Project

INEVITABLE

Goal: INEVITABLE project is targeting at resource and energy intensive sectors of the process industry, with focus on the steel and nonferrous metals sector.
Since these industries have an enormous impact on energy and resource consumption, and consequently on the environmental footprint, improvements of energy and material efficiency represent major results of the project with positive impacts on both process sustainability and environment.
The focus of INEVITABLE is to develop high-level supervisory control systems for different production plants and to demonstrate them in operational environment to enable autonomous operation of the processes based on embedded cognitive reasoning.
The project approach is based on three enabling technological areas:
(i) data collection & sensor technologies,
(ii) tools for data analysis, control and optimization,
(iii) digitalization infrastructure;
The application of these enabling technologies will be an important step towards digital transformation and optimization of selected production processes.

Date: 1 October 2019 - 31 March 2023

Updates
0 new
0
Recommendations
0 new
0
Followers
0 new
3
Reads
0 new
15

Project log

Miha Glavan
added a research item
Unwanted oscillations are common source of problems in industrial processes that contain rotational elements. The procedures for detecting and isolating such periodic disturbances are often based on the application of FFT and subsequent analysis in the frequency domain. The approach presented here modifies this procedure: all rotating elements in the system are assumed to produce unwanted oscillations, and the resulting hypothetical power spectral density is continuously compared to the real power spectrum generated by the main process variable. When the real oscillations occur, the results of the comparison indicate their probable source(s). The approach is first demonstrated and tested on simulated data and then verified on real recorded data. The method is primarily intended for inspection of a cold rolling mill whose data were used for verification.
Dejan Gradišar
added a project goal
INEVITABLE project is targeting at resource and energy intensive sectors of the process industry, with focus on the steel and nonferrous metals sector.
Since these industries have an enormous impact on energy and resource consumption, and consequently on the environmental footprint, improvements of energy and material efficiency represent major results of the project with positive impacts on both process sustainability and environment.
The focus of INEVITABLE is to develop high-level supervisory control systems for different production plants and to demonstrate them in operational environment to enable autonomous operation of the processes based on embedded cognitive reasoning.
The project approach is based on three enabling technological areas:
(i) data collection & sensor technologies,
(ii) tools for data analysis, control and optimization,
(iii) digitalization infrastructure;
The application of these enabling technologies will be an important step towards digital transformation and optimization of selected production processes.
 
Dejan Gradišar
added a research item
Experimental data for paper "MRP using BPP": D. Gradišar, M. Glavan. Material requirements planning using variable-sized bin packing problem formulation with due date and grouping constraints. Submitted to Processes, 2020.