Optimizing Efficiency and Sustainability in Advanced Manufacturing Systems
An Engineering Perspective
Bibliographic Data
| ID | 22358579 |
|---|---|
| Authors | Rui Chai (0000-0001-7799-0645, University of Selangor), Chenyuhao Du (University of Selangor), Ting Li (0000-0002-9614-1566, University of Selangor) |
| Year | 2024 |
| Volume | 3 |
| Issue | 7 |
| Pages | 1584-1592 |
| Publication date | 2024-10-15 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Ecohumanism (JOURNAL) |
| Journal identifiers | ISSN: 2752-6798 • E-ISSN: 2752-6801 |
| Publisher | Creative Publishing House (PUBLISHER • GB) |
| DOI | 10.62754/joe.v3i7.4321 |
| OpenAlex | W4409734630 |
| Language | EN |
| References cited | 1 |
Sustainable manufacturing needs to take into account the social, environmental, and economic effects of product distribution and production at the same time. In essence, the execution, assessment, and response of sustainable manufacturing depend on comprehensive measurements, sophisticated choices, and legislation. This study examines current research on ideas, practices, and resources for sustainable manufacturing. Engineering research has tackled design, development, assessment, and process management challenges at the industrial level. Engineering research has also tackled issues with supply chain design, production scheduling and preparation, and facility management at the level of manufacturing systems. Manufacturing techniques and procedures continue to be associated with being hazardous, polluting, and ineffective, despite their economic importance. By focusing on sustainable systems and procedures, researchers from academia and industry are rethinking manufacturing as a source of creativity to fulfill the demands of society in the future. There are still a lot of challenges and possibilities in decision-making and process- and systems-level research, even with recent advancements. A number of these issues that are pertinent to research, design, execution, and teaching in manufacturing processes and systems are emphasized
Management science · Manufacturing engineering · Sustainability · Systems engineering · Computer Science · Digital Transformation in Industry · Engineering · Artificial Intelligence
| Highly cited | No |
|---|