Production ramp-up in multi-stage discrete manufacturing systems: A conceptual framework for model-based quality maturity assurance in the automotive industry based on a systematic literature review

A significant share of production ramp-ups fail to meet the defined targets. Achieving the defined product and process requirements for production validation and thus for start of production is of crucial importance. Numerous changes during production ramp-up pose a challenge for established quality assurance methods. This situation emphasizes the need to research and develop approaches that can consistently represent changes to support the mitigation of quality deviations during ramp-up. This paper proposes a conceptual framework for a model-based approach to quality maturity assurance in discrete multi-stage manufacturing systems based on automotive industry standards. A systematic literature review was conducted to identify possible methods for modelling quality-related product-process interactions that can integrate both knowledge from the development phase and empirical data during ramp-up. The findings are evaluated for their suitability for an interpretable graphical representation of cause-effect relationships and quantification of uncertainty through probabilistic modelling. The results show that Bayesian networks are a frequent modelling approach reported for this purpose, which are proposed for modelling relationships between quality characteristics. The approach is integrated into a concept consisting of the elements data acquisition, model development and risk evaluation. Finally, maturity levels according to automotive standards frame the concept to guide the modelling process from completed production planning to product and process release. This work contributes to developing a model-based understanding of quality assurance during ramp-up to overcome data shortage and improve the understanding of quality factors affecting production validation. Implications are discussed to highlight future research directions.

Authors

Institutions

Publication Details

Journal
Procedia CIRP
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procir.2024.12.095
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Production ramp-up in multi-stage discrete manufacturing systems: A conceptual framework for model-based quality maturity assurance in the automotive industry based on a systematic literature review

Felix Sohnius, Marcos Padrón Hinrichs, Robert Schmitt
Procedia CIRP
Manufacturing Process and Optimization
article

Production ramp-up in multi-stage discrete manufacturing systems: A conceptual framework for model-based quality maturity assurance in the automotive industry based on a systematic literature review

Felix Sohnius, Marcos Padrón Hinrichs, Robert Schmitt
article en

Abstract

A significant share of production ramp-ups fail to meet the defined targets. Achieving the defined product and process requirements for production validation and thus for start of production is of crucial importance. Numerous changes during production ramp-up pose a challenge for established quality assurance methods. This situation emphasizes the need to research and develop approaches that can consistently represent changes to support the mitigation of quality deviations during ramp-up. This paper proposes a conceptual framework for a model-based approach to quality maturity assurance in discrete multi-stage manufacturing systems based on automotive industry standards. A systematic literature review was conducted to identify possible methods for modelling quality-related product-process interactions that can integrate both knowledge from the development phase and empirical data during ramp-up. The findings are evaluated for their suitability for an interpretable graphical representation of cause-effect relationships and quantification of uncertainty through probabilistic modelling. The results show that Bayesian networks are a frequent modelling approach reported for this purpose, which are proposed for modelling relationships between quality characteristics. The approach is integrated into a concept consisting of the elements data acquisition, model development and risk evaluation. Finally, maturity levels according to automotive standards frame the concept to guide the modelling process from completed production planning to product and process release. This work contributes to developing a model-based understanding of quality assurance during ramp-up to overcome data shortage and improve the understanding of quality factors affecting production validation. Implications are discussed to highlight future research directions.

Procedia CIRPVol. 135
Fraunhofer Institute for Production Technology IPT (DE), RWTH Aachen University (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 72%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.