Time templates for discrete event fault monitoring in manufacturing systems

Holloway, L.E.; Chand, S.

doi:10.1109/acc.1994.751830

Cited by 50 publications

(21 citation statements)

References 4 publications

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“…Some of these include Discrete Event Systems (DES) in [1] and [2]. Despite their theoretical soundness, however, the construction of viable DES models for complex domains such as manufacturing systems has proven to be very difficult due to state explosion and the need for accurate detailed modelling which is not always feasible for manufacturing systems.…”

Section: Introductionmentioning

confidence: 99%

A methodology for developing local smart diagnostic models using expert knowledge

Madsen

Søndberg-Jeppesen

Lohse

et al. 2015

2015 IEEE 13th International Conference on Industrial Informatics (INDIN)

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Abstract-This paper describes an innovative modular component-based modelling approach for diagnostics and condition-monitoring of manufacturing equipment. The approach is based on the use of object-oriented Bayesian networks, which supports a natural decomposition of a large and complex system into a set of less complex components. The methodology consists of six steps supporting the development process: Begin, Design, Implement, Test, Analyse, and Deploy. The process is iterative and the steps should be repeated until a satisfactory model has been achieved. The paper describes the details of the methodology as well as illustrates the use of the componentbased modelling approach on a linear axis used in manufacturing. This application demonstrates the power and flexibility of the approach for diagnostics and condition-monitoring and shows a significant potential of the approach for modular componentbased modelling in manufacturing and other domains.

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Section: Introductionmentioning

confidence: 99%

A methodology for developing local smart diagnostic models using expert knowledge

Madsen

Søndberg-Jeppesen

Lohse

et al. 2015

2015 IEEE 13th International Conference on Industrial Informatics (INDIN)

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“…Extensions of the above work can be found in [4] where the authors study testability of DES. In [14], the authors present a template monitoring scheme based on timing and sequencing relationships of events for fault monitoring in manufacturing systems. In [34], the authors propose a Petri net based method for failure diagnosis of manufacturing systems which uses Petri net models for failure detection and fault trees for failure isolation.…”

Section: Introduction Etection and Isolation Of Failures In Largementioning

confidence: 99%

Failure diagnosis using discrete-event models

Sampath

Sengupta

Lafortune

et al. 1996

IEEE Trans. Contr. Syst. Technol.

577

159

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Abstruct-Detection and isolation of failures in large, complex systems is a crucial and challenging task. The increasingly stringent requirements on performance and reliability of complex technological systems have necessitated the development of sophisticated and systematic methods for the timely and accurate diagnosis of system failures. We propose a discrete-event systems (DES) approach to the failure diagnosis problem. This approach is applicable to systems that fall naturally in the class of DES; moreover, for the purpose of diagnosis, continuous-variable dynamic systems can often be viewed as DES at a higher level of abstraction. We present a methodology for modeling physical systems in a DES framework and illustrate this method with examples. We discuss the notion of diagnosability, the construction procedure of the diagnoser, and necessary and sufficient conditions for diagnosability. Finally, we illustrate our approach using realistic models of two different heating, ventilation, and air conditioning (HVAC) systems, one diagnosable and the other not diagnosable. While the modeling methodology presented here has been developed for the purpose of failure diagnosis, its scope is not restricted to this problem; it can also be used to develop DES models for other purposes such as control. A detailed treatment of the theory underlying our approach can be found in a companion paper [27].

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“…Consequently, it is important to develop diagnostic methodologies for informationally decentralized systems. This fact is also recognized in Holloway and Chand (1994) and Boubour et al (1997).…”

Section: Introductionmentioning

confidence: 57%

“…Consequently, the problem of failure diagnosis has received considerable attention in the literature. Many schemes ranging from fault-tree (Lapp and Powers, 1977) and analytical redundancy (Willsky, 1976;Frank, 1990) methods to discrete event system (DES) approaches (Sampath et al, 1995;Lin, 1994;Bavishi and Chong, 1994;Holloway and Chand, 1994;Boubour et al, 1997;Cassandras and Lafortune, 1998), model based reasoning (Davis and Hamscher, 1992) and expert systems (Scherer and White, 1987) methods, have been proposed to approach this problem. For a brief description of these methods and additional references, the interested reader is referred to Pouliezos and Stavrakakis (1994) and the introduction of Sampath et al (1995).…”

Section: Introductionmentioning

confidence: 99%

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Coordinated decentralized protocols for failure diagnosis of discrete event systems

Debouk

Lafortune²,

Teneketzis³

SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218)

113

133

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Abstract. We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosability, originally introduced in Sampath et al. (1995) for centralized systems, to the proposed coordinated decentralized architecture. We specify three protocols that realize the proposed architecture; each protocol is defined by the diagnostic information generated at the local sites, the communication rules used by the local sites, and the coordinator's decision rule. We analyze the diagnostic properties of each protocol. We also state and prove conditions for a language to be diagnosable under each protocol. These conditions are checkable off-line. The on-line diagnostic process is carried out using the diagnosers introduced in Sampath et al. (1995) or a slight variation of these diagnosers. The key features of the proposed protocols are: (i) they achieve, each under a set of assumptions, the same diagnostic performance as the centralized diagnoser; and (ii) they highlight the "performance vs. complexity" tradeoff that arises in coordinated decentralized architectures. The correctness of two of the protocols relies on some stringent global ordering assumptions on message reception at the coordinator's site, the relaxation of which is briefly discussed.

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Time templates for discrete event fault monitoring in manufacturing systems

Cited by 50 publications

References 4 publications

A methodology for developing local smart diagnostic models using expert knowledge

A methodology for developing local smart diagnostic models using expert knowledge

Failure diagnosis using discrete-event models

Coordinated decentralized protocols for failure diagnosis of discrete event systems

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