Surekha Rathi Samundi D. and Rajasekar R.
This study aims to investigate the wake behind an oscillating airfoil at a various angle of incidence and Reynolds number in a deep dynamic stall condition.
Abstract
Purpose
This study aims to investigate the wake behind an oscillating airfoil at a various angle of incidence and Reynolds number in a deep dynamic stall condition.
Design/methodology/approach
NACA 0012 airfoil is allowed to undergo harmonic pitching motion about the quarter chord axis at Reynolds numbers of 0.5 * 105, 1.17 * 105, 1.7 * 105 and 2.12 * 105, and the reduced frequency of 0.1. The experiments are conducted at a set of mean and amplitude angle of attack that covered the angle of incidence from −5° to 25°. The wake rake is placed at a distance of one chord from the trailing edge of the airfoil.
Findings
The hysteresis of the flow during the upstroke and the downstroke motion are captured. The huge growth in the velocity defect and the wake thickness beyond the angle of attack of 15° explicate the appearance of the strong unsteady effects on the wake. The results also show that at the reduced frequency of 0.1, the wake structure is of drag producing type due to the momentum deficit.
Originality/value
Streamwise velocity profile and the turbulent intensity profiles are presented to show the effects of Reynolds number and angle of incidence on the wake behind the oscillating airfoil at the reduced frequency of 0.1, and in the intermediate range of Reynolds number is the novelty of the study.
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Alivarani Mohapatra, Byamakesh Nayak and Kanungo Barada Mohanty
This paper aims to propose a simple, derivative-free novel method named as Nelder–Mead optimization algorithm to estimate the unknown parameters of the photovoltaic (PV) module…
Abstract
Purpose
This paper aims to propose a simple, derivative-free novel method named as Nelder–Mead optimization algorithm to estimate the unknown parameters of the photovoltaic (PV) module considering the environmental conditions.
Design/methodology/approach
At a particular temperature and irradiation, experimental current-voltage (I-V) and power-voltage (P-V) characteristics are drawn and considered as a reference model. The PV system model with unknown model parameters is considered as the adaptive model whose unknown model parameters are to be adapted so that the simulated characteristics closely matches with the experimental characteristics. A single diode (Rsh) model with five unknown model parameters is considered here for the parameter estimation.
Findings
The key advantages of this method are that parameters are estimated considering environmental conditions. Experimental characteristics are considered for parameter estimation which gives accurate results. Parameters are estimated considering both I-V and P-V curves as most of the applications demand extraction of the actual power from the PV module.
Originality/value
The proposed model is compared with other three well-known models available in the literature considering various statistical errors. The results show the superiority of the proposed model with a minimum error for both I-V and P-V characteristics.
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Raja Sreedharan V., Vijaya Sunder M., Vandana Madhavan and Anand Gurumurthy
Nowadays, firms are keen on improving the quality culture in the organizations. The proven success of Lean and Six Sigma has given rise to the synergetic Lean Six Sigma (LSS…
Abstract
Purpose
Nowadays, firms are keen on improving the quality culture in the organizations. The proven success of Lean and Six Sigma has given rise to the synergetic Lean Six Sigma (LSS) approach that has been catching fire in the past one decade. However, there exists a gap between the understanding and implementation of LSS in the organizations, especially in the emerging economies. Taking this as a valuable opportunity, the purpose of this paper is to present a development of LSS training module.
Design/methodology/approach
This study starts with a literature review of LSS to reinforce the understanding of the research subject in scope of manufacturing sector. Then, an online questionnaire was designed and used to collect responses from 181 companies located in the Indian sub-continent. Subsequently, the results obtained from the survey were analyzed using COARSE approach.
Findings
This study reveals two key findings and associated contributions. First, it was found that the overall awareness of LSS within the responded manufacturing firms is about 70.4 percent. Second, there is no single standard training module that exists in any of the sampled firms to cater to their quality programs. Hence, in order to improve the LSS awareness which could subsequently help managers as a resource for creating an efficient workplace, this paper presents a structured LSS training framework.
