PROCESS DEVELOPMENT IN MECHANICAL ENGINEERING: INNOVATIONS, CHALLENGES, AND OPPORTUNITIES

Engineering Science & Technology Journal, Journal Year: 2024, Volume and Issue: 5(3), P. 901 - 912

Published: March 24, 2024

Process development in mechanical engineering encompasses a broad spectrum of innovations, challenges, and opportunities that drive advancements various industries. This review delves into the multifaceted landscape process within engineering, highlighting key themes trends. Innovations are propelled by continuous quest for efficiency, sustainability, enhanced performance. Advances additive manufacturing, automation, digitalization have revolutionized traditional manufacturing processes, enabling creation complex geometries with unprecedented precision speed. Additive techniques such as 3D printing offer versatility material selection design freedom, facilitating rapid prototyping customization while minimizing wastage. Automation technologies, including robotics AI-driven systems, optimize production workflows, augmenting productivity reducing human error. Moreover, digital twins simulation tools empower engineers to simulate processes virtually, accelerating product cycles costly experimentation. However, alongside these face myriad challenges. The integration new technologies often requires substantial investment infrastructure workforce training. Quality control assurance remain critical concerns, particularly where ensuring part integrity repeatability is paramount. Furthermore, sustainability implications emerging must be carefully evaluated mitigate environmental impact resource depletion. Despite presents abundant growth advancement. rise Industry 4.0 initiatives fosters collaboration between academia, industry, government, driving research efforts towards sustainable interconnected ecosystems. advent advanced materials, composites biomaterials, unlocks possibilities lightweight structures, performance, tailored functionalities. Additionally, pursuit circular economy principles promotes efficiency waste reduction throughout lifecycle. In conclusion, characterized dynamic interplay innovation, opportunities. By embracing addressing leveraging collaborative partnerships, can transformative change across industries, paving way more efficient, sustainable, future. Keywords: Process, Development, Mechanical, Engineering, Innovation, Review.

Language: Английский

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AI-Driven risk assessment: Revolutionizing audit planning and execution

Finance & Accounting Research Journal, Journal Year: 2024, Volume and Issue: 6(6), P. 1069 - 1090

Published: June 15, 2024

Artificial Intelligence (AI) is profoundly transforming risk assessment in audit planning and execution, offering unparalleled advancements efficiency, accuracy, strategic decision-making. This review explores the role of AI-driven revolutionizing process, highlighting its benefits challenges associated with implementation. AI technologies, particularly machine learning advanced data analytics, are enhancing auditors' ability to identify, assess, manage risks. Traditional methods often rely on historical static models, which can be limited their predictive power. In contrast, approaches leverage vast datasets, continuously updating from new information provide dynamic precise evaluations. One primary process analyze large volumes rapidly. algorithms identify patterns anomalies that may indicate potential risks, might missed by human auditors due cognitive biases or overload. capability ensures a more comprehensive accurate assessment, enabling focus high-risk areas allocate resources effectively. Moreover, enhances audits. By providing real-time insights into emerging allows anticipate address issues proactively. forward-looking approach not only improves efficiency execution but also strengthens overall management framework organizations. Despite these advantages, integrating poses several challenges. Ensuring quality integrity crucial, as systems relevant produce reliable assessments. Additionally, "black box" nature some models create transparency issues, making it difficult for explain how specific assessments were derived. Addressing algorithmic ensuring compliance regulatory standards critical concerns. conclusion, detect risks greater precision efficiency. However, fully realize potential, must navigate related quality, transparency, ethical considerations. doing so, profession technologies achieve robust effective practices, ultimately organizational resilience accountability. Keywords: AI-Driven, Risk Assessment, Revolutionizing, Audit Planning Execution

Language: Английский

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Ethical Considerations in AI-Powered Work Environments: A Literature Review and Theoretical Framework for Ensuring Human Dignity and Fairness

International Journal of Scientific Research and Management (IJSRM), Journal Year: 2024, Volume and Issue: 12(03), P. 6166 - 6178

Published: March 21, 2024

This article critically examines the integration of artificial intelligence (AI) into work environments, focusing on ethical implications that arise. It seeks to underscore need for balancing technological advancements with protection human dignity and fairness, exploring how AI's transformative potential can be harmonized core tenets rights. The utilizes a comprehensive literature review construct theoretical framework outlines capabilities considerations. encompasses interdisciplinary foundations AI, including its roots in cognitive psychology, decision theory, computer engineering. further delves dilemmas presented by AI workplace, such as privacy concerns, risk bias, issues accountability, broader impact exploration is aimed at understanding complexities labor market occupational safety health. findings highlight dual nature both catalyst efficiency innovation source challenge. It's important include lot different points view everyone process developing make it more fair respect Laws policies keep changing up progress protect people legally from possible abuses. Strong moral guidelines clear systems are also needed reduce bias. study's originality value emphasize discussions rights contexts, contribute technology governance discussions, discuss debates dignity, face advancement.

