Pub Date : 2023-10-05DOI: 10.1080/23311916.2023.2257955
Wasiu Adeyemi Oke, Nahier Aldhafferi, Saibu Saliu, Taoreed O. Owolabi, Abdullah Alqahtani, Abdullah Almurayh, Talal F. Qahtan
Spinel ferrites are magnetic oxide materials with potentials to promote green technology in magnetic refrigeration which is known to be economically clean, energy saving and efficient. Maximum magnetic entropy change of spinel ferrites decides and controls the applicability as well as the strength of spinel ferrite magnetic oxide since it measures the hugeness of magnetocaloric effect. However, experimental determination of maximum magnetic entropy change requires intensive procedures, costly equipment and consumes appreciable time. Intelligent models are presented in this work using spinel-ferrite-molecular-based descriptors such as the ionic radii of spinel ferrites constituents, applied magnetic field and their concentrations. The developed intelligent models for prediction of spinel ferrite maximum magnetic entropy change include extreme learning machine (ELM) and hybrid genetic-algorithm-coupled support vector regression (GSVR). The developed ELM model has correlation coefficient (CC) and mean absolute error (MAE) of 98.45% and 0.117 J/kg/K, respectively, while the developed GSVR model has CC of 80.87% and MAE of 0.129 J/kg/J. The developed ELM model which is based on empirical risk minimization principle shows better performance over GSVR model that premises on structural minimization risk principle with improvement of 0.06%, 17.86% and 8.765% using root mean square error, CC and MAE yardsticks, respectively. Closeness of the estimates of the developed models with the experimental values is a strong indication of the potentials of the proposed intelligent methods in facilitating practical implementation of magnetic cooling refrigeration to solve energy crisis which promote efficiency and environmental friendliness.
{"title":"Modeling the magnetocaloric effect of spinel ferrites for magnetic refrigeration technology using extreme learning machine and genetically hybridized support vector regression computational methods","authors":"Wasiu Adeyemi Oke, Nahier Aldhafferi, Saibu Saliu, Taoreed O. Owolabi, Abdullah Alqahtani, Abdullah Almurayh, Talal F. Qahtan","doi":"10.1080/23311916.2023.2257955","DOIUrl":"https://doi.org/10.1080/23311916.2023.2257955","url":null,"abstract":"Spinel ferrites are magnetic oxide materials with potentials to promote green technology in magnetic refrigeration which is known to be economically clean, energy saving and efficient. Maximum magnetic entropy change of spinel ferrites decides and controls the applicability as well as the strength of spinel ferrite magnetic oxide since it measures the hugeness of magnetocaloric effect. However, experimental determination of maximum magnetic entropy change requires intensive procedures, costly equipment and consumes appreciable time. Intelligent models are presented in this work using spinel-ferrite-molecular-based descriptors such as the ionic radii of spinel ferrites constituents, applied magnetic field and their concentrations. The developed intelligent models for prediction of spinel ferrite maximum magnetic entropy change include extreme learning machine (ELM) and hybrid genetic-algorithm-coupled support vector regression (GSVR). The developed ELM model has correlation coefficient (CC) and mean absolute error (MAE) of 98.45% and 0.117 J/kg/K, respectively, while the developed GSVR model has CC of 80.87% and MAE of 0.129 J/kg/J. The developed ELM model which is based on empirical risk minimization principle shows better performance over GSVR model that premises on structural minimization risk principle with improvement of 0.06%, 17.86% and 8.765% using root mean square error, CC and MAE yardsticks, respectively. Closeness of the estimates of the developed models with the experimental values is a strong indication of the potentials of the proposed intelligent methods in facilitating practical implementation of magnetic cooling refrigeration to solve energy crisis which promote efficiency and environmental friendliness.