Abstract
Advancement of IoT and ICT provide infrastructure to manage, monitor and control Cyber-Physical Systems (CPS) through timely provision of real-time information from the shop floor. Although real-time information in CPS such as resource failures can be detected based on IoT and ICT, improper response to resource failures may cripple CPS and degrade performance. Effective operations of CPS relies on an effective scheme to evaluate the impact of resource failures, support decision making needed and take proper actions to respond to resource failures. This motivates us to develop a methodology to assess the impact of resource failures on operations of CPS and provide the decision support as needed. The goal of this study is to propose solution algorithms to analyze robustness of CPS with respect to resource failures in terms of the impact on temporal properties. Given CPS modeled by a class of discrete timed Petri nets (DTPNs), we develop theory to analyze robustness of CPS by transforming the models to residual spatial-temporal network (RSTN) models in which capacity loss due to resources is reflected. We formulate an optimization problem to determine the influence of resource failures on CPS based on RSTNs and analyze the feasibility to meet the order deadline. To study the feasibility to solve a real problem, we analyze the computational complexity of the proposed algorithms. We illustrate the proposed method by application scenarios. We conduct experiments to study efficiency and verify computational feasibility of the proposed method to solve a real problem.
Highlights
The advancement of information and communications technology (ICT) and Internet of Things (IoT) [1] provides the infrastructure for Cyber-Physical Systems (CPS) [2,3] to manage, monitor and control manufacturing systems
As this paper focuses on influence of resource failures on temporal property of CPS, a class of deterministic discrete timed Petri nets are adopted
As the goal of this paper is to develop a method to assess the impact of resource failures on the system after the occurrence of failures, we model resource failures as loss of tokens in discrete timed Petri nets
Summary
The advancement of information and communications technology (ICT) and Internet of Things (IoT) [1] provides the infrastructure for Cyber-Physical Systems (CPS) [2,3] to manage, monitor and control manufacturing systems. ICT refers to technologies involving any kind of computing/communication devices, networking components and information systems that enable efficient interaction in the digital world, while IoT can be defined as the network of physical objects embedded with sensors, software and relevant ICT technologies for interacting with other objects/systems over the Internet. In CPS for manufacturing systems, failures of machines/resources are unavoidable. Managers often wonder and worry about whether the original due dates of orders can still be met when failures of machines/resources occur, i.e., whether the manufacturing system is robust with respect to the failures. Providing a decision support tool for managers to assess the impact of failures of machines/resources on the orders is an important issue
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