Modeling and online scheduling of flexible manufacturing systems using stochastic Petri nets

Hatono, Itsuo; Yamagata, Keiichi; Tamura, Hiroyuki

doi:10.1109/32.67588

Cited by 55 publications

(21 citation statements)

References 7 publications

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“…For this reason stochastic Petri nets (SPNs) were first described by Molloy [25,26] who attached stochastic, exponentially distributed times to transitions. The exponential distribution has several properties that make it particularly useful for the analysis of systems [27], and describes accurately some real-life distributions, such as failure distributions. Formally, SPNs are continuous-time systems.…”

Section: Relevant Literaturementioning

confidence: 99%

Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Simon¹,

Oyekan²,

Hutabarat³

et al. 2018

Int. j. simul. model.

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Discrete-Event Simulation (DES) is commonly used for the simulation of manufacturing systems. In many practical cases, DES practitioners have to make simplifications or to use the software in an unconventional or convoluted fashion to meet their needs. Petri nets enable the development of transparent models which allow increased flexibility and control for designers. Furthermore, Petri nets take advantage of a solid mathematical ground and constitute a simple language. However, Petri nets lack the software capabilities to realise their full potential. This study investigates the suitability and relevance of Discrete-Event Simulation (DES) software for Petri net modelling in the context of manufacturing systems. A framework is developed for the modelling of different classes of Petri nets on DES. Analytical models of asynchronous flow lines are developed. Initial results show that the analytical models are without closed-form solution and the explosion of the state space is observed, justifying the use of computational methods and simulation for the analysis of manufacturing systems. This study shows that the gain in flexibility provided by Petri nets provides a new insight into the effects of stochasticity on setup and failure times in manufacturing systems.

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Section: Relevant Literaturementioning

confidence: 99%

Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Simon¹,

Oyekan²,

Hutabarat³

et al. 2018

Int. j. simul. model.

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show abstract

“…Even though many of the scheduling problems in a production system that use real time control systems have attracted many researchers (13), (14), (15), (16) , most have not employed any feedback method of real time production control such as we have adopted in ARTCOPS, where the number of parts on the CONV is counted as output value with the multiple disordered IF-THEN rules collated together. Furthermore, the pull production system with ARTCOPS is not simply a feasible system due to the following two points of difficulties.…”

Section: Problems Statementmentioning

confidence: 99%

Real Time Part Input Control of a Pull Production System by Finding IF-THEN Rules

Ramli

Yamamoto

Qudeiri

2007

JAMDSM

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This paper considers the part input problem of a production system where two Flexible Transfer Lines (FTLs) consisting of an up-stream production line and a down-stream production line while operating under Just In Time (JIT) production management. The up-stream production line processes the raw material after receiving them from suppliers, and after processing them, delivers the processed product to a down-stream production line via a conveyer. In this paper, we have proposed a novel idea for a part input real time control system, known as Algorithm for Real Time Control of Part Input Systems (ARTCOPS). The algorithm is useful when FTLs are in operation under a production order that is different from the pre-decided production schedule. Simulations of virtual production systems have been carried out to verify that ARTCOPS is useful in real time control, although the production orders are different from the pre-decided production scheduling.

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“…al. [9]. With this type of handling uncertainty one obtains Petri net models which are very'well suited for simulation.…”

Section: Specifying Goods Flow Situationsmentioning

confidence: 99%

“…al. [9], Tamura, Hatono [22]; for cyclic job shops or assembly systems, see Harhalakis, Laftit, Proth [8]; for communication and computer systems, see Garg [7], Holiday, Venon [14], Magott [16], Molloy [19]). …”

mentioning

confidence: 99%

Decision Systems: The Relation Between Problem Specification and Mathematical Analysis

Wessels

1993

Lecture Notes in Economics and Mathematical Systems

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In this paper it is demonstrated that automated support for decision making of a tactical or strategic nature requires a solver-indepen dent medium for describing decision situations. Such a medium may be specific for one environment, but it is also possible to develop media for certain types of environments. By using such a medium one obtains a decoupling of problem formulation and method of analysis. This makes it possible to use (parts of) the problem formulation as input for different types of models. Such problem formulations may provide mathematical models themselves, although they might also contain some less formal features.The decoupling makes it possible to choose problem formulations which are much closer to the original decision situation than would otherwise be possible with formulations in terms of a preselected solver. The argumentation is illustrated by treating a language for specifying goods flow problems in some detail. This language is based on timed coloured Petri-nets.

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Modeling and online scheduling of flexible manufacturing systems using stochastic Petri nets

Cited by 55 publications

References 7 publications

Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Adapting Petri Nets to DES: Stochastic Modelling of Manufacturing Systems

Real Time Part Input Control of a Pull Production System by Finding IF-THEN Rules

Decision Systems: The Relation Between Problem Specification and Mathematical Analysis

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