Multivariate data analysis and machine learning classification have become popular tools to extract features without physical models for complex environments recognition. For electronic noses, time sampling over multiple sensing elements must be a fair compromise between a period sufficiently long to output a meaningful information pattern and sufficiently short to minimize training time for practical applications. Particularly when a reactivity’s kinetics differ from the thermodynamics in sensitive materials, finding the best compromise to get the most from the data is not obvious. Here, we investigate the influence of data acquisition to improve or alter data clustering for molecular recognition on a conducting polymer electronic nose. We found out that waiting for sensing elements to reach their steady state is not required for classification, and that reducing data acquisition down to the first dynamical information suffices to recognize molecular gases by principal component analysis with the same materials. Especially for online inference, this study shows that a good sensing array is not an array of good sensors, and that new figures of merit should be defined for sensing hardware using machine learning pattern recognition rather than metrology.
{"title":"Steady vs. Dynamic Contributions of Different Doped Conducting Polymers in the Principal Components of an Electronic Nose’s Response","authors":"Wiem Haj Ammar, Aicha Boujnah, Aimen Boubaker, Adel Kalboussi, Kamal Lmimouni, Sébastien Pecqueur","doi":"10.3390/eng4040141","DOIUrl":"https://doi.org/10.3390/eng4040141","url":null,"abstract":"Multivariate data analysis and machine learning classification have become popular tools to extract features without physical models for complex environments recognition. For electronic noses, time sampling over multiple sensing elements must be a fair compromise between a period sufficiently long to output a meaningful information pattern and sufficiently short to minimize training time for practical applications. Particularly when a reactivity’s kinetics differ from the thermodynamics in sensitive materials, finding the best compromise to get the most from the data is not obvious. Here, we investigate the influence of data acquisition to improve or alter data clustering for molecular recognition on a conducting polymer electronic nose. We found out that waiting for sensing elements to reach their steady state is not required for classification, and that reducing data acquisition down to the first dynamical information suffices to recognize molecular gases by principal component analysis with the same materials. Especially for online inference, this study shows that a good sensing array is not an array of good sensors, and that new figures of merit should be defined for sensing hardware using machine learning pattern recognition rather than metrology.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136061141","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}
A quantitative evaluation of the musical timbre and its variations is important for the analysis of audio recordings and computer-aided music composition. Using the FFT acoustic descriptors and their representation in an abstract timbral space, variations in a sample of monophonic sounds of chordophones (violin, cello) and aerophones (trumpet, transverse flute, and clarinet) sounds are analyzed. It is concluded that the FFT acoustic descriptors allow us to distinguish the timbral variations in the musical dynamics, including crescendo and vibrato. Furthermore, using the Random Forest algorithm, it is shown that the FFT-Acoustic provides a statistically significant classification to distinguish musical instruments, families of instruments, and dynamics. We observed an improvement in the FFT-Acoustic descriptors when classifying pitch compared to some timbral features of Librosa.
{"title":"Comparative Study of Musical Timbral Variations: Crescendo and Vibrato Using FFT-Acoustic Descriptor","authors":"Yubiry Gonzalez, Ronaldo C. Prati","doi":"10.3390/eng4030140","DOIUrl":"https://doi.org/10.3390/eng4030140","url":null,"abstract":"A quantitative evaluation of the musical timbre and its variations is important for the analysis of audio recordings and computer-aided music composition. Using the FFT acoustic descriptors and their representation in an abstract timbral space, variations in a sample of monophonic sounds of chordophones (violin, cello) and aerophones (trumpet, transverse flute, and clarinet) sounds are analyzed. It is concluded that the FFT acoustic descriptors allow us to distinguish the timbral variations in the musical dynamics, including crescendo and vibrato. Furthermore, using the Random Forest algorithm, it is shown that the FFT-Acoustic provides a statistically significant classification to distinguish musical instruments, families of instruments, and dynamics. We observed an improvement in the FFT-Acoustic descriptors when classifying pitch compared to some timbral features of Librosa.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136236450","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}
Houdaifa Khalifa, Olusegun Stanley Tomomewo, Uchenna Frank Ndulue, Badr Eddine Berrehal
The accurate prediction of underground formation lithology class and tops is a critical challenge in the oil industry. This paper presents a machine-learning (ML) approach to predict lithology from drilling data, offering real-time litho-facies identification. The ML model, applied via the web app “GeoVision”, achieves remarkable performance during its training phase with a mean accuracy of 95% and a precision of 98%. The model successfully predicts claystone, marl, and sandstone classes with high precision scores. Testing on new data yields an overall accuracy of 95%, providing valuable insights and setting a benchmark for future efforts. To address the limitations of current methodologies, such as time lags and lack of real-time data, we utilize drilling data as a unique endeavor to predict lithology. Our approach integrates nine drilling parameters, going beyond the narrow focus on the rate of penetration (ROP) often seen in previous research. The model was trained and evaluated using the open Volve field dataset, and careful data preprocessing was performed to reduce features, balance the sample distribution, and ensure an unbiased dataset. The innovative methodology demonstrates exceptional performance and offers substantial advantages for real-time geosteering. The accessibility of our models is enhanced through the user-friendly web app “GeoVision”, enabling effective utilization by drilling engineers and marking a significant advancement in the field.
