General Information Model and Its Application for Rock Excavation in Underground Work Sites

Esa Viljamaaa, Irina Peltomaab & Annemari Kaarankac

a VTT Technical Research Centre of Finland, P.O. Box 1100 90571 Oulu Finlandb VTT Technical Research Centre of Finland, P.O. Box 3, 92101 Raahe Finland

c University of Oulu, Department of Mechanical Engineering, Erkki Koiso-Kanttilankatu 3, FI-90570 Oulu Finland

E-mail: esa.viljamaa@vtt.fi, irina.peltomaa@vtt.fi, annemari.kaaranka@oulu.fi

AbstractIn the underground mining and tunnelling rock

excavation processes, there is plethora of differentmachine, tool and information system providersinvolved and practically no general informationmodel covering the complete process. Thecompetition in the field is getting more intense andall the actors should intensify their operations. Theinformation management and integration ofdifferent information systems’ data is among themost interesting enablers for such a betteroperational efficiency. The main goal of the researchwas to develop flexible methods for betterapplication interoperability and informationmanagement for the underground rock excavationprocesses. The research used a literature survey, acommercial systems survey, professional interviewsand worksite observations in order to develop a newgeneral information model for rock excavation anddefine a toolchain for the exploitation of thedeveloped model. In this research, the informationmodel for underground rock excavation actions wasdeveloped applying applicable parts of existingstandards and software tools. The main informationmodel can be extended by using separately designedsub-models. In addition to information model also atoolchain of how to practically do the modeldevelopment and information integration, has beendescribed. These actions will enhance informationmanagement and application interoperability in therock excavation processes and enable more efficientinformation exploitation leading potentially to bettercontrolled processes, more efficient work phases andcost savings.

Keywords -Information Model, Information Management,

Data Integration, IFC, IREDES, Rock Excavation

1 IntroductionLike in many other industries, the underground

mining and tunnelling operations are facing more globaland more severe competition than earlier. This meansthat all the operations must be intensified and mademore cost-effective to meet new challenges. Also thecommon demand for less polluting and safer processesis pressing system and process developers and managersglobally.

In order to intensify processes, more accurate andmore extensive information about the processes isneeded. The days when a company could thrive withstand-alone systems for different enterprise functionsare over. Enterprise systems focused on differentfunctions in a company may never become one, but theymust share information to assure success. [1] In theunderground mining and tunnelling operations, theremay be tens or hundreds of different sources ofinformation that are potentially useful from the processcontrol and management point of view. Thisinformation should be brought to the disposal of theprocess management either as an individual data sourcesor rather as integrated information. Better methods forconverting the raw data into integrated and usefulinformation for both a product and a process controlthrough the complete value chain are essential fordevelopment of mines [2]. There are few commercialsolutions in the market to integrate information in thetunnelling operations, but those solutions remain to bevendor specific, closed and covering only some narrowsub-fields of needed total view for information.Information management solution must ensure that theright people and the right processes have the rightinformation and the right resources at the right time [1].

In this research, the general information flow andinformation system integration were improved by meansof the developed application interoperability concept

The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)

consisting of a new information model and a definedtoolchain for information integration concerning themodel. The model was based on industry standard fromthe building construction field that was combined withde-facto rock excavation communication method alongwith other necessary parts. The model is mainlytargeting the improved process management anddecision making support among other benefits. Thispaper discusses mainly how the model was developedand its applicability will be tested later on in a real-lifein real environment with a developed pilot system. Theresults of the research are potentially applicable withinadvanced mining and tunnelling worksites with properprocess data collection systems and production controlsoftware. A practical functionality of results of theresearch will be validated in subsequent comparativeresearch phase.

2 MethodsThe information model and the toolchain developed

in the research were based on information collectedfrom a literature survey, worksite visits and personnelinterviews involved to work in tunnelling andunderground mining operations.

2.1 State-of-the-ArtFor the underground mining and tunnelling

operations there are several commercial solutions,however these solutions are concentrated on certainfunctions or are tightly vendor specific. Interoperableand overall information management solution for wholechain of underground mining and tunnelling operationsdoesn’t exist.

