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The purpose of this paper is to demonstrate the potential of simulation approach for performance evaluation in a complex environment with a case of application from Indian Nuclear Power Plant.

In this work, stochastic simulation approach is applied to availability evaluation of AC Power supply system of Indian Nuclear Power Plant (INPP). In the presently followed test, maintenance policies on diesel generators and circuit breakers are considered to exactly model the practical scenario. System success logic incorporates the functional dependencies and dynamics in the sequence of operations and maintenance policies. In each iteration (random experiment), from simulated random behaviour of the system, uptime and down time are calculated based on system success logic. After sufficient number of iterations, unavailability and other required reliability measures are estimated from the results.

The subsystems of AC Power Supply System of NPP are having multi‐states due to surveillance tests and scheduled maintenance activities. In addition, the operation of DG involves starting and running (till its mission time) which is a sequential (or conditional) event. Furthermore, the redundancies and dependencies are adding to the complexity.

This paper emphasizes the importance of realistic reliability modelling in complex operational scenario with Monte‐Carlo simulation approach. Simulation procedure for evaluating the availability/reliability of repairable complex engineering systems having stand‐by tested components is presented. The same simulation model finds application in importance measures calculation, technical specification optimization and uncertainty quantification.

This chapter studies the link between urban planning and health. Access to safe drinking water is already a very serious issue for large urban populations in fast-growing economies such as India. Water availability is further being impacted by climate change, leading to the drastically increased spread of water-related diseases.

Leh Town, which is located in an ecologically vulnerable semi-arid region of the Himalayas in Ladakh, has been considered for this study because it is undergoing large-scale transformation due to rapid growth in its tourism industry. In 2012–2013 our interdisciplinary group comprising researchers from Germany and India conducted field surveys, including geographic information system-based (GIS) mapping of point sources of water pollution, questionnaire surveys of 200 households and 70 hotels and guesthouses and semi-structured interviews. We also reviewed secondary medical data.

We found that diarrhoeal incidence has increased in the local population in Leh in the past decade, which may be linked to water pollution: Further, we found that rapidly increasing water consumption coupled with a lack of adequate water and sanitation infrastructure is causing serious water pollution.

Further, data is needed for causal connections between water pollution and health impacts to be conclusively drawn.

This study discusses the use of GIS to support a call for the need for more integrated urban planning and decision-making that holistically addresses water and health challenges in Leh and advocates the development of a decentralized or hybrid sanitation system to support water resources conservation as a central dimension of an integrated health management approach.

GIS is also a very useful platform for supporting participatory urban planning in Leh.

With such an integrated urban planning approach, Leh would be a lighthouse example for other towns in the region.

The purpose of this paper is to explore fire risk and preparedness, with regard to water flow rates and building types in London, focusing on Southall district.

A land use survey was carried out to identify water requirements for firefighting across the study area. Local fire hydrant flow rates were analysed, using measurements taken during 2013 and archive data held by the London Fire Brigade (LFB). QGIS was used to explore relationships between fire hydrant flow rates, urban fire risk and socio-economic vulnerability data held by the LFB.

A new type of map, which includes data on water flow rates and building types, was created using QGIS and applied to Southall district, resulting in a map showing Combined Vulnerability to fires. Inadequate fire hydrant water supply was found across many parts of the borough.

This new approach to the evaluation and mapping of urban fire risk could be applied in other cities, to assess problems with water supply and the firefighting water flow requirements of various building types. The methodology can thus assist with adaptations to urban fire resource allocation, tactics, planning and preparedness.

When socio-economic data are also available, this Geographical Information System-based methodology becomes very useful for assessing fire risk and developing strategies for preparedness and response.

This is the first time that London’s fire hydrant water pressures have been mapped and linked with socio-economic vulnerability maps, to produce a Combined Vulnerability map for assessing fire risk.

The purpose of this paper is to develop a methodology using quality function deployment (QFD) approach for aligning competitive strategy with supply chain strategy.