{"title":"Machine Learning-Based Real-Time Prediction of Formation Lithology and Tops Using Drilling Parameters with a Web App Integration","authors":"Houdaifa Khalifa, Olusegun Stanley Tomomewo, Uchenna Frank Ndulue, Badr Eddine Berrehal","doi":"10.3390/eng4030139","DOIUrl":"https://doi.org/10.3390/eng4030139","url":null,"abstract":"The accurate prediction of underground formation lithology class and tops is a critical challenge in the oil industry. This paper presents a machine-learning (ML) approach to predict lithology from drilling data, offering real-time litho-facies identification. The ML model, applied via the web app “GeoVision”, achieves remarkable performance during its training phase with a mean accuracy of 95% and a precision of 98%. The model successfully predicts claystone, marl, and sandstone classes with high precision scores. Testing on new data yields an overall accuracy of 95%, providing valuable insights and setting a benchmark for future efforts. To address the limitations of current methodologies, such as time lags and lack of real-time data, we utilize drilling data as a unique endeavor to predict lithology. Our approach integrates nine drilling parameters, going beyond the narrow focus on the rate of penetration (ROP) often seen in previous research. The model was trained and evaluated using the open Volve field dataset, and careful data preprocessing was performed to reduce features, balance the sample distribution, and ensure an unbiased dataset. The innovative methodology demonstrates exceptional performance and offers substantial advantages for real-time geosteering. The accessibility of our models is enhanced through the user-friendly web app “GeoVision”, enabling effective utilization by drilling engineers and marking a significant advancement in the field.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136236416","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}
Adopting a multiscale approach is crucial for optimizing urban and building performance, prompting inquiries about the link between a technology’s local efficiency (building scale) and its broader impact (city-wide). To investigate this correlation and devise effective strategies for enhancing building and city energy performance, we experimentally examined a commercial nano-ceramic Thermal Barrier Coating (TBC) on a small-scale building and assessed numerically its influence on mitigating Urban Heat Islands (UHIs) at a city scale, translated in our case by the use of the thermal comfort index: the Universal Thermal Climate Index (UTCI). Our results reveal that the coating significantly curbs heat transfer locally, reducing surface temperatures by over 50 ∘C compared to traditional roofs and attenuating more than 70% of heat flux, potentially alleviating air conditioning demands and associated urban heat effects. However, implementing such coatings across a city does not notably advance overall efficiency and might trigger minor overheating on thermal perception. Hence, while nano-ceramic coatings indirectly aid UHI mitigation, they are not a standalone fix; instead, an integrated strategy involving efficient coatings, sustainable urban planning, and increased vegetation emerges as the optimal path toward creating enduringly sustainable, pleasant, and efficient urban environments to counter urban heat challenges effectively.