Commercial solutions for underground mineplanning include Dassault Systèmes GEOVIA’s Surpac[3], CAE’s CAE Studio 5D Planner [4], and MintecInc.’s MineSight [5]. Commercial solutions for tunnelconstruction site planning include Trimble’s BusinessCenter HCE [6], Tekla’s Tekla Civil [7], and VianovaSystems’s Novapoint [8]. Integration and accessing toplanning information is usually possible throughcommon file formats.

In academia, the application interoperabilityresearch in underground mining and tunnelling fields isnot executed widely. However the need for improvedinformation integration and management in mines isnoted in the research [2][9]. Compared to undergroundmining operations the interoperability research is moreadvanced in the field of AEC/FM (architecture,engineering, construction and facilities management).[10] have reviewed wireless web services enablingtechnologies, [11] have made an extensive review from

data and application integration research in constructiondomain, and [12] have conducted a comprehensivereview on system integration technologies in AEC/FM.In the following, few information management studiesfrom AEC/FM field are introduced.

[13] present domain taxonomy for highwayconstruction. The taxonomy is based on IndustryFoundation Classes (IFC) and several otherclassification systems. It uses seven major domains toclassify construction concepts: Process, Product, Project,Actor, Resource, Technical Topics, and Systems. Thetaxonomy was used to develop an ontology for theconstruction domain including semantic relationshipsand axioms. The major ontological model is process-oriented and can be summarized as follows:Construction knowledge is encapsulated in severaloverlapping Systems, where a set of Actors use a set ofResources to produce a set of Products following certainProcesses that are part of a Project according toboundary conditions and within the confines of the workenvironment (Technical Topics). [13] The operation ofthe developed domain ontology was evaluated during ae-COGNOS project [14] as a part of a web basedknowledge management software, which connectedvarious systems using a Web Service technology. Thedevelopment of the ontology architecture was continuedby adding more knowledge levels (applicationknowledge, user knowledge) to domain ontology [15].

[16] present more general level domain ontologycalled Infrastructure and Construction PROcessOntology (IC-PRO-Onto) for infrastructure andconstruction domain. IC-PRO-Onto captures the mostfundamental concepts in the domain in a structured,extendable, and flexible format. It uses five concepts torepresent things: Entity, Constraint, Attribute, Modality,and Family. An Entity is a Project, Action, Actor,Product, Resource, or Mechanisms. Concepts werestructured into hierarchal taxonomies using sub-sumption and aggregation relationships. Thetaxonomical classification of concepts supports multi-perspective viewing of the same process throughProcess Modality Views including Core Processes,Management Processes, Knowledge IntegrationProcesses, and Support Processes. [16]

[17] present AEC-domain specific ontology mergerOnto-Integrator. Existing ontology mergers could notfully address requirements set by AEC domain, which ismultidisciplinary and has several stakeholders. Onto-Integrator uses semantic similarity comparison andrelational concept analysis (RCA) for merging ontologytaxonomies and relations, and knowledge baseintegration for axiom merging. The merging approachuses a heuristic. [17]

[18] have developed an IFC based ontology, whichpurpose is information retrieval from an IFC model. The

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ontology source is IFC2x3 version and the ontologyformat is Web Ontology Language (OWL) 2 DL. Theontology consists of two parts Basic and ExtendedOntology. The Basic Ontology includes those ontologycomponents that are derived from the IFC specificationdirectly. Extended Ontology is the ontology componentsthat are not originally included in the IFC specificationsbut are added according to the requirement of thesystem. These components facilitate the informationretrieval when the inputted query includes terminologiesthat are not readily available in the IFC specifications.[18]

[19] introduce semantic web services basedapproach to enable interoperability between Computer-Aided Design (CAD) and Geographical InformationSystem (GIS). The approach consists of three modules:Task Interpretation, Web Service Matching, and WebService Composition. The implementation of thesemodules requires development in for examplealgorithms and Quality of Service parameters. [19]

[20] propose a method for intensifying roadconstruction process management. Method utilizesresent advances in communication and machine controlsystems, and the development of informationmanagement technologies. The prototypeimplementation called Dynamic Site Control Center(DSCC) enhances the information acquisition duringroad construction process. DSCC integrates informationfrom different companies’ information systemsparticipating to road construction process. In ontology-based integration process DSCC combines and refinesthe information gained and visualizes it for users. DSCContology forms from sub-ontologies, corresponding sub-processes of infrastructure building process. DSCCimproves the process management’s situation awarenessand provides platform independent access andvisualization tool for process data. [21][22][20]

In the following two central data exchange formatsare introduced more closely as they are centralbackground formats in our information modeldevelopment.

