A Multi-Part Production Planning System for a Distributed Network of 3D Printers under the Context of Social Manufacturing

Makanda, Inno Lorren Désir; Yang, Maolin; Shi, Haoliang; Guo, Wei; Jiang, Pingyu

doi:10.3390/machines10080605

Cited by 12 publications

(1 citation statement)

References 37 publications

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“…Similarly, an eight-step innovative technique for multi-part AM was suggested by Jiang et al [ 71 ] in order to shorten overall manufacturing time and acquire optimal part locations and nozzle travel paths. In order to decrease the overall manufacturing cost and time, studies including part-to-printer allocation and stacking of multiple parts for a distributed network of Fused Deposition Modeling (FDM) were also conducted [ 72 ]. Ransikarbum et al [ 73 ] optimized component orientation, part-to-printer allocation, and path planning with FDM 3D printers using an unique framework based on reasoning algorithms.…”

Section: Literature Surveymentioning

confidence: 99%

A Multi-Part Orientation Planning Schema for Fabrication of Non-Related Components Using Additive Manufacturing

et al. 2022

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Additive manufacturing (AM) is a technique that progressively deposits material in layer-by-layer manner (or in additive fashion) for producing a three-dimensional (3D) object, starting from the computer-aided design (CAD) model. This approach allows for the printing of complicated shaped objects and is quickly gaining traction in the aerospace, medical implant, jewelry, footwear, automotive, and fashion industries. AM, which was formerly used for single part customization, is currently being considered for mass customization of parts because of its positive impacts. However, part quality and build time are two main impediments to the deployment of AM for mass production. The optimal part orientation is fundamental for maximizing the part’s quality as well as being critical for reducing the fabrication time. This research provides a new method for multi-part AM production that improves quality while reducing overall build time. The automatic setup planning or orientation approach described in this paper employs two objective functions: the quality of the build component and the build time. To tackle the given problem, it introduces a three-step genetic algorithm (GA)-based solution. A feature-based technique is utilized to generate a collection of finite alternative orientations for each component within a specific part group to ensure each part’s individual build quality. Then, a GA was utilized to find the best combination of part build orientations at a global optimal level to reduce material consumption and build time. A case study of orienting nine components concurrently inside a given building chamber was provided for illustration. The findings suggest that the developed technique can increase quality, reduce support waste, and shorten overall production time. When components are positioned optimally rather than in random orientations, build time and support volume are reduced by approximately 7% and 16%, respectively.

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Section: Literature Surveymentioning

confidence: 99%

A Multi-Part Orientation Planning Schema for Fabrication of Non-Related Components Using Additive Manufacturing

et al. 2022

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Machine as a smart service: a hybrid knowledge graph approach

Ren,

Jiang,

2024

Flex Serv Manuf J

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Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems

Varriale,

Cammarano,

Michelino

et al. 2023

J Intell Manuf

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Scientific research on emerging technologies underscored the advantages of their implementation within production systems, with a particular focus on artificial intelligence (AI). In particular, the integration of AI with other cutting-edge technologies is a relevant topic which can potentially lead to huge impacts in terms of business performance. Yet, literature on the subject, although rich, is still fragmented, limited to specific cases and applications, but lacking in a comprehensive classification framework. Therefore, using a systematic literature review, this study provides an overview of how the combination of AI and other cutting-edge technologies could potentially improve market and organisational performance in business functions and processes. By classifying the literature of case studies and real-world applications into specific taxonomies, the research considers an indicator, the co-occurrence ratio, highlighting the most significant and emerging combinations between AI and other cutting-edge technologies, also specifying the contexts in which they are used. The study shows that AI is strongly interconnected with other cutting-edge technologies, suggesting a research agenda in which the integration of AI with other emerging technologies is promising within specific production systems contexts, providing benefits and opportunities for companies.

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A Multi-Part Production Planning System for a Distributed Network of 3D Printers under the Context of Social Manufacturing

Cited by 12 publications

References 37 publications

A Multi-Part Orientation Planning Schema for Fabrication of Non-Related Components Using Additive Manufacturing

A Multi-Part Orientation Planning Schema for Fabrication of Non-Related Components Using Additive Manufacturing

Machine as a smart service: a hybrid knowledge graph approach

Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems

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