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135481182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-05DOI: 10.1080/23311916.2023.2264066
Malikasab Bagawan, Suresh T. Dundur, Rajesh Gurani, Raviraj Shetty, Rajesh Nayak, S. V. Udaya Kumar Shetty, Madhukara Nayak, Adithya Hegde
Elastomers are the class of materials that are widely used in a variety of industrial, commercial, and consumer applications due to their unique mechanical properties, including high elasticity, high flexibility, and high resilience. However, there are many challenges in machining of elastomers such as poor surface finish, build up of heat, degradation of elastomers, etc. To overcome these challenges, cryogenic cooling assistance has been introduced as a means of improving the machinability of elastomers. This paper presents a soft computing approach for optimizing the surface roughness and cutting force during turning of elastomers under different lubrication conditions. Three types of elastomers, namely Nitrile Rubber (NBR), Polyurethane Rubber (PU), and Neoprene Rubber (CR), are studied, and a cryogenic fluid delivery system is employed to improve the machining process. Taguchi’s L27 array is used to vary the input parameters, and a Back-Propagation Artificial Neural Network (BPANN) model is developed to predict the cutting force and surface roughness. The cutting force and surface roughness are analyzed under different cooling conditions, cutting speeds, feeds, and depths of cut for various elastomers. The results show that changes in cutting conditions significantly affect the cutting force and that the type of lubrication used affects the cutting force by altering the material’s physical properties. Cutting force is significantly influenced by cutting conditions, and NBR requires the highest cutting force compared to PU and CR. Further, at a cutting speed of 55 m/min, a feed of 0.11 mm/rev, and a depth of cut of 0.25 mm, the cutting force for NBR (85.1 N), while for PU (75.1 N) and CR (80.3 N), respectively. Finally, with LN2 lubrication conditions, the Cutting Force decreased by 45% and Surface Roughness decreased by 16.9%. This study provides insights into the factors affecting the elastomer machining process, which can be useful for optimizing the machining process parameters and improving machining efficiency.
弹性体是一类广泛应用于各种工业，商业和消费应用的材料，由于其独特的机械性能，包括高弹性，高柔韧性和高弹性。然而，在弹性体的加工中存在许多挑战，如表面光洁度差、热量积累、弹性体降解等。为了克服这些挑战，低温冷却辅助已经被引入作为提高弹性体可加工性的一种手段。提出了一种软计算方法来优化弹性体在不同润滑条件下车削时的表面粗糙度和切削力。对丁腈橡胶(NBR)、聚氨酯橡胶(PU)和氯丁橡胶(CR)三种弹性体进行了研究，并采用低温流体输送系统改进了加工工艺。利用田口L27阵列改变输入参数，建立了反向传播人工神经网络(BPANN)模型来预测切削力和表面粗糙度。分析了各种弹性体在不同冷却条件、切削速度、进给量和切削深度下的切削力和表面粗糙度。结果表明，切削条件的变化对切削力有显著影响，所使用的润滑类型通过改变材料的物理性质来影响切削力。切削力受切削条件影响较大，NBR对切削力的要求高于PU和CR，且在切削速度为55 m/min、进给量为0.11 mm/rev、切削深度为0.25 mm时，NBR的切削力为85.1 N, PU为75.1 N, CR为80.3 N。最后，在LN2润滑条件下，切削力降低了45%，表面粗糙度降低了16.9%。研究结果揭示了弹性体加工过程的影响因素，为优化加工工艺参数，提高加工效率提供了依据。
