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Prediction of energy consumption in the industry 4.0 platform - Solutions overview

  • APA Group

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)455-468
Number of pages14
JournalJournal of Theoretical and Applied Mechanics
Volume59
Issue number3
DOIs
Publication statusPublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Artificial intelligence
  • IPOE
  • Industry 4.0
  • Mechanical engineering
  • Production engineering
  • Production management

ASJC Scopus subject areas

  • Mechanical Engineering

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