{"title":"Experimental and Numerical Analysis on a Thermal Barrier Coating with Nano-Ceramic Base: A Potential Solution to Reduce Urban Heat Islands?","authors":"Bruno Malet-Damour, Dimitri Bigot, Garry Rivière","doi":"10.3390/eng4030138","DOIUrl":"https://doi.org/10.3390/eng4030138","url":null,"abstract":"Adopting a multiscale approach is crucial for optimizing urban and building performance, prompting inquiries about the link between a technology’s local efficiency (building scale) and its broader impact (city-wide). To investigate this correlation and devise effective strategies for enhancing building and city energy performance, we experimentally examined a commercial nano-ceramic Thermal Barrier Coating (TBC) on a small-scale building and assessed numerically its influence on mitigating Urban Heat Islands (UHIs) at a city scale, translated in our case by the use of the thermal comfort index: the Universal Thermal Climate Index (UTCI). Our results reveal that the coating significantly curbs heat transfer locally, reducing surface temperatures by over 50 ∘C compared to traditional roofs and attenuating more than 70% of heat flux, potentially alleviating air conditioning demands and associated urban heat effects. However, implementing such coatings across a city does not notably advance overall efficiency and might trigger minor overheating on thermal perception. Hence, while nano-ceramic coatings indirectly aid UHI mitigation, they are not a standalone fix; instead, an integrated strategy involving efficient coatings, sustainable urban planning, and increased vegetation emerges as the optimal path toward creating enduringly sustainable, pleasant, and efficient urban environments to counter urban heat challenges effectively.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135107081","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}
Mining plays a pivotal role in economies worldwide, contributing to employment, infrastructure, and the supply of essential raw materials. Chile’s global mining powerhouse, particularly in copper production, exemplifies this industry’s economic significance. The supplier selection process in the mining industry, a complex and multifaceted task, is explored in detail, specifically focusing on explosives procurement, a critical component for mineral extraction. The paper underscores the importance of informed supplier selection decisions, especially for SMEs, which often need more resources and capabilities for efficient management. To address these challenges, the study proposes applying the Analytic Hierarchical Process (AHP), a multi-criteria decision-making methodology, to identify and prioritize the criteria and sub-criteria pertinent to choosing explosives suppliers. A case study in the Coquimbo Region, Chile, involving SMEs in the mining sector is the empirical foundation for this research. Our research highlights that the foremost criterion for SMEs in the Coquimbo Region’s mining sector is “relationship with the environment and communities”. This reflects the national context of mining community tensions and the rising environmental standards and social expectations, which can profoundly impact mining operations. “Quality of products and services” is the second most crucial criterion, underscoring SMEs’ drive to enhance productivity and efficiency. “Contractual compliance” follows closely, signifying the integration of SMEs into broader social and environmental sustainability efforts. Conversely, “innovation” ranks as the least relevant criterion, indicating that SMEs prioritize traditional processes due to limited resources and cost constraints. These insights are valuable for mining supplier company managers, emphasizing the need for sustainability, corporate social responsibility, and management control systems.
{"title":"Analytical Hierarchical Process to Establish the Criteria for Choosing Explosives Suppliers in Small and Medium Mining Companies","authors":"Edison Ramírez Olivares, Mauricio Castillo-Vergara","doi":"10.3390/eng4030137","DOIUrl":"https://doi.org/10.3390/eng4030137","url":null,"abstract":"Mining plays a pivotal role in economies worldwide, contributing to employment, infrastructure, and the supply of essential raw materials. Chile’s global mining powerhouse, particularly in copper production, exemplifies this industry’s economic significance. The supplier selection process in the mining industry, a complex and multifaceted task, is explored in detail, specifically focusing on explosives procurement, a critical component for mineral extraction. The paper underscores the importance of informed supplier selection decisions, especially for SMEs, which often need more resources and capabilities for efficient management. To address these challenges, the study proposes applying the Analytic Hierarchical Process (AHP), a multi-criteria decision-making methodology, to identify and prioritize the criteria and sub-criteria pertinent to choosing explosives suppliers. A case study in the Coquimbo Region, Chile, involving SMEs in the mining sector is the empirical foundation for this research. Our research highlights that the foremost criterion for SMEs in the Coquimbo Region’s mining sector is “relationship with the environment and communities”. This reflects the national context of mining community tensions and the rising environmental standards and social expectations, which can profoundly impact mining operations. “Quality of products and services” is the second most crucial criterion, underscoring SMEs’ drive to enhance productivity and efficiency. “Contractual compliance” follows closely, signifying the integration of SMEs into broader social and environmental sustainability efforts. Conversely, “innovation” ranks as the least relevant criterion, indicating that SMEs prioritize traditional processes due to limited resources and cost constraints. These insights are valuable for mining supplier company managers, emphasizing the need for sustainability, corporate social responsibility, and management control systems.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135202890","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}
