Model-Based Management of Asset Information

David Kampert∗, Ulrich EppleChair of Process Control Engineering, RWTH Aachen University

{kampert, epple}@plt.rwth-aachen.de

Martin Mertens†

Ineos Koln GmbHmartin.mertens@ineos.com

1 Introduction

Software tools for engineering tasks typically aim at well-defined aspects of an overall project, for which they em-ploy domain-specific models. Managing information onassets is an important cross-sectional task, which makesthe exchange of information valuable to many domains.In order to enable software tools to exchange information,the underlying meta-model needs to be open and common.This primarily accounts for the contents of the meta-model(what is modeled), which is a different issue than the ques-tion how the model is technically represented. Hence, inthis article the combination of an appropriate meta-modelfor asset information along with its integration into a ser-vice-oriented architecture is discussed from a conceptualperspective. It is not intentended to provide details of apossible implementation.

2 Meta-Models in Information Exchange

Model-driven approaches for the engineering of automa-tion systems allow handling individual tasks in a genericway. This is accomplished by common meta-models,which define the syntax and semantics of individual mod-els generically and to a reasonable extent. In case of P&I-Diagrams, for example, the meta-model contains graphicalsymbols for the representation of various devices in indi-vidual plant models, which may provide information onrepresented devices up to a certain level of detail. Soft-ware tools usually have an implicit knowledge on the meta-model, but interoperation of different software tools hasthe prerequisite of using an open meta-model, i.e. commonknowledge on structure and semantics of the exchangedinformation. Common technical means to represent theinformation is also mandatory, but may be answered by re-spective model transformations. Standardized meta-modelson the logical level are thus the basis for interoperation ofengineering tools, independent from the technical repre-sentation (e.g. files, databases, ontologies,...).

Finding an appropriate meta-model for information ex-change means finding the coarsest-grained building-blocksthat are common for all model instances. Here, the term“coarse-grained” not only applies to the size of informa-

∗The author gratefully acknowledges support by the German ResearchFoundation (DFG).

†The author contributed to this work during his affiliation with theChair of Process Control Engineering, RWTH Aachen University.

tion chunks, but also to structural degrees of freedom. Theappropriate level is a case-by-case tradeoff and can onlybe found if the objects that are modeled are analyzed care-fully.

3 Meta-Models for Asset Information Man-

agement

In industrial automation, models under consideration areoften models of technical resources, which are intendedto reflect the resources’ properties. Though there are cer-tainly other important kinds of models (e.g. functional orstructural models), descriptions based on properties areamong the most frequently met paradigm for providinginformation on assets. It is therefore an important goalto structure them in a common meta-model. For limitedapplication purposes this was accomplished by definingmeta-models for the description of technical devices, ofwhich IEC 61360 [3], IEC 62264 [2] and NE 100 [5] areprominent examples. These aim at standardized specifica-tions of devices as needed in e-commerce, i.e. informa-tion on device classes. They are neither intended to bedescriptions of assets in general, nor do they address themanagement of individual assets in conjunction with de-vice classes. Consequently, these solutions are applied inelectronic catalogs, but not on a larger scale for informa-tion exchange on industrial assets. There is nonethelessreasonable hope that a meta-model for managing informa-tion on industrial assets can be defined, since all of theabove-mentioned standards are sharing the same idea ofdescribing assets by means of properties. The commonmeta-model needs to be unbiased in terms of the kind ofmodeled assets and business perspectives, but should in-corporate the information that it is meant for describingreal-world assets. However, the key requirement for suc-cessful integration of information from different sources isnot to use identical data structures, but to have a commonidea of the information contents. With this goal in mind,a reasonable approach to find the common ground of allmodels is to consider them as representations of things (ofcertain kinds) that have properties and property values. Acorresponding meta-model was introduced in [4]. In theproposed modeling concept assets are seen to be prop-erty carriers with respective properties. These propertiesare classified and mutually independent characteristics thatcan be associated with values by means of statements, e.g.

statements whether the value was measured, is requiredor is asserted [6]. The definition of individual propertiesis beyond the scope of the meta-model; existing propertydefinitions may be used for this purpose. An implementa-tion of the model is currently under development.

