Load and energy management for factories through multi-stage production planning and optimization

Süße, Marian; Prell, Bastian; Stoldt, Johannes; Strehle, Hanns-Martin; Richter, Mark; Schlegel, Andreas; Pütz, Matthias

doi:10.1016/j.procir.2019.01.076

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…These efforts reflect Europe's commitment to transitioning towards a greener, more sustainable energy system. Based on this, it is clear that finding an easily accessible everyday way to reduce energy consumption in manufacturing companies could help as well [3].…”

Section: Introductionmentioning

confidence: 98%

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

Skėrė,

Bastida-Molina,

Hurtado-Pérez

et al. 2023

Machines

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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.

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Section: Introductionmentioning

confidence: 98%

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

Skėrė,

Bastida-Molina,

Hurtado-Pérez

et al. 2023

Machines

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“…In the energy shop of the non-ferrous metallurgy enterprise under consideration, hydrogen is produced, which is necessary to meet the needs of the shops in process gas, which is the main reducing agent in furnaces and welding machines. The structural technological scheme of hydrogen production is shown in Figure 1 [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

“…After gas blowers or compressors, hydrogen is purified and dried from moisture and oxygen (4) (hydrogen content in hydrogen-gas by volume is not less than 99.983%) in the installation, the most energy-intensive consumers, which are calcining furnaces. After completing operations (1)(2)(3)(4), hydrogen is directed to the distribution manifold, from where it is transported through pipelines (5) to the shops to the consumers [5][6][7]. All shop consumers belong to the II (electrolyzers, calcining furnaces, gas blowers, compressors) and III (electric distillers) categories of power supply reliability.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of energy consumption in the production of hydrogen

Klyuev

Guzueva

Kunitsyn

2022

J. Phys.: Conf. Ser.

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The article discusses the technological process of hydrogen production at metallurgy. Mathematical models of the dependence of power consumption and specific consumption depending on various parameters have been obtained, which make it possible to calculate and predict. In the electrolyzer, the change in the component of the specific power consumption by the amount of potassium dichromate (chromium peak) over time is analyzed. Therefore, the analysis of the dependence of the specific power consumption in time was carried out directly on the basis of the results of an experimental study of the dependence of the change in time of the voltage on the electrolyzer when the electrolyzer was loaded with chromium peak. The most important issue of reducing electricity consumption due to the use of a gas holder in the mode of consumer-regulator has been investigated. Controlling the level of deviations in power consumption (±2%) in comparison with the normative (±5%) allows increasing the margin of "safety" in terms of load regulation time, reducing the likelihood of it going beyond the normative level and, accordingly, reducing the payment for deviations in the volume of electrical energy consumption.

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Combining material flow simulation and optimization for sustainable manufacturing – application in automotive paint shops

Süße,

Xie,

Ihlenfeldt

2024

Procedia CIRP

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Load and energy management for factories through multi-stage production planning and optimization

Cited by 4 publications

References 19 publications

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

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

Mathematical modeling of energy consumption in the production of hydrogen

Combining material flow simulation and optimization for sustainable manufacturing – application in automotive paint shops

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