{"title":"Soft computing approach for optimization of turning characteristics of elastomers under different lubrication conditions","authors":"Malikasab Bagawan, Suresh T. Dundur, Rajesh Gurani, Raviraj Shetty, Rajesh Nayak, S. V. Udaya Kumar Shetty, Madhukara Nayak, Adithya Hegde","doi":"10.1080/23311916.2023.2264066","DOIUrl":"https://doi.org/10.1080/23311916.2023.2264066","url":null,"abstract":"Elastomers are the class of materials that are widely used in a variety of industrial, commercial, and consumer applications due to their unique mechanical properties, including high elasticity, high flexibility, and high resilience. However, there are many challenges in machining of elastomers such as poor surface finish, build up of heat, degradation of elastomers, etc. To overcome these challenges, cryogenic cooling assistance has been introduced as a means of improving the machinability of elastomers. This paper presents a soft computing approach for optimizing the surface roughness and cutting force during turning of elastomers under different lubrication conditions. Three types of elastomers, namely Nitrile Rubber (NBR), Polyurethane Rubber (PU), and Neoprene Rubber (CR), are studied, and a cryogenic fluid delivery system is employed to improve the machining process. Taguchi’s L27 array is used to vary the input parameters, and a Back-Propagation Artificial Neural Network (BPANN) model is developed to predict the cutting force and surface roughness. The cutting force and surface roughness are analyzed under different cooling conditions, cutting speeds, feeds, and depths of cut for various elastomers. The results show that changes in cutting conditions significantly affect the cutting force and that the type of lubrication used affects the cutting force by altering the material’s physical properties. Cutting force is significantly influenced by cutting conditions, and NBR requires the highest cutting force compared to PU and CR. Further, at a cutting speed of 55 m/min, a feed of 0.11 mm/rev, and a depth of cut of 0.25 mm, the cutting force for NBR (85.1 N), while for PU (75.1 N) and CR (80.3 N), respectively. Finally, with LN2 lubrication conditions, the Cutting Force decreased by 45% and Surface Roughness decreased by 16.9%. This study provides insights into the factors affecting the elastomer machining process, which can be useful for optimizing the machining process parameters and improving machining efficiency.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135481572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-04DOI: 10.1080/23311916.2023.2265231
Mohammed M. Sabri, Alaa M. Almansoori, Riyadh Aziz Ghadban
The current research utilizes a low voltage scanning electron microscopy (LV-SEM) with an electron beam along with low loading energy of lower than 2.2 KeV to minimize damage and specimen surface charging. The NovaSEM, is used as an efficient tool in the current study due to the high resolution information it can gather as images and its high magnification nanometers. Polyamide 12 (PA12), as a polymer matrix, and Cloisite 30B (C30B) nanoclay, as a filling material, were the materials tested in this study. From the results obtained, CBS was found to be a significant and valuable tool for certain complex tasks when studying and analyzing polymer/clay interfaces. CBS in conjunction with beam deceleration in a LV-SEM was used to map the C30B clay distribution on PA12 particles and within PA12-nanoclay nanocomposites manufactured from the latter’s clay distribution particles within the polymer particles’ surfaces. This SEM experimentation has demonstrated that using the clay’s air plasma design preceding the composite preparation resulted in removing the large clay assemblages. The plasma treatment has improved the interfacial adhesion and dispersion in the nanoclay/PA12 composite, resulting in similar maximum stress values which were both higher than the pure PA12. Thus, the mechanical tests exhibited performance enhancement for the resulting composites defined in the present work, and the enhancement of this method can be identified via SEM imaging.
