1. //
  2. Start
  3. //
  4. Publications
  5. Neural Networks for Energy Optimization ...
  6. Output formats
  7. //

Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises

Research output: Contributions to collected editions/works › Chapter

Standard

Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises. / Willenbacher, Martina; Wohlgemuth, Volker; Risch, Lisa.
Advances and New Trends in Environmental Informatics. ed. / Volker Wohlgemuth; Stefan Naumann; Grit Behrens; Hans-Knud Arndt; Maximilian Höb. Springer, 2023. p. 129-145.

Research output: Contributions to collected editions/works › Chapter

Harvard

Willenbacher, M, Wohlgemuth, V & Risch, L 2023, Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises. in V Wohlgemuth, S Naumann, G Behrens, H-K Arndt & M Höb (eds), Advances and New Trends in Environmental Informatics. Springer, pp. 129-145. https://doi.org/10.1007/978-3-031-18311-9_8

APA

Willenbacher, M., Wohlgemuth, V., & Risch, L. (2023). Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises. In V. Wohlgemuth, S. Naumann, G. Behrens, H.-K. Arndt, & M. Höb (Eds.), Advances and New Trends in Environmental Informatics (pp. 129-145). Springer. https://doi.org/10.1007/978-3-031-18311-9_8

Vancouver

Willenbacher M, Wohlgemuth V, Risch L. Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises. In Wohlgemuth V, Naumann S, Behrens G, Arndt HK, Höb M, editors, Advances and New Trends in Environmental Informatics. Springer. 2023. p. 129-145 doi: 10.1007/978-3-031-18311-9_8

Bibtex

@inbook{15b25bfb4b7a4e3bbb131ba95a7c4ce7,
title = "Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises",
abstract = "Due to the highly dynamic development processes of manufacturing companies (economic, demographic, sociological, ecological-biological processes), there are high requirements to find scientific answers to environmentally specific questions, considering the profitability and ensuring ongoing operation, and to integrate the developed models to improve the efficiency of the use of materials for energy reduction into the process flow. Decision-making is thus hampered on the one hand by the achievement of solutions in shortened innovation and production cycles and on the other hand by the complexity of the systems and processes of the environmental sector. Furthermore, there are often organizational obstacles and personnel difficulties in the introduction of intelligent algorithms in SMEs. This article describes the conception and development of an artificial neural network for the optimization of production processes regarding the reduction of energy under the aspect of quality assurance for manufacturing SMEs. It describes the development and implementation of the model for the analysis and adaptation of parameter settings to machines in the production process, which determines the ideal configuration to reduce energy consumption and improve quality. In the test of the model on four machines of a plastic-producing SME, it was proven that a total annual energy saving of 50,000 kWh can be achieved.",
keywords = "Sustainability sciences, Communication",
author = "Martina Willenbacher and Volker Wohlgemuth and Lisa Risch",
year = "2023",
doi = "10.1007/978-3-031-18311-9_8",
language = "English",
isbn = "978-3-031-18313-3",
pages = "129--145",
editor = "Volker Wohlgemuth and Stefan Naumann and Grit Behrens and Hans-Knud Arndt and Maximilian H{\"o}b",
booktitle = "Advances and New Trends in Environmental Informatics",
publisher = "Springer",
address = "Germany",

}

RIS

TY - CHAP

T1 - Neural Networks for Energy Optimization of Production Processes in Small and Medium Sized Enterprises

AU - Willenbacher, Martina

AU - Wohlgemuth, Volker

AU - Risch, Lisa

PY - 2023

Y1 - 2023

N2 - Due to the highly dynamic development processes of manufacturing companies (economic, demographic, sociological, ecological-biological processes), there are high requirements to find scientific answers to environmentally specific questions, considering the profitability and ensuring ongoing operation, and to integrate the developed models to improve the efficiency of the use of materials for energy reduction into the process flow. Decision-making is thus hampered on the one hand by the achievement of solutions in shortened innovation and production cycles and on the other hand by the complexity of the systems and processes of the environmental sector. Furthermore, there are often organizational obstacles and personnel difficulties in the introduction of intelligent algorithms in SMEs. This article describes the conception and development of an artificial neural network for the optimization of production processes regarding the reduction of energy under the aspect of quality assurance for manufacturing SMEs. It describes the development and implementation of the model for the analysis and adaptation of parameter settings to machines in the production process, which determines the ideal configuration to reduce energy consumption and improve quality. In the test of the model on four machines of a plastic-producing SME, it was proven that a total annual energy saving of 50,000 kWh can be achieved.

AB - Due to the highly dynamic development processes of manufacturing companies (economic, demographic, sociological, ecological-biological processes), there are high requirements to find scientific answers to environmentally specific questions, considering the profitability and ensuring ongoing operation, and to integrate the developed models to improve the efficiency of the use of materials for energy reduction into the process flow. Decision-making is thus hampered on the one hand by the achievement of solutions in shortened innovation and production cycles and on the other hand by the complexity of the systems and processes of the environmental sector. Furthermore, there are often organizational obstacles and personnel difficulties in the introduction of intelligent algorithms in SMEs. This article describes the conception and development of an artificial neural network for the optimization of production processes regarding the reduction of energy under the aspect of quality assurance for manufacturing SMEs. It describes the development and implementation of the model for the analysis and adaptation of parameter settings to machines in the production process, which determines the ideal configuration to reduce energy consumption and improve quality. In the test of the model on four machines of a plastic-producing SME, it was proven that a total annual energy saving of 50,000 kWh can be achieved.

