# Improving Energy Efficiency in Manufacturing: A Novel Expert System Shell

arXiv: https://arxiv.org/abs/2411.01272 · HTML: https://mlsanity.com/paper/2411.01272/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 22 references that are in the map.
- First posted on arXiv 2 Nov 2024.

## Builds on (most cited first, 1 of 1)

- [A systematic review on expert systems for improving energy efficiency in the manufacturing industry](https://mlsanity.com/paper/2407.04377/) (2024)

## Abstract (arXiv)

Expert systems are effective tools for automatically identifying energy efficiency potentials in manufacturing, thereby contributing significantly to global climate targets. These systems analyze energy data, pinpoint inefficiencies, and recommend optimizations to reduce energy consumption. Beyond systematic approaches for developing expert systems, there is a pressing need for simple and rapid software implementation solutions. Expert system shells, which facilitate the swift development and deployment of expert systems, are crucial tools in this process. They provide a template that simplifies the creation and integration of expert systems into existing manufacturing processes. This paper provides a comprehensive comparison of existing expert system shells regarding their suitability for improving energy efficiency, highlighting significant gaps and limitations. To address these deficiencies, we introduce a novel expert system shell, implemented in Jupyter Notebook, that provides a flexible and easily integrable solution for expert system development.