An automated solution for importing critical assets information into BIM 3D Model

NgHMandFadeyiMO(2021).Anautomatedsolutionforimportingcriticalassetsinformation intoBIM3DModel.BuiltEnvironmentAppliedResearchSharing#05.ISSUUDigital Publishing. ©BEARSreservestherighttothisappliedresearcharticle

An automated solution for importing critical assets information into BIM 3D Model

Ng

Hui Min and Moshood Olawale Fadeyi,*

Sustainable Infrastructure Engineering (Building Services) Programme, Singapore Institute of Technology, 10, Dover Drive, Singapore 138683, Singapore

*Corresponding author’s email: fadeyi.moshood@singaporetech.edu.sg

ABSTRACT

Facility managers or facility management firms usually painstakingly and manually import building critical assets information from assets information requirements (AIR) to a building 3D model. Unfortunately, such practice requires a lot of resources, manpower, time, energy, material, etc., to deliver the required usefulness – Quantity of quality that serves the function needed without compromising safety. Thus, value delivery is compromised for all stakeholders involved. There are many times that there are many errors in the imported critical assets information, further compromising value delivery for all stakeholders involved. This project aims to identify the root cause of the deficiency in value delivery and use digital solutions to optimise the process of value delivery. Specifically, the project aims to develop an automated solution that can reduce the time and potentially manpower and energy required to import a building's critical assets information from an automated AIR generator, previously developed by the authors, to a building 3D model with no error. The proposed automated solution was developed using Python Scripting in Dynamo for Revit and experimentally tested for the required efficiency and effectiveness. The developed automated solution provided a 99% time reduction over the manual method currently adopted in the digital facility management industry with zero error in importing critical assets information. The findings also show no limitation to the number of building critical assets and their information that one person can do. The resources saved due to the developed automated solution can be deployed to other projects to deliver more value instead of focusing on one project for several months or more. The developed automated solution can aid the achievement of high value-oriented productivity in the facility management industry.

Keywords: Asset Information Requirements (AIR), Digital Facility Management, Productivity, Dynamo, Building Information Modelling

1. INTRODUCTION

Buildinginformationmodelling(BIM)iscrucialtofacilitatingstakeholders’collaborationand activities, including planning, designing, construction, and management, at different building delivery stages, starting with an authored 3D model (Singh and Wang, 2011; Poirier et al. 2017). The 3D virtual building model is known as the building information model, which contains all the accurate building information and parameters across the entire building lifecycle. The benefit inherent in such an intelligent 3D model facilitates the need to have a digital twin of an existing building. Digital twinaids non-intrusive and productive preventive and corrective maintenance of an existing building for optimum performance and value delivery (Stojanovic et al., 2018; Halmetoja, 2019). Of particular importance is the critical assets information in the 3D model used for the delivery of digital twin. Critical assets are assets that are important for overall building operations. A digital twin is a replication of an actual building and its information in digital form (Tao et al. 2018a, b). However, the informationusedfordevelopingadigitaltwinneedstobecomplete,accurate,relevant,andup to datetobe useful.

The authors had a personal experience of a company in Singapore that provides digital solutions for facility management to enhance the reliability of using digital twin to improve productivity. The company's activities include the development of an integrated facility management digital platform that manages overall building spaces, assets, and operations. However, this company always faces a major issue in managing information from as-built modelsastheas-builtinformationisofteninaccurate.Withoutanyadvancedtechnologiesand knowledgeableprogrammers,verification,consolidation,andupdatingofbuildinginformation modelsduringtheprocesshadalwaysbeenaproblem.Manualconsolidationofcriticalassets’ informationisthecurrentmethodbeingadoptedbythiscompanytodevelopassetinformation requirements (AIR), verify, consolidate, and update assets information in a BIM 3D model. Accordingtothecompany’sStandardofProcedure,thecriticalassetsinformationgivenbythe client to the company is consolidated into AIR format, which is used for updating the informationinthe3Dmodel.

Intheauthors'previous applied researcheffortand reportedinNgand Fadeyi (2020), an AIR generator was created to facilitate automated consolidation of all asset information from the

PDFformattedequipmentlistandoperationmaintenancemanualintoasingleExceltemplate. In the developed AIR Generator, all asset’s information will be consolidated into a standard AIR template in just a simple click, making the overall process efficient and effective. The automated AIR generation solution had solved the manual method of consolidating critical assets’ information. However, the importation of critical assets’ information from AIR to a BIM3Dmodelisstillbeingdonemanually.ThefragmentedsoftwarefunctionsofBIMRevit would cause moretime to inputthe informationfor every criticalasset intoa BIM3D model.

