Virginie Fortineau

Thomas Paviot

Ludovic Louis-Sidney

Samir Lamouri

SWRL as a rule language for ontology-based models in power plant design

Keywords: rules, power plant, ontology, Description Logics (DL), SWRL

Current standard models have improved interoperability in Product Lifecycle Management. But the increase of constrains surrounding information management in an industrial context, and notably for power plant design, like the increase of data, actors, systems and the need of automation and collaboration leads to an increasing use of ontologybased models. However, the design of power plants presents a specific issue, which is rules expression and validation. This need of rules is generated by safety, interoperability or collaboration constrains. The Semantic Web Rule Language (SWRL) is an ontological language based on OWL-DL that allows in addition rules expression. This paper presents SWRL rules and their industrial applications but also limits of this language in PLM applications. It proposes in consequence other rules languages.

Context of the study

Process and power plants have specific issues involving information management along the product lifecycle, because plants are specific products. Some of these issues are [START_REF] Mun | Sharing product data of nuclear power plants across their lifecycles by utilizing a neutral model[END_REF]:

long term information storage (from design to maintenance and disassembly); a large number of data produced; lots of actors and application systems involved; control policies and safety and checking constraints.

Like in many industrial fields, Product Lifecycle Management (PLM) is a global methodology that could provide efficient solutions to these issues [START_REF] Terzi | Product lifecycle management -from its history to its new role[END_REF]. Performing interoperability between information systems is a crucial step of this methodology [START_REF] Wegner | Interoperability[END_REF], that must be achieved in terms of organization, technic and models semantic. Moreover, on a semantic viewpoint, expressing and validating rules is a determining issue in today's modeling. A rule is in this context a specification of a requirement or a constraint about the product or its management [START_REF] Mun | ISO 15926-based data repository and related web services for sharing lifecycle data of process plants[END_REF]. These rules are the focus of this study.

Semantic models have been developed to enhance interoperability in plant design, such as the Generic Product Model (GPM) used in nuclear applications in South Korea [START_REF] Mun | Sharing product data of nuclear power plants across their lifecycles by utilizing a neutral model[END_REF]. Standard semantic models also exist, that are especially adapted to plant specificities, like Part Librairies (ISO 10303) [START_REF] Wei | Design of building component library based on ifc and plib standard[END_REF] and PLCS (ISO 10303, AP 239) 3 that are both expressed in EXPRESS language. However, the increasing need of safety and process automation and the complexity of these languages led to the development of ontology-based models, like ISO 15926 [START_REF] Kim | Integration of distributed plant lifecycle data using ISO 15926 and Web services[END_REF], that is expressed in the Web Ontology Language (OWL). Indeed, in various industrial fields, the use of ontologies has enhanced interoperablity along the product lifecycle. The question is then to wonder if ontology-based models are able to express and validate required rules during power plant design.

As a consequence, the present paper is organized as follow: the section 2 exposes the benefits of ontology-based models in PLM applications. Then the section 3 presents SWRL functionalities, SWRL being an ontological rule language, and its industrial applications. Section 5 discusses the capabilities of SWRL as a rule language in term of rule expression, implementation and validation and proposes other rule languages as research prospects. Finally section 6 concludes this paper.

Inference ontologies to enhance Product Lifecycle Management

Definition of inference ontologies

Ontologies are, according to the widely accepted definition given by Gruber [START_REF] Gruber | Towards principles for the design of ontologies used for knowledge sharing[END_REF],"an explicit specification of a conceptualization". In mathematical words, an ontology is a set of classes, properties connecting classes to one another, restrictions on properties and axioms [START_REF] Maedche | Ontology learning for the semantic web[END_REF]. As Fankam [START_REF] Fankam | Ontodb2: support of multiple ontology models within ontology based database[END_REF] explains, there exist two kinds of ontologies: storage ontologies and inference ontologies. Storage ontologies are used for information capture, storage, classification and reuse from heterogeneous sources. Contrarily to storage ontologies, inference ontologies can reason to infering information. Inference is the ability to make deductions about instances, regarding the classes, properties and restrictions defined [START_REF] Krima | OntoSTEP: OWL-DL ontology for STEP[END_REF] and is performed by inference engines. The Web Ontology Language (OWL) is the only standard language -recommanded by the W3C since 2004 -which expresses inference ontology-based models [START_REF] Antoniou | Web Ontology Language : OWL. Handbook on ontologies[END_REF] (see figure 1). Moreover, OWL-DL is the most widespread sub-language of OWL in industrial applications. Since 2004, a large number of inference ontology-based models for PLM applications have emerged. This statement is explained by Ishak [START_REF] Ishak | Integration of Semantic Interoperability in a Distributed Architecture for Multi-Site Planning[END_REF] by the fact that "ontologies propose a simple, exhaustive, implementable and humanly understandable description of the domain".

Expected benefits of inference ontologies in PLM

Expected and noticed benefits of inference ontology-based models in PLM are of various kinds, according to the literature, but can be classified into three categories, as following.

Integration and completeness: current PLM models suffer from a lack of content. It has been estimated that around 50 % of the available information is not stored in current information systems [START_REF] Ben Kheder | An analysis of the interaction among design, industrialization and production[END_REF]. Moreover, information retrieval and reuse are not efficient in most systems too [START_REF] Louis-Sidney | A conceptual model for the implementation of IKOES (an inter-knowledge objects exchange system) in automotive industry[END_REF]. Inference ontologies provide a great expressivity that makes it possible to integrate information from different abstraction levels [START_REF] Fiorentini | STEP-OAGIS harmonization joint working group[END_REF]. They improve knowledge capture and reuse [START_REF] Chang | An ontology-based support for product conceptual design[END_REF] because they can deal with different kinds and sources of information. Illustrations of these abilities are the works of Yang [START_REF] Yang | Product configuration knowledge using ontology web language[END_REF] and Dong [START_REF] Dong | Ontology-based service product configuration system modeling and development[END_REF] in product configuration, the work of Jeong [START_REF] Jeong | Validation of an ontology-based approach for enhancing human simulation in general assembly environments[END_REF] which integrates different kinds of knowledge to improve design simulations and the work of Matsokis [START_REF] Matsokis | Ontology applications in PLM[END_REF] which provides an ontology-based product model.