2.1.1 IFC

Industry Foundation Classes (IFC) is a schemadeveloped to define an extensible set of consistent datarepresentations of building information for exchangebetween AEC software applications. It is a neutralexchange format, which was designed as an extensible“framework model”. That is, its developers intended itto provide broad, general definitions of objects and datafrom which more detailed and task-specific modelssupporting particular exchanges could be defined. Itcovers all building information supporting full lifecyclefrom planning and design to maintenance. [23] However,

[24] state that the formal standards on BuildingInformation Modelling (BIM), such as the IFCs arecomplex and have not had the resources for rapiddevelopment and promotion that their potential deserved.In addition IFC has been weakened by varied non-consistent implementations [23]. Therefore it may takesome time for this approach to be widely adopted [25].

Nevertheless IFC has become an internationalstandard for data exchange and integration within thebuilding construction industries. While IFC is able torepresent a wide range of building design, engineering,and production information, the range of possibleinformation to be exchanged in the AEC industry ishuge. The IFC coverage increases with every releaseand addresses limitations, in response to user anddeveloper needs. The latest version IFC 4 has about 800entities (data objects), 358 property sets, and 121 datatypes. While these numbers indicate the complexity ofIFC, they also reflect the semantic richness of buildinginformation, addressing multiple different systems,reflecting the needs of different applications, rangingfrom energy analysis and cost estimation to materialtracking and scheduling. [23]

From system architecture perspective the IFCconsists of four conceptual layers: Resource, Core,Interoperability, and Domain Layers. [26] The bottomlayers define base reusable constructs which are genericfor all types of products. The base entities are thencomposed to define commonly used objects in AEC,termed Shared Objects in interoperability layer. At thetop level are the domain-specific extensions, which dealwith different specific entities needed for a particularuse. [23] .

All IFC models provide a common general buildingspatial structure for the layout and accessing of buildingelements. It organizes all object information into thehierarchy of Project-Site-Building-Building-Storey-Space. Each higher-level spatial structure is anaggregation of lower-level ones, plus any elements thatspan the lower-level classes. All application-definedobjects, when translated to an IFC model, are composedof the relevant object type and associated geometry,relations, and properties. In addition to objects thatmake up a building, IFC also includes process objectsfor representing the activities used to construct abuilding, analysis geometry that is often abstracted fromthe building geometry, and analysis input and resultproperties. [23]

Model views are another level of specification,above the IFC schema. Model View Definitions (MVDs)identify what should be expected for an exchange to beeffective. MVDs specify exactly what informationshould be exchanged, and in what form and structure theIFC entities are to be used. Defining MVDs requiresprinciple decisions and workarounds because the IFC

The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)

itself does not address a number of semantic issuescomprehensively. Two sets of semantics are at the coreof any successful model exchange. One of which is theuser or application functional semantics defining theinformation that must be exchanged and the other beingthe representational semantics available in IFC or otherdata modelling schema representing the user intentions.[27]

2.1.2 IREDES

The need for effective exchange of processinformation was driven force for standardizationinitiative called International Rock Excavation DataExchange Standard (IREDES) [28]. The objective ofIREDES is to define a “common electronic language”for easy and standardized data exchange betweenmining machines and corporate IT systems. [29]IREDES is based on eXtensible Markup Language(XML) technology and uses XML schema to define theformats of the machine generated files. Thus, theproduced data report is understandable for both humansand machines. [30] XML structure supports objectoriented software design and data encapsulation.Furthermore all major databases provide standard XMLimport and export features. [29]

