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1 – 10 of 162
Article
Publication date: 31 May 2023

Blerina Bylykbashi and Risto Vasil Filkoski

The purpose of this study is optimization of existing PV system and by making the optimization to reach the heights energy performance from the system.

Abstract

Purpose

The purpose of this study is optimization of existing PV system and by making the optimization to reach the heights energy performance from the system.

Design/methodology/approach

The methodology used in this work is analytical as well as software using PV*SOL premium software. Both methods are used to achieve a more realistic analysis of the results achieved at the end of the work.

Findings

After analyzing the optimization of the PV system in terms of certain atmospheric conditions, it is clear that the optimization of the system is necessary. Through the optimization of the systems, a better performance of the system is achieved, as well as in the case in question, it affects the increase of the energy generated annually up to 500 kWh.

Originality/value

This work is the original work of the author, which represents a part of the topic of the doctorate.

Details

International Journal of Innovation Science, vol. 16 no. 2
Type: Research Article
ISSN: 1757-2223

Keywords

Abstract

Details

Compliance and Financial Crime Risk in Banks
Type: Book
ISBN: 978-1-83549-042-6

Open Access
Article
Publication date: 31 October 2023

Emilia Kääriä and Ahm Shamsuzzoha

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the…

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Abstract

Purpose

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the most visible process to the customer, and therefore, its punctual and fluent order management is vital. It is observed that the high degree of manual work in the O2C process causes mistakes, delays and rework in the process. The purpose of this article is therefore to analyze the case company's current state of the O2C process as well as to identify the areas of development in this process by deploying the means of Lean Six Sigma tools such as value stream mapping (VSM).

Design/methodology/approach

The study was conducted as a mix of quantitative and qualitative analysis. Based on both the quantitative and qualitative data, a workshop on VSM was organized to analyze the current state of the O2C process of a case company, engaged in the energy and environment sector in Finland.

Findings

The results found that excessive manual work was highly connected to inadequate or incorrect data in pricing and invoicing activities, which resulted in canceled invoices. Canceled invoices are visible to the customer and have a negative impact on the customer experience. This study found that by improving the performance of the O2C process activities and improving communication among the internal and external stakeholders, the whole O2C process can perform more effectively and provide better customer value.

Originality/value

The O2C process is the most visible process to the customer and therefore its punctual and fluent order management is vital. To ensure that the O2C process is operating as desired, suitable process performance metrics need to be aligned and followed. The results gathered from the case company's data, questionnaire interviews, and the VSM workshop are all highlighted in this study. The main practical and managerial implications were to understand the real-time O2C process performance, which is necessary to ensure strong performance and enhance continuous improvement of the O2C process that leads to operational excellence and commercial competitiveness of the studied case company.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 11
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 4 April 2023

Prasenjit Biswas, Deepak Patel, Archana Mallik and Sanjeev Das

The purpose of this paper is to develop a concept and design to cast Al alloys/metal matrix composites (MMCs) by continuous casting process. The various steps involved in the…

107

Abstract

Purpose

The purpose of this paper is to develop a concept and design to cast Al alloys/metal matrix composites (MMCs) by continuous casting process. The various steps involved in the evolution of the design have been reported and discussed in this study.

Design/methodology/approach

On the basis of developed design concept, initial prototype design has been prepared in this study. The casting process's melt flow pattern was studied via computer simulation, and the resulting changes were implemented in the original design. The single-phase fluid flow pattern through bottom feeding technique is studied. The equipment was fabricated based on computer simulation and water modelling studies. Finally, validation was performed for the preparation of Al alloys/ MMCs after parameter optimisation. The results were observed in the optical metallography to confirm the alloying and Al MMC preparation.

Findings

The developed continuous casting process with bottom feeding technique for the addition of constituent particles shows more efficiency in comparison to the existing batch processes. The final manufactured setup demonstrates effective Al alloy/MMC production as the basis for final fabrication has been accomplished by both computer simulation and water model test. In addition, the microstructure exhibits homogeneous distribution, validating the reliability of the setup.

Originality/value

Integrating continuous casting with continuous reinforcement or master alloy addition is novel in this area. The constraints that batch production had that have been rectified will also lower the contemporary cost of production.

Details

World Journal of Engineering, vol. 21 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 25 March 2024

Morten Jakobsen

The purpose of this paper is to gain insight into how management accountants can become relevant business partners out of respect for existing locally developed accounts of…

Abstract

Purpose

The purpose of this paper is to gain insight into how management accountants can become relevant business partners out of respect for existing locally developed accounts of economic performance for decision-making.

Design/methodology/approach

The paper is based on qualitative semi-structured interviews with local business actors, in this case, families from seven financially successful Danish dairy farms. The casework and the analysis have been informed by pragmatic constructivism.

Findings

The local business actors do not use the official accounting system for ongoing cost-management-related decision-making. Instead, they use several epistemic methods that include locally developed decision models, experiences, rules of thumb and intuition. The farmers use these vernacular accountings to compensate for the cost management illusion that the formal accounting system tends to create. What the study suggests is that when management accountants engage as business partners, they are likely to enter a space where accounting is already present.

