Abstract
Glass manufacturing is an energy-intensive process where small changes in operational parameters can significantly impact efficiency, emissions, and quality. This paper presents a fuzzy-based simulation model developed as a first phase of a broader hybrid optimisation framework aimed at improving sustainability and performance. The model uses fuzzy logic to estimate key performance indicators (KPIs) based on configurable input parameters and integrates a reliability function to capture forming machine degradation. An interactive tool was implemented in Julia programming language to support simulation, visualise KPI trends, and extract performance insights. Initial results show consistent system behaviour and provide a foundation for optimisation in future phases of the framework.
| Original language | English |
|---|---|
| Title of host publication | 2025 30th International Conference on Automation and Computing (ICAC) |
| Publisher | IEEE |
| Number of pages | 6 |
| ISBN (Electronic) | 9798331525453 |
| DOIs | |
| Publication status | Published - 16 Oct 2025 |
Bibliographical note
For the purpose of open access, the author(s) has applied a Creative Commons attribution (CC BY) licence to any Author Accepted Manuscript version arisingFunding
This work has received funding from UKRI Horizon Europe Guarantee with Ref no 10063954 for the project \"H2GLASS: advancing Hydrogen (H2) technologies and smart production systems to decarbonise the Glass and Aluminium Sectors\". Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the UKRI, European Union or the European Health and Digital Executive Agency. Neither the European Union nor granting authority can be held responsible for them.
Keywords
- Fuzzy logic
- Glass manufacturing
- Process optimisation
- Simulation model
- Sustainability