IREDES architecture consists of three differentlevels: IREDES Base, Application Profile, andEquipment Profile. The IREDES Base level covers alldata which objects in other levels require. TheApplication Profile level contains all informationspecific for one application purpose (e.g. Planning Data,or Production Quality Log). This is information whichmay be used independently from a specific type ofequipment. The Equipment Profile level adds detailed,equipment specific information to each ApplicationProfile applicable for the specific equipment type. Thefirst available Equipment Profiles cover the Drill Rigsand LHD’s/Trucks as transport. [29][30] presents the idea of IREDES On-line whichpurpose is to setup an industry standard to enablevolatile data to be transferred via network reliably suchthat the machine current status is visible to authenticatedusers. Volatile data includes real time data and currentstatus information as these types of data vary rapidlyover time. IREDES On-line suggests two alternativeways for communication: direct or infrastructurecommunication. In direct or peer-to-peercommunication end user connects to machine using IPaddress, and machine acts as a server responding toclient requests. In infrastructure communication thecommunication between machine and end user is donevia server. This is more efficient method as machine’scalculation resources are limited and software ispurpose specific. In infrastructure communication there

is possibility to send more complex requests to server,for example ask for history information of the machine.[30]

2.2 Personnel Surveys and ObservationsPart of the information needed for the developed

information model and its application were gatheredfrom personnel surveys from two different Finnishworksites. Other worksite was a tunnel construction sitefrom a Helsinki subway expansion project and otherwas from an underground hard rock mining site.Although a final product of those separate work sites aredifferent (ore and a subway tunnel), the productionprocesses in the rock excavation phases are quite similar.Due to the worksite similarity, the replies to inquirywere processed as they were all from a single site. Partof the information was collected by interviewingpersonnel from different levels of responsibility fromproduction planning staff and work supervisors to themachine operators as well as maintenance andmeasurements personnel. Rest of the individual datawas collected by paper inquiries.

Questions in the interviews and the inquiries wereabout the current good and bad practises, bottlenecksand improvement suggestions related to informationflow in general and also special ones related toassignment of the specific staff member in the question.Most of the interviews were done while a currentinterviewee was actually doing his duty making it alsopossible to do actual worksite observation and notesbased on communication between different actors in theprocess.

The technology level of those two work sitesinvolved varied between modern production controlsystems and all-covering production Wi-Fi to the paperbased reporting method and analogue walkie-talkiecommunication system. There were 23 personsinterviewed and 76 replies to inquiry.

Table 1 depicts a job type share of employees thatanswered the inquiry.

Table 1. Share of different job types in the inquiry.Job Type Number %

Management 1 1Production planning and systemengineers

12 16

Measurements staff 2 3Work supervision 8 11Maintenance and equipping staff 20 26Machine operators etc. 28 373rd party contract supervision 1 1Safety personnel 4 5Sum 76 100

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3 ResultsThe resulting model and the data integration

toolchain were based on the literature survey of theacademia and the commercial systems as well asprofessional interviews and inquiries.

3.1 Information ModelBased on the literature survey and the professional

interviews and inquiries, there were multiplerequirements gathered related to developed informationmodel. The requirements included topics from modelgeneral requirements to single data fragments fromprocess to be included to the model structure.

First, there were multiple requirement suggestionsreceived from interviewees related to detailedinformation fragments of different sub-topics inunderground tunnelling process. Depending the positionof an interviewee there were many differentperspectives brought up. Different work planning andprocess follow-up terms like project, task andassignment with related performance parameters likecost, time, a sequence and such were consideredimportant for the model. Also sub-process and machinespecific topics like drilling, blasting and haulingmachine use, process and maintenance relatedparameters were supposed to be included to the model.

The system designers and State-of-the-Art researchpointed out quite obvious requirements for the model;the model should be modular and extensible in order toguarantee its updateability. Also it was supposed to besemantic in nature for application design that candistribute intelligence of the system also to the modelside.

The core of the developed information modelconsists of selected components from IFC4 andIREDES definitions. Since the main goal of the researchwas to develop tools for an improved information flowto the tunnelling operations, only applicable parts wereselected. From the IFC4 definition, Core schemas withResource schemas were applied with ConstructionManagement Domain schema. These schemas were thenextended using the tunnelling process specificinformation gathered from the IREDES definition,professional interviews and the SoA research. Theextension was named as TunnelBuildingDomain. SinceIREDES is mainly an information exchange format thatmay be getting more common in the future, the activitydefinition in the developed information model ismapped to IREDES working sequence for latercompatibility. The developed model does not cover thephysical tunnel model, but physical models can beadded to the main model using mechanisms provided byIFC relationship connectors. The model structure and

the basis are depicted in Figure 1.