{"title":"Scanning electron microscopy as a valuable tool to optimize the properties of the polymer/clay nanocomposites","authors":"Mohammed M. Sabri, Alaa M. Almansoori, Riyadh Aziz Ghadban","doi":"10.1080/23311916.2023.2265231","DOIUrl":"https://doi.org/10.1080/23311916.2023.2265231","url":null,"abstract":"The current research utilizes a low voltage scanning electron microscopy (LV-SEM) with an electron beam along with low loading energy of lower than 2.2 KeV to minimize damage and specimen surface charging. The NovaSEM, is used as an efficient tool in the current study due to the high resolution information it can gather as images and its high magnification nanometers. Polyamide 12 (PA12), as a polymer matrix, and Cloisite 30B (C30B) nanoclay, as a filling material, were the materials tested in this study. From the results obtained, CBS was found to be a significant and valuable tool for certain complex tasks when studying and analyzing polymer/clay interfaces. CBS in conjunction with beam deceleration in a LV-SEM was used to map the C30B clay distribution on PA12 particles and within PA12-nanoclay nanocomposites manufactured from the latter’s clay distribution particles within the polymer particles’ surfaces. This SEM experimentation has demonstrated that using the clay’s air plasma design preceding the composite preparation resulted in removing the large clay assemblages. The plasma treatment has improved the interfacial adhesion and dispersion in the nanoclay/PA12 composite, resulting in similar maximum stress values which were both higher than the pure PA12. Thus, the mechanical tests exhibited performance enhancement for the resulting composites defined in the present work, and the enhancement of this method can be identified via SEM imaging.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135646128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-03DOI: 10.1080/23311916.2023.2262805
Raviraja M Holla, D Suma
This paper introduces a highly efficient approach for progressive image secret sharing through the Discrete Hartley Transform (DHT), offering distinct advantages over existing methods. Leveraging DHT in the color domain, our approach achieves progressive sharing of color images while maintaining robustness and minimal visual impact. By optimizing quantization table selection, our method focuses on maximizing image recovery fidelity. Our extensive experiments showcase the efficacy of our proposed method, highlighting its potential for secure image sharing and superior image quality enabled by the real-number DHT transformation. Notably, our approach demonstrates strong security robustness and high-quality image reconstruction through histogram analysis. Objective assessment values of 88.106 (PSNR), 0.884 (NCC), 0.095 (NAE), and 0.895 (SSIM) underscore the superiority of our method. These results, coupled with its unique contributions and key factors, position our work as a promising solution in the field of image security and distribution, motivating further exploration and inspiring related research endeavors.
{"title":"Progressive Hartley image secret sharing for high-quality image recovery","authors":"Raviraja M Holla, D Suma","doi":"10.1080/23311916.2023.2262805","DOIUrl":"https://doi.org/10.1080/23311916.2023.2262805","url":null,"abstract":"This paper introduces a highly efficient approach for progressive image secret sharing through the Discrete Hartley Transform (DHT), offering distinct advantages over existing methods. Leveraging DHT in the color domain, our approach achieves progressive sharing of color images while maintaining robustness and minimal visual impact. By optimizing quantization table selection, our method focuses on maximizing image recovery fidelity. Our extensive experiments showcase the efficacy of our proposed method, highlighting its potential for secure image sharing and superior image quality enabled by the real-number DHT transformation. Notably, our approach demonstrates strong security robustness and high-quality image reconstruction through histogram analysis. Objective assessment values of 88.106 (PSNR), 0.884 (NCC), 0.095 (NAE), and 0.895 (SSIM) underscore the superiority of our method. These results, coupled with its unique contributions and key factors, position our work as a promising solution in the field of image security and distribution, motivating further exploration and inspiring related research endeavors.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135740416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.1080/23311916.2023.2262820
Vijayalaxmi Sonkamble, K. Narasimhan, Asim Tewari
The progressive deformations of a shear band formation were studied to understand the fracture mechanism of AA6082(T6) sheets. The fracture characteristics of the alloys can be dictated by the intermetallic particles. Damage evolution of the alloy is quantitatively characterized as a function of strain. Larger, elongated, and favorably oriented particles fracture first (with initial deformation), and with progressive deformation (blanking), smaller and rounded particles start breaking. These broken particles become a crack nucleus for matrix cracking and coalescences. In the initial deformation stages, fragmentation of particles takes place without significant void growth. However, with subsequent deformation stages, the fragmentation process has been enhanced with multi-fragmentation and re-fracturing of previously broken particles. Larger particles nucleate voids at much lower strains with void growth. Crack has initiated in the shear band, preferably from the punch side (the punch side is sharper than the die side), and cracks are found almost parallel to the loading axis.