Research limitations/implications
Although this paper presents the importance of LSS and associated awareness level among the responded firms, more empirical evidence is required to generalize the model findings. Second, this study is scoped to firms that work out of the Indian sub-continent, and this provides a future opportunity to expand the scope of this research toward a global study for a comparison between emerging and developed economies. Third, this study is limited to manufacturing firms and hence paves an opportunity to research on a similar theme in services context as well.
Practical implications
Before embarking on an LSS journey, an organization can use the LSS training module proposed in this study to assess the employee awareness on LSS. Furthermore, organizations that already have a mature LSS practice can incorporate the LSS training module for periodic evaluation of the employees for effective change management.
Originality/value
The training module presented in this paper is the original contribution by the authors. This is no association to any single identifiable organization or associated funding. The direct practical implication of its application in real time is the value that managers could derive from the proposed LSS training framework.
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Vedapradha R and Hariharan Ravi
The study aim is to evaluate the contribution of Blockchain technology (Cryptobanking) using expected operating model (EOM) to address the pain points in reconciliation at middle…
Abstract
Purpose
The study aim is to evaluate the contribution of Blockchain technology (Cryptobanking) using expected operating model (EOM) to address the pain points in reconciliation at middle and back-office operational levels in assessing the significance of this technology on return on investment.
Design/methodology/approach
A structured questionnaire was designed to collect primary data using a stratified sampling method from 120 respondents working in leading Investment banks operating in the geographical locality of urban Bangalore. Demographic variables, accounting variables, data reporting variables, approach variables, variables of EOM were considered to validate the hypothesis with the help of statistical tools, namely ANOVA, and Multiple Stepwise Regression Analysis.
Findings
The results obtained confirm that there is significant difference in reconciliation with implementation of an innovative business process. Financial analysis is the highest predictor of ROI when integrated with technology as the adapted Blockchain innovation in reconciliation is the most influencing factor in enhancing, improving ROI playing a pivotal role in the Investment banks.
Originality/value
Blockchain technology (Cryptobanking) facilitates in transforming the reconciliation process of these banks with improved operational efficiency. Blockchain and settlement platforms offer inter-organization solutions facilitating in the reconciliation of various transactions in real-time through a trust-based network in the form of digital settlements with better consortiums.
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Raja Sreedharan V., R. Raju, Vijaya Sunder M. and Jiju Antony
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
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.
Practical implications
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.
Originality/value
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.
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Detection of low-frequency pressures such as heart rate in the range of 1 Hz is one of the applications of low-frequency resonator. In this paper, the structure of the resonator…
Abstract
Purpose
Detection of low-frequency pressures such as heart rate in the range of 1 Hz is one of the applications of low-frequency resonator. In this paper, the structure of the resonator is in the form of a plate, whose mathematical model has been extracted according to past works and is reported.
Design/methodology/approach
This paper presents an electromechanical microresonator that can be used as an ultra-low-frequency pressure sensor. It is very important to choose the right material for the sensors to have the optimal conditions. In this work, by proposing the innovative use of polytetrafluoroethylene material with low stiffness coefficient, the necessary conditions are provided to reduce the vibration frequency of the resonator.
Findings
The proposed design is simulated with the help of COMSOL, and its results are compared with the results of the mathematical model, which are very close to each other. Therefore, by inferring the results, the authors can rely on accurate simulations and finalize the similar designs with full confidence before fabrication.
Originality/value
There are important advantages regarding the geometry of the proposed design structure that is the possibility of detecting a pressure of 1 Pa only with voltages less than 2 V. On the other hand, the pull-in effect causes very low frequencies to be achieved in detection with the help of the proposed resonator. Also, the linear and nonlinear behavior of the resonator by applying different pressures has been studied and reported to find the appropriate operating range of the resonator and its limitations.
