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The principal intention behind the activity is to regulate the speed, current and commutation of the brushless DC (BLDC) motor. Thereby, the authors can control the torque.

In order to regulate the current and speed of the motor, the Multi-resolution PID (MRPID) controller is proposed. The altered Landsman converter is utilized in this proposed suppression circuit, and the obligation cycle is acclimated to acquire the ideal DC-bus voltage dependent on the speed of the BLDC motor. The adaptive neuro-fuzzy inference system-elephant herding optimization (ANFIS-EHO) calculation mirrors the conduct of the procreant framework in families.

Brushless DC motor's dynamic properties are created, noticed and examined by MATLAB/Simulink model. The performance will be compared with existing genetic algorithms.

The presented approach and performance will be compared with existing genetic algorithms and optimization of different structure of BLDC motor.

This paper seeks to present a feedback error learning neuro‐controller for an unstable research helicopter.

Three neural‐aided flight controllers are designed to satisfy the ADS‐33 handling qualities specifications in pitch, roll and yaw axes. The proposed controller scheme is based on feedback error learning strategy in which the outer loop neural controller enhances the inner loop conventional controller by compensating for unknown non‐linearity and parameter uncertainties. The basic building block of the neuro‐controller is a nonlinear auto regressive exogenous (NARX) input neural network. For each neural controller, the parameter update rule is derived using Lyapunov‐like synthesis. An offline finite time training is used to provide asymptotic stability and on‐line learning strategy is employed to handle parameter uncertainty and nonlinearity.

The theoretical results are validated using simulation studies based on a nonlinear six degree‐of‐freedom helicopter undergoing an agile maneuver. The neural controller performs well in disturbance rejection is the presence of gust and sensor noise.

The neuro‐control approach presented in this paper is well suited to unmanned and small‐scale helicopters.

The study shows that the neuro‐controller meets the requirements of ADS‐33 handling qualities specifications of a helicopter.

This paper aims to present the design of a stability augmentation system (SAS) in the longitudinal and lateral axes for an unstable helicopter.

The feedback controller is designed using linear quadratic regulator (LQR) control with full state feedback and LQR with output feedback approaches. SAS is designed to meet the handling qualities specification known as Aeronautical Design Standard (ADS‐33E‐PRF). A helicopter having a soft inplane four‐bladed hingeless main rotor and a four‐bladed tail rotor with conventional mechanical controls is used for the simulation studies. In the simulation studies, the helicopter is trimmed at hover, low speeds and forward speeds flight conditions. The performance of the helicopter SAS schemes are assessed with respect to the requirements of ADS‐33E‐PRF.

The SAS in the longitudinal axis meets the requirement of the Level 1 handling quality specifications in hover and low speed as well as for forward speed flight conditions. The SAS in the lateral axis meets the requirement of the Level 2 handling quality specifications in both hover and low speed as well as for forward speed flight conditions. The requirements of the inter axis coupling is also met and shown for the coupled dynamics case. The SAS in lateral axis may require an additional control augmentation system or adaptive control to meet the Level 1 requirements.

The study shows that the design of a SAS using LQR control algorithm with full state and output feedbacks can be used to meet ADS‐33 handling quality specifications.

The purpose of this study is to understand the behavior of hybrid bio-composites under varied applications.

Fabrication methods and material characterization of various hybrid bio-composites are analyzed by studying the tensile, impact, flexural and hardness of the same. The natural fiber is a manufactured group of assembly of big or short bundles of fiber to produce one or more layers of flat sheets. The natural fiber-reinforced composite materials offer a wide range of properties that are suitable for many engineering-related fields like aerospace, automotive areas. The main characteristics of natural fiber composites are durability, low cost, low weight, high specific strength and equally good mechanical properties.

The tensile properties like tensile strength and tensile modulus of flax/hemp/sisal/Coir/Palmyra fiber-reinforced composites are majorly dependent on the chemical treatment and catalyst usage with fiber. The flexural properties of flax/hemp/sisal/coir/Palmyra are greatly dependent on fiber orientation and fiber length. Impact properties of flax/hemp/sisal/coir/Palmyra are depended on the fiber content, composition and orientation of various fibers.

This study is a review of various research work done on the natural fiber bio-composites exhibiting the factors to be considered for specific load conditions.

Positive experiences with working from home (WFH) during the Corona pandemic (COVID-19) have motivated many employees to continue WFH after the pandemic. However, factors influencing employees' WFH intentions against the backdrop of experiences during pandemic-induced enforced working from home (EWFH) are heterogeneous. This study investigates factors linked to information technology (IT) professionals' WFH intentions.

This mixed-methods study with 92 IT professionals examines the effects of seven predictors for IT professionals' WFH intentions. The predictors are categorized according to the trichotomy of (1) characteristics of the worker, (2) characteristics of the workspace and (3) the work context. Structural equation modeling is used to analyze the quantitative survey data. In addition, IT professionals' responses to six open questions in which they reflect on past experiences and envision future work are examined.

Quantitative results suggest that characteristics of the worker, such as segmentation preference, are influencing WFH intentions stronger than characteristics of the workspace or the work context. Furthermore, perceived productivity during EWFH and gender significantly predict WFH intentions. Contextualizing these quantitative insights, the qualitative data provides a rich yet heterogeneous list of factors why IT professionals prefer (not) to work from home.

Reasons influencing WFH intentions vary due to individual preferences and constraints. Therefore, a differentiated organizational approach is recommended for designing future work arrangements. In addition, the findings suggest that team contracts to formalize working patterns, e.g. to agree on the needed number of physical meetings, can be helpful levers to reduce the complexity of future work that is most likely a mix of WFH and office arrangements.