{"title":"Microstructural stages of intermetallic fracture during sheared deformation of AA6082 sheet","authors":"Vijayalaxmi Sonkamble, K. Narasimhan, Asim Tewari","doi":"10.1080/23311916.2023.2262820","DOIUrl":"https://doi.org/10.1080/23311916.2023.2262820","url":null,"abstract":"The progressive deformations of a shear band formation were studied to understand the fracture mechanism of AA6082(T6) sheets. The fracture characteristics of the alloys can be dictated by the intermetallic particles. Damage evolution of the alloy is quantitatively characterized as a function of strain. Larger, elongated, and favorably oriented particles fracture first (with initial deformation), and with progressive deformation (blanking), smaller and rounded particles start breaking. These broken particles become a crack nucleus for matrix cracking and coalescences. In the initial deformation stages, fragmentation of particles takes place without significant void growth. However, with subsequent deformation stages, the fragmentation process has been enhanced with multi-fragmentation and re-fracturing of previously broken particles. Larger particles nucleate voids at much lower strains with void growth. Crack has initiated in the shear band, preferably from the punch side (the punch side is sharper than the die side), and cracks are found almost parallel to the loading axis.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136278909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.1080/23311916.2023.2257945
Sidra Naz, M.H. Tahir, Farrukh Jamal, Muhammad Ameeq, Shakaiba Shafiq, John T. Mendy
In this study, we presented a group acceptance sampling plan for situations in which the lifetime of an item followed a flexible new Kumaraswamy exponential distribution for applications to quality control reliability. This study includes a detailed analysis of the operating characteristic function values, producer risk, and minimum required group size for the acceptance number, which are determined by three shape parameters. To determine the quality index, we used the median and tested various parametric values to obtain the optimized values. These optimized values are presented in the tables and graphically for a better understanding. In addition, we explain the results of our study using two real-life datasets and an example. Comparison has been also made between GASP and OSP.
{"title":"A group acceptance sampling plan based on flexible new Kumaraswamy exponential distribution: An application to quality control reliability","authors":"Sidra Naz, M.H. Tahir, Farrukh Jamal, Muhammad Ameeq, Shakaiba Shafiq, John T. Mendy","doi":"10.1080/23311916.2023.2257945","DOIUrl":"https://doi.org/10.1080/23311916.2023.2257945","url":null,"abstract":"In this study, we presented a group acceptance sampling plan for situations in which the lifetime of an item followed a flexible new Kumaraswamy exponential distribution for applications to quality control reliability. This study includes a detailed analysis of the operating characteristic function values, producer risk, and minimum required group size for the acceptance number, which are determined by three shape parameters. To determine the quality index, we used the median and tested various parametric values to obtain the optimized values. These optimized values are presented in the tables and graphically for a better understanding. In addition, we explain the results of our study using two real-life datasets and an example. Comparison has been also made between GASP and OSP.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135344849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-28DOI: 10.1080/23311916.2023.2261231
C.P. Natesh, Y.M. Shashidhara, H.J. Amarendra, Raviraj Shetty, Rajesh Nayak, S. V. UdayKumar Shetty, Madhukara Nayak, Adithya Hegde
This paper discusses about process input optimization to obtain desired output characteristics such as Surface Roughness (microns), Thrust Force (N) and Torque (N-m) during drilling of AISI 316 L Stainless Steel under minimum quantity formulated neem oil lubrication condition based on Taguchi Design of Experiments (TDOE), Response Surface Methodology (RSM) and Desirability Functional Analysis (DFA) by varying flow rate (ml.min−1), stand-off distance (mm), flow pressure (Bar) and nozzle exit diameter (mm). Formulated Neem Oil possesses natural lubricating properties that reduce friction and heat generation, thus prolonging the tool life and improving surface finish. Additionally, it is biodegradable and environmentally friendly, making it a sustainable choice for machining operations. From the experimental investigation using TDOE, it was observed that there was considerable improvement in thrust force, surface roughness and torque with modified neem oil as a lubricant. Further, plot for main effects and Analysis of Variance (ANOVA) are successfully used to identify the optimum process input parameters and their percentage of contribution (P%) on output parameters. RSM is successfully used to generate a second order mathematical model which can be effectively used to analyze the process parameters. Further, from Desirability Functional Analysis (DFA), minimum surface roughness (0.34 microns), thrust force (1292.37 N) and torque (14.71 N-m) value were predicted. Finally, Back Propagation Artificial Neural Network (BPANN) analysis has been adopted to predict the surface roughness, thrust force and torque with a minimal error of 1.46%, 0.017% & 0.17%, respectively. The adoption of Neem oil formulations has been successful in improving machining characteristics. Its versatility across an array of machining processes and materials, in tandem with the global momentum toward greener manufacturing paradigms, positions it as a promising lubricant for various machining practices.