With the manual method of updating critical assets information into a BIM 3D model, errors are prone to occur. The inaccurate building information could disrupt the overall building operations.

As a consultancy firm, the product's efficiency and reliability are crucial to gain the client’s trust,especiallyinthefacilitymanagementindustry,inwhichtheproductwillaffecttheoverall building operations. However, the process of importing assets informationintoa 3D modelis time-consuming as the information is often inaccurate. In addition to inaccurate information, if the 3Dmodelcontainsmanyunnecessarydetailsandinformation,thefile will require more timetoload,causingadelayinupdatingtheinformation.Asolutionwasdevelopedtoeliminate unnecessarydetailsandinformationina3Dmodelsubmittedbycontractortofacilitymanager and owners for facility management (Chua and Fadeyi 2020 and 2021). The current project reported in this paper aims to develop a solution that improves the productivity of importing critical assets information into a BIM 3D model. The objectives of the study are: (i) development of an automated solution that could help fulfill the project's aim, and (ii) To examinetheefficiency(time-saving)andeffectivenessofthedevelopedautomatedsolutionin importingassetsinformationintoaRevitmodel.

2. CURRENT STATE

2.1CommandsforimportingAssetsinformationintoBIM3Dmodel

The current method of importing critical assets information into a BIM 3D model is to insert theinformationindividually,asshowninFigure1.Thismethodistime-consumingandtedious, andtherearearoundsixteentypesofinformationtobeinsertedintotheBIM3Dmodel.Within a typical building, the total number of critical assets will be minimally 300, which causes the manual process of inserting to be tedious and time-consuming. Long term exposure to

computerscreenscouldalsocauseahealthproblem(Akkayaetal.,2018).Afterfacingthe computerforlong-durationandresultingstress,humanstendtomakeanerrorinwhichthe buildinginformationwillbeinaccurate.

Figure1:Currentmethodofimportingcriticalassetsinformationintoa3Dmodel

Theproposedsolutionistodesigncommandsusingprogrammingsoftware,whichwillbe integratedwithBIMRevit.Thissetofcommandswillautomatetheentireprocessofgetting theinformationfromAIR,identifythespecificasset,andinsertthespecificassetinformation intoaBIMmodel.AcommandintheBIM3Dmodelwillneedtoallowuserstouploadthe AIRfile,fromwhichtheinformationwillbeimported.Thissolutionshouldbedonewitha singleclick,andallinformationimportedfromAIRwillneedtobeaccurate.Asshownin Figure2,theentireworkprocessofimportingtheinformationwillbeautomated,whichwill preventhumanerrorfromoccurring.Hence,theaccuracyoftheinformationwillneedtobe 100%error-free.BIMRevitsupportsvariousprogrammingsoftwaresuchasDynamo,Python, andMicrosoftVisualStudio(C#).DynamoandPythonwillbeusedtodevelopthissolutionas thissoftwareiseasiertouseandunderstandascomparedtoC#programming.

Figure2:Proposedsolutionworkprocess

2.2DynamoProgramming

Dynamo is part of the visual programming tool that uses a programming language to extend Revit's usefulness in the Architecture Engineering and Construction (AEC) industry. In the conventional programming process, users will need to input the source code to create programmes. Unlike other programming tools, Dynamo has manipulative graphic elements known as “nodes,” in which elements will embed source codes. However, the work process around Autodesk Revit is all being done using the manual method, which is too timeconsuming. In the conventional practice, Autodesk Revit had been heavily used to: construct building models from 2-Dimensional to 3-Dimensional, the input of project elements information,andcheckingfortheexistenceof clashesbetweenbuildingsystems.

Dynamo for Revit uses a visual scripting tool to automate repetitive tasks, manage data, or generate complex geometry. The scripting of Dynamo is easier to understand as compared to theusualprogrammingtools.AsaproductofAutodesk,Dynamousestheconnectionbetween nodes to create scripts that improve work processes. Instead of creating a set of source code fromscratch,userswillbeabletousetheavailablenodesinthestandardDynamoplatformor lookformorecustomnodesonline.Dynamoplatformprovidestheflexibilityofallowingusers tocustomise theirnodesusingPythonprogramming.

2.3PythonProgramming

Python is a powerful high-level programming language with dynamic source coding data structures and ability making it an attractive option in rapid application development. As comparedtootherinterpretedprogrammingsoftwaresuchasJavaScriptandC++,Pythