MétaCan
Menu
Back to cohort
Record W2903118185 · doi:10.7771/2159-6670.1181

Collaborative Product–Service Approach to Aviation Maintenance, Repair, and Overhaul. Part I: Quantitative Model

2018· article· en· W2903118185 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Aviation Technology and Engineering · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsMcGill University
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorMcGill University
KeywordsOriginal equipment manufacturerAirframeAircraft maintenanceAviationService (business)Product (mathematics)Product-service systemBusinessEngineeringProcess managementBusiness modelEngineering managementOperations managementManufacturing engineeringComputer scienceAeronauticsMarketingAerospace engineering

Abstract

fetched live from OpenAlex

This two-part paper proposes a new collaborative approach to airframe maintenance, repair, and overhaul (MRO). A quantitative model is introduced in Part I to represent the business relationships between original equipment manufacturers (OEMs) and MRO enterprises. In Part II, the presented model is used to assess potential financial benefits obtained by each of these stakeholders as a result of the collaboration. The quantitative model is built to capture the main dependencies between an independent MRO enterprise operating in South America and its interactions with three major airframe OEMs. Interviews were conducted with MRO and OEM professionals to identify the most impactful operational resources on MRO activities. Stakeholders with different characteristics in terms of production capacity, annual revenue, fleet size, and age are considered in numerical studies to quantify the viability of the proposed collaborative business model in different scenarios. The obtained results show that optimal investment levels must be determined for each stakeholder to ensure the viability of the proposed collaborative business model, confirming the need for a quantitative method to aid service designers making decisions. The novel collaborative model contributes to the relatively scarce literature on the topic, and promotes effective and structured collaboration between OEMs and MRO enterprises aiming at delivering higher added value to end customers (operators).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.202
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it