Categorical Modeling Method of Intelligent WorkFlow

Crăciunean, Daniel-Cristian; Karagiannis, Dimitris

doi:10.1007/978-3-030-05918-7_11

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…In this way, we can exploit both the graph representation of the models which can easily be transformed in other graphs (i.e. Petri net), and the categorical approach to metamodeling [18], [19].…”

Section: Formalizing the Concept Of Modeling Methodsmentioning

confidence: 99%

Improving the Training Methods for Designers of Flexible Production Cells in Factories of the Future

Mironescu

Crăciunean

Florea

et al. 2020

Boosting Collaborative Networks 4.0

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This work proposes a design method for flexible manufacturing systems (FMS). The method reduces the learning curve by helping employees to solve problems related to the design and optimization of the layout, operation and control of FMS, avoiding the drawbacks of current tools. The approach uses Domain Specific Modeling Languages (DSML) for specification of FMS. The paper presents the definition of the DSML and the implementation of the graphical modeling and simulation tool bringing important contributions to development of the domain through the use of constructions from categories theory for DSML specifications. This mathematical basis allows the definition of constraints to avoid supplementary costs and eventual damages through incorrect or incomplete specification of the solutions. By interconnecting with ADOxx of the DSML and tool developed, facilitates access to other analysis and simulation tools like Bee-up, Petri net, better exploration of the design space and extended support for the design activity.

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Section: Formalizing the Concept Of Modeling Methodsmentioning

confidence: 99%

Improving the Training Methods for Designers of Flexible Production Cells in Factories of the Future

Mironescu

Crăciunean

Florea

et al. 2020

Boosting Collaborative Networks 4.0

Self Cite

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“…Modeling and simulation are the most common approaches in the process of designing these systems. Modeling makes it possible to simulate and analyze production processes as well as make decisions before the actual construction of the manufacturing line [7] [8]. Also, after the construction of the production line, the models can be used for its optimization and diagnosis.…”

Section: Introductionmentioning

confidence: 99%

A Monadic Co-simulation Model for Cyber-physical Production Systems

Crăciunean¹

2022

IJACSA

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The production flexibility required by the new industrial revolutions is largely based on heterogeneous Cyber-Physical Production Systems models that cooperate with each other to perform complex tasks. To accomplish tasks at an acceptable pace, CPPSs should be based on appropriate cooperation mechanisms. To this end a CPPS must be able to provide services in the form of functionalities to other CPPSs, and also to use functionalities of other CPPSs. The cooperation of two CPPS systems is done by co-simulating the two models that allow the partial or total access of the functionalities of one system, by the other system. Requests from one CPPS to another CPPS create connection moments of the two models that can only be performed in certain states of the two models. Also, the answers to these requests create connections between the two models in other subsequent states. Optimal aggregation of the behaviors of the two models, by co-simulation, is essential because otherwise it can lead to very long waiting times and can cause major problems if not done correctly. We will see in this paper that the behavior of such a simulation model can be represented by a category, and the co-simulation of two models can be defined by a monad determined by two adjoint functors between the simulation categories of the two models.

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“…All these components can be specified in various modeling languages. But there is a need for a specific language to assemble the system components into a workflow [3] and coordinate the behavior of these components. In our opinion, these interaction problems can be solved elegantly by cosimulation [4].…”

Section: Introductionmentioning

confidence: 99%

Implementing the Behavioral Semantics of Diagrammatic Languages by Co-simulation

Crăciunean¹

2020

IJACSA

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Due to the multidisciplinary nature of cyberphysical systems, it is impossible for an existing modeling language to be used effectively in all cases. For this reason, the development of domain-specific modeling languages is beginning to become an integral part of the modeling process. This diversification of modeling languages often implies the need to co-simulate subsystems in order to obtain the effect of a complete system. This paper presents how behavioral semantics of a diagrammatic DSML can be implemented by co-simulation. For the formal specification of the language we used mechanisms from the category theory. To specify behavioral semantics, we introduced the notion of behavioral rule as an aggregation between a graph transformation and a behavioral action. The paper also contains a relevant example and demonstrates that the implementation of behavioral semantics of a diagrammatic model can be achieved by co-simulating standalone FMUs associated to behavioral rules.

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Categorical Modeling Method of Intelligent WorkFlow

Cited by 4 publications

References 7 publications

Improving the Training Methods for Designers of Flexible Production Cells in Factories of the Future

Improving the Training Methods for Designers of Flexible Production Cells in Factories of the Future

A Monadic Co-simulation Model for Cyber-physical Production Systems

Implementing the Behavioral Semantics of Diagrammatic Languages by Co-simulation

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