Generation of STEP AP214 Models From Discrete Event Systems for Process Planning and Control

Falkman, Petter; Nielsen, Johan; Lennartson, Bengt; Euler-Chelpin, Astrid von

doi:10.1109/tase.2007.909632

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…Among different available information standards to represent material flow data and layout related data, ISO 10303 (STEP) has exposed a rigorous potential to structure and integrates heterogonous data from different information sources. Using STEP to exchange 3D geometrical model, product structure, manufacturing process plans, material flow data, kinematic data, and so forth has been shown and proven in [4][5][6][7][8][9][10]. STEP is intended to handle product data throughout its entire life cycle.…”

Section: Step Standardmentioning

confidence: 99%

Service Oriented Integration of Distributed Heterogeneous IT Systems in Production Engineering Using Information Standards and Linked Data

Zadeh

Lindberg

El‐khoury

et al. 2017

Modelling and Simulation in Engineering

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While design of production systems based on digital models brings benefits, the communication of models comes with challenges since models typically reside in a heterogeneous IT environment using different syntax and semantics. Coping with heterogeneity requires a smart integration strategy. One main paradigm to integrate data and IT systems is to deploy information standards. In particular, ISO 10303 STEP has been endorsed as a suitable standard to exchange a wide variety of product manufacturing data. One the other hand, service-oriented tool integration solutions are progressively adopted for the integration of data and IT-tools, especially with the emergence of Open Services for Lifecycle Collaboration whose focus is on the linking of data from heterogeneous software tools. In practice, there should be a combination of these approaches to facilitate the integration process. Hence, the aim of this paper is to investigate the applications of the approaches and the principles behind them and try to find criteria for where to use which approach. In addition, we explore the synergy between them and consequently suggest an approach based on combination of them. In addition, a systematic approach is suggested to identify required level of integrations and their corresponding approaches exemplified in a typical IT system architecture in Production Engineering.

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Section: Step Standardmentioning

confidence: 99%

Service Oriented Integration of Distributed Heterogeneous IT Systems in Production Engineering Using Information Standards and Linked Data

Zadeh

Lindberg

El‐khoury

et al. 2017

Modelling and Simulation in Engineering

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show abstract

“…Much research has already been conducted on information modeling required for manufacturing processes, DES, online simulation, NC data and interlocking [1][2], However, little has been investigated concerning the connection between information and DES models and integrating this information with other type of data. Furthermore; More than 20 methods, including languages, methodologies, tools and standards, have been reported to specify processes of different domains [3].…”

Section: Related Workmentioning

confidence: 99%

An Approach for Manufacturing Process Representation in Product Lifecycle Management

Shariatzadeh¹,

Sivard²,

Lindberg³

2013

KEM

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Current Product Lifecycle Management systems (PLM) have concentrated on product design, not on manufacturing engineering with its development of e.g. Material flows and layouts. This paper proposes an approach to describe how to represent the main required manufacturing process data using ontologies together with generic data standards. This approach makes it possible to develop translations between different software, and also providing users with the meaning of different concepts. It contributes to an efficient management of manufacturing information, with a focus on the material flow information as used in Discrete Event Simulation -DES.

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“…Based on the international standard for process relations and information exchange, STEP-AP214 (ISO 10303-1 1994), Falkman et al (2008) proposed a number of process operators that are useful in our setting. Inspired by that work, the following specification types were chosen to be considered:…”

Section: Specification Typesmentioning

confidence: 99%

Time-Optimal Coordination of Flexible Manufacturing Systems Using Deterministic Finite Automata and Mixed Integer Linear Programming

Kobetski

Fabian

2009

Discrete Event Dyn Syst

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Automation and flexibility are often mentioned as key concepts in modern production industry. To increase the level of flexibility, deterministic finite automata (DFA) can be used to model, specify and verify the production systems. Often, it is also desirable to optimize some production criteria, such as for example the cycle time of a manufacturing cell. In this paper, a method for automatic conversion from DFA to a mixed integer linear programming (MILP) formulation is first presented. This conversion is developed for a number of DFA structures that have shown to be useful in practical applications. Special attention is paid to reducing the search region explored by the MILP solver. Second, a conversion from the MILP solution to a DFA supervisor is described. This allows to combine the advantages of DFA modeling with the efficiency of MILP and supervisory control theory to automatically generate time-optimal, collision-free and non-blocking working schedules for flexible manufacturing systems.

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Generation of STEP AP214 Models From Discrete Event Systems for Process Planning and Control

Cited by 8 publications

References 11 publications

Service Oriented Integration of Distributed Heterogeneous IT Systems in Production Engineering Using Information Standards and Linked Data

Service Oriented Integration of Distributed Heterogeneous IT Systems in Production Engineering Using Information Standards and Linked Data

An Approach for Manufacturing Process Representation in Product Lifecycle Management

Time-Optimal Coordination of Flexible Manufacturing Systems Using Deterministic Finite Automata and Mixed Integer Linear Programming

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