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Purpose of this study is to design a compact gap coupled anchor shape patch antenna for wireless local area network/high performance radio local area network and worldwide interoperability for microwave access applications.

An anchor shape microstrip antenna is conceived, designed, simulated and measured. The anchor shape antenna is transformed to its rectangular equivalent by conserving the patch area. Modeling and simulation of the antenna is performed by Ansys high frequency structure simulator (HFSS) electromagnetic solver based on the concept of finite element method. The simulated results are experimentally verified by using Agilent E5071C vector network analyzer. Theoretical analysis of an electromagnetically gap coupled anchor shape microstrip patch antenna has been performed by obtaining the lumped element equivalent of the transformed antenna.

The proposed antenna has a compact conducting patch of dimension 0.26λ × 0.12λ mm² (λ is calculated at lower resonating frequency of 3.56 GHz) with impedance bandwidths of 100 and 140 MHz and antenna gains of 1.91 and 3.04 dB at lower resonating frequency of 3.56 GHz and upper resonating frequency of 5.4 GHz, with omni-directional radiation pattern.

In literature, one does not encounter anchor shape antenna using the concept of gap coupling and parasitic patches. The design has been optimized for wireless local area network/worldwide interoperability for microwave access applications with a relatively low patch area (291.12 mm²) as compared to other reported antennas for wireless local area network/worldwide interoperability for microwave access applications. Transformed antenna and the actual experimental antenna behavior varies, but the resonant frequencies of the transformed antenna as observed by theoretical analysis and simulated results (by high frequency structure simulator) are reasonably close, and the percentage difference between the resonant frequencies (both at lower and upper bands) is within the permissible limit of 1-2.5 per cent. Results confirm the theoretical proposition of transformation of shapes in antenna design, which allows a designer to adapt the design shape according to the application.

The lack of proper dissemination of market information is observed as the main reason of poor marketing of the agricultural produce in India. Application of information and communication technology (ICT) can bridge this information gap by means of dissemination of required marketing information specifically targeted at the farmers. The purpose of this paper is to study the impact of ICT on marketing of rice in Uttar Pradesh, one of the biggest northern states of India.

As rice is the dominant crop of Uttar Pradesh, the impact of ICT on net price received (NP_f) by rice producers of the state is studied. An attempt is also made to identify the factors that influence the use of ICT. Primary data are collected through a multistage sampling technique. Single, multiple dummy and binary logistic regression models are used in the present work.

A significant difference is observed in the NP_f of the farmers using ICT than that of non-users. Education and land holding type also have a positive and significant impact on ICT use.

In the existing literature, the study related to the impact of ICT on agricultural marketing is almost absent for India in general, and Uttar Pradesh in particular. ICT has created impact in almost all directions of life. It is expected that the implementation of ICT will create a notable impact on the income level of the farmers. The present study will give a direction in this regard. The study is based on primary data and original work of the authors.

This paper aims to deal with the selection of the sustainability-oriented Green Lean Six Sigma (GLS) project for the manufacturing industry in the complex decision-making environment. Moreover, the study also proposes a GLS implementation framework for improved organizational performance.

GLS project selection has been done based on the six sustainability-oriented criteria formed from 17 sub-criteria (found from the literature and developed by authors). The weights of the criteria have been determined through the entropy method. The projects have been ranked based on the criteria through the advanced decision-making approach: grey relation analysis (GRA). The results of the study were validated using best worst method and sensitivity analysis.

It has been found that the productivity-related criterion is the most significant among other criteria with entropy weight of 0.2721. GRA has been used in this research work to rank the potential GLS projects in a manufacturing industry based on six sustainability criteria, to select a project that exhibits the maximum potential for sustainable improvement. The machine shop has been found as the most significant GLS project with grey relation grade of 0.4742.

The present study facilitates practitioners and industrial managers to implement an inclusive GLS approach for improved sustainability dynamics through effective GLS project selection and implementation framework.

With increased globalized competition in recent times, new projects are being considered as the foundation stone for organizational success. The decision-making becomes quite complex to select an effective project due to the intriguing nature of various criteria, sub-criteria and different aspects of sustainability. To the best of the authors’ knowledge, the present study is the first of its kind that provides ways for the selection of sustainability-oriented GLS projects.

This study aims to introduce a modern higher efficiency predictor–corrector iterative algorithm.

Furthermore, the efficiency of new algorithm is analyzed on the based on Chun-Hui He’s iteration method.

In comparison with the current robust algorithms, the newly establish algorithm behaves better and efficient, whereas the current existing algorithm fails or slows in the considered test examples.

The modified Chun-Hui He’s algorithm has great practical implication in numerous real-life challenges in different area of engineering, such as Industrial engineering, Civil engineering, Electrical engineering and Mechanical engineering.

The paper presents a modified Chun-Hui He’s algorithm for solving the nonlinear algebraic models exist in various area.