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Paolo Manghi, Michele Artini, Claudio Atzori, Alessia Bardi, Andrea Mannocci, Sandro La Bruzzo, Leonardo Candela, Donatella Castelli and Pasquale Pagano
The purpose of this paper is to present the architectural principles and the services of the D-NET software toolkit. D-NET is a framework where designers and developers find the…
Abstract
Purpose
The purpose of this paper is to present the architectural principles and the services of the D-NET software toolkit. D-NET is a framework where designers and developers find the tools for constructing and operating aggregative infrastructures (systems for aggregating data sources with heterogeneous data models and technologies) in a cost-effective way. Designers and developers can select from a variety of D-NET data management services, can configure them to handle data according to given data models, and can construct autonomic workflows to obtain personalized aggregative infrastructures.
Design/methodology/approach
The paper provides a definition of aggregative infrastructures, sketching architecture, and components, as inspired by real-case examples. It then describes the limits of current solutions, which find their lacks in the realization and maintenance costs of such complex software. Finally, it proposes D-NET as an optimal solution for designers and developers willing to realize aggregative infrastructures. The D-NET architecture and services are presented, drawing a parallel with the ones of aggregative infrastructures. Finally, real-cases of D-NET are presented, to show-case the statement above.
Findings
The D-NET software toolkit is a general-purpose service-oriented framework where designers can construct customized, robust, scalable, autonomic aggregative infrastructures in a cost-effective way. D-NET is today adopted by several EC projects, national consortia and communities to create customized infrastructures under diverse application domains, and other organizations are enquiring for or are experimenting its adoption. Its customizability and extendibility make D-NET a suitable candidate for creating aggregative infrastructures mediating between different scientific domains and therefore supporting multi-disciplinary research.
Originality/value
D-NET is the first general-purpose framework of this kind. Other solutions are available in the literature but focus on specific use-cases and therefore suffer from the limited re-use in different contexts. Due to its maturity, D-NET can also be used by third-party organizations, not necessarily involved in the software design and maintenance.
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Anand S. Patel and Kaushik M. Patel
India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological…
Abstract
Purpose
India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.
Design/methodology/approach
A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.
Findings
Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.
Research limitations/implications
This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.
Originality/value
The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.
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Satish Kumar, Tushar Kolekar, Ketan Kotecha, Shruti Patil and Arunkumar Bongale
Excessive tool wear is responsible for damage or breakage of the tool, workpiece, or machining center. Thus, it is crucial to examine tool conditions during the machining process…
Abstract
Purpose
Excessive tool wear is responsible for damage or breakage of the tool, workpiece, or machining center. Thus, it is crucial to examine tool conditions during the machining process to improve its useful functional life and the surface quality of the final product. AI-based tool wear prediction techniques have proven to be effective in estimating the Remaining Useful Life (RUL) of the cutting tool. However, the model prediction needs improvement in terms of accuracy.
Design/methodology/approach
This paper represents a methodology of fusing a feature selection technique along with state-of-the-art deep learning models. The authors have used NASA milling data sets along with vibration signals for tool wear prediction and performance analysis in 15 different fault scenarios. Multiple steps are used for the feature selection and ranking. Different Long Short-Term Memory (LSTM) approaches are used to improve the overall prediction accuracy of the model for tool wear prediction. LSTM models' performance is evaluated using R-square, Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) parameters.
Findings
The R-square accuracy of the hybrid model is consistently high and has low MAE, MAPE and RMSE values. The average R-square score values for LSTM, Bidirection, Encoder–Decoder and Hybrid LSTM are 80.43, 84.74, 94.20 and 97.85%, respectively, and corresponding average MAPE values are 23.46, 22.200, 9.5739 and 6.2124%. The hybrid model shows high accuracy as compared to the remaining LSTM models.
Originality/value
The low variance, Spearman Correlation Coefficient and Random Forest Regression methods are used to select the most significant feature vectors for training the miscellaneous LSTM model versions and highlight the best approach. The selected features pass to different LSTM models like Bidirectional, Encoder–Decoder and Hybrid LSTM for tool wear prediction. The Hybrid LSTM approach shows a significant improvement in tool wear prediction.