The science of catalysis has a direct impact on the world economy and the energy environment that positively affects the environmental ecosystem of our universe. Any catalyst, before being tested in a reaction, must undergo a specific characterization protocol to simulate its behavior under reaction conditions. In this work, these steps that must be carried out are presented, both generically and with examples, to the support and to the catalyst itself before and after the reaction. The first stage consists of knowing the textural and structural properties of the support used for the preparation of the catalysts. The specific surface area and the pore volume are fundamental properties, measured by N2 adsorption at −196 °C when preparing the catalyst, dispersing the active phase, and allowing the diffusion and reaction of the reactants and products on its surface. If knowing the structure of the catalyst is important to control its behavior against a reaction, being able to analyze the catalyst used under the reaction conditions is essential to have knowledge about what has happened inside the catalytic reactor. The most common characterization techniques in heterogeneous catalysis laboratories are those described in this work. As an application example, the catalytic conversion of CO2 to CH4 has been selected and summarized in this work. In this case, the synthesis and characterization of Cu and Ni catalysts supported on two Al2O3 with different textural properties, 92 and 310 m2/g, that allow for obtaining various metallic dispersions, between 3.3 and 25.5%, is described. The catalytic behavior of these materials is evaluated from the CO2 methanation reaction, as well as their stability from the properties they present before and after the reaction.
{"title":"On the Genesis of a Catalyst: A Brief Review with an Experimental Case Study","authors":"Simón Yunes, Jeffrey Kenvin, Antonio Gil","doi":"10.3390/eng4030136","DOIUrl":"https://doi.org/10.3390/eng4030136","url":null,"abstract":"The science of catalysis has a direct impact on the world economy and the energy environment that positively affects the environmental ecosystem of our universe. Any catalyst, before being tested in a reaction, must undergo a specific characterization protocol to simulate its behavior under reaction conditions. In this work, these steps that must be carried out are presented, both generically and with examples, to the support and to the catalyst itself before and after the reaction. The first stage consists of knowing the textural and structural properties of the support used for the preparation of the catalysts. The specific surface area and the pore volume are fundamental properties, measured by N2 adsorption at −196 °C when preparing the catalyst, dispersing the active phase, and allowing the diffusion and reaction of the reactants and products on its surface. If knowing the structure of the catalyst is important to control its behavior against a reaction, being able to analyze the catalyst used under the reaction conditions is essential to have knowledge about what has happened inside the catalytic reactor. The most common characterization techniques in heterogeneous catalysis laboratories are those described in this work. As an application example, the catalytic conversion of CO2 to CH4 has been selected and summarized in this work. In this case, the synthesis and characterization of Cu and Ni catalysts supported on two Al2O3 with different textural properties, 92 and 310 m2/g, that allow for obtaining various metallic dispersions, between 3.3 and 25.5%, is described. The catalytic behavior of these materials is evaluated from the CO2 methanation reaction, as well as their stability from the properties they present before and after the reaction.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135259416","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}
The business world is becoming more competitive. Therefore, it is crucial to increase the flexibility of production by decreasing the time used in the processes of preparing the production lines for new items’ production, reducing changeover and setup times. This paper presents a case study where the main goal is to reduce the setup time of welding robots. Single Minute Exchange of Die (SMED) was implemented, using other tools such as the Spaghetti Diagram, ERCS Analysis (Eliminate, Rearrange, Combine, Simplify), Gemba Walk, Standardized Work, Flowcharts, and Pareto Diagram. The setup time decreased by 36% in the welding robots studied, decreasing the motions by 43% during the changeover process and reducing the time from the categories: “transportation”, “main”, “other”, and “waiting”. In addition to SMED implementation, this study offers an integrated study of several Lean tools and Quality tools to achieve the maximum reduction of changeover and setup times.