This study aims to experimentally investigate the influence of considered process parameters, i.e. pulse on time, pulse off time, peak current and gap voltage, on tool wear rate (TWR) in electrical discharge machining (EDM) of iron (Fe)-based shape memory alloy (SMA) through designed experiments. The parametric optimization for TWR has also been attempted using the desirability approach and genetic algorithm (GA).

The response surface methodology (RSM) in the form of Box–Behnken design has been used to scheme out the experiments. The influence of considered process inputs has also been observed through variance analysis. The reliability and fitness of the developed mathematical model have been established with test results. Microstructure analysis of machined samples has also been evaluated and analyzed using a scanning electron microscope (SEM). SEM images revealed the surface characteristics such as micro-cracks, craters and voids on the tool electrode surface. SEM images provide information about the surface integrity and type of wear on the surface of the tool electrode.

The input parameters, namely, pulse on time and pulse off time, are major influential factors impacting the TWR. High TWR has been reported at large pulse on time and small pulse off time conditions whereas higher TWR is reported at high peak current input settings. The maximum and minimum TWR values obtained are 0.073 g/min and 0.017 g/min, respectively. The optimization with desirability approach and GA reveals the best parametric values for TWR i.e. 0.01581 g/min and 0.00875 g/min at parametric combination as pulse on time = 60.83 µs, pulse off time = 112.16 µs, peak current = 18.64 A and gap voltage = 59.55 V, and pulse on time = 60 µs, pulse off time = 120 µs, peak current = 12 A and gap voltage = 40 V, correspondingly.

Proposed work has no limitations.

SMAs have been well known for their superior and excellent properties, which make them an eligible candidate of paramount importance in real-life industrial applications such as orthopedic implants, actuators, micro tools, stents, coupling, sealing elements, aerospace components, defense instruments, manufacturing elements and bio-medical appliances. However, its effective and productive processing is still a challenge. Tool wear study while processing of SMAs in EDM process is an area which has been less investigated and of major concern for exploring the various properties of the tool and wear in it. Also, the developed mathematical model for TWR through the RSM approach will be helpful in industrial revelation.

The purpose of this study is to explore and model the strategies to overcome the barriers of Lean Six Sigma (LSS) implementation in Indian small manufacturing enterprises (SMEs).

In this research, 31 strategies of LSS implementation in SMEs have been identified through detailed literature review and out of them, 13 are finalized using statistical tools like CIMTC and Importance-Index analysis. Moreover, the consistency of finalized strategies was examined through reliability test using SPSS software version 22. The finalized strategies are modelled through interpretive structural modelling (ISM) and classified them using MICMAC based on their driving and dependency power.

The key findings of this techno-managerial study are identification and modelling of 13 strategies to overcome adoption challenges of LSS in context of Indian SMEs. The usage of ISM-MICMAC approach provides the guidance to industrialist consider the mutual interaction of strategies during planning and scheduling for LSS projects.

Due to human involvement and judgements, there may be chance of biasness and subjectivity during construction of self-interaction matrix. Also, the number of identified strategies to overcomes barriers of LSS adoption may vary by altering nature, scope and region of research.

Literature is full of studies regarding LSS barriers and its rankings. Also, few studies explored the solutions of LSS barriers and prioritized them. To the best of the authors’ knowledge, our study is very rare to witness which expose the strategies to overcome the barriers and frame the mutual interaction are per the driving and dependence power of strategies. The application of ISM-MICMAC approach suggests a roadmap for implementing LSS approach efficiently through considering developed ISM model of strategies in context of SMEs.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

This paper aims to uncover the significance of capacity, capacity utilization (CU) and its role in the quality and productivity improvement in an industrial environment. Besides, the current study is also aiming to explore the various ways to estimate CU and its status across the world.

In the present study, a comprehensive literature review on capacity and CU is carried out to expose the research direction in the field of CU. This work is primarily focused on capacity, CU and their estimation methods based on the research in various industries of different countries and current status in present scenario across the world.

The literature reveals that CU estimation is carried out by some government/central agencies at the national or sector level rather than the industry level in most of the productive nations. As far as industrial growth is concerned, capacity management should be carried out at a particular industry level so that engineering managers can be able to find out loopholes for huge capacity waste within the plant. It is observed that CU in the industrial sectors mainly computed by time series method, survey method, economic approach and engineering approach worldwide.

This paper tries to cover almost all research work in the field of CU in various industrial sectors. However, the organizations which are producing the product with limited demand may get benefit inadequately.

This paper provides a vision to management toward productivity improvement through optimal utilization of available resources. As in most organizations, CU issues are much neglected areas.

This paper provides valuable insights on capacity and CU in the industrial sector across the world. Besides, it focused on comprehensive literature of capacity and various methods to estimate CU in industrial sectors.