Variation Propagation Modelling and Cost-Oriented Process Optimisation for Aircraft Assembly

  • Vincent McKenna

Student thesis: Doctoral ThesisDoctor of Philosophy


Overconstrained assemblies, such as aircraft sub-assemblies, present a challenge to production planners, as variations in parts can make it difficult to achieve all assembly Key Characteristics (KCs) simultaneously. Despite assigning tight tolerances to sub-component manufacture, part variation propagation necessitates expensive and time consuming variation management processes such as shimming in order to ensure the final assembly is within specification. This thesis focuses on how the overall production cost can be minimised, and presents a methodology to relate part manufacture and assembly variation to the associated manufacture and assembly costs.
The proposed methodology is underpinned by a variation propagation model for overconstrained assemblies. Part, fixture and assembly features are modelled using the homogeneous transformation matrix method. An algorithm is developed to model the assembly technique, which has a major impact on assembly variations in overconstrained assemblies.
Using a sensitivity study, the variation propagation model quantifies and ranks the part and fixture features with the largest impact on assembly variation. The effect of the variation propagation caused by the assembly method is also quantified using the proposed method.
The cost of variation is determined by combining the variation propagation model with an Activity Based Costing model. The model considers the variation and cost implications of different part fabrication and assembly processes. The cost of variation management processes required at assembly due to accumulated variation is also evaluated. The summation of these costs gives the total cost of production related to variation.
To determine the best combination of part fabrication and assembly processes, a cost-oriented process optimisation is proposed using the combined variation and cost modelling methodology. A Monte Carlo simulation is applied to the variation propagation model to approximate the random nature of variation occurrence. The cost model then determines the average total production cost for each combination of processes. This facilitates the selection of the processes and techniques which give the lowest total production cost.
The result is the ability to analyse the trade-offs between the total time, cost and achievable geometric tolerance limits of the entire production chain, and therefore design optimal production strategies. An overconstrained real industrial assembly case study (hinge brackets to wing spar) is used to validate the methodology and illustrate its cost reduction potential.
Date of AwardJul 2020
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SponsorsNorthern Ireland Department for the Economy
SupervisorAdrian Murphy (Supervisor) & Yan Jin (Supervisor)


  • Variation propagation
  • aerospace assembly
  • process selection
  • cost estimation
  • overconstrained assemblies

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