Interoperation of software tools benefits from the pro-posed meta-model because multiple domains can contri-bute and request information to and from one asset model.Furthermore, information may be provided on single de-vices or entire device classes. Different domains may main-tain their point of view to assets and are yet able to inte-grate their information because the meta-model only incor-porates the common ideas. E.g., statements regarding thecurrent operational parameters of a pump can be made onthe part of plant operation, while the pump’s vendor canprovide assertions on these properties for all pumps of thatkind. The information can be exploited to detect inconsis-tencies automatically by comparing statement values, in-dependent from knowledge about the properties’ seman-tics. In general, any application that needs to access infor-mation on asset properties is enabled to do so on the levelof granularity that is required for exactly this purpose.

4 Incorporating the Meta-Model in IT Sys-

tems

By establishing a generic meta-model for industrial assets,many important aspects of the information environment inan industrial facility can be modeled in a unified way. Thisis a mandatory prerequisite for information exchange be-tween software tools, but needs a technical representationof the model in order to make data accessible. However,it must be noted that the crucial design decisions in thedevelopment of a corresponding system are taken by themeta-model’s definition.

In the past years, service-oriented architectures (SOAs)have gained increasing attention and are seen to be a fu-ture paradigm of industrial IT infrastructures (see e.g. [1]).SOAs may be composed by “black-box” systems that onlyhave a known interface, which makes common meta-mo-dels inevitable: The internal data strucutres may differ fromsystem to system, but a common idea of the exchanged in-formation needs to exist. In case of asset management, avaluable advantage of SOAs is the possibility to central-ize information access, which supports the meta-model’sstrengths from the technical side. Contrary to file-baseddata exchange, information may be spread over multiplelocations (i.e. multiple domains may contribute informa-tion), while allowing to access information using a cen-tralized interface, which provides a single virtual model.This can be realized by a central service for accessing assetproperty information, which in background retrieves infor-mation from various registered sources, forming a feder-ated database. Servers that contribute information to theoverall system need to implement a standardized serviceinterface, which allows for accessing the internal data asdefined by the common meta-model.

In practice, the proposed architecture brings three ma-jor advantages towards file-based information exchange,

which still is widely spread. The first one obviously isthat inconsistencies due to differing file versions cannotoccur. Secondly, information regarding one asset can beautomatically analyzed for inconsistencies in terms of con-tradictory statements on identical properties. Consistencychecks that involve property semantics may be implemen-ted under domain-specific knowledge of specialized engi-neering tools. The third mayor advantage is the possibil-ity to employ generic algorithms to enrich the informationcontents. E.g., devices that are able to fulfill a modeledrole may be automatically found or contradictory state-ments may be detected in order to resolve conflicts in anearly planning phase.

5 Conclusion

Basically, it can be concluded that an appropriate meta-model for asset information along with information ex-change over service interfaces constitutes a promising de-sign pattern for interoperation of engineering tools. It de-mands a common basic model, which is realizable in caseof managing asset information since involved software toolsare dealing with the same information environment. Theway in which individual tools handle the contained infor-mation is not affected and leaves the necessary flexibility.In order to realize the proposed architecture, the remain-ing task is twofold: On the one hand, model elements needto be standardized in order to obtain common semantics.Existing standards may be employed for this purpose. Thesecond part of the task is the definition of the necessaryservice interface, especially in terms of supported func-tionality and operation granularity. This is subject to on-going research work and will be implemented in a softwareprototype.

References

[1] Thomas Bangemann, Christian Diedrich, Armando WalterColombo, and Stamatis Karnouskos. SOCRADES – ServiceOriented Architecture in der Automatisierungstechnik. InAutomation 2008, Baden-Baden, pages 65–68, 2008.

[2] International Electrotechnical Commission. IEC 62264:Enterprise-control system integration – Part 1: Models andterminology, March 2003.

[3] International Electrotechnical Commission. IEC 61360:Standard data element types with associated classificationscheme for electric items – Part 2: EXPRESS dictionaryschema, February 2004.

[4] Ulrich Epple. Merkmale als Grundlage der Interoperabilitattechnischer Systeme. at – Automatisierungstechnik, 59:440–450, 2011.

[5] NAMUR: User Association for Automation in Process In-dustries. NE 100, Version 3.2: Use of Lists of Properties inProcess Control Engineering Workflows, June 2010.

[6] Martin Mertens and Ulrich Epple. Plant Asset ManagementFunctions driven by Property Models. In ETFA 2009: 14thIEEE International Conference on Emerging Technologiesand Factory Automation, 2009.