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- Leng, Jiewu, et al.
(författare)
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Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges
- 2024
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 73, s. 349-363
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Forskningsöversikt (refereegranskat)abstract
- With the continuous development of human-centric, resilient, and sustainable manufacturing towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for additional functionalities, new features, and tendencies in the industrial landscape. On the other hand, the technology-driven Industry 4.0 paradigm is still in full swing. However, there exist many unreasonable designs, configurations, and implementations of Industrial Artificial Intelligence (IndAI) in practice before achieving either Industry 4.0 or Industry 5.0 vision, and a significant gap between the individualized requirement and actual implementation result still exists. To provide insights for designing appropriate models and algorithms in the upgrading process of the industry, this perspective article classifies IndAI by rating the intelligence levels and presents four principles of implementing IndAI. Three significant opportunities of IndAI, namely, collaborative intelligence, self-learning intelligence, and crowd intelligence, towards Industry 5.0 vision are identified to promote the transition from a technology-driven initiative in Industry 4.0 to the coexistence and interplay of Industry 4.0 and a value-oriented proposition in Industry 5.0. Then, pathways for implementing IndAI towards Industry 5.0 together with key empowering techniques are discussed. Social barriers, technology challenges, and future research directions of IndAI are concluded, respectively. We believe that our effort can lay a foundation for unlocking the power of IndAI in futuristic Industry 5.0 research and engineering practice.
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| 2. |
- Wang, Jinxin, et al.
(författare)
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Machining Properties of Stone-Plastic Composite Based on an Empirically Validated Finite Element Method
- 2023
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Ingår i: Advanced Engineering Materials. - : John Wiley & Sons. - 1438-1656 .- 1527-2648. ; 25:8
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Tidskriftsartikel (refereegranskat)abstract
- High-cutting performance is an essential metric for improving the suitability of materials for industrial applications. Herein, the machining properties of stone-plastic composite are assessed through a finite element method to explore orthogonal cutting behavior by diamond cutters. The key aspects examined in this work are the effects of tool geometry and cutting parameters on the cutting force, temperature, chip formation, von Mises stress, and surface quality finish. Primary findings show that chip continuity increases proportionally with increase in rake angle but decreases with cutting speed and depth. Meanwhile, both cutting stability and surface quality are negatively correlated with cutting speed and depth but positively correlated with rake angle. These results support the adoption of cutting conditions using greater rake angle, higher cutting speed, and shallower cutting depth to obtain higher cutting performance, that is, greater cutting stability and surface quality in the finishing machining of stone-plastic composites.
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