https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Energy and Water Usage in the Manufacturing Industry: A study case to analyse, compare and decide where to reduce energy and water utilization
Mälardalen University, School of Business, Society and Engineering.
Mälardalen University, School of Business, Society and Engineering.
2020 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Increasing concern about global climate change has led to a growing interest in energy usage and water consumption. It is well known that changes in consumption habits lead to more efficient use of energy and water sources. Nowadays, globalization, environmental concerns, and the shortage of resources have led to an increase of stakeholder pressure on companies to expand their focus to sustainability. Also, the high impact that the savings can have in the financial status of the company. It is encouraging the headboards to study and improve the ways water and energy are being used within the processes. Significant economic savings and benefits for the environment could be achieved with slight changes in the company. As an overview, this project starts with the extraction of data from a platform for energy management in an industrial company. Then, it goes through the understanding of the energy and water usage data set. Later, a methodology to handle and process the data will be set. It is intending to extract relevant information using clustering. The idea is to compare the usage profiles between different factories, using key performance indicators and reducing the initial data set. Once the benchmarking is performed, some critical parameters will be selected to support the decision-making process related to investments to reduce the energy usage and water consumption in a specific location. Finally, the case of study will be implemented with the measurements from Alfa Laval. We will study how, from daily measurements with a very low investment and using the proper algorithms and methodologies, the main behaviours and features in an industrial location can be extracted from the utilization data. These characteristics can be used to develop strategies or productions schemes based on the interests of the energy manager and the company.

Place, publisher, year, edition, pages
2020. , p. 72
Keywords [en]
Clustering, DB-index, Energy benchmarking, Energy management, Energy signature, Energy usage, k-means, KPI’s, load profile, Silhouette index, TOPSIS.
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-49146OAI: oai:DiVA.org:mdh-49146DiVA, id: diva2:1447832
External cooperation
Alfa Laval
Subject / course
Energy Engineering
Supervisors
Examiners
Available from: 2020-06-26 Created: 2020-06-26 Last updated: 2020-06-26Bibliographically approved

Open Access in DiVA

fulltext(5901 kB)444 downloads
File information
File name FULLTEXT01.pdfFile size 5901 kBChecksum SHA-512
c2c280219aba791261efacdeeb80224a23da97368d8b8a4a61522b76455e84b989713db40cedf5201dca1d2efd2a3408230e84a3eaa416594827949a52016970
Type fulltextMimetype application/pdf

By organisation
School of Business, Society and Engineering
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 444 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 251 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf