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ARTICLE
Prediction of energy consumption in the Industry 4.0 platform- solutions overview
| 1 | APA Group, Gliwice, Poland |
| 2 | Silesian University of Technology, Faculty of Mechanical Engineering, Gliwice, Poland |
CORRESPONDING AUTHOR
Submission date: 2021-04-20
Final revision date: 2021-06-05
Acceptance date: 2021-06-07
Online publication date: 2021-07-14
Publication date: 2021-07-25
Journal of Theoretical and Applied Mechanics 2021;59(3):455–468
KEYWORDS
Industry 4.0artificial intelligenceIPOEproduction managementmechanicalengineeringproduction engineering
TOPICS
ABSTRACT
For a long time, scientific and technical work has been focused on production management,
which affects both the correctness of the process and the costs generated. One of the integral
elements of the production process management is energy, which has an impact on the organization
of work, operation of machines or production. Predicting the energy consumption
of smart facilities is crucial for implementing energy-efficient management systems, the area
of this problem is a key aspect of smart grids whereby loads must be planned in real time.
One of the main tasks of intelligent systems is to optimize the energy demand and costs
to maximize energy efficiency of the facility. According to forecasting requirements, the following
article presents several approaches to prediction of energy consumption models for
production engineering systems. The proposed models were adopted and analyzed in terms
of their usability and were trained and validated with the use of real data collected from the
electrical installation of some company using the APA IPOE system.
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