Generative AI in the Manufacturing Process: Theoretical Considerations

Doung Cong Doanh, Zdenek Dufek, J. Ejdys, R. Ginevičius, P. Korzyński, G. Mazurek, Joanna Paliszkiewicz, Krzysztof Wach, E. Ziemba
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Abstract

Abstract The paper aims to identify how digital transformation and Generative Artificial Intelligence (GAI), in particular, affect the manufacturing processes. Several dimensions of the Industry 4.0 field have been considered, such as the design of new products, workforce and skill optimisation, enhancing quality control, predictive maintenance, demand forecasting, and marketing strategy. The paper adopts qualitative research based on a critical review approach. It provides evidence of the GAI technology support in the mentioned areas. Appropriate use of emerging technology allows managers to transform manufacturing by optimising processes, improving product design, enhancing quality control, and contributing to overall efficiency and innovation in the industry. Simultaneously, GAI technologies facilitate predictive analytics to forecast and anticipate future demand, quality issues, and potential risks, improve a marketing strategy and identify market trends.
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制造过程中的生成式人工智能:理论考虑
摘要 本文旨在明确数字化转型,特别是生成式人工智能(GAI)如何影响生产流程。本文考虑了工业 4.0 领域的多个方面,如新产品设计、劳动力和技能优化、加强质量控制、预测性维护、需求预测和营销策略。本文采用基于批判性评论方法的定性研究。它提供了 GAI 技术支持上述领域的证据。适当使用新兴技术可以让管理者通过优化流程、改进产品设计、加强质量控制以及促进行业整体效率和创新来实现制造业转型。与此同时,GAI 技术还能促进预测分析,预测未来需求、质量问题和潜在风险,改进营销战略并确定市场趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Engineering Management in Production and Services
Engineering Management in Production and Services Business, Management and Accounting-Management Information Systems
CiteScore
3.40
自引率
0.00%
发文量
27
审稿时长
7 weeks
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