Language: Английский

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Synergizing AI and Business: Maximizing Innovation, Creativity, Decision Precision, and Operational Efficiency in High-Tech Enterprises

Journal of Open Innovation Technology Market and Complexity, Journal Year: 2024, Volume and Issue: 10(3), P. 100352 - 100352

Published: Aug. 14, 2024

The study was conducted on 125 US based high-tech firms from software engineering, hardware production, biotechnology, and telecommunications. Senior-level executives, including CEOs, board members, CTOs, provided insights through structured questionnaires. Key findings indicate that AI adoption significantly enhances organizational capabilities in terms of employees' innovation, creativity, experimentation. Moreover, adaptation positively impacts decision making thus yielding more accurate timely valuable decisions. These contribute to both theoretical understanding managerial practice by guiding strategic investments technologies, fostering advocating for ethical deployment practices. Future should examine longitudinal across industries regions optimize benefits minimize risks digital transformation efforts. It also integrate qualitative methods deeper appropriate governance systems.

Language: Английский

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AI Agents from Copilots to Coworkers: Historical Context, Challenges, Limitations, Implications, and Practical Guidelines

Published: April 10, 2024

This paper examines the transformative journey of Artificial Intelligence (AI) agents from copilots to integral coworkers within diverse sectors. Beginning with a foundational overview, we delve into historical evolution AI agents, highlighting key technological milestones and shift simple automated tools sophisticated decision-making systems capable learning adapting over time. We explore capabilities including problem-solving, predictive analytics, automation, their applications across healthcare, business, education, showcasing role in diagnostics, customer service, personalized learning, among other areas. also address integration workplace, presenting strategies for collaboration between humans AI, outline challenges ethical considerations that accompany development deployment technologies. A comprehensive tutorial provides insight process emphasizing goal definition, data handling, algorithm selection, guidelines. consider pathway towards General (AGI) societal implications widespread integration, proposing equitable use.

Language: Английский

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AI-Driven Inventory Management for Optimizing Operations With Quantum Computing

Advances in logistics, operations, and management science book series, Journal Year: 2024, Volume and Issue: unknown, P. 125 - 140

Published: June 30, 2024

This chapter explores the transformative potential of integrating artificial intelligence (AI) with quantum computing to revolutionize inventory management practices. In today's dynamic business environment, efficient is paramount for organizations seeking meet customer demand while minimizing costs and maximizing profitability. By harnessing AI's cognitive capabilities computing's computational prowess, this elucidates how can achieve unprecedented levels optimization in their operations. From forecasting order fulfillment supply chain risk mitigation, AI-driven empowers make data-driven decisions unparalleled accuracy agility. Through real-world examples case studies, showcases tangible benefits leveraging AI management, paving way enhanced operational efficiency, improved satisfaction, sustainable competitive advantage marketplace.

Language: Английский

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Smart quality control of Industry 4.0 by artificial intelligence-powered robot vision, a review

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 255 - 285

Published: Jan. 1, 2025

Language: Английский

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Charting the Course of Leadership Through the Digital Era

Advances in logistics, operations, and management science book series, Journal Year: 2025, Volume and Issue: unknown, P. 119 - 156

Published: Jan. 24, 2025

This chapter aims to provide actionable strategies for empowering leaders in leveraging technology amplify their leadership efficacy contemporary business environments by employing extensive literature review and deep learning models, a method Artificial Intelligence (AI). It investigates the effectiveness of three approaches—Transformational, Transactional, Servant Leadership—in meeting high-performance expectations within organizational contexts. The performance these styles based on scores have been analyzed using data analysis techniques neural network including Generative Adversarial Networks (GANs) Variational Autoencoders (VAEs). Furthermore, Deep Convolutional (DCGANs), utilized visualize complex dynamics. findings from this comprehensive valuable insights into strengths limitations each approach, guiding strategic development initiatives decision-making processes.

Language: Английский

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The Role of Artificial Intelligence in Transforming Business Models

Advances in business strategy and competitive advantage book series, Journal Year: 2025, Volume and Issue: unknown, P. 71 - 98

Published: Jan. 3, 2025

Artificial Intelligence (AI) is transforming the way businesses work, driving a fundamental instability in traditional business paradigms. This chapter addresses role of AI model innovation, investigating how companies employ technologies to enhance decision-making, optimize processes, and generate new value propositions. By integrating into may change from static, linear models dynamic, data-driven strategies, allowing for better scalability agility. Through series case studies examples, illustrates significant sectors industries where AI-driven have arisen. It also covers barriers adoption, including technological, ethical, organizational hurdles, offers insights future trends developing landscape AI-powered transformations.

Language: Английский

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AI-Powered Business Process Automation

Advances in finance, accounting, and economics book series, Journal Year: 2025, Volume and Issue: unknown, P. 199 - 224

Published: Feb. 7, 2025

This chapter examines how automating business processes and changing management practices can be achieved through the use of artificial intelligence (AI). It draws attention to increasing AI across a range industries emphasizes it improve productivity judgment overall performance. The looks at major managerial tasks that supports like employee engagement performance offers case studies real-world application insights. Businesses without sacrificing data security or fairness by taking ethical issues privacy concerns significance responsible deployment into account. potential for ongoing innovation difficulties businesses may encounter in putting these technologies practice are highlighted this exploration future trends AI-powered automation. looking implement their best practical lessons gleaned from industry as guide.

Language: Английский

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