Reasoning and automation: the explosion of the number of data generated by information systems and the constant reduction of time-to-market raise the need of automated and intelligent systems. Inference ontology-based models provide intelligence, in the sense of the"ability to explicit implicit informations from the model specification" [START_REF] Baader | Description Logics as ontology languages for the semantic web[END_REF]. This functionality of inference ontology-based models comes from reasoning. Vegetti [START_REF] Vegetti | PRONTO: An ontology for comprehensive and consistent representation of product information[END_REF] uses for instance reasoning to automate Bill of Materials (BOM) generation for product families. Lim [START_REF] Lim | A methodology for building a semantically annotated multy-faceted ontology for product family modeling[END_REF] automatically generates design annotations with inference ontologies to improve decision making at the design stage. According to Brandt [START_REF] Brandt | An ontology-based approach to knowledge management in design processes[END_REF] and Raza [START_REF] Raza | Knowledge-based flexible and integrated PLM system at Ford[END_REF], deductions that an inference engine provides can be better than that of humans, and transform the model into a source of intelligent data.

Flexibility, extensibility and collaboration: current PLM tools fail to adapt to the perpetual evolutions of product environment [START_REF] Yang | Product configuration knowledge using ontology web language[END_REF]. They are too rigid to deal with processes that are by nature dynamic [START_REF] Catalano | A product design ontology for enhancing shape processing in design workflows[END_REF]. PLM systems need for instance a "'timely and precise information retrieval" [START_REF] Lim | A methodology for building a semantically annotated multy-faceted ontology for product family modeling[END_REF]. Ontologies are web semantic tools. Consequently, they are well adapted to web applications and collaboration and are by nature extendable. This extensibility is a way -according to Gimenez [START_REF] Gimenez | PRONTO: An ontology for comprehensive and consistent representation of product information[END_REF] -to prevent inference ontology-based models and information they contain from premature obsolescence. It is therefore possible to continuously adapt the model to product and process evolutions.

These noticed benefits of inference ontologies are even more important in power plant design. Automation, collaboration and information storage are crucial issues in designing plants. Ontologies are consequently a potential solution that might be explored to model plant information. The ISO 15926 proposes for instance OWL as the applicative language and XML as the normative syntax of its model. However, a limiting point to using inference ontology-based models is their ability to express and validate all required rules. The next section proposes SWRL as a rule language for ontology-based models.

3 Expressing rules in ontological models

SWRL as an ontological rule language

The Semantic Web Rule Language (SWRL) is a standard language based on OWL-DL and on the Rule Markup Language (RuleML) which provides both OWL-DL expressivity and rules from RuleML [START_REF] Horrocks | SWRL: A Semantic Web Rule Language combininig OWL and RuleML[END_REF] (see again figure 1). It is the only approach that gathers ontology and rules in product development [START_REF] Fiorentini | An analysis of description logic augmented with domain rules for the development of product models[END_REF]. Rules in SWRL are implication rules. Hence, the syntax of SWRL is of the following form [START_REF] Mun | Knowledge-based part similarity measurement utilizing ontology and multi-criteria decision making technique[END_REF]:

antecedent → consequent (1)
This syntax implies that the consequent must be true when the antecedent is satisfied. OWL expressions can occur in both antecedent and consequent [START_REF] Hirankitti | A meta-reasoning approach for reasoning with SWRL ontologies[END_REF]. Different kinds of rules can be expressed in SWRL according to the literature. Next section presents only the one that are involved in case of power plant design, such as control and access policies (because of legal requisitions); configuration, association and naming rules (to enhance interoperation between actors and retrieve information); automation and strategic rules (to improve process and reduce Time-to-Market); assembly rules (related to product assembly constraints); and design rules, like design checking or product consistency checking.

Expressing rules in SWRL

Control policies have already been implemented using SWRL in healthcare field [START_REF] Beimel | Using OWL and SWRL to represent and reason with situation-based access control policies[END_REF]. In this usecase, OWL-DL part of SWRL is used to provide a model of the hospital organization, and control policies are expressed as implication rules on classes and properties from the OWL-DL part. However, in this case, the organization arround the product must be modelized as well as the product itself to perform these control checking. This enlarge again informations required in the model.

Naming and classification rules are particulary well adapted to SWRL syntax, because OWL expressions are based on classes and properties. As explained by Fiorentini [START_REF] Fiorentini | An analysis of description logic augmented with domain rules for the development of product models[END_REF], SWRL provides association rules, and allows to "associate instances to new classes and to create properties between instances". Examples of the use of SWRL in such cases can be found in Zhao [START_REF] Zhao | OWL/SWRL representation methodology for EXPRESS-driven product information model[END_REF] that provides a methodology to translate EXPRESS-driven models to OWL and SWRL, and in Dong [START_REF] Dong | Ontology-based service product configuration system modeling and development[END_REF] and Yang [START_REF] Yang | Product configuration knowledge using ontology web language[END_REF] in case of product configuration.

