Formulation of reliability-related objective functions for design of intelligent mechatronic systems. (August 2017)

• Record Type: Journal Article
• Authors: Kaul, Thorben; Meyer, Tobias; Sextro, Walter
• Other Names: Podofillini Luca guest-editor.; Sudret Bruno guest-editor.; Stojadinović Božidar guest-editor.; Zio Enrico guest-editor.; Kröger Wolfgang guest-editor.
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 231:Number 4(2017:Aug.)
• Page Start: 390
• Page End: 399
• Publication Date: 2017-08
• Subjects: Integrated model -- reliability -- system behavior -- Bayesian network -- multiobjective optimization; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X17709376
• Languages: English
• ISSNs: 1748-006X

Abstract

State-of-the-art mechatronic systems offer inherent intelligence that enables them to autonomously adapt their behavior to current environmental conditions and to their own system state. This autonomous behavior adaptation is made possible by software in combination with complex sensor and actuator systems and by sophisticated information processing, all of which make these systems increasingly complex. This increasing complexity makes the design process a challenging task and brings new complex possibilities for operation and maintenance. However, with the risk of increased system complexity also comes the chance to adapt system behavior based on current reliability, which in turn increases reliability. The development of such an adaption strategy requires appropriate methods to evaluate reliability based on currently selected system behavior. A common approach to implement such adaptivity is to base system behavior on different working points that are obtained using multiobjective optimization. During operation, selection among these allows a changed operating strategy. To allow for multiobjective optimization, an accurate system model including system reliability is required. This model is repeatedly evaluated by the optimization algorithm. At present, modeling of system reliability and synchronization of the models of behavior and reliability is a laborious manual task and thus very error-prone. Since system behavior is crucial for system reliability, an integrated model is introduced that integrates system behavior and system reliability. The proposed approach is used to formulate reliability-related objective functions for a clutch test rig that are used to compute feasible working points using multiobjective optimization.