Search Results - subject:"Smart Manufacturing"

Artificial intelligence and smart manufacturing: An analysis of strategic and performance narratives

Horobet, Alexandra; Tudor, Cristiana Doina; Dinca, Zeno; … - In: Amfiteatru Economic Journal 26 (2024) 66, pp. 440-457

This paper examines how artificial intelligence and smart manufacturing concepts are reflected in the business strategy … uncovering connections between smart manufacturing, strategy, and performance themes based on code frequencies, co … shaped this economic sector. Key findings reveal that while smart manufacturing codes were less frequent, robots and …

Persistent link: https://www.econbiz.de/10014632142

Artificial intelligence and smart manufacturing : an analysis of strategic and performance narratives

Horobet, Alexandra; Tudor, Cristiana Doina; Dinca, Zeno; … - In: Amfiteatru economic : an economic and business research … 26 (2024) 66, pp. 440-457

Persistent link: https://www.econbiz.de/10014574521

Leveraging supply chain reaction time : the effects of big data analytics capabilities on organizational resilience enhancement in the auto-parts industry

Bronzo, Marcelo; Barbosa, Marcelo Werneck; Sousa, Paulo … - In: Administrative Sciences : open access journal 14 (2024) 8, pp. 1-25

Big data analytics capabilities (BDACs) are strategic capabilities that expedite decision-making processes, empowering organizations to mitigate the impacts of supply chain disruptions. These capabilities enhance the ability of companies to be more proactive in detecting and predicting...

Persistent link: https://www.econbiz.de/10015071510

Enhancing stability and robustness in online machine shop scheduling : a multi-agent system and negotiation-based approach for handling machine downtime in industry 4.0

Didden, Jeroen B. H. C.; Dang, Quang-Vinh; Adan, Ivo - In: European journal of operational research : EJOR 316 (2024) 2, pp. 569-583

Persistent link: https://www.econbiz.de/10014575531

The "dark side" of Industry 4.0 : how can technology be made more sustainable?

Dieste, Marcos; Orzes, Guido; Culot, Giovanna; Sartor, Marco - In: International journal of operations & production management 44 (2024) 5, pp. 900-933

Persistent link: https://www.econbiz.de/10015055692

Few-shot learning for defect detection in manufacturing

Zajec, Patrik; Rožanec, Jože M.; Theodoropoulos, Spyros; … - In: International journal of production research 62 (2024) 19, pp. 6979-6998

Persistent link: https://www.econbiz.de/10015084918

Digitalization and Development: Ecosystem for Promoting Industrial Revolution 4.0 Technologies in Malaysia

Rasiah, Rajah (contributor); Low, Wah Yun (contributor); … - 2023

This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the...

Persistent link: https://www.econbiz.de/10014520294

Digital twin for smart manufacturing : a review

Soori, Mohsen; Arezoo, Behrooz; Dastres, Roza - In: Sustainable manufacturing and service economics 2 (2023), pp. 1-15

smart manufacturing can reduce time to market by designing and evaluating the manufacturing processes in virtual … process. In this paper, application of digital twin in smart manufacturing systems is reviewed to analyze and discuss the … and evaluating previous papers in order to propose fresh concepts and approaches by using digital twins in smart …

Persistent link: https://www.econbiz.de/10014555539

Aspects of resilience for smart manufacturing systems

Fowler, Daniel S.; Epiphaniou, Gregory; Higgins, Matthew D. - In: Strategic change 32 (2023) 6, pp. 183-193

Persistent link: https://www.econbiz.de/10014429079

Designing a conceptual framework for Industry 4.0 technologies to enable circular economy ecosystem

Ejaz, Muhammad Rahim; Hegedűs, Dániel - In: Managing global transitions : international research journal 21 (2023) 2, pp. 121-148

Persistent link: https://www.econbiz.de/10014308522

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