Space Administration (NASA) MS(1)-0317 with a static stall setup at a Reynolds number of 6 million, is chosen to investigate these models. The pre-stall and post-stall regions, which are in the range of angles of attack 0°–20°, are simulated.

RANS turbulence models with the Boussinesq approximation are the most commonly used cost-effective models for engineering flows. Four RANS models are considered to predict the static stall of two airfoils: Spalart–Allmaras (SA), Menter’s k – ω shear stress transport (SST), k – kL and SA-Bas Cakmakcioglu modified (BCM) transition model. All the simulations are performed on an in-house unstructured-grid compressible flow solver.

All the turbulence models considered predicted the lift and drag coefficients in good agreement with experimental data for both airfoils in the attached pre-stall region. For the NACA-0012 airfoil, all models except the SA-BCM over-predicted the stall angle by 2°, whereas SA-BCM failed to predict stall. For the NASA MS(1)-0317 airfoil, all models predicted the lift and drag coefficients accurately for attached flow. But the first three models showed even further delayed stall, whereas SA-BCM again did not predict stall.

The numerical results at high Re obtained from this work, especially that of the NASA MS(1)-0317, are new to the literature in the knowledge of the authors. This paper highlights the inability of RANS models to predict the stall phenomenon and suggests a need for improvement in modeling flow physics in near- and post-stall flows.

Tourism is one of the fastest growing sectors and plays a key role for the economy of various countries. Tourism sector provides lot of opportunities and challenges to its stakeholders. Tourist's safety and security plays a vital role to increase the tourists to a location. Tourism policing plays an essential role to build destination image. Governments are making many efforts through tourism policing to protect the safety and security of the domestic and foreign tourist and also to handle overtourism and enhance responsible tourism. This paper analyses the importance of tourism policing to attract more tourists and its impact on tourist destination image building.

Three-dimensional (3D) printing, one of the important technological pillars of Industry 4.0, is changing the landscape of future manufacturing. However, the limited build volume of a commercially available 3D printer is one inherent constraint, which holds its acceptability by the manufacturing business leaders. This paper aims to address the issue by presenting a novel classification of the possible ways by which 3D-printed parts can be joined or welded to achieve a bigger-sized component.

A two-step literature review is performed. The first section deals with the past and present research studies related to adhesive bonding, mechanical interlocking, fastening and big area additive manufacturing of 3D printed thermoplastics. In the second section, the literature searches were focused on retrieving details related to the welding of 3D printed parts, specifically related to friction stir welding, friction (spin) welding, microwave and ultrasonic welding.

The key findings of this review study comprise the present up-to-date research developments, pros, cons, critical challenges and the future research directions related to each of the joining/welding techniques. After reading this study, a better understanding of how and which joining/welding technique to be applied to obtain a bigger volume 3D printed component will be acquired.

The study provides a realistic approach for the joining of 3D printed parts made by the fused deposition modeling (FDM) technique.

This is the first literature review related to joining or welding of FDM-3D printed parts helping the 3D printing fraternity and researchers, thus increasing the acceptability of low-cost FDM printers by the manufacturing business leaders.

This case provides insights about the importance of market research, market segmentation, distribution, product positioning, branding and advertising for a small but growing enterprise. This case provides insights into nuances about organizing and running a family-owned small business –Bhuira Jams has to objectively decide on its way-forward which can be a pure social enterprise or a pure commercial enterprise. This case provides understanding regarding the differences between the two models in terms of funding, accounting, legal, marketing and operational aspects.

In January 2017, Linnet Mushran had just won an award from the PHD Chamber of Commerce for her work in generating local employment for rural women in the village Bhuira, Himachal Pradesh, India. This award did make her feel happy. However, more than happiness, it got her thinking as to how would Bhuira Jams – the child born out of her passion for mountains and out of the desire to do something good survive in the coming years? Bhuira Jams was never designed like a formal business. Being a family run socially relevant business, Bhuira Jams faces the challenge of operational efficiency, along with an uphill task in marketing and distribution. Almost 35 per cent of its sales comes from Fabindia, which re-sells the Bhuira products under the Fabindia label. Thus, currently there is very little focus and expenditure in Bhuira on marketing and distribution. Another challenge faced by Bhuira Jams is driven by the health and lifestyle changes occurring in the Indian society. Consumer preferences are shifting towards low fat diets, and there is growing Americanization of the Indian society. This can be a double whammy for Bhuira’s main product line of preserves, which are high on calorie and are traditionally British.

Bhuira Jams conceptually is close to a family owned business due to the involvement of husband, daughter-in-law and son-in-law of Linnet. Thus, this case provides insights into nuances about organizing and running a family owned small business.

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CSS 11: Strategy

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.