Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes

Minna Räikkönen; Teuvo Uusitalo; Saara Hänninen; Andrea Barni; Claudio Capuzzimati; Alessandro Fontana; Marco Pirotta

doi:10.1007/978-3-031-25448-2_56

Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes

Minna Räikkönen (Corresponding author), Teuvo Uusitalo, Saara Hänninen, Andrea Barni, Claudio Capuzzimati, Alessandro Fontana, Marco Pirotta

University of Applied Sciences and Arts of Southern Switzerland (SUPSI)

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

Since the manufacturing industry is one of the major global energy consumers and carbon emitters, energy efficiency has emerged as one of the industry's key drivers. Additionally, digital technologies offer companies significant opportunities to boost productivity and generate cost savings while simultaneously reducing the environmental impact. This study establishes a framework for economic and environmental indicators supporting smart manufacturing and asset management operations. The framework contributes to the sustainability assessment of digital solutions focused on increasing energy efficiency. In this setting, the emphasis is particularly on LCC (Life Cycle Costing) and LCA (Life Cycle Assessment) indicators. The approach is being tested in four different types of pilot companies in the manufacturing sector. The study examines the indicators from several angles at the process and machine levels. In the next phase of our research, software tools for the energy efficiency-oriented online LCC and LCA will be developed to make the indicator framework practical.

Original language	English
Title of host publication	16th WCEAM Proceedings
Editors	Adolfo Crespo Márquez, Juan Francisco Gómez Fernández, Vicente González-Prida Díaz, Joe Amadi-Echendu
Publisher	Springer
Pages	602–611
Number of pages	10
Edition	1
ISBN (Electronic)	978-3-031-25448-2
ISBN (Print)	978-3-031-25447-5
DOIs	https://doi.org/10.1007/978-3-031-25448-2_56
Publication status	Published - Feb 2023
MoE publication type	A4 Article in a conference publication
Event	16th World Congress on Engineering Asset Management, WCEAM 2022 - Sevilla, Spain Duration: 5 Oct 2022 → 7 Oct 2022

Publication series

Series	Lecture Notes in Mechanical Engineering
ISSN	2195-4356

Conference

Conference	16th World Congress on Engineering Asset Management, WCEAM 2022
Abbreviated title	WCEAM 2022
Country/Territory	Spain
City	Sevilla
Period	5/10/22 → 7/10/22

Keywords

economic indicators
environmental indicators
energy efficiency
digital technologies
manufacturing
asset management
sustainability assessment

UN SDGs

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

Access to Document

10.1007/978-3-031-25448-2_56

DENiM: Digital intelligence for collaborative ENergy management in Manufacturing
Hänninen, S., Kortelainen, J., Virtanen, J., Katajamäki, K., Kivikytö-Reponen, P., Korvola, T., Lämsä, V., Räikkönen, M., Uusitalo, T., Zou, G., Virkkunen, R. & Hyrynen, J.
1/11/20 → 31/10/24
Project: EU project

Cite this

Räikkönen, M., Uusitalo, T., Hänninen, S., Barni, A., Capuzzimati, C., Fontana, A., & Pirotta, M. (2023). Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes. In A. Crespo Márquez, J. F. Gómez Fernández, V. González-Prida Díaz, & J. Amadi-Echendu (Eds.), 16th WCEAM Proceedings (1 ed., pp. 602–611). Springer. Lecture Notes in Mechanical Engineering https://doi.org/10.1007/978-3-031-25448-2_56

Räikkönen, Minna ; Uusitalo, Teuvo ; Hänninen, Saara et al. / Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes. 16th WCEAM Proceedings. editor / Adolfo Crespo Márquez ; Juan Francisco Gómez Fernández ; Vicente González-Prida Díaz ; Joe Amadi-Echendu. 1. ed. Springer, 2023. pp. 602–611 (Lecture Notes in Mechanical Engineering).

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title = "Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes",

abstract = "Since the manufacturing industry is one of the major global energy consumers and carbon emitters, energy efficiency has emerged as one of the industry's key drivers. Additionally, digital technologies offer companies significant opportunities to boost productivity and generate cost savings while simultaneously reducing the environmental impact. This study establishes a framework for economic and environmental indicators supporting smart manufacturing and asset management operations. The framework contributes to the sustainability assessment of digital solutions focused on increasing energy efficiency. In this setting, the emphasis is particularly on LCC (Life Cycle Costing) and LCA (Life Cycle Assessment) indicators. The approach is being tested in four different types of pilot companies in the manufacturing sector. The study examines the indicators from several angles at the process and machine levels. In the next phase of our research, software tools for the energy efficiency-oriented online LCC and LCA will be developed to make the indicator framework practical.",

