Summary of A Systematic Review on Expert Systems For Improving Energy Efficiency in the Manufacturing Industry, by Borys Ioshchikhes et al.
A systematic review on expert systems for improving energy efficiency in the manufacturing industry
by Borys Ioshchikhes, Michael Frank, Matthias Weigold
First submitted to arxiv on: 5 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper reviews expert systems (ESs) that aim to improve energy efficiency in the manufacturing industry, which is crucial for achieving climate neutrality by 2050. The ESs analyzed automatically identify potential energy-saving opportunities and can play a significant role in reducing electricity consumption. The review examines 54 articles published between 1987 and 2023, classifying them based on various factors such as system boundaries, manufacturing types, and application purposes. The analysis reveals research gaps, suggesting promising topics for future study. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper looks at how expert systems can help the manufacturing industry become more energy efficient. Expert systems are computer programs that can automatically find ways to save energy. This is important because factories use a lot of electricity, and there’s not enough trained staff to make sure they’re using it efficiently. The study looked at 54 articles published over 36 years to see what expert systems have been used for in this area. It also explored how these systems work, who uses them, and where the gaps are that need to be filled. |
