Abstract
Due to ever-increasing complexity of cutting-edge engineering systems, the need for managing structural complexity and modularity of such systems is becoming important. The complexity of the overall system architecture is mostly decided during the initial concept generation stage, when configurations of major modules within the system are determined. In this paper, we present a multi-objective optimization framework for (1) minimizing the variation in complexity allocation to individual modules, while (2) maximizing for the degree of modularity. The optimization framework was applied to a case study, where a trailing bogie system for railroad train was optimized for structural complexity allocation among individual modules and overall system modularity. The modularity maximizing decomposition is shown to induce a large variation in module-level complexity distribution with a small fraction of modules sharing a disproportionately large chunk of overall system complexity, while equitable distribution of module-level complexity leads to erosion in the degree of modularity achieved for the resulting system decomposition.
Highlights
One of the most fundamental heuristic guidelines in complex system design is to keep the system architecture as simple as possible
The optimization framework was applied to a case study, where a trailing bogie system for railroad train was optimized for structural complexity allocation among individual modules and overall system modularity
We presented a multi-objective optimization framework that minimizes the variation in complexity allocation among individual modules, while maximizing the overall degree of modularity of the system
Summary
One of the most fundamental heuristic guidelines in complex system design is to keep the system architecture as simple as possible. Contrary to basic design rules, architectures of latest cutting-edge engineering systems are becoming more complex due to ever-increasing complexity of new technologies and infrastructures to support them, as well as demand for better lifecycle performances (Frey et al 2007). This overall trend necessitates an important need for proper system architecture complexity management process. Each module in the system performs a specific function required by the system to achieve overall system performance objective This allows system architects to replace individual modules to improve specific functionality carried out by that specific module, with minimum impact to the rest of the system. While each module has its own internal structural arrangement, its connection to other modules is
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