{"title":"Setup Time Reduction of an Automotive Parts Assembly Line Using Lean Tools and Quality Tools","authors":"Cátia Oliveira, Tânia M. Lima","doi":"10.3390/eng4030134","DOIUrl":"https://doi.org/10.3390/eng4030134","url":null,"abstract":"The business world is becoming more competitive. Therefore, it is crucial to increase the flexibility of production by decreasing the time used in the processes of preparing the production lines for new items’ production, reducing changeover and setup times. This paper presents a case study where the main goal is to reduce the setup time of welding robots. Single Minute Exchange of Die (SMED) was implemented, using other tools such as the Spaghetti Diagram, ERCS Analysis (Eliminate, Rearrange, Combine, Simplify), Gemba Walk, Standardized Work, Flowcharts, and Pareto Diagram. The setup time decreased by 36% in the welding robots studied, decreasing the motions by 43% during the changeover process and reducing the time from the categories: “transportation”, “main”, “other”, and “waiting”. In addition to SMED implementation, this study offers an integrated study of several Lean tools and Quality tools to achieve the maximum reduction of changeover and setup times.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135741955","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}
Because textile industries are intensely water-consuming and generate a huge quantity of wastewater, the present study examines the scope of using solar thermal technology to treat wastewater from textile industries. A hybrid technology, comprising a compound parabolic concentrator-based solar thermal system in conjunction with a Membrane Distillation (MD) system, is experimented with for wastewater treatment in textile industries. The MD system requires a water temperature of around 90 °C for efficient functioning. The advanced MD technology using waste heat combined with solar heat to meet the system’s thermal load is technologically evaluated for an experimental textile industry in India. Moreover, the present study critically analyses the techno economics of the proposed hybrid technology. A detailed financial analysis has revealed that, besides technological superiority, the recommended technology is also financially rewarding for wastewater treatment in the textile industry. To cope with the delayed payback period, financial incentives are recommended so that the system becomes a lucrative technological option.
{"title":"Solar Thermal Technology Aided Membrane Distillation Process for Wastewater Treatment in Textile Industry—A Technoeconomic Feasibility Assessment","authors":"Mukesh Kumar Gupta, Rajendra B. Mohite, Salunkhe Madhav Jagannath, Pankaj Kumar, Dipak Shankar Raskar, Malay Kumar Banerjee, Suraj Kumar Singh, Dragana Dogančić, Bojan Đurin","doi":"10.3390/eng4030135","DOIUrl":"https://doi.org/10.3390/eng4030135","url":null,"abstract":"Because textile industries are intensely water-consuming and generate a huge quantity of wastewater, the present study examines the scope of using solar thermal technology to treat wastewater from textile industries. A hybrid technology, comprising a compound parabolic concentrator-based solar thermal system in conjunction with a Membrane Distillation (MD) system, is experimented with for wastewater treatment in textile industries. The MD system requires a water temperature of around 90 °C for efficient functioning. The advanced MD technology using waste heat combined with solar heat to meet the system’s thermal load is technologically evaluated for an experimental textile industry in India. Moreover, the present study critically analyses the techno economics of the proposed hybrid technology. A detailed financial analysis has revealed that, besides technological superiority, the recommended technology is also financially rewarding for wastewater treatment in the textile industry. To cope with the delayed payback period, financial incentives are recommended so that the system becomes a lucrative technological option.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135782467","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}
Paulliny Araújo Moreira, Reimison Moreira Fernandes, Lucas Veiga Avila, Leonardo dos Santos Lourenço Bastos, Vitor William Batista Martins
Background: Artificial Intelligence has been an area of great interest and investment in the industrial sector, offering numerous possibilities to enhance efficiency and accuracy in production processes. In this regard, this study aimed to identify the adoption challenges of Artificial Intelligence and determine which of these challenges apply to the industrial context of an emerging economy, considering the aspects of Industry 4.0. Methods: To achieve this objective, a literature review was conducted, and a survey was carried out among professionals in the industrial field operating within the Brazilian context. The collected data were analyzed using a quantitative approach through Cronbach’s alpha and the Lawshe method. Results: The results indicate that to enhance the adoption of Artificial Intelligence in the industrial context of an emerging economy, taking into account the needs of Industry 4.0, it is important to prioritize overcoming challenges such as “Lack of clarity in return on investment,” “Organizational culture,” “Acceptance of AI by workers,” “Quantity and quality of data,” and “Data protection”. Conclusions: Therefore, based on the achieved results, it can be concluded that they contribute to the development of strategies and practical actions aimed at successfully driving the adoption of Artificial Intelligence in the industrial sector of developing countries, aligning with the principles and needs of Industry 4.0.
