Energy Consumption Analysis and Efficiency Enhancement in Manufacturing Companies Using Decision Support Method for Dynamic Production Planning (DSM DPP) for Solar PV Integration

Author:

Skėrė Simona1ORCID,Bastida-Molina Paula23,Hurtado-Pérez Elías23,Juzėnas Kazimieras1

Affiliation:

1. Faculty of Mechanical Engineering and Design, Kaunas University of Technology, 51424 Kaunas, Lithuania

2. Instituto Universitario de Investigación en Ingeniería Energética (IIE), Universitat Politècnica de València (UPV), 46022 Valencia, Spain

3. Departamento de Ingeniería Eléctrica, Universitat Politècnica de València (UPV), 46022 Valencia, Spain

Abstract

The Industrial Revolution brought major technological progress and the growth of manufacturing, which resulted in significant changes in energy use. However, it also brought about new environmental issues such as increased energy needs, unstable electricity costs, and worsened greenhouse gas effects. Nowadays, it is crucial to analyze energy use to stay competitive. Manufacturers, highly dependent on electricity, can save energy and enhance efficiency by improving production methods. This article presents the findings of a research study conducted on a Lithuanian manufacturing company, aiming to investigate its electricity consumption over a 15-month period from 2022.01 to 2023.03—detailed data about the monthly consumption of the six most powerful machines and their active and standby hours are presented. The total electricity consumption of those matched 173.62 MWh. Employing the Decision Support Method for Dynamic Production Planning (DSM DPP), which was previously developed and refined, the study examines the potential for time savings and, subsequently, energy savings, through process reorganization. A detailed three-month production orders observation period demonstrates tangible time savings while using the proposed DSM DPP—time savings of approximately 5% can be achieved. Compared to that, production might achieve a 20% productivity increase with advanced technology implementation, so 5% is a great result for an easily adaptable method. Based on this, changes in energy consumption and CO2 emissions due to electricity consumption are calculated and presented knowing that the company uses energy from the grid. Adaptation of the replanning method resulted in a reduction of electricity use by 175 kWh and a reduction of CO2 consumption by 27 kgCO2. With proper production planning, energy and CO2 consumption can be decreased, which is a high priority in today’s world.

Funder

ERASMUS+

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Optimization,Mechanical Engineering,Computer Science (miscellaneous),Control and Systems Engineering

Reference21 articles.

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2. European Commission (2023, August 05). (n.d.). 2050 Long-Term Strategy. Available online: https://climate.ec.europa.eu/eu-action/climate-strategies-targets/2050-long-term-strategy_en.

3. Load and energy management for factories through multi-stage production planning and optimization;Prell;Procedia CIRP,2019

4. The evolution of production scheduling from Industry 3.0 through Industry 4.0;Jiang;Int. J. Prod. Res.,2021

5. Industry 4.0 technologies: Critical success factors for implementation and improvements in manufacturing companies;Pozzi;Prod. Plan. Control,2023

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