Abstract
The Commercial Aircraft Cooperation of China (COMAC) ARJ21 fuselage’s final assembly process is used as a case study. The focus of this paper is on the condition based maintenance regime for the (semi-) automatic assembly machines and how they impact the throughput of the fuselage assembly process. The fuselage assembly process is modeled and analyzed by using agent based simulation in this paper. The agent approach allows complex process interactions of assembly, equipment, and maintenance to be captured and empirically studied. In this paper, the built network is modeled as the sequence of activities in each stage, which are parameterized by activity lead time and equipment used. A scatter search is used to find multiobjective optimal solutions for the CBM regime, where the maintenance related cost and production rate are the optimization objectives. In this paper, in order to ease computation intensity caused by running multiple simulations during the optimization and to simplify a multiobjective formulation, multiple Min-Max weightings are used to trace Pareto front. The empirical analysis reviews the trade-offs between the production rate and maintenance cost and how sensitive the design solution is to the uncertainties.
Highlights
Nowadays, aircraft manufacturers are operating in a global competitive environment
Both Discrete Event Simulation (DES) and Agent Based Simulation (ABS) allow the important aspects like quality, cost, and time to be simulated and analyzed which provide the basis in Manufacturing System Development (MSD) and Product Realization Process (PRP) [23]
More automatic assembly machines have increasingly been used in the aircraft assembly lines as a mean to deliver high production rate while meeting high quality requirements
Summary
Aircraft manufacturers are operating in a global competitive environment. Increasing production rate and reducing costs are the key drivers in aircraft manufacturing. ISRN Aerospace Engineering logistics) contracts [17], and generic stochastically deteriorating systems [18] In these examples, it has been shown that CBM can potentially improve the overall cost and production rate of the manufacturing systems by increasing the machine availability while reducing the maintenance cost [17, 18]. In a highly complex process it is simpler to model using ABS; complex interactions between entities (e.g., machine, service, and process) can be naturally captured in ABS without having to reformulate a problem into the queue theory framework as required by DES [21, 22] Both DES and ABS allow the important aspects like quality, cost, and time to be simulated and analyzed which provide the basis in Manufacturing System Development (MSD) and Product Realization Process (PRP) [23].
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