Vulnerability evaluation method applied to manufacturing systems. (December 2018)

• Record Type: Journal Article
• Authors: Guibing, Gao; Wenhui, Yue; Wenchu, Ou; Hao, Tang
• Is Part Of: Reliability engineering & system safety. Volume 180(2018)
• Page Start: 255
• Page End: 265
• Publication Date: 2018-12
• Subjects: Complex network -- Manufacturing system -- Vulnerability -- Scale model -- Evaluation; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2018.06.011
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: A mechanism to evaluate the MS's vulnerability under threats is proposed. The indices of topological structure vulnerability and the functional vulnerability are given. The multidimensional spatial computing model of vulnerability is build. Abstract: The safe operation requirement for an enterprise depends significantly on the uninterrupted and reliable functioning of its manufacturing system (MS). However, this system is frequently subjected to different disturbances and destructions, such as safety accidents, equipment fault, and misoperation. Therefore, a sophisticated evaluation mechanism and an effective alleviation design for the vulnerability of a MS are of great importance for the reliable functioning of the MS. This study proposes a detailed methodology to comprehensively assess the vulnerability of a MS subject to different disturbances by using complex networks and simulation technology. The proposed methodology includes a complex network expression for the MS, a description of the equipment failure scenarios, a method to analyze the vulnerability of the MS, and an evaluation method to quantify the vulnerability value. The vulnerability of a MS is evaluated in terms of its work, including the topological structure vulnerability and function vulnerability. Different vulnerability metrics are described, and the vulnerability information is quantified by the multidimensional spatial computing method. Subsequently, the effectiveness of the proposed method is validated in the engineering assembly manufacturing system (EAMS).