Planet 2050 and the Future of Manufacturing: Data-Driven Approaches to Sustainable Production in Large Vehicle Manufacturing Plants

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

This paper explores the future of manufacturing plants in large vehicle through lens a single European complex. An example plant that originally massmanufactured line products, complex is currently navigating shift to more mixed model production and electric powertrains. Using innovative datasets generated year-long stakeholder co-design process, diverse set partners collectively formed project design new, data-driven approaches challenge. The collected explored data sources, including product bills materials, facility layout data, current system capabilities, energy usage carbon generation, machine uptime failures, factory control strategies, planning processes, quality data. provides summary key analyses, feedback from stakeholders, early technical interpretations, as well broader reflections contextual descriptions factory-particularly its goals challenges. supported stakeholders exploring potential digital transform facilitate system's CO2 reduction pathway. concludes by outlining several thematic issues facing plants.

Язык: Английский

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Harnessing Big Data and AI/ML for Personalized Retail Experiences

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

The retail industry has undergone a significant transformation over the last few decades, primarily fueled by rapid technology adoption and advancing consumer interests. In an expanding digital landscape, novel technologies like social media, mobile applications, analytics have dramatically altered how consumers shop. Today, developed penchant for personalized experiences, on-demand services, instant information gratification. Consequently, retailers are compelled to craft more individualized shopping experiences developing collaborations across various touchpoints channels. emergence of channels allows be both active customers online audience members. growing presence varied behavior create massive volume about their preferences, referred as 'big data.' This information, when harnessed intelligently, can significantly benefit generating insights into customer preferences past behavior. A well-harnessed big data infrastructure enables tailor communications target specific adeptly. advancements in artificial intelligence machine learning fields decade provided opportunities exploit personalization. Data mining techniques, including those derived from multidisciplinary field statistical natural language processing, this purpose. work, impact data, AI, ML on sector rise is discussed. also presents background stimulating factors that prompted overview current vision AI use scenarios.

Язык: Английский

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Leveraging AI And Big Data For Enhanced Security In Biometric Authentication: A Comprehensive Model For Digital Payments

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

The paper offers an epitomized overview of the state-of-the-art frameworks, algorithms, and methods in domain biometric cryptography for mobile transactions. rapid technological advancement has led to popularity various systems. association these systems different fields digital life, such as banking, e-commerce, or m-commerce, cannot be overlooked. However, daily transactions have augmented risk breaches security privacy concerns, which found their solution authentication 1 These diverse applications encounter many challenges, including trade-off between recognition accuracy computational complexity, advanced fake attributes, issues, continuous efforts enhanced estimation entropy. To address companies are leveraging oncoming paradigms like Internet Things, cloud computing, big data, artificial intelligence. Among them, AI data been researched most by industry, since they can add significant value.

Язык: Английский

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Reinforcement Learning for Collaborative Decision-Making in Multi-Agent Systems: Applications in Supply Chain Optimization

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

In an increasingly interconnected world, effective decision-making within multi-agent systems is crucial for optimizing complex processes, particularly in supply chains. This paper explores the application of reinforcement learning (RL) techniques to enhance collaborative among autonomous agents chain environments. We present a framework that leverages deep facilitate coordination and negotiation between agents, allowing them dynamically adapt changing conditions shared objectives. Through series simulations real-world case studies, we demonstrate how our approach improves operational efficiency, reduces costs, enhances responsiveness disruptions. Our findings highlight potential RL transform traditional management, providing pathway more resilient intelligent capable thriving today's volatile markets. By integrating into decision-making, offer new insights agent interactions achieving synergistic outcomes complex,

Язык: Английский

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Revolutionizing Predictive Healthcare with Big Data and AI/ML

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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Revolutionizing Healthcare: The Role of Generative AI in Big Data Analytics for Predictive Diagnostics

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Generative AI is at the heart of revolutionizing healthcare, particularly in assimilating vast amounts multi-omic data. It holds promise generating in-silico data sets designed from first principles biology, physics, chemistry, and mathematics, thus enabling biology a priori understanding. Creating trustable biological datasets crucial for facilitating interpretations, translations, extrapolations systems. This trust revolves around scientific validity conceptual models system, which are typically system-specific post-processed code-wise laboratory experiment data, including healthy conditions, perturbations, applied diagnosis measures.Artificial Intelligence (AI) reshaping healthcare sector, enhancing patient health proactively managing disease. can process large than human intelligence, allowing coordinated insights improved situational awareness. creates significant challenge regarding security since all require user development accuracy improvements. Ethical considerations include understanding why an model made certain decision, as some act "black boxes" that cannot predict outcomes. AI, subfield focused on producing synthetic resembling real input allows design simulate complex As exposed to more training information, these generate solutions environments.

Язык: Английский

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Predictive Analytics in Vehicle Manufacturing: Enhancing Engine Performance and Operational Efficiency in Modern Automotive Plants

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

This essay highlights the significance of using predictive analytics in vehicle manufacturing to develop decision-based models for enhancing engine performance and operational efficiency plants. Proper identification parameters their control would significantly benefit automotive units by providing an avenue unsupervised regulation as well controlling values that contribute objectives. A critical insight be understand how this analysis aids modern plants shifting present rule-based decision-making a more informed, data-based decision model. In plants, informed lead not only better products but also standardized, efficient outcomes two main impacts sought after manufacturers. The scope research is implement model thermal management system diesel analytics. quantitative developed through experimental studies on stationary examine influencing factors objectives system. further discusses extraction examination relations between various algorithms. adaptive time window methodology employed deal with naturally occurring deviations. Machine learning algorithms provide medium incorporating peripheral influences. It concluded identified central can used feedback loop parameter focusing specific detail. details strategies deployed research.

Язык: Английский

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Transparent Insights into AI: Analyzing CNN Architecture through LIME-Based Interpretability for Land Cover Classification

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Март 17, 2025

The realization that complex deep learning models may make morally significant decisions has led to a growing interest in Explainable Artificial Intelligence (XAI), whose primary concern is understanding why it made particular predictions or recommendations. This paper investigates the effectiveness of different Convolutional Neural Network (CNN) architectures are employed on satellite images from Airbus SPOT6 and SPOT7 Datasets. evaluated designs MobileNetV2, Alex Net, ResNet50, VGG16, DenseNet, Inception-ResNet v2, InceptionV3, XceptionNet, EfficientNet. MobileNetV2 showed best other classification parameters such as accuracy 99.20%, precision rate 99.39%, recall 99.00 %, F1 score be at maximum with 99.16 % an AUC (Area Under Curve) detected across all categories correctly 99.96%. research study uses LIME (Local Interpretable Model-agnostic Explanations) examine system classify wind turbines. creates interpretable models, white box estimate predictions. helps identify key factors classification, making model more interpretable. heatmaps attention maps areas SPOT impact MobileNet classifications. enhances trust AI opens up opportunities for behaviour.

Язык: Английский

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Generative AI in Designing Family Health Plans: Balancing Personalized Coverage and Affordability

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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AI-Driven Phishing Email Detection: Leveraging Big Data Analytics for Enhanced Cybersecurity

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Язык: Английский

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