Improving Energy Efficiency in Manufacturing: A Novel Expert System Shell
This addresses the need for efficient tools to reduce energy consumption in manufacturing, contributing to climate targets, but it is incremental as it builds on existing expert system shells.
The paper tackled the problem of lacking simple and rapid software solutions for developing expert systems to improve energy efficiency in manufacturing, by introducing a novel expert system shell implemented in Jupyter Notebook that offers a flexible and easily integrable solution.
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.