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AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity.

The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity.

The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm³ and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm³. The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains.

The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications.

To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

Maintenance actions are initiated by the annual maintenance budget (AMB) allocated for a plant system. It ensures that the assets are kept in a healthy and reliable state. The purpose of this paper is to scientifically evaluate the AMB for an air conditioning (AC) plant system, which forms an integral part of facility management.

This paper estimates the AMB of an AC system for specific contextual conditions using incidence matrix of the budget influencing variables. The diagonal elements of the matrix represent the values of the budget variables, whereas the off-diagonal elements represent the degree of influence among these. The maintenance budget function is derived from this matrix and is used to evaluate the AMB for the AC system as a percentage of its asset replacement value (ARV).

The AMB for the AC plant system considered in the work is evaluated as 11.1 per cent of ARV for the conditions unique to its context. The actual maintenance expenditure is lower by 7.6 per cent than the estimated value of the budget.

The results of the methodology are a good guide for practicing facility managers. The shortcoming of the methodology is that it relies on fixed weights of the inter-relations among the budget variables, which may not be necessarily true.

This approach is expected to aid the maintenance managers in envisaging the AMB for their plant systems which operate under contextual conditions specific to their plant.

There is no evidence to indicate existence of maintenance budget evaluation methodology for an AC plant system based on its contextual conditions. This paper attempts to fill this gap.

The study analyzes significant parameters defining the credit worthiness, economic viability and managerial efficiency of special purpose vehicles (SPVs) of infrastructure development firms engaged in the execution of road projects under PPP model in India.

The study is based on a comprehensive review of credit rating reports of major rating agencies. In particular, 18 special purpose vehicles (13 BOT-toll–based and 5 BOT-annuity–based road projects) during the period 2010–2019 were considered to conduct a comparative analysis of their rating progression. Considering both financial as well as nonfinancial parameters, their segregation was done on the basis of strengths, constraints and key rating sensitivities influencing the ratings of SPVs involved in road projects under PPP model.

Promoters' credibility emerged as an important factor affecting PPP credit ratings. Other prominent factors included nature of stretch and regulatory terms and conditions and the project's potential to generate cash flows. Inability of PPP projects to generate the projected levels of toll collections was a major constraint and hampered ratings over time. Growth in traffic was a key sensitive area in a toll-based project. Interestingly, despite the fixed nature of revenues, BOT (annuity) projects were impacted by rating changes.

Fewer sample projects (for which the data were available) was a constraint. Future research could consider larger data sets to provide deeper insights. An examination of credit rating parameters using rating reports of projects in other developing nations could provide meaningful implications. The findings of this research however cannot be undermined as the study bridges a gap in existing literature pertaining to the examination of PPP model from a credit rating perspective.

This study would guide project developers, government agencies and awarding agencies of PPP road projects to anticipate the challenges and take adequate steps to mitigate them.

Research in the area of PPP projects is skewed toward risk assessment with respect to financial parameters. The present study emphasizes the rating framework of SPVs. Comprehensive examination of factors affecting project ratings in the form of projects' strengths, constraints and sensitivities would provide inputs to academics and researchers.

After working through the case, the students should be able to understand Indian political economy and the brand building process of NaMo; identify the media mix strategies used to build the brand NaMo in India; evaluate possible future growth strategies for brand NaMo; and compare and contrast brand NaMo with business brands.

Narendra Modi popularly called as NaMo was the current Prime Minister of India. He belonged to Bhartiya Janata Party (BJP) which won India’s general elections in two consecutive terms 2014 and 2019. NaMo was recognised worldwide for his prudence in leading the country to greater heights of achievement. NaMo started his political journey as the worker of BJP at a tender age. His rise in political career was akin to flagship brand overtaking the parent brand. All the steps taken in the past to position himself as a cult brand, will it fortify to NaMo’s victory in 2024 general elections? Business firms may follow NaMo’s strategies. What can the business brands emulate from NaMo to market and position themselves? Can political success be transpired to business success?

This case is designed for use in a graduate-/postgraduate-level marketing course in segments on brand management, brand expansion and the marketing strategies of a market leader. The case can also be used in a brand management course to discuss brand management models (e.g. Keller’s brand resonance pyramid and brand value chain). This case has particular application for classes that focus on brand equity, STP for any brand (segmentation, targeting and positioning) and brand value chain. The case looks in detail at the Indian political market and brand building process of NaMo and examines competitive moves since its inception. This case can be used in brand management, media management courses. The dilemma can be explained as part of a marketing course for postgraduate and executive programmes.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 8: Marketing.

The case tracks Dineout's evolution into a full-scale tech solution provider for restaurants. In 2020, the COVID-19 pandemic struck the world. Several countries, including India, implemented complete lockdowns to control the spread of the virus. Stringent measures to ensure social distancing, night curfews and restrictions on social gatherings continued, which were a severe blow to the restaurant industry. The restaurants' revenue streams dried up as the diners avoided dining out and preferred food deliveries, which was against Dineout's core business model. The case ends with the questions on how Dineout should wade through the pandemic when its entire business model was being challenged.

Textile industry is considered to be one of the largest consumers of water. There needs to be an alternative for water in textile wet processing. Solvent dyeing can be an approach to replace the use of water in dyeing for water conservation.

In this study, the dyeing of polyester was carried out using conventional and solvent dyeing methods. The solvent used was non-aqueous, deep eutectic solvent (DES) prepared using choline chloride and urea. Dyeing parameters such as time, temperature and pH were optimized for a concentration of dye using the solvent and were compared with the conventional dyeing.

The prepared solvent was characterized in terms of Fourier-transform infrared resonance and ¹H and ¹³C nuclear magnetic resonance to analyze the reaction between choline chloride and urea. Dyeing performance in terms of K/S and fastness properties of dyed fabrics were evaluated and found to be at par against conventional dyeing.

Use of DES as a dyeing medium is a novel approach in the textile industry.

Dyeing of silk fabric was studied to increase dye uptake using eco-friendly glycerine based eutectic solvent (GES), which acts as a swelling agent.

The swelling behaviour of silk fabric in GES was analyzed using three-dimensional laser scanning microscope. Dyeing parameters such as time, temperature and GES concentration were optimized using design of experiments.

In total, 5.34 F-value and 0.0014 p-value of ANOVA represent that the model is significant. An optimized GES assisted dyeing was carried out with two different classes of dyes such as Acid Blue 281 and Acid Red 151 and further compared with that of conventional aqueous dyeing method.

At 70°C, silk fabric achieves desired colour strength after 35 min of dyeing (10 min lesser than conventional) using GES assisted dyeing method. % Dye exhaustion of GES assisted dye bath was carried out and found to be very good. Fastness properties such as washing, light and rubbing fastness of conventional and GES assisted dyed silk fabric showed comparable results.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.