Figure 1. The basis and the structure of thedeveloped model.

Figure 2. Snippet from the model class hierarchy.

SoA

Interviews

IREDES

IFCKernel

IFCControl

Extension

IFCProduct

Extension

IFCProcess

Extension

IFCConstructionManagement

Domain

IFC Shared Management Elements

TunnelBuildingDomain

The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)

The information model and its components werecomposed to a class hierarchy following the example ofthe original IFC4 model. An example snippet from themodel can be seen in Error! Reference source notfound., where TunnelBuildingDomain sub-classes areinherited from the ifcResource class. The model wasmodelled following the principles of Unified ModellingLanguage (UML) Domain Model extension. This modeltype is so called Domain Model that can be later ongrounded to a physical model e.g. Structured QueryLanguage (SQL) database scripts etc.

3.2 The Model ApplicationA prerequisite for the application interoperability is

usage of a common information model. In addition,there are also multiple other actions that may be done toenable successful multi-actor data share. This chapterexplains briefly how the model can be developed anddeployed in practise.

First, the main information model must be modelledusing some appropriate enterprise architect softwaretool. It may be done using UML Domain Model toolthat also supports different relationships betweenentities. The domain model may then be derived to aphysical model that includes database tables and theirrelations.

Secondly, an essential data may be then brought todatabase tables. E.g. any ETL (Extract, Translate, Load)tool may be used in order to upload and convert datafrom data sources to the database and to the model. The

important data is then easily accessed from the databaseover enterprise service bus (ESB) solution or othercommunication solution. Figure 3 shows an explanatorydevelopment and application of the presentedinformation model.

4 DiscussionIn this research, the application interoperability of

underground rock excavation processes intensificationwas enabled by developing a common informationmodel and by defining a practical way to exploit theresulted information model.

The research developed an information model andits application description that were based on literaturesurvey, professional inquiry and interviews andworksite observation periods.

The developed model was based in IFC4 andIREDES standard definitions. Currently there is noholistic standard information model available forunderground rock excavation processes, but IFC4 havebeen used as a basis in few other information modelresearches [13]. However, in this research, thedeveloped model was realized without utilization ofsemantic web standard languages like ResourceDescription Framework (RDF) or OWL. In addition tothe model development, also the short description howthe model could be applied was presented.

Figure 3. Model development and application practises.

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There are several benefits while using the developedmodel; it is derived from standards or de-factotechnologies meaning that a part of it has been reviewedin long run by experts from the different fields. IFC isstill developing and maybe in some day there will alsobe an extension of a tunnelling physical model on it.

The developed model has been realized using UMLwhich enables that the domain model can be read in andupdated in multiple software. Also it is easy to derive aphysical model automatically out of the domain model,in order to quicken the deployment. Due to the nature ofIFC4, the model should be very easily extended andadded to upper models.

Of course, there are also disadvantages in thedeveloped model. Information models are alwaysdifficult to get standardized. The developed model is notmodelled using “pure” semantic technologies meaningthat some of the advantages of semantic web cannot beused. E.g. the model cannot be automatically aligned ormapped to other models using those highly advancedsemantic linking technologies. Also it should be notedthat the inquiry was only concerning two Finnishcompanies. There may be different requirements formodels used in other work cultures with differenttechnology readiness levels and practises.

There are many potential steps for further researchwork in the field of the application interoperability ofunderground rock excavation. First, the model and itsapplicability in practise should be tested in comparativetests in real-life environment including modelrealization and actual use as a basis for the applicationinteroperability. In addition to the applicability, also itspotential financial benefits should be researched. Alsothe information integration features of the model shouldbe increased by modelling the wholeness with realsemantic methods in order to enable automated mappingor aligning of other models to it. Also, the possibility toadd real IFC-like tunnel physical model to main modelshould be developed.

5 AcknowledgementsThis research was conducted in a research project

called “Flexible Optimization of Underground MineProduction” that was mainly funded by Finnish FundingAgency for Innovation, TEKES. Also the contributionof co-funding companies is highly appreciated.

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