This study extends literature reflecting on COVID-19-induced changes, specifically the emerging debate about why employees want to continue WFH. It is crucial for researchers and practitioners to understand which factors influence IT professionals' WFH intentions and how they impact the design and implementation of future hybrid work arrangements.

Concrete is a building material widely used for the infrastructural development. Cement is the binding material used for the development of concrete. It is the primary cause of CO₂ emission globally. The purpose of this study is to develop sustainable concrete material to satisfy the present need of construction sector. Geopolymer concrete (GPC) is a sustainable concrete developed without the use of cement. Therefore, investigations are being conducted to replace the cement by 100% with high calcium fly ash (FA) as binding material.

High calcium FA is used as cementitious binder, sodium hydroxide (NaOH) and sodium silicates (Na₂SiO₃) are used as alkaline liquids for developing the GPC. Mix proportions with different NaOH molarities of 4, 6, 8 and 10 M are considered to attain the appropriate mix. The method of curing adopted is ambient and oven curing. Workability, compressive strength and microstructure characteristics of GPC are analysed and presented.

An increase of NaOH in the mix decreases the workability. Compressive strength of 29 MPa is obtained for Mix-I with 8 M under ambient curing. A polynomial relationship is obtained to predict the compressive strength of GPC. Scanning electron microscope analysis is used to confirm the geo-polymerisation process in the microstructure of concrete.

This research work focuses on finding some alternative cementitious material for concrete that can replace ordinary portland cement (OPC) to overcome the CO₂ emission owing to the utilisation of cement in the construction industry. An attempt has been made to use the waste material (high calcium FA) from thermal power plant for the production of GPC. GPC concrete is the novel building material and alternative to conventional concrete. It is the ecofriendly product contributing towards the improvement of the circular economy in the construction industry. There are several factors that affect the property of GPC such as type of binder material, molarity of activator solution and curing condition. The novelty of this work lies in the approach of using locally available high calcium FA along with manufactured sand for the development of GPC. As this approach is rarely investigated, to prove the attainment of compressive strength of GPC with high calcium FA, an attempt has been made during the present investigation. Other influencing parameter which affects the strength gain has also been analysed in this paper.

The purpose of this paper is to review the existing literature on Lean Six Sigma (LSS) for services, construct a morphological analysis (MA) framework and identify research gaps to point to future research possibilities and priorities.

The MA framework is based on literature review of 175 papers published from 2003 to 2015, across 67 journals recognised by Scopus or ABS Academic Journal Quality Guide 2015. A three-phased methodology is used by the authors, with Phase1 featuring a five-stage systematic review protocol to identify relevant journal papers for review; Phase2 presenting a framework for classifying the reviewed papers in terms of their fundamental, methodological, chronological and sector-wise orientations; and Phase3 constructing an MA framework on the classified papers and identifying the research gaps.

The MA framework constructed based on six dimensions, namely, organizational context of applications, desired outcomes, implementation systems, LSS tools and techniques, integration with other management philosophies and evaluation methods, involving 40 focused themes, has revealed 355 distinct research gaps as opportunities for future research.

This paper confirms the existence of substantial scope and points to specific topics for further research in the area of LSS for services. The findings demonstrate the gaps in academic research on the subject. In addition, the study also helps organisational leaders and practitioners to look at LSS from a holistic perspective in the services context.

The MA framework of the existing literature on LSS for services presents a unique, systematic effort to identify research opportunities. In addition, a five-stage systematic review protocol is proposed in this paper. This could be valuable to researchers and practitioners in enabling them to systematically review the literature on research subjects of interest to them.

Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue.

This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review.

To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE.

The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process.

The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment.

The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.

The purpose of this paper is to present the influence of plastic pyrolysis oil blended with gasoline at 10 per cent with and without ethanol additive at 5 per cent in a three-cylinder petrol engine.

The engine is running at standard working processes. The result of 10PPO is compared with pure petrol and additive-added blend. The outcomes clears that, the engine performance is reduced by using plastic oil blended with petrol and NO_x emission rates are increasing substantially.

To control the emission rate, ethanol is added, and corresponding performance reveals that brake thermal efficiency is 4.52 per cent increase compared to pure petrol and 7.03 per cent increase compared to without additive blend.

Emissions such as CO and NOx are considerably controlled with additive blend.

To address service failure issues, scholars have recognized several service recovery (SR) mechanisms. However, there exist many barriers that retard an effective SR process, and those often lead to negative consequences. Although this is a generic problem applicable across markets, it becomes critical in B2B markets, as they deal with high impact and corporate customers. The purpose of this paper is to identify these SR barriers in B2B markets and explore their linkages toward identifying the key driving barriers.

A four-phased methodology to address this call in the IT services industry was used. First, the identification phase led to the selection of 27 barriers based on literature. Second, in the prioritization phase, 12 salient barriers were prioritized with the help of an expert panel. Third, in the modelling phase, the total interpretive structural modelling (TISM) technique was used to examine the mutual influences among these barriers toward modelling their linkages using a digraph. Finally, in the classification phase, these barriers were graphically plotted and classified into four quadrants based on their dependence and driving powers by using Matriced Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis.

Two strategic barriers, namely, technology obsolescence and poor top management commitment, presented the strongest challenges against effective SR, as they were least dependent on other barriers and exerted strong influence over the operational barriers to executing SR.

Because the strategic level barriers, exerting strong influence against effective SR, arise from the strategic choices of board and the C-suite, this paper helps them anticipate the recovery-related after effects of their choices, thus helping them in making better decisions.

This paper contributes to research as it is first of its kind to explore and link SR barriers in B2B markets.