Details

A non-compensatory framework integrating LCA and QFD for robust manufacturing sustainability decisions under uncertainty: : an OCC paper machine case study
ID Rihar, Lidija (Author), ID Jenko, Marjan (Author)

.pdfPDF - Presentation file, Download (2,46 MB)
MD5: E769F1DC17FC7363BA155BEA6F8753DC
URLURL - Source URL, Visit https://www.mdpi.com/2227-9717/14/4/649 This link opens in a new window

Abstract
Manufacturing decarbonization and sustainability improvement require decision-support methods that can prioritise actions across multiple, often conflicting dimensions, including product quality, process stability, resource efficiency, and environmental performance. In industrial practice, such decisions are further complicated by stochastic variability and the presence of dominant drivers, which limit the usefulness of conventional linear, weighted- sum scoring approaches. This paper proposes a non-compensatory decision framework with explicit stochastic uncertainty propagation that integrates quality function deployment (QFD) with life cycle assessment (LCA) to support robust, value-driven prioritisation of manufacturing improvement actions under uncertainty. The approach combines QFD-style influence factor modelling with LCA-based environmental indicators and employs a non- linear, non-compensatory aggregation scheme to reduce sensitivity to arbitrary weighting and to better capture dominant and tail-risk effects. Uncertainty is propagated using Monte Carlo simulation, and the stability of prioritisation outcomes is analysed using sensitivity measures. The framework is demonstrated on an industrial old corrugated container (OCC) paper machine line using operational data from plant information systems, including quality, process control, laboratory, and maintenance databases. Results show that the proposed integration yields more stable and interpretable prioritisation of improvement actions than conventional compensatory scoring methods, particularly under variable operating conditions. The proposed approach enables practical, data-driven sustainability decision-making in complex manufacturing processes under variable operating conditions and alternative process configurations.

Language:English
Keywords:non-compensatory aggregation, decision-support framework, uncertainty analysis
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FS - Faculty of Mechanical Engineering
Publication status:Published
Publication version:Version of Record
Year:2026
Number of pages:20 str.
Numbering:Vol. 14, issue 4, art. no. 649
PID:20.500.12556/RUL-179991 This link opens in a new window
UDC:004.94:502.131.1
ISSN on article:2227-9717
DOI:10.3390/pr14040649 This link opens in a new window
COBISS.SI-ID:269790467 This link opens in a new window
Publication date in RUL:27.02.2026
Views:248
Downloads:118
Metadata:XML DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Record is a part of a journal

Title:Processes
Shortened title:Processes
Publisher:MDPI AG
ISSN:2227-9717
COBISS.SI-ID:523353113 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:nekompenzacijska agregacija, struktura za podporo odločanju, analiza negotovosti

Projects

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P2-0270-2022
Name:Proizvodni sistemi, laserske tehnologije in spajanje materialov

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back