Co-design (concurrent engineering) is an important prerequisite for finding the best design solution for both future aircraft and the corresponding industrial systems. This paper discusses the use of simulation in the process of co-defining the optimal industrial system configuration for a future aircraft with a case study determining the logistic system for the aircraft fuselage manufacturing. The scope of the paper includes the industrial performance, the logistics costs, and the environmental footprint of the logistic system. To study the large design space, the generation and the execution of the simulation have to be automated in a scalable cloud infrastructure.
The analysis of the industrial system, particularly the logistics system, may use a mixed approach of agent-based and discrete event simulation, implemented in AnyLogic. All system elements were represented by agents, while their behavior partially followed the discrete event paradigm. The simulation model supported the parameter uncertainty (e.g., process duration, transport speed) and topology variability (the structure of the logistics network) defined in the input configuration data. It used dynamic instantiation of a specific simulation model based on input configuration data at startup.
The simulation was embedded into a complex modeling and analysis environment for defining the system parameters and constraints, the automated (logistics system) scenario generation, the simulation-based key performance indicator calculation, and the results visualization and comparison. Compared to manually defined and modeled scenarios (with a small number of parameter variations and a very small number of topology variants), the automated, data-driven, and cloud-based approach supported the detailed analysis of a large number of scenarios by simulation while at the same time reducing the costs of manual modeling.