Process automation is determining to reduce time-to-market and to manage complex product design. As Raza [START_REF] Raza | Knowledge-based flexible and integrated PLM system at Ford[END_REF] experimented in case of ERP systems, ontologies and SWRL rules allow knowledge management by providing intelligent data that "feed automated processes to aid agile manufacturing". In another context, Rossello [START_REF] Rossellò-Busquet | OWL ontologies and SWRL rules applied to energy management[END_REF] achieves automated actions with a SWRL-based model involving energy management. Elenius [START_REF] Elenius | Reasoning about resources and hierarchical tasks using OWL and SWRL, International Semantic Web Conference[END_REF] automates military events analysis with a SWRL-based reasoning. Finally, Matsokis [START_REF] Matsokis | Ontology applications in PLM[END_REF] and Lim [START_REF] Lim | A methodology for building a semantically annotated multy-faceted ontology for product family modeling[END_REF] enhance the extendability of OWL models with SWRL rules by automating design annotations or knowledge (i.e. classes and properties) creation under a "learnable" approach.

The design of complex products, like power plants, involves a lot of components and assembly relationships. Design assembly rules can be expressed in SWRL. For instance Kim [START_REF] Kim | Ontology-based assembly design and information sharing for collaborative product development[END_REF] uses SWRL rules to express features relations in product design. In the same way, the National Institute of Standards and Technology (NIST) recently transformed the Open Assembly Model in a OWL-DL based model with SWRL rules [START_REF] Fiorentini | Towards an ontology for Open Assembly Model[END_REF]. Finally, Mun [START_REF] Mun | Knowledge-based part similarity measurement utilizing ontology and multi-criteria decision making technique[END_REF] has expressed dependancy relations in SWRL in case of injection mould design.

Design checking rules and business rules are probably the most complex rules because they depend on a lot of conditions. However, Wicaksono [START_REF] Wicaksono | Ontology-driven requirements elicitation in product configuration systems[END_REF] performs SWRL rules to detect design conflicts in product configuration. Even if SWRL is able to provide restrict rules, partof relationships and other design oriented axioms [START_REF] Fiorentini | Towards an ontology for Open Assembly Model[END_REF] [START_REF] Fiorentini | An analysis of description logic augmented with domain rules for the development of product models[END_REF], few applications of SWRL in design checking or modeling exist. Moreover, they involve mostly services or processes than the product itself.

SWRL rules execution and implementation

Current OWL editors like Protégé4 allow OWL-DL-based model expression and reasoning. But reasoning on SWRL rules demands to use an external engine. In some cases, this external engine is specificaly designed for the demanding application like in Kim [START_REF] Kim | Ontology-based assembly design and information sharing for collaborative product development[END_REF], but most of industrial models use a JESS Rule Engine 5 . JESS means Java Expert System Shell and is based on the Java language [START_REF] Dong | Ontology-based service product configuration system modeling and development[END_REF]. OWL ontology and SWRL rules are translated into Jess rules, via a JESS Bridge [START_REF] Yang | Product configuration knowledge using ontology web language[END_REF]. The JESS engine can then reason on the knowledge divided in two categories: JESS facts, derived from OWL model, and JESS rules, derived from OWL restrictions and SWRL rules (see figure 2). Once the JESS engine is run, it provides configuration results that are returned to OWL ontology [START_REF] Fiorentini | Towards an ontology for Open Assembly Model[END_REF]. SWRL-JessBridge is the JESS Rule Engine provided by Protégé [START_REF] Rossellò-Busquet | OWL ontologies and SWRL rules applied to energy management[END_REF] but it must be separatly downloaded. OWL-DL, and consequently SWRL, works usually under the Open World Assumption (OWA) [START_REF] Fiorentini | An analysis of description logic augmented with domain rules for the development of product models[END_REF], because they originally focus on the Semantic Web, that deals with an unlimited knowledge resource (internet). The OWA means that "if a proposition cannot be proved to be true with the current knowledge, the system cannot declare this proposition as false" [START_REF] Drummond | The Open World Assumption[END_REF]. Unlike OWA, Closed World systems assume that empty knowledge is false, in fact that the available knowledge in the model is exhaustive. Industrial information systems can be considered on one side as closed worlds in which information should be threated under the Closed World Assumption (CWA) [START_REF] Wang | Reasoning over OWL/SWRL ontologies under CWA and UNA for industrial applications[END_REF], since their information sources are finite. But on the other side, the interest of using ontologies is the extendability of the model, which is based on OWA. This is an important paradox that constraints model design. The same query, on the same model, could give different results regarding if the reasoning is made under a closed or an open world. Expressing control rules in SWRL, implies for instance to reason in a closed world [START_REF] Beimel | Using OWL and SWRL to represent and reason with situation-based access control policies[END_REF]. Works are going on to reason on SWRL-based models, under the CWA, like the work of Wang [START_REF] Wang | Reasoning over OWL/SWRL ontologies under CWA and UNA for industrial applications[END_REF] that proposes a new reasoner called BCAR that for. SWRL has difficulties dealing with complex rules. For instance, it is not possible in theory to create rules with numbered predicates [START_REF] Elenius | Reasoning about resources and hierarchical tasks using OWL and SWRL, International Semantic Web Conference[END_REF]. This limitation can be overtaken with SWRL built-ins [START_REF] Rossellò-Busquet | OWL ontologies and SWRL rules applied to energy management[END_REF]. Built-ins allow to define a rdf list of OWL arguments, that then feed a SWRL rule as an unique antecedent. However, this method is complex. This difficulty in expressing complex rules call into question the ability of SWRL to expressing design rules, that can depend on a lot of arguments. Because of it, preference is sometimes given to C++ language to express design checking rules of nuclear plants.