QFD and utility‐based optimization approach are employed to achieve strategic fit between the competitive and supply chain strategies. The supply chain performance is defined by using the information contained in the House of Quality of QFD and utility functions.

Supply chain performance index is computed for the different sets of supply chain design objectives. An illustrative example is presented in this paper to describe the QFD approach for aligning competitive and supply chain strategies.

Application of QFD approach is a new approach to design a supply chain through aligning competitive and supply chain strategies.

The purpose of this paper is to demonstrate a methodology to design a supply chain with a view to achieve a strategic fit between competitive and supply chain strategies.

Quality function deployment (QFD)-based optimization methodology is employed to design a supply chain for a product through aligning the competitive and supply chain strategies. Normal boundary intersection (NBI) method is adopted to obtain optimal weights of the supply chain design objectives. Weighted additive model is developed for multi-objective optimization. Utility-based attribute function, which structure the relationship between the elements of competitive and supply chain strategies is established. The utility functions and the information contained in the House of Quality (HOQ) of QFD are used to define the supply chain performance (SCP).

SCP index is computed using the set of supply chain design objectives obtained by solving the weighted additive model. On the basis of SCP index, the supply chain activities are planned accordingly. An illustrative example is presented in this paper to describe the QFD-based optimization methodology for designing a supply chain.

QFD-based optimization is a novel approach to design a supply chain with a focus on aligning competitive and supply chain strategies.

This paper aims to determine new-normal uncertainty considerations stemming from the COVID-19 pandemic to consider within transaction-cost analysis for pharmaceuticals. It also aims to propose new-normal market entry strategies to address the uncertainty as a result of COVID-19's implications and provide for lack of knowledge and information in an uncertain business environment by way of Internet of Things (IoT) ecosystem for pharmaceutical market entry.

In this paper, we focus on the uncertainty facet within transaction-cost analysis consideration and utilise a descriptive three-case study approach taking in Johnson and Johnson (J&J), GlaxoSmithKline (GSK) and Novartis to present an ADO (Antecedent-Decisions-Outcomes) understanding of their usual market entry approach, the approach undertaken during the pandemic and the outcomes thereafter facilitating new-normal uncertainty considerations to factor in. Further with this insight, we develop a conceptual framework addressing the transaction-cost analysis implications of uncertainties toward lack of knowledge and information for a new-normal market entry approach and operating strategy for pharmaceuticals applicable due to IoT (Internet of Things).

Uncertainty (external and internal) is different now in the new-normal business environment for pharmaceuticals and boils down to acute shortage of knowledge and information impact to make an appropriately informed decision. Therefore, considering the changed factors to consider, pharmaceuticals need to be able to undertake market entry with vaccines and medicines by way of IoT thereby enabling, the filling of the gap via real-time data access and sharing, including enhancing predictive analysis for sustenance.

The paper's findings have many theoretical implications highlighted in the manuscript.

The paper's findings have many practical implications highlighted in the manuscript.

This is the first study to our knowledge that throws light on transaction-cost analysis theory's uncertainty facet for pharmaceuticals. It is also the first study that provides a new-normal market entry strategy for pharmaceutical companies built on interoperability of real-time IoT.

The purpose of this paper is to develop the methodology which can facilitate the concept of reconfiguration in the manufacturing system.

Design methodology includes the calculation of similarity matrix, formation of part family, and selection of part family. ALC algorithm has been used for part family formation and three criteria have been considered for the selection of part family. These criteria are reconfiguration effort, under-utilization cost, and floor space cost. AHP has been used to calculate the weights of criteria and reference ideal method has been used for the selection of alternatives.

In the manufacturing system, machines should be grouped on the basis of reconfiguration cost. When the time period is less, light machines and Group 1 machines are added and removed. In the case study, the concept of reconfiguration is useful for families (A, B, C, D). Machines can be reused by adding/removing some modules of machines. The concept of reconfiguration becomes more useful when it is implemented with lean manufacturing. Lean manufacturing techniques Jidoka and Poka-yoke are used to increase the diagnosability of the system.