{"title":"Artificial Intelligence and Industry 4.0? Validation of Challenges Considering the Context of an Emerging Economy Country Using Cronbach’s Alpha and the Lawshe Method","authors":"Paulliny Araújo Moreira, Reimison Moreira Fernandes, Lucas Veiga Avila, Leonardo dos Santos Lourenço Bastos, Vitor William Batista Martins","doi":"10.3390/eng4030133","DOIUrl":"https://doi.org/10.3390/eng4030133","url":null,"abstract":"Background: Artificial Intelligence has been an area of great interest and investment in the industrial sector, offering numerous possibilities to enhance efficiency and accuracy in production processes. In this regard, this study aimed to identify the adoption challenges of Artificial Intelligence and determine which of these challenges apply to the industrial context of an emerging economy, considering the aspects of Industry 4.0. Methods: To achieve this objective, a literature review was conducted, and a survey was carried out among professionals in the industrial field operating within the Brazilian context. The collected data were analyzed using a quantitative approach through Cronbach’s alpha and the Lawshe method. Results: The results indicate that to enhance the adoption of Artificial Intelligence in the industrial context of an emerging economy, taking into account the needs of Industry 4.0, it is important to prioritize overcoming challenges such as “Lack of clarity in return on investment,” “Organizational culture,” “Acceptance of AI by workers,” “Quantity and quality of data,” and “Data protection”. Conclusions: Therefore, based on the achieved results, it can be concluded that they contribute to the development of strategies and practical actions aimed at successfully driving the adoption of Artificial Intelligence in the industrial sector of developing countries, aligning with the principles and needs of Industry 4.0.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135878631","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}
In the present study, the concept of utilizing two circular cam-track disks, of the same central angle, in combination with one circular roller is presented. The roller is restrained to move within a vertical groove, and at the same time it rotates with rolling-contact on both cam tracks. When the upper cam is fully travelled by the roller, the same occurs with the lower one, despite their different lengths. Therefore, during the rolling contact, the two cams always sweep the same central angle. The aforementioned configuration of the two circular arcs may be considered as a unit cell, which can be repeated an even number of times, and when folded forms a closed circular groove between two cam-track disks. For better understanding, a manufactured prototype and 3D CAD-models have been developed. The operation of this setup as a gearless automotive differential is demonstrated by performing two bench experiments, which are then explained by a simplified mechanical model. The latter focuses on the implementation of the principle of the inclined plane, in which an upper limit of the inclination angle is imposed in accordance with the coefficient of friction at the friction disks. Previous patents on gearless differentials are discussed and other possible applications in mechanical engineering are outlined.
{"title":"Power Transmission Using Circular Elements Bounded by Given Central Angle in Rolling Contact","authors":"Christopher G. Provatidis","doi":"10.3390/eng4030132","DOIUrl":"https://doi.org/10.3390/eng4030132","url":null,"abstract":"In the present study, the concept of utilizing two circular cam-track disks, of the same central angle, in combination with one circular roller is presented. The roller is restrained to move within a vertical groove, and at the same time it rotates with rolling-contact on both cam tracks. When the upper cam is fully travelled by the roller, the same occurs with the lower one, despite their different lengths. Therefore, during the rolling contact, the two cams always sweep the same central angle. The aforementioned configuration of the two circular arcs may be considered as a unit cell, which can be repeated an even number of times, and when folded forms a closed circular groove between two cam-track disks. For better understanding, a manufactured prototype and 3D CAD-models have been developed. The operation of this setup as a gearless automotive differential is demonstrated by performing two bench experiments, which are then explained by a simplified mechanical model. The latter focuses on the implementation of the principle of the inclined plane, in which an upper limit of the inclination angle is imposed in accordance with the coefficient of friction at the friction disks. Previous patents on gearless differentials are discussed and other possible applications in mechanical engineering are outlined.","PeriodicalId":10630,"journal":{"name":"Comput. Chem. Eng.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136024392","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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