What is it about?
New manufacturing expertise, along with user expectations for gradually modified products and facilities, is creating changes in manufacturing scale and distribution. Standardization is essential for every industrial manufactured sector that delivers goods to consumers. Digital manufacturing (DM) is a vital component in the scheduling of all knowledge-based manufacturing. Additive Manufacturing (AM) is recognized as a useful technique in the area of sustainable development goals (SDGs). Modern Development techniques are inspected as a tool for the practices that are being adopted. Additive Manufacturing (AM) was introduced as an advanced technology that includes a new era of complicated machinery and operating systems.
Featured Image
Why is it important?
ML algorithms can optimize design and manufacturing processes, predict equipment failures, and enhance product quality in additive manufacturing. IoT enables real-time monitoring and control of the additive manufacturing process, leading to better resource management and reduced waste. Analyzing large datasets generated during manufacturing helps in understanding patterns, improving efficiency, and reducing errors. Digital twins allow virtual simulation of the manufacturing process, enabling better decision-making, predictive maintenance, and optimization before actual production.
Perspectives
The review likely explores how each of these technologies—Machine Learning (ML), Internet of Things (IoT), Big Data, Digital Twins, and Blockchain—contributes to additive manufacturing. It would analyze how these technologies work together to optimize AM processes, improve precision, reduce waste, and enhance production efficiency. The review might assess how these technologies contribute to reducing the carbon footprint of manufacturing processes, minimizing waste, and optimizing the use of materials. It could explore the role of digital technologies in resource optimization, including energy savings and reducing the use of non-renewable resources in AM.
Vaseem Akram Shaik
Read the Original
This page is a summary of: A Systematic Review of Additive Manufacturing Solutions Using Machine Learning, Internet of Things, Big Data, Digital Twins and Blockchain Technologies: A Technological Perspective Towards Sustainability, Archives of Computational Methods in Engineering, April 2024, Springer Science + Business Media,
DOI: 10.1007/s11831-024-10116-4.
You can read the full text:
Contributors
The following have contributed to this page
