Research On Nonlinear Modeling And Optimizing Of Capacity For Aircraft Assembly System

Capacity is one of the important indexes to evaluate the ability of assembling or processing for the manufacturing system.As for the aircraft assembly system(AAS),scientific analysis and optimization of capacity provides an important guarantee of improving management and market competitiveness for the aviation manufacturing industry.Currently,with some LP(Lean production)methods such as pulsing assembly and JIT(Just-in-Time)being applied to aviation industry from common industries,the production and organization of AAS have changed dramatically,which brings forward higher requirements of accurate capacity analysis,prediction and optimization.However,capacity analysis and optimization of AAS in China are relatively extensive and lagging at present.Effectiveness and timeliness of the present methods depend on managers’ experience as well as statistical analytical skills.What is worse,many key factors affecting capacity are difficult to select and describe quantitatively and dynamically.Meanwhile,AAS is a typical multiple-input single-output(MISO)production system and its operation shows evident nonlinear characteristics,which leads to multi-level and multi-dimensional complexity of capacity modeling and optimizing.Therefore,considering the nonlinear characteristics of AAS,it is great theoretical and practical significance for studying the modeling,analyzing and optimizing of capacity so as to describe the operation state and control the capacity.Based on the above analysis,this dissertation will devote itself to investigate several key technologies regarding nonlinear modeling and optimizing of capacity for AAS in order to improve the capacity and keep balancing the system.The main contents and innovation of this dissertation are summarized as follows.1)Chapter 1 analyses the significance and challenge of capacity nonlinear modeling and optimizing for AAS.The domestic and overseas research status including nonlinear modeling,capacity analyzing and assembly line balancing(ALB),etc.of large scale manufacturing system has also been reviewed.The critical issues demanding to be promptly studied of this dissertation is pointed out.2)Chapter 2 proposes a nonlinear dynamic model of capacity based on control parameters analysis.Firstly,the nonlinear characteristics and capacity constraints of AAS is analyzed according to the requirements of capacity modeling and optimizing.Then,the PRL(productivity,reliability,and learning effect)& PCL(productivity,cost,and learning effect)coupling dynamic models of system capacity are constructed by choosing the key control parameters of capacity.The dynamic development of assembling productivity affected by these control parameters’ nonlinear coupling is described quantitatively.Subsequently,the macro-operation state of AAS is analyzed and the bifurcation points when the system falls into to chaos are solved out.Thus the control boundary which ensures steady operation of AAS can be calculated from the key control parameters.Finally,the proposed PRL&PCL models have been tested on several practical cases and the results show their feasibility and superiority.3)Chapter 3 proposes a dynamic capacity analysis approach based on the calculation of effective man-hour(EMH),in order to obtain the capacity of assembly units in AAS.In view of assemblers,a personnel EMH calculation method is presented based on nonlinear revision of multi-factors.Several key factors which affect personnel operational capacity are selected and used for quantitatively revising the theoretical man-hour,and then the EMH of assembly units can be solved.In view of automatic assembly equipment,a method of calculating the equipment’s EMH based on a dynamic mixed Weibull distribution model is proposed.The effect of all subsystems on availability of the whole equipment is analyzed,and the dynamic mixed Weibull distribution model of availability with three parameters is established,with the purpose of calculating the EMH of assembly units.Finally,the feasibility of proposed methods was justified by several practical cases.4)Chapter 4 investigates the effect of assemblers’ difference and mobility on the balance of AAS,and proposes an assembly system balancing approach based on dynamic personnel allocation.The control boundary ensuring the steady operation of AAS from Chapter 2 is set as constraint,and the EMH results from Chapter 3 are chosen as inputs,the fixed multi-skilled workers and the cross-station mobile workers are assigned respectively in order to balance AAS.Firstly,two balancing models based on dynamical allocation of multi-skilled workers and cross-station mobile workers are established.Secondly,two types of adaptive binary particle swarm optimization algorithms(A-BPSO)are designed to improve the applicability in the context of this dissertation.Finally,the proposed models and algorithms have been tested on several practical cases and the results show their feasibility.5)Chapter 5 develops several functional modules of the aircraft assembling capacity management system.Based on the existing manufacturing execution system(MES)and assembly resume data used in an aircraft manufacturing company,four modules including effective data acquisition,capacity dynamical analysis,capacity balancing and visual simulation have been built according to the practical requirements.This dissertation provides a theoretical basis for these modules and realizes the dynamic calculation and optimal control of capacity for AAS.