{"title":"Soft computing for sustainable drilling of AISI 316L stainless steel under formulated neem oil minimum quantity lubrication condition","authors":"C.P. Natesh, Y.M. Shashidhara, H.J. Amarendra, Raviraj Shetty, Rajesh Nayak, S. V. UdayKumar Shetty, Madhukara Nayak, Adithya Hegde","doi":"10.1080/23311916.2023.2261231","DOIUrl":"https://doi.org/10.1080/23311916.2023.2261231","url":null,"abstract":"This paper discusses about process input optimization to obtain desired output characteristics such as Surface Roughness (microns), Thrust Force (N) and Torque (N-m) during drilling of AISI 316 L Stainless Steel under minimum quantity formulated neem oil lubrication condition based on Taguchi Design of Experiments (TDOE), Response Surface Methodology (RSM) and Desirability Functional Analysis (DFA) by varying flow rate (ml.min−1), stand-off distance (mm), flow pressure (Bar) and nozzle exit diameter (mm). Formulated Neem Oil possesses natural lubricating properties that reduce friction and heat generation, thus prolonging the tool life and improving surface finish. Additionally, it is biodegradable and environmentally friendly, making it a sustainable choice for machining operations. From the experimental investigation using TDOE, it was observed that there was considerable improvement in thrust force, surface roughness and torque with modified neem oil as a lubricant. Further, plot for main effects and Analysis of Variance (ANOVA) are successfully used to identify the optimum process input parameters and their percentage of contribution (P%) on output parameters. RSM is successfully used to generate a second order mathematical model which can be effectively used to analyze the process parameters. Further, from Desirability Functional Analysis (DFA), minimum surface roughness (0.34 microns), thrust force (1292.37 N) and torque (14.71 N-m) value were predicted. Finally, Back Propagation Artificial Neural Network (BPANN) analysis has been adopted to predict the surface roughness, thrust force and torque with a minimal error of 1.46%, 0.017% & 0.17%, respectively. The adoption of Neem oil formulations has been successful in improving machining characteristics. Its versatility across an array of machining processes and materials, in tandem with the global momentum toward greener manufacturing paradigms, positions it as a promising lubricant for various machining practices.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-27DOI: 10.1080/23311916.2023.2262812
Anuj Deshmukh, Yogeesha Pai
With the application of composites in various industries viz. aerospace, automobile, defence and marine, it becomes essential to carry out the Compression After Impact (CAI) and vibration tests to study their behavior in different environmental conditions. This study investigates the significance of CAI and damping characteristics of the aramid-basalt/epoxy interply composites under different hygrothermal conditions. In this examination, laminates were exposed to three different ageing conditions, namely, ambient (ageing in distilled water at 25°C), sub-zero (ageing in distilled water at −10°C), and humid (ageing in an environmental chamber maintained at 40°C and 60% relative humidity) for a duration of 180 days. Moisture saturated specimens were subjected to low velocity impacts (LVI) of 10 J and 15 J energy levels using drop weight impact method. CAI test was carried out on post impact specimens to analyze the residual compressive strengths. Furthermore, impact hammer and impedance tube tests were also conducted to compute the damping properties and sound transmission loss (dB) of the specimens. The results were compared with the pristine samples to analyze the effect of hygrothermal conditions on the CAI and vibrational properties. The results indicated that the moisture has a detrimental effect on the compressive residual strength, natural frequency, and sound transmission loss of the specimens. The Scanning Electron Microscopy (SEM) of fractured CAI specimens displayed the occurrence of various types of damages such as fiber fractures, delamination, matrix fractures, etc as the primary reason for failure of the specimens.