Finally, "SWRL rules cannot be used to modify existing information in an ontology" [START_REF] Rossellò-Busquet | OWL ontologies and SWRL rules applied to energy management[END_REF]. Indeed, SWRL rules originally create new knowledge, i.e. new instances or new properties between existing instances. It cannot change the value of an instance. For example, let imagine a class expressing a machine status, with instances "on" and "off" expressing if the machine is turned on or off. If the machine status changes from on to off, an SWRL rule can express that "off" is a new instance connected to "machine". Then the machine status owns both "on" and "off" instances, since the SWRL rule does not replace "on" by "off". As for complex rules, this drawback can be avoided by using Built-ins. But it demands an SWRLbuiltinbridge, and a specific OWL model describing built-ins, which is an heavy and complex solution.

Exploring other rule languages

Other rules languages showed various capacities in modeling and checking rules in information systems. As the case in point, The OMG supports the Object Constraint Language (OCL) [START_REF]OMG: Object Constraint Language (OCL), version 2.3[END_REF]. It can be used to describe additional constraints about objects in a model and makes it possible to check intrinsic model coherency and coherency between model and model instantiation. The language being particularly expressive, its use without restriction leads in practice to undecidability when the checking operations are performed automatically. Nevertheless, operating over on an appropriate fragment insure decidability with actual DL reasoners [START_REF] Queralt | OCL-Lite: Finite reasoning on UML/OCL conceptual schemas[END_REF]. Model upon which OCL constraints apply are UML models, however translation works have already begun and revealed a compatibility between UML and OWL [START_REF]OMG: Ontology Definition Metamodel (ODM)[END_REF] along with OCL and SWRL [START_REF] Milanovic | Sharing ocl constraints by using web rules[END_REF]. The possibilities of expressing rules provided by OCL, additionally its close world orientation (more in line with industrial information system context, as presented above) could lead to a joint use with SWRL.

At last, another possibility would be to express rules using the EXPRESS modeling language [START_REF]Industrial automation systems and integration -Product data representation and exchange -Part 11: Description methods: The EXPRESS language reference manual[END_REF]. The EXPRESS-G graphical part of the language looks similar to UML regarding modeling possibilities (e.g. attributes, inheritance, aggregation, polymorphism). However EXPRESS-M provides a rich set of rule modeling capabilities, based upon the concept of local and global rules. Local rules constrain the values of individual attributes or combinations of attributes for every entity instance. Global rules can be applied to check the consistency of a set of instances using queries, functions and procedures. Barbeau et al. [START_REF] Barbeau | OntoSTEP: Enriching product model data using ontologies[END_REF] as well as Zhao et al [START_REF] Zhao | OWL/SWRL representation methodology for EXPRESS-driven product information model[END_REF] studied how to convert an EXPRESS model to an OWL/SWRL representation, but none of them managed to get converted all the semantics of rule restrictions.

Conclusion

In industrial applications, and specificaly for power plant design, inference ontologies appear as a relevant way to enhance information management during product lifecycle. But expressing rules is a crucial issue at the design step. These rules are of various kinds and demand a high expressivity. SWRL is the most appropriate rule language for ontology-based models because it is based on OWL-DL. It provides in addition implication rules. Even if several and various industrial applications of this language exist, it presents limitations that are explored in this paper, notably concerning the OWA and design checking. Therefore, other rule languages should be explored, such as OCL and EXPRESS, that are compliant to UML-based models.

This work is the starting point of a global industrial project involving power plant design, which aims to improving information management. For this project, ontologies could be an efficient way of classifiying, storing and exchanging information, according to ISO 15926 recommandations. Expressing business rules is a crucial issue of this project, and could be achieved by SWRL. However, the literature reveals limitations of this language that lead the authors to investigate the use of other rule languages as a complement. The concurrent use of OWL, SWRL, OCL and EXPRESS and the interoperability of rule models has then to be further investigated, with the purpose to take benefit from each approach while ensuring the consistency of this aggregated model.

Fig. 1 .

 1 Fig. 1. Standardized OWL Languages

Fig. 2 .

 2 Fig. 2. SWRL rules execution with JESS engine

http://www.plcs.org/ap239/index.html

http://protege.stanford.edu/

http://herzberg.ca.sandia.gov/jess/


Thomas Paviot

Virginie Fortineau

Samir Lamouri

Ludovic Louis-Sidney

A modeling language for 3D process plant layout representation, exchange and visualization

Keywords: 3D Plant Layout, Computer Aided-Design, Constructive Solid Geometry, STEP, COLLADA, WebGl

In the nuclear industry, achieving Long Term Data Preservation is a requirement for nuclear power plants to be safely built, operated over five or six decades and retired. Among them, CAD data suffers from some strong dependencies on the software vendors and its data model thus leading to a possible weakness in the preservation workflow. This paper presents a modeling language, suitable for the 3D representation of a process plant layout, based upon a procedural Constructive Solide Geometry (CSG) approach. The language execution, as well as the layout rendering and exchange, are experimented using a platform independent implementation, based on free software and open standards.

Industrial context

In the nuclear industry, designing power plants requires to ensure the long term data preservation (LTDP) of the 3D Computer Aided-Design (CAD) data that are generated by the engineering teams, due to strong safety regulations and because of the long lifecycle nature of this complex system (around one hundred years from early design, to building, operation and maintenance up to the final retirement). This research focuses on some specific stage of the early power plant engineering: the layout design. According to Theodosiou et al. [START_REF] Theodosiou | Information models of layout constraints for product life-cycle management: a solid-modelling approach[END_REF], the layout of complex products and systems "describes the system's structure and components as well as related procedures and constraints". Facilities layout is concerned with the spatial arrangement of a set of departments or equipment items . This is an important stage at the design level, which often results in a complex problem due to the high number of decisions involved [START_REF] Barbosa-Póvoa | Optimal 3D layout for industrial facilities[END_REF]. This layout design takes place at the conceptual design stage [3] and is used for early design reviews related to regulation checks, first design decisions or preliminary simulations. The main asumption of this paper is that the 3D representation of the layout only needs simple boundary volumes that constraint all the subcomponents that are further part of the plant.

