Abstract
Nowadays, it is evident that electricity is an indispensable source of energy in the production sectors when industry 4.0 transformation and sustainability become important at the same time. Electricity consumption forecast has crucial importance for effective energy planning in many production sectors. It is important to predict the total consumption of energy consumption and to make a production plan according to it and therefore to make all the functions in the supply chain cost and optimization plans. In this study, Artificial Neural Networks (ANN) method is used for electricity demand estimation for production processes of cold chain product in the fast moving consumer goods sector (FMCG). The impact of the observed independent variables is analyzed on electricity consumption. Estimates in the model are made for the following periods based on the last three years’ electricity consumption of the one of the big fast moving goods company located in Turkey.
Original language | English |
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Title of host publication | Proceedings of the International Symposium for Production Research 2019 |
Editors | Numan M. Durakbasa, Muhammed Nafis Osman Zahid, Radhiyah Abd. Aziz, Ahmad Razlan Yusoff, Nafrizuan Mat Yahya, Fazilah Abdul Aziz, Mohd Yazid Abu, M. Günes Gençyilmaz |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 51-61 |
Number of pages | 11 |
ISBN (Print) | 9783030313425, 9789811509490 |
DOIs | |
Publication status | Published - 2020 |
Event | 19th International Symposium for Production Research, ISPR 2019 - Vienna, Austria Duration: 28 Aug 2019 → 30 Aug 2019 |
Publication series
Name | Lecture Notes in Mechanical Engineering |
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ISSN (Print) | 2195-4356 |
ISSN (Electronic) | 2195-4364 |
Conference
Conference | 19th International Symposium for Production Research, ISPR 2019 |
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Country/Territory | Austria |
City | Vienna |
Period | 28/08/19 → 30/08/19 |
Bibliographical note
Publisher Copyright:© 2020, Springer Nature Switzerland AG.
Keywords
- Artificial Neural Network (ANN)
- Electricity consumption
- FMCG
- Forecasting