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author = "Minna R{\"a}ikk{\"o}nen and Teuvo Uusitalo and Saara H{\"a}nninen and Andrea Barni and Claudio Capuzzimati and Alessandro Fontana and Marco Pirotta",

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booktitle = "16th WCEAM Proceedings",

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Räikkönen, M , Uusitalo, T , Hänninen, S, Barni, A, Capuzzimati, C, Fontana, A & Pirotta, M 2023, Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes. in A Crespo Márquez, JF Gómez Fernández, V González-Prida Díaz & J Amadi-Echendu (eds), 16th WCEAM Proceedings. 1 edn, Springer, Lecture Notes in Mechanical Engineering, pp. 602–611, 16th World Congress on Engineering Asset Management, WCEAM 2022, Sevilla, Spain, 5/10/22. https://doi.org/10.1007/978-3-031-25448-2_56

Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes. / Räikkönen, Minna (Corresponding author); Uusitalo, Teuvo ; Hänninen, Saara et al.

16th WCEAM Proceedings. ed. / Adolfo Crespo Márquez; Juan Francisco Gómez Fernández; Vicente González-Prida Díaz; Joe Amadi-Echendu. 1. ed. Springer, 2023. p. 602–611 (Lecture Notes in Mechanical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes

AU - Räikkönen, Minna

AU - Uusitalo, Teuvo

AU - Hänninen, Saara

AU - Barni, Andrea

AU - Capuzzimati, Claudio

AU - Fontana, Alessandro

AU - Pirotta, Marco

PY - 2023/2

Y1 - 2023/2

N2 - Since the manufacturing industry is one of the major global energy consumers and carbon emitters, energy efficiency has emerged as one of the industry's key drivers. Additionally, digital technologies offer companies significant opportunities to boost productivity and generate cost savings while simultaneously reducing the environmental impact. This study establishes a framework for economic and environmental indicators supporting smart manufacturing and asset management operations. The framework contributes to the sustainability assessment of digital solutions focused on increasing energy efficiency. In this setting, the emphasis is particularly on LCC (Life Cycle Costing) and LCA (Life Cycle Assessment) indicators. The approach is being tested in four different types of pilot companies in the manufacturing sector. The study examines the indicators from several angles at the process and machine levels. In the next phase of our research, software tools for the energy efficiency-oriented online LCC and LCA will be developed to make the indicator framework practical.

AB - Since the manufacturing industry is one of the major global energy consumers and carbon emitters, energy efficiency has emerged as one of the industry's key drivers. Additionally, digital technologies offer companies significant opportunities to boost productivity and generate cost savings while simultaneously reducing the environmental impact. This study establishes a framework for economic and environmental indicators supporting smart manufacturing and asset management operations. The framework contributes to the sustainability assessment of digital solutions focused on increasing energy efficiency. In this setting, the emphasis is particularly on LCC (Life Cycle Costing) and LCA (Life Cycle Assessment) indicators. The approach is being tested in four different types of pilot companies in the manufacturing sector. The study examines the indicators from several angles at the process and machine levels. In the next phase of our research, software tools for the energy efficiency-oriented online LCC and LCA will be developed to make the indicator framework practical.

KW - economic indicators

KW - environmental indicators

KW - energy efficiency

KW - digital technologies

KW - manufacturing

KW - asset management

KW - sustainability assessment

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DO - 10.1007/978-3-031-25448-2_56

M3 - Conference article in proceedings

SN - 978-3-031-25447-5

T3 - Lecture Notes in Mechanical Engineering

SP - 602

EP - 611

BT - 16th WCEAM Proceedings

A2 - Crespo Márquez, Adolfo

A2 - Gómez Fernández, Juan Francisco

A2 - González-Prida Díaz, Vicente

A2 - Amadi-Echendu, Joe

PB - Springer

T2 - 16th World Congress on Engineering Asset Management, WCEAM 2022

Y2 - 5 October 2022 through 7 October 2022

ER -

Räikkönen M , Uusitalo T , Hänninen S, Barni A, Capuzzimati C, Fontana A et al. Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes. In Crespo Márquez A, Gómez Fernández JF, González-Prida Díaz V, Amadi-Echendu J, editors, 16th WCEAM Proceedings. 1 ed. Springer. 2023. p. 602–611. (Lecture Notes in Mechanical Engineering). doi: 10.1007/978-3-031-25448-2_56

Economic and Environmental Indicators for Assessing Energy Efficiency Improvements in the Smart Manufacturing Processes

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Projects

DENiM: Digital intelligence for collaborative ENergy management in Manufacturing

Cite this