As underlined by Lorie [START_REF] Lorie | Long term preservation of digital information[END_REF], the challenge of LTDP is "to ensure that the information, generated today, can survive long term changes in storage media, devices and data formats". This paper focuses on the latter: how to keep control over the 3D data format representing the plant layout? In other words, the purpose is to get free from any CAD package vendor for this representation.

Open standards are known to be a priori suitable regarding this issue [START_REF] Rachuri | Information sharing and exchange in the context of product lifecycle management: Role of standards[END_REF]. For instance, The STandard for the Exchange of Product data (STEP) [START_REF] Pratt | Introduction to ISO 10303: the STEP standard for product data exchange[END_REF] provides a Boundary Representation (BRep) description of a shape topology/geometry that can be transfered from one CAD package to another. However, this transfer is not conservative from a semantical viewpoint: a lot of information is lost during the conversion, especially the design intent or parametric representation of the shape. This semantic loss occurs whatever the standardized neutral format may be (IGES for surfacic representation, STL and VRML mesh based representation etc.), i.e. these standards only allows to exchange a snapshot of the 3D model without any information about the design process that led to this topological/geometrical state. These models are "difficult or impossible to edit" [START_REF] Pratt | Towards the standardized exchange of parameterized feature-based CAD models[END_REF] which is in contradiction with Lorie's challenge. Other approaches then need to be investigated.

As a consequence, the paper is structured as follows: section 2 deals with the literature review related to macro parametric and procedural approaches in the CAD area. Section 3 proposes a modeling language suitable for the 3D layout design. The language, its execution and a visualization workflow are experimented in section 4. Finally, section 5 concludes the paper.

Macro-parametric design methodology

This section explores the macro-parametric approach as a potential solution to the issue presented above. According to Yang et al. [START_REF] Yang | An XML-based macro data representation for a parametric CAD model exchange[END_REF], a macroparametric method describes the parametric information of a CAD model as "a design command sequence", here defined as a procedural approach. Past researches dealing with this topic can be classified into two categories:

1. Product data exchange or macroparametric approach as a way to exchange models between different CAD packages: for instance, Choi et al. [START_REF] Choi | Exchange of CAD Part Models Based on the Macro-Parametric Approach[END_REF] proposed a macroparametric approach to exchange CAD models in an heterogenous environment. This approach is further extended to a feature-based macrofile format supporting the representation of the history-based parametric design [START_REF] Mun | A Set of Standard Modeling Commands for the History-Based Parametric Approach[END_REF]. These works are based upon an XML files description. Pratt et al. [START_REF] Pratt | Towards the standardized exchange of parameterized feature-based CAD models[END_REF] enriched the STEP standard semantics with parametric modeling features [START_REF]Industrial automation systems and integration -Product data representation and exchange -Part 111: Integrated application resource: Elements for the procedural modelling of solid shapes[END_REF]. 2. Synchronized collaborative design or macroparametric approach as a way to enable wide scale and real-time design collaboration: the exchange of a command sequence is here considered as an efficient way to reduce the necessary network bandwith compared with the one required to transfer netural format files. For instance, Li et al. [START_REF] Li | Real-time collaborative design with heterogeneous CAD systems based on neutral modeling commands[END_REF] introduce a set of neutral CAD modeling command for real-time and wide collaboration.

Researchers who developed MP approaches used Parametric Feature Modeling (PFM) concepts and defined a set of commands that map a small common subset from the most famous CAD packages available on the market. These works suffer from three major drawbacks:

incompleteness of the set of commands: whether it is to exchange models or to enable wide-scale real-time collaboration in an heterogeneous environment, the common features between CAD packages are restricted to basic operations (for instance Sketch, Protrusion, Revolution etc.). Indeed beyond basic functions proposed by every CAD package, many advanced functions are specific to a software: the receiver system won't be able to rebuild the model since it is missing the function, the PFM approach results in a high number set of commands that rely on a complex data model: the XML or ASCII file size that describes a model instance might be huge, the XML description is not human readable, as well as a set of EXPRESS instances serialized to an plain-text ASCII or XML file. These files cannot be edited and modified by a designer who would like to modify the geometry of the model. The modification has to be done from a CAD software.

For these reasons, current MP approaches are not judged suitable for the present research: the plant layout 3D model should be described in a simple way, be human readable and modified from outside any CAD package. The next section proposes a solution to overcome these issues.

3 Constructive Solid Geometry modeling language for 3D preliminary design

This section introduces a procedural Constructive Solide Geometry (CSG) [START_REF] Lions | Domain decomposition for CAD[END_REF] modeling language. The idea of CSG is to combine simple 3D shapes to more complex ones with boolean operations in 3-dimensional space. CSG modeling has been superseded by PFM in most of the usual current CAD packages, however CSG is interesting in the current study case because only basic shapes are needed for the plant layout representation and because CSG is based upon a small set of shapes/transformations leading to a lightweight model specification. Subsection 3.1 introduces the language semantics and subsection 3.2 deals with its syntax.

Model semantics

The semantics of the language is based upon the geometry foundation, the geometry factory and the layout factory.

The Layout Factory: this is the top-level component, composed of the base Layout class, which is a container for the geometry, sublayouts, and their absolute placements in the 3D space.