{"title":"Compression after impact & vibrational analysis of aramid-basalt/epoxy interply composites under hygrothermal conditions","authors":"Anuj Deshmukh, Yogeesha Pai","doi":"10.1080/23311916.2023.2262812","DOIUrl":"https://doi.org/10.1080/23311916.2023.2262812","url":null,"abstract":"With the application of composites in various industries viz. aerospace, automobile, defence and marine, it becomes essential to carry out the Compression After Impact (CAI) and vibration tests to study their behavior in different environmental conditions. This study investigates the significance of CAI and damping characteristics of the aramid-basalt/epoxy interply composites under different hygrothermal conditions. In this examination, laminates were exposed to three different ageing conditions, namely, ambient (ageing in distilled water at 25°C), sub-zero (ageing in distilled water at −10°C), and humid (ageing in an environmental chamber maintained at 40°C and 60% relative humidity) for a duration of 180 days. Moisture saturated specimens were subjected to low velocity impacts (LVI) of 10 J and 15 J energy levels using drop weight impact method. CAI test was carried out on post impact specimens to analyze the residual compressive strengths. Furthermore, impact hammer and impedance tube tests were also conducted to compute the damping properties and sound transmission loss (dB) of the specimens. The results were compared with the pristine samples to analyze the effect of hygrothermal conditions on the CAI and vibrational properties. The results indicated that the moisture has a detrimental effect on the compressive residual strength, natural frequency, and sound transmission loss of the specimens. The Scanning Electron Microscopy (SEM) of fractured CAI specimens displayed the occurrence of various types of damages such as fiber fractures, delamination, matrix fractures, etc as the primary reason for failure of the specimens.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135536591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Supply chain (SC) performance is being advanced through digitalization, automation, and real-time visibility, leading to improved operational efficiency, optimized inventory management, and proactive solutions for problems. This study focuses on managing SC performance by developing a real-time Microsoft Power BI dashboard using the ADR method. The aim is to help small business owners effectively and affordably manage their supply chains. The research analyzed data from Ly Foods Ltd. and utilized Microsoft Power BI to create the dashboard. The study highlights how this state-of-the-art dashboard enhances the measurement of operational and decision-making processes by providing efficient, visible, accessible, and shareable information. The findings demonstrate the potential benefits of leveraging advanced technologies to enhance supply chain management (SCM) practices. This research makes a significant contribution to the field of SCM by illustrating how SC performance can be managed using the ADR method and the SC key performance indicators (KPIs). The results of this study have important implications for businesses of all sizes, as they enhance SC efficiency and profitability.