Originality/value

This paper argues that local business actors practice epistemic methods where they develop and use vernacular accountings to support their managerial practice, also in the absence of a professional management accountant. These vernacular accountings may lead the local actors into an illusion because the vernacular accountings do not necessarily have an inherent economic logic and theoretical reliability. The role of the management accountant in such a setting is hence to understand, support and advance local epistemic methods. Becoming a business partner requires a combination of management accounting analytical skills and a sense of empathy and sensitivity regarding what is already at play and how this can become an object of discussion without violating the values of the other.

Details

Qualitative Research in Accounting & Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1176-6093

Keywords

Article
Publication date: 17 June 2021

Ambica Ghai, Pradeep Kumar and Samrat Gupta

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered…

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Abstract

Purpose

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

Design/methodology/approach

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

Findings

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

Research limitations/implications

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

Practical implications

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

Social implications

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

Originality/value

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 27 January 2023

Dhanalakshmi K.M., Kavya G. and Rajkumar S.

This paper aims to propose a single element, dual feed, polarisation diversity antenna. The proposed antenna operates from 2.9 to 10.6 GHz for covering the entire ultra-wideband…

Abstract

Purpose

This paper aims to propose a single element, dual feed, polarisation diversity antenna. The proposed antenna operates from 2.9 to 10.6 GHz for covering the entire ultra-wideband (UWB) frequency range. The antenna is designed for usage in massive multiple input multiple output (MIMO) and closed packaging applications.

Design/methodology/approach

The size of the antenna is 24 × 24 × 1.6 mm3. The radiating element of the antenna is derived from the Sierpinski–Knopp (SK) fractal geometry for miniaturization of the antenna size. The antenna has a single reflecting stub placed between the two orthogonal feeds, to improve isolation.

Findings

The proposed antenna system exhibits S11 < −10 dB, S21 < −15 dB and stable radiation characteristics in the entire operating region. It also offers an envelope correlation coefficient < 0.01, a diversity gain > 9.9 dB and a capacity loss < 0.4 bps/Hz. The simulated and measured outputs were compared and results were found to be in similarity.

Originality/value

The proposed UWB-MIMO antenna has significant size reduction through usage of SK fractal geometry for radiating element. The antenna uses a single radiating element with dual feed. The stub is between the antenna elements which provide a compact and miniaturized MIMO solution for high density packaging applications. The UWB-MIMO antenna provides an isolation better than −20 dB in the entire UWB operating band.

Open Access
Article
Publication date: 18 May 2023

Anna Trubetskaya, Alan Ryan and Frank Murphy

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment…

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Abstract

Purpose

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

Design/methodology/approach

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

Findings

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

Research limitations/implications

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

Originality/value

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.

Details

International Journal of Lean Six Sigma, vol. 15 no. 8
Type: Research Article
ISSN: 2040-4166

Keywords

Open Access
Article
Publication date: 24 January 2024

Jasmine Elizabeth Black, Damian Maye, Anna Krzywoszynska and Stephen Jones

This paper examines how key actors in the UK food system (FS) understand the role of the local food sector in relation to FS resilience.

Abstract

Purpose

This paper examines how key actors in the UK food system (FS) understand the role of the local food sector in relation to FS resilience.

Design/methodology/approach

Discourse analysis was used to assess and compare the framings of the UK FS in 36 publications released during Covid-19 from alternative food networks (AFNs) actors and from other more mainstream FS actors, including the UK government.

Findings

The analysis shows that AFNs actors perceive the UK FS as not resilient and identify local FSs as a route towards greater resilience (“systemic” framing). In contrast, other food actors perceive the UK FS as already resilient, with the role of local food limited to specific functions within the existing system (“add-on” framing). The two groups converge on the importance of dynamic public procurement and local abattoir provision, but this convergence does not undermine the fundamental divergence in the understanding of the role of “the local” in resilient UK FSs. The local food sector’s messages appear to have gone largely unheard in mainstream policy.

Research limitations/implications

The paper presents an analysis of public sector reports focused on the UK FS released during the Covid-19 pandemic years 2020–2021. The corpus inclusion criteria mean that publications during this period which focus on other food sector issues, such social injustices, climate change and health, were not included in the analysis, although they may have touched upon local food issues. The authors further recognise that Covid-19 had a longer lasting effect on FSs than the years 2020–2021, and that many other publications on FSs have been published since. The time span chosen targets the time at which FSs were most disrupted and therefore aims to capture emerging issues and solutions for the UK FS. The authors’ insights should be further validated through a more complete review of both public reports and academic papers covering a wider base of food-related issues and sectors as well as a broader timespan.

Originality/value

A comparison of how different FS actors understand the importance of local food, especially in relation to resilience, has not been undertaken to date. The findings raise important questions about the disconnect between AFN actors and other actors in the framing of resilience. Considering the need to ensure resilience of the UK FS, this study's findings raise important insights for UK food policy about the “local food blindspot” and for food movement actors wishing to progress their vision of transformative change.

Details

British Food Journal, vol. 126 no. 13
Type: Research Article
ISSN: 0007-070X

Keywords

Open Access
Article
Publication date: 12 October 2023

V. Chowdary Boppana and Fahraz Ali

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the…

424

Abstract

Purpose

This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

Design/methodology/approach

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

Findings

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

Research limitations/implications

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

Practical implications

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

Originality/value

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

Details

International Journal of Industrial Engineering and Operations Management, vol. 6 no. 2
Type: Research Article
ISSN: 2690-6090

Keywords

1 – 10 of 162