The geometry foundation: composed of ten basic classes: Point (a cartesian point (x, y, z)), Vector (from its cartesian coordinates (v x , v y , v z )), Matrix (a 4 * 4 array), and six basic shapes (Box, Cylinder, Sphere, Cone, Torus, Wedge) that inherit from an abstract Shape class (see figure 1). The geometry factory: a set of functions enabling a procedural treatment. These functions allow to instanciate classes, create geometry and perform boolean operations to generate the final geometry. The geometry factory provides three boolean operations that take two shapes as arguments and return the result shape: fuse, cut, common. Table 1 illustrates the boolean operations of two overlapping shapes A and B utilising Venn diagrams. A set of three transformations (translate, rotate, scale) allows to moving or deforming shapes. Table 2 illustrates these 3D shape transformations (they are presented on a 2D projection view on table 2).

Syntax definition

The purpose is to make the previous set of commands be computer-interpretable, the definition of an unamiguous syntax is thus mandatory. The syntax of a programming language is the set of rules that define the combinations of symbols that are considered to be correctly structured programs in that language [START_REF] Friedman | Essentials of programming languages[END_REF] (variable affectation, conditionnal expressions etc). The resulting model has to be human readable, easily understandable and usable by a design engineer and 2. Geometry factory: shape transformations must produce the smallest program size as possible, in order to ensure that the 3D layout definition is actually robust over a long time period (it must be reusable for decades). The definition of a specific syntax requires the development of a robust lexer and parser: developping a new syntax from scratch or use an existing one has to be balanced regarding this effort and the previous criterions. High level programming languages, such as Java, Scheme or Python, are potential candidates: they provide a strong abstraction over machine language and a robust and mature platform-independant implementation. This is experimented in the next section.

A B C = fuse(A, B) C = common(A, B) C = cut(A, B) C = cut(B, A)

Experiments

Experiments presented in this section deal with a basic example (4.2), measurement of the language intepreter performance (4.3) and an exchange/visualization workflow (4.4). Results are discussed in subsection 4.5.

Language syntax choice

As discussed at the end of the previous section, the decision was took to use the syntax of some existing high-level interpreted language: the Python programming language [START_REF] Lutz | Programming Python: Object-Oriented Scripting[END_REF], depicted by Dubois [START_REF] Dubois | Ten good practices in scientific programming[END_REF] as "clear and intuitive for engineers and scientists". The language interpreter was implemented using only free and open source software libraries: pythonOCC1 and OpenCascade TM Technology library 2 . Following tests were performed on a Mac OSX machine running 2 64bit cores.

Basic test for the CSG engine

The simple following model aims to represent a cooling tower, considered as the result of a set boolean operations involving a cylinder and a torus. The following program produces the output as presented on figure 2 (units are in meter). Figure 2(a) shows the basic shapes (cylinder,torus, presented in a wireframe mode) that are passed to the cut operation, the output shape is shown on figure 2(b). cyl = cylinder(13,13) tor = external_volume = cut(cyl,tor) volume_to_remove = scale(external_volume,point(0,0,0),0.9) cooling_tower_geometry = cut(external_volume,volume_to_remove) Multiple instanciation stress test: this test aims to checking the ability of the engine to create many instances of elementary shapes in a reasonable time with a reasonable memory consumption. "Reasonable" here means tha the test should be performed on a personal computer in less than a few minutes while consuming less than 1Gb of memory. This test case creates n random basic geometries (toruses, boxes, spheres) and measures the computing time as well as the memory consumption (see results in table 3). t c (n) and M c (n) appear to be both linear functions of n. 3. Multiple geometry instanciation in a 3D layout

Exchange and rendering of the 3D layout

Beyond checking the feasibility of the modeling language to deal with many complex shapes, we investigated as well the possibility to exchange and visualize the resulting layout, so that this modeling approach can be integrating into usual design and checking PLM workflows. In this test case, we consider a basic layout composed of one shop floor and a pressure vessel. The 3D model for the pressure vessel is obtained from elementary volumes (spheres, cylinders and boxes). Regarding the exchange with other CAD packages, STEP is the most famous neutral format, especially the 203 and 214 Application Protocols. Moreoever, it is natively supported by usual CAD softwares for a long time. Ding et al. [START_REF] Ding | Product representation in lightweight formats for product lifecycle management (PLM)[END_REF] report many different file formats for the exchange of tesselations. Among them, JT, 3DXML or PDF3D are the most known, but COLLADA3 was further investigated since it the interest of being a free and open standard. At last, a way of rendering this tesselation using open standards was also experimented. The recent WebGl4 standard brings 3D to the internet together with COLLADA [START_REF] Milivojević | Evaluation and visualization of 3D models using COLLADA parser and WebGL technology[END_REF]: we experimented the visualization of the 3D layout within a webbrowser supporting this new feature. This leads to a plugin free online visualization, which is much practical for distant project reviews or digital mockup investigation and inspection on computers that does not have any CAD package installed. At last, it would allow to render the layout on lightweight mobile terminals (e.g. smartphones, tablets) thus enabling in situ project reviews. The experiment result is presented on figure 4: the model, expressed using the modeling language presented in section 3, is processed by the engine, which generates a STEP file, a COLLADA 1.4 file (imported into Google SketchUp to demonstrate the file consitency) as well as a WebGl JavaScript Object Network (JSON) object served to a web client (Firefox 11).

Results and discussions

The stress tests demonstrated that it is possible to easily create a 3D bounding volume and generate the geometry: topology consistency, computing time and memory consumption allow running this kind of language on a personal computer. The visualization workflow described in the last subsection shows it is possible to store a tesselation using the COLLADA data model: the mesh size however still has to be reduced in order to provide a ligthweight tesselation to the renderer. The WebGl based renderer allows to checking the current WebGl implementations of modern webbrowsers in this context: they appear to be increadibly stable, mature and efficient, according to the other tests that were ran. This global workflow although has to be experimented for huge layouts involving dozens of thousands of components. To conclude this discussion, the model and the software prototype presented above provide a way to: describe a 3D volume with a simple and human readable model, execute this model thanks to a language based upon a high-level programming language syntax, generates a platform independant visualization solution (WebGl/web browser) as well as a neutral representation (STEP) ready for the exchange with third part CAD tools and, at last, a COLLADA file ready for tesselation exchange. Although a CAD kernel is still required for supporting this workflow, the dependency over one specific CAD solution is removed: the control over all 3D layout assets is ensured.