通过数字化、自动化和实时可见性，供应链(SC)的性能得到了提升，从而提高了运营效率，优化了库存管理，并为问题提供了积极的解决方案。本研究的重点是通过使用ADR方法开发一个实时Microsoft Power BI仪表板来管理SC绩效。其目的是帮助小企业主有效和经济地管理他们的供应链。该研究分析了来自Ly Foods Ltd.的数据，并利用Microsoft Power BI创建了仪表板。该研究强调了这种最先进的仪表板如何通过提供高效、可见、可访问和可共享的信息来增强对运营和决策过程的测量。研究结果证明了利用先进技术来增强供应链管理(SCM)实践的潜在好处。本研究通过说明如何使用ADR方法和供应链关键绩效指标(kpi)来管理供应链绩效，对供应链管理领域做出了重大贡献。本研究的结果对各种规模的企业都有重要的意义，因为它们提高了供应链的效率和盈利能力。
{"title":"Managing supply chain performance using a real time Microsoft Power BI dashboard by action design research (ADR) method","authors":"Dewan Hafiz Nabil, Md. Habibur Rahman, Altaf Hussain Chowdhury, Brenno Castrillon Menezes","doi":"10.1080/23311916.2023.2257924","DOIUrl":"https://doi.org/10.1080/23311916.2023.2257924","url":null,"abstract":"Supply chain (SC) performance is being advanced through digitalization, automation, and real-time visibility, leading to improved operational efficiency, optimized inventory management, and proactive solutions for problems. This study focuses on managing SC performance by developing a real-time Microsoft Power BI dashboard using the ADR method. The aim is to help small business owners effectively and affordably manage their supply chains. The research analyzed data from Ly Foods Ltd. and utilized Microsoft Power BI to create the dashboard. The study highlights how this state-of-the-art dashboard enhances the measurement of operational and decision-making processes by providing efficient, visible, accessible, and shareable information. The findings demonstrate the potential benefits of leveraging advanced technologies to enhance supply chain management (SCM) practices. This research makes a significant contribution to the field of SCM by illustrating how SC performance can be managed using the ADR method and the SC key performance indicators (KPIs). The results of this study have important implications for businesses of all sizes, as they enhance SC efficiency and profitability.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135538408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.1080/23311916.2023.2261236
Breda Kearney, Olivia McDermott
This study seeks to investigate the impact of strengthened requirements for clinical evaluation for medical device manufacturers in Europe due to the new Medical Device Regulations. Qualitative interviews were conducted with eight clinical evaluation consultants from eight different European countries who review and approve clinical evaluation reports for manufacturers prior to their submission to notified bodies. The study describes the sources of device clinical evaluation evidence and describes the consultants’ recommendations and challenges encountered when reviewing Clinical Evaluation Reports. The findings from the study demonstrate that understanding what constitutes sufficient clinical evidence poses the biggest challenge to the generation of an MDR-compliant Clinical Evaluation Report. Additionally, the study identified a knowledge and skills gap in the generation and assessment of acceptable regulatory and clinical data. Further, there is heterogeneity in the reviews of Clinical Evaluation Reports received by consultants and inadequate guidance to enable compliance by manufacturers. This study found that some manufacturers of certain CE-marked medical devices are planning to remove them from the EU market upon expiration of their certificate, and in the case of new innovative devices, some manufacturers may launch in other non-EU markets.
{"title":"Challenges faced by manufacturers with clinical evaluation under the new European Medical Device Regulations","authors":"Breda Kearney, Olivia McDermott","doi":"10.1080/23311916.2023.2261236","DOIUrl":"https://doi.org/10.1080/23311916.2023.2261236","url":null,"abstract":"This study seeks to investigate the impact of strengthened requirements for clinical evaluation for medical device manufacturers in Europe due to the new Medical Device Regulations. Qualitative interviews were conducted with eight clinical evaluation consultants from eight different European countries who review and approve clinical evaluation reports for manufacturers prior to their submission to notified bodies. The study describes the sources of device clinical evaluation evidence and describes the consultants’ recommendations and challenges encountered when reviewing Clinical Evaluation Reports. The findings from the study demonstrate that understanding what constitutes sufficient clinical evidence poses the biggest challenge to the generation of an MDR-compliant Clinical Evaluation Report. Additionally, the study identified a knowledge and skills gap in the generation and assessment of acceptable regulatory and clinical data. Further, there is heterogeneity in the reviews of Clinical Evaluation Reports received by consultants and inadequate guidance to enable compliance by manufacturers. This study found that some manufacturers of certain CE-marked medical devices are planning to remove them from the EU market upon expiration of their certificate, and in the case of new innovative devices, some manufacturers may launch in other non-EU markets.","PeriodicalId":10464,"journal":{"name":"Cogent Engineering","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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