Industrial case study has been considered.

Market competition is increasing rapidly and it increases the demand and variety of products, due to which manufacturing enterprises are forced to adapt a manufacturing system which can adjust its capacity and functionality quickly at low cost. To reconfigure manufacturing system from one product/product family to another product/product family, changes can be done in hardware and/or software components in response to sudden changes in the market or in regulatory requirements.

An integrated approach for reconfiguration has been proposed considering the industrial application. It includes weighted Jaccard function, ALCA, AHP, RIM. The methodology for calculation of reconfiguration effort, under-utilization cost, and floor space cost has been presented for industrial case.

The purpose of this study is to cover the influence of selected printing parameters at a macro and micro-geometrical level, focusing on the dimensions, geometry and surface of printed parts with short carbon fibers reinforced PLA. For this case study, a hollow cylindrical shape is considered, aiming to cover the gap detected in previous works analyzed.

Nowadays, additive manufacturing plays a very important role in the manufacturing industry, as can be seen through its numerous research and applications that can be found. Within the engineering industry, geometrical tolerances are essential for the functionality of the parts and their assembly, but the variability in three-dimensional (3D) printing makes dimensional control a difficult task. Constant development in 3D printing allows, more and more, printed parts with controlled and narrowed geometrical deviations and tolerances. So, it is essential to continue narrowing the studies to achieve the optimal printed parts, optimizing the manufacturing process as well.

Results present the relation between the selected printing parameters and the resulting printed part, showing the main deviations and the eligible values to achieve a better tolerance control. Also, from these results obtained, we present a parametric model that relates the geometrical deviations considered in this study with the printing parameters. It can provide an overview of the piece before printing it and so, adjusting the printing parameters and reducing time and number of printings to achieve a good part.

The main contribution is the study of the geometry selected under a 3D printing process, which is important because it considers parts that are created to fit together and need to comply with the required tolerances. Also, we consider that the parametric model can be a suitable approach to selecting the optimal printing parameters before printing.

Purpose – This chapter asks what we should make of the gift exchanges that take place between workers and their managers on the floor of a massive offshore manufacturing unit in South India. Such exchanges appear anomalous in the ethnography of global manufacturing yet here they underpinned the organisation of hyper-intensive production processes.

Findings – Following diverse acts of giving, this chapter shows how these transactions constituted the performative and relational grounds on which workers came to know themselves and sought to shape the world around them. In doing so it extends the anthropology of work and labour by showing that acts of giving are integral to global commodity production.

A widespread focus on the plant-based antimicrobial cotton fabric finishes has been accomplished with notable importance in recent times. The antimicrobials prevent microbial dwelling in fabrics, which causes severe infections to the fabric users. Chemical disinfectants were conventionally used in fabrics to address this challenge; however, they were found to be toxic to humans. Thus, the present study aims to deal with the utilization of phytochemical extracts from different parts of Pongamia pinnata as antimicrobial coatings in cotton fabrics.

The root, bark and stem were collected and washed several times using tap water. Then, the leaves were dried at room temperature and the root and bark were dried using an oven at 40ºC. After drying, they were ground into fine powder and extracted with ethanol using the Soxhlet apparatus. After that the extract was coated on the fabric tested for antimicrobial studies.

The results reported that the leaf extract of P. pinnata-coated fabric exhibited enhanced antibacterial property towards gram-negative Escherichia coli bacteria, followed by root, bark and stem. The wash durability test in the extract-coated fabric samples revealed that dip-coating retained antibacterial activity until five washes. Thus, the current study clearly suggests that the leaf extract from P. pinnata is highly useful to develop antibacterial cotton fabrics as health-care textiles.

The novelty of the present work is to obtain the crude extract from the leaves, bark, root and stem of P. pinnata and evaluate their antibacterial activity against E. coli, upon being coated on cotton fibres. In addition, the extracts were subjected to wash durability analysis to study the coating efficiency of the phytochemicals in cotton fabrics and a probable mechanism for the antibacterial activity of P. pinnata extracts was also presented.