Conclusion -Further works

This paper introduced a modeling language suitable for 3D process plant layout representation. This language uses a procedural Constructive Solid Geometry approach. Experimentations demonstrated that it can be executed in order to generate simple geometries intended to represent the boundary volume of complex components. Morover, the paper also contributes a workflow to enable exchange of the resulting geometry as a STEP file, visualization storage using the COLLADA standard as well as a webbrowser based visualization enabling online rendering. Further research purposes are to reduce the tesselation size, add parametric features in order to provide more flexibility and develop a business object ontology on top of this model.

Fig. 1 .

 1 Fig. 1. Geometry factory: basic shapes instanciation

Fig. 2 .

 2 Fig. 2. Model for a cooling tower

Fig. 3 .

 3 Fig. 3. CSG engine stress test for boolean operations

n 10 10 2 10 3 10 4 10 5

 5 computing time tc in ms 2, 2 15 140 1, 47 15, 8 memory consumption MC in M b 0, 47 0, 7 7 87, 7 903 Table

Fig. 4 .

 4 Fig. 4. Pressure vessel model ready for a PLM workflow

Table 1 .

 1 Geometry factory: boolean operations

	Original shape	translate	rotate	scale
	Table

http://www.pythonocc.org

http://www.opencascade.org

http://collada.org

http://www.khronos.org/webgl/


Virginie Fortineau

Thomas Paviot

Samir Lamouri

ip 2011Doctoral Spring

Keywords: semantic interoperability, ontology, PLM, standards

In the production enterprises, interoperability between information systems used is the key for a successfull Product Lifecycle Management approach. Despite many research works, the preservation of the information ow along the product life is still problematical because of the scientic and technological locks existing. These locks are identied in this paper and a new federative approach of interoperability is proposed, based upon the use of ontologies and semantic web tools.

Introduction

During the last decades, the production enterprises have changed their products and processes. The rise of product diversity, the collaborative and concurrent engineering, the externalization of the production are indeed usual in todays production. They aim at reducing the time-to-market and increasing the competitivity; but raise the complexity of the product environment. Mastering the current complexity in production is a crucial key for maintening the constant progress required.

The Product Lifecycle Management (PLM) is an approach to master the inherent complexity of product development among the whole product life (from the design to the recycling step), by "integrating and making available all of the information produced through all phases of a product's life cycle to everyone in an organization" [START_REF] Sudarsan | A product modeling framework for product lifecycle management[END_REF]. A PLM approach requires inter alia to ensure interoperability between the dierent participants in product development and their specic information systems. However, it is well known in the litterature that the existing lack of interoperability is actually an important brake on achieving a successfull PLM strategy [START_REF] Noël | The PPO design model with respect to digital enterprise technologies among product life cycle[END_REF].

In this paper, the rst section describes the interoperability and the product modeling issues at the design and manufacturing steps. Then section 3 raises the research problematic induced and exposes the proposed approach. Finally the section 4 concludes this work.

2 Problem statement

Design/Manufacturing information systems

In production enterprises, "the main need today is the communication of updated data from engineering to production management" [START_REF] Ben Kheder | An analysis of the interaction among design, industrialization and production[END_REF]. The present work consequently focuses on the design/manufacturing interface.

The design information systems can be classied into three categories [START_REF] Pahl | Engineering design : a systematic approach[END_REF]: the authoring systems (that generate technical design data, like CAD systems), the product data management systems (PDM) and the design management systems (that enable collaborative work). The manufacturing systems can also be classied into three categories [START_REF] Paviot | A Methodology for solving interoperability problems in the eld of Product Lifecycle Management[END_REF]: the Enterprise Resource Planning (ERP), the Manufacturing Execution Systems (MES) and the Advanced Planning Systems (APS). These diverse systems describe the product in dierent specic ways, depending on their own needs. But they all have to collaborate and quickly et eciently share information: interoperability is required.

Interoperability related denitions

Wegner [START_REF] Wegner | Interoperability[END_REF] denes interoperability as "the ability of two systems (or more) to communicate, cooperate, exchange services and data, thus despite the dierences in languages, implementations, executive environments and abstraction models". Therefore, ensuring interoperability proceeds in three levels: the technical, semantical and the organizational levels [START_REF] Eif | European interoperability framework -White paper[END_REF]. The present work especially focuses on the semantical level, that deals with preserving the semantic ow of information from any loss during the product lifecycle and ensuring good understanding of these information from each participant; while keeping the perspective of proposing the adapted technical solution.

There are three manners of achieving semantical interoperability [START_REF]Systèmes d'automatisation industrielle -concepts et règles pour modèles d'entreprise[END_REF] [9]: integration (all participants share a standard format), unication (a meta-level structure establishes semantic equivalence between the participants) and federation ("models must be dynamically accomodated rather than having a predetermined meta-model").

Most of the current works deals with unication approaches [START_REF] Tursi | Ontological approach for product-centrics information system interoperability in networked manufacturing enterprises[END_REF] [11] [START_REF] Paviot | A generic multiCAD/multiPDM interoperability framework[END_REF], since it is more agile and exible than the integration approach, and because the current federative approaches based on ontologies alignment are not convincing for the moment [START_REF] Homann | Similarité sémantique inter-ontologies basée sur le contexte[END_REF]. Indeed, most of the time, the ontology alignment (that is global) is made from a set of correspondances between entities (that are local) from the dierent ontologies [START_REF] Zimmermann | Formalizing ontology alignment and its operations with category theory[END_REF]. This paradox generates lacks in nowadays federative approaches of interoperability.