KW - Sustainability sciences, Communication

UR - https://www.mendeley.com/catalogue/68fe2d97-a03e-33ea-ac0b-cfb81080fcf3/

U2 - 10.1007/978-3-031-18311-9_8

DO - 10.1007/978-3-031-18311-9_8

M3 - Chapter

SN - 978-3-031-18313-3

SN - 978-3-031-18310-2

SP - 129

EP - 145

BT - Advances and New Trends in Environmental Informatics

A2 - Wohlgemuth, Volker

A2 - Naumann, Stefan

A2 - Behrens, Grit

A2 - Arndt, Hans-Knud

A2 - Höb, Maximilian

PB - Springer

ER -

DOI

Recently viewed

Publications

  1. Belief in free will affects causal attributions when judging others’ behavior
  2. Multi-agent systems' asset for smart grid applications
  3. Vector Fields Autonomous Control for Assistive Mobile Robots
  4. A comparison of the strength of biodiversity effects across multiple functions
  5. Set-Oriented and Finite-Element Study of Coherent Behavior in Rayleigh-Bénard Convection
  6. A switching observer for sensorless control of an electromagnetic valve actuator for camless internal combustion engines
  7. Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence
  8. Accuracy Improvement by Artificial Neural Networks in Technical Vision System
  9. How difficult is the adaptation of POS taggers?
  10. Microstructure refinement by a novel friction-based processing on Mg-Zn-Ca alloy
  11. A Kalman estimator for detecting repetitive disturbances
  12. Bulk and local textures of pure magnesium processed by rotary swaging
  13. On the Hausdorff dimension of fractals given by certain expansions of real numbers
  14. Hands in Focus: Sign Language Recognition Via Top-Down Attention
  15. Absolutely continuous random power series in reciprocals of Pisot numbers
  16. Visual Detection of Traffic Incident through Automatic Monitoring of Vehicle Activities
  17. The use of knowledge in inter-organisational knowledge-networks
  18. A Smart Sensing Architecture for Misalignment Measurements
  19. Towards a Heuristic for Scheduling Offshore Installation Processes
  20. A Model Based Feedforward Regulator Improving PI Control of an Ice-Clamping Device Activated by Thermoelectric Cooler
  21. Drawing as a Generative Activity and Drawing as a Prognostic Activity
  22. The Use of Anti-Windup Techniques in Didactic Level Systems
  23. Geometric Properties on the Perfect Decoupling Disturbance Control in Manufacturing Systems
  24. A sensorless control using a sliding-mode observer for an electromagnetic valve actuator in automotive applications
  25. Experimental analysis of measurement process for a QCM using the pulse coincidence method
  26. The Automated will
  27. Automatic generation of periodic representative volume elements for matrix-inclusion composites and their efficiency in multiscaling
  28. Concurrently Observed Actions Are Represented Not as Compound Actions but as Independent Actions
  29. The role of supervisor support for dealing with customer verbal aggression. Differences between ethnic minority and ethnic majority workers
  30. Intelligent software system for replacing a force sensor in the case of clearance measurement
  31. Magnesium recycling: State-of-the-Art developments, part II
  32. CaO dissolution during melting and solidification of a Mg-10 wt.% CaO alloy detected with in situ synchrotron radiation diffraction
  33. Feel the Music! Exploring the Cross-modal Correspondence between Music and Haptic Perceptions of Softness
  34. Self-Compassion as a Facet of Neuroticism? A Reply to the Comments of Neff, Tóth-Király, and Colosimo (2018)
  35. A switching model predictive control for overcoming a hysteresis effect in a hybrid actuator for camless internal combustion engines
  36. Wavelet characterizations for anisotropic Besov spaces
  37. Anonymized Firm Data under Test: Evidence from a Replication Study
  38. Simulation of stresses during casting of binary magnesium-aluminum alloys
  39. Privacy-Preserving Localization and Social Distance Monitoring with Low-Resolution Thermal Imaging and Deep Learning
  40. A microsystem for growth inhibition test of Enterococcus faecalis based on impedance measurement
  41. Using an adaptive memory strategy to improve a multistart heuristic for sequencing by hybridization
  42. High temperature deformation mechanisms and processing map for hot working of cast-homogenized Mg-3Sn-2Ca alloy
  43. Assessing pre-travel online destination experience values of destination websites
  44. Analysis of life cycle datasets for the material gold
  45. Using Long-Duration Static Stretch Training to Counteract Strength and Flexibility Deficits in Moderately Trained Participants
  46. Compression behavior of typical silicone rubbers for soft robotics applications at elevated temperatures
  47. Exploring intrinsic, instrumental and relational values for sustainable management of social-ecological systems
  48. Intra-firm Wage Compression and Cost Coverage of Training