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dc.contributor.authorAkkus, Yusuf
dc.contributor.authorAnnighöfer, Björn
dc.date.accessioned2026-08-23T08:00:07Z
dc.date.available2026-08-23T08:00:07Z
dc.date.copyright2026/10/01
dc.date.issued2026
dc.identifier.issn2690-702X
dc.identifier.otherjavs-26-1006.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4315929
dc.description.abstractAbstract. This study introduces an empirical approach to quantify the feasibility of transferring development methods across domains. The approach evaluates transfer proposals using an overall feasibility score and specific criteria such as cost, quality, and time. The Project Management Triangle was selected as the basis for this decision tool because its constraints can be quantified. The model produces a score on a scale from 0 to 10, based on two elements: the impact on automotive development and the relevance for automotive practices. Relevance was determined through a survey of 126 engineers from a commercial vehicle manufacturer, focusing on preferences regarding methods, processes, and tools. Survey results were used to weight the three constraints, improving forecast accuracy for the automotive domain. Model validation employed a previous study on common cause analysis for redundant chassis control systems, where aviation best practices were adapted for automotive. Engineers who applied gave their observed score. The forecasted feasibility score of 6.758 was compared with an observed score of 5.833, yielding an accuracy of 14%, which classifies the model as good. The proposed method offers three contributions: it provides a quantified feasibility assessment for cross-domain transfers, combines qualitative and quantitative indicators, and customizes weighting based on target group relevance. Limitations include reliance on data from a single manufacturer and validation based on one-method transfer. Overall, the approach demonstrates potential as a decision-support tool for reducing risks in cross-domain technology adoption.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleForecast of the Feasibility of Aviation-to-Automotive Methods Transfer by Empirical Quantification
dc.typeJournal Paper
dc.journal.volume6
dc.journal.issue4
dc.journal.titleJournal of Autonomous Vehicles and Systems
dc.identifier.doi10.1115/1.4071924
dc.journal.fristpage99
dc.journal.lastpage106
dc.page8
dc.treeJournal of Autonomous Vehicles and Systems:;2026:;volume( 006 ):;issue:004
dc.contenttypeFulltext


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