Information modeling

The interoperability between information systems optimizes the information exchange and is therefore crucial in a PLM approach. But an interoperable system is useless if the transported data are ineciently extracted and stored. Less than 50% of Manufacturing Bill of Material (MBOM) are for instance stored into PDM, ERP or MES systems [START_REF] Ben Kheder | An analysis of the interaction among design, industrialization and production[END_REF].

The production data are extracted and formalized via the specic product models at each step of the product lifecycle. The choice of the product model constricts the quantity and the quality of the extracted information. It also determines the formatting of the data. The product models used in actual unication approaches can be ad hoc, but are most of the time based on standards data models, using standard languages (for instance the STandard for the Exchange of Productdata (STEP)) and standard visualisation (for instance the Unied Modeling Language (UML)) [START_REF] Oh | Mapping product structures between cad and pdm systems using uml[END_REF]. These standards help to perform mapping between the information systems, but these mapping are built manually, providing a static description of the product, which is not compliant with actual enterprise needs for agility and exibility. Contrariwise, semantic models "can enable entities to achieve reliable and ecient collaboration [by] inferring new knowledge, querying, retrieving and storing" [START_REF] Fiorentini | An analysis of description logic augmented with domain specic rules for the development of product models[END_REF]. They enable a federative approach of interoperability, bringing intelligence to the product information.

3 Research question

Problematic

The problem statement is resumed on the gure 1. The state of the art reveals a rising need of interoperability and information exchange due to the growing complexity and competition that production enterprises are facing. Information are available in the dierent product models and need to dynamically and intelligently circulate between the dierent systems. The litterature also shows that the main current need of interoperability relies at the design/manufacturing interface. The research question arised is therefore how providing federative interoperability between design and manufacturing systems. This means using ontologies and implies to dynamically model the semantic interactions between design and manufacturing.

Ontologies for the PLM

The semantic models are based on the use of ontologies, than can be expressed into two standard languages: the Ontology Web Language (OWL) and the RDF graphs [START_REF] Vacher | Toward the use of ontologies for scientic knowledge modeling and integration in production community[END_REF]. According to the usual denition, ontologies are a "formal, explicit specication of a shared conceptualization" [START_REF] Gruber | Towards principles for the design of ontologies used for knowledge sharing[END_REF]. As part of the semantic web technologies, ontologies are consequently a relevant tool for working on a federative approach of interoperability [START_REF] Zhang | Exploring semantic web technologies for ontology-based modeling in collaborative engineering design[END_REF]. Recently, several works proposed product modeling based on ontologies, like the Open Assembly Model (OAM) [START_REF] Fiorentini | Towards an ontology for Open Assembly Model[END_REF], but also service modeling [START_REF] Dong | Ontology-based service product conguration system modeling and development[END_REF] and process modeling [START_REF] Brandt | An ontologybased approach to knowledge management in design processes[END_REF].

The OWL-DL language is a logic-based representation formalism creating an object oriented model. But as [START_REF] Fiorentini | An analysis of description logic augmented with domain specic rules for the development of product models[END_REF] revealed, OWL is not sucient to contain the expressivity requirements for product modeling: domain specic rules, expressed in Semantic Web Rule Language (SWRL), must be added to the OWL-DL model.

EBOM/MBOM views

EBOM and MBOM representations are specic views of the design and manufacturing workows, containing all the product information, but mostly implicitly. Even if they share a commun graphical representation (a tree-like structure), they describe very dierent features. The EBOM describes the virtual product whereas the MBOM carries the manufacturing process used by the Material Requirement Planning [START_REF] Orlicky | Net change material requirements planning[END_REF]. Expressing the meaning of the parent/child relationship in these BOMs, as well as the one of the items, are the key for explicitely modeling the design and manufacturing information.

Proposed approach for achieving a federative interoperability in the area of PLM

The scientic approach is described on gure 2. The idea is to propose a conceptualization via a simple and minimal product model, based on ontologies and rules. This model must be able to describe the design and manufacturing entities and the links between them. It is built according to the queries and reasoning demanded by the interactions between design and manufacturing. The prerequisite of this work is therefore to understand the specic viewpoints and needs of both design and manufacturing work, and how they interact together. After extracting data from design and manufacturing specic models, this global model is then able to reason and infer data that are afterwards resited into the local views. Thus, the dynamic mapping between design and manufacturing are indirectly but completely achieved. The extracting data step will be based on the use of standards (see gure 2) that already exists at each level. For instance, OntoSTEP We intend to pursue then the reection by including to this product modeling the process too. In a global approach of interoperability, the establishment of this product/process link is indeed the main way to include knowledge to the information [START_REF] Tsuchiya | Improving knowledge creation ability trough organizational learning[END_REF].

Conclusion

The present paper expresses through the state of the art the current need of interoperability between information systems in the Product Lifecycle Management. It also shows that the federative approach, based on the use of ontologies, and coupled with the denition of semantic models seems to be an eective way to answer the actual problems in production enterprises interoperability. Our research will rst focus on the design/manufacturing interface, and aim at dening a global ontological product model. Thus, semantic correspondances between EBOM and MBOM would be indirectly but completely established. This semantical modeling will be completed with the proposition of a robust technical architecture and will be validated on a use case.

Figure 1 :

 1 Figure 1: The need of federative interoperability in production enterprises

Figure 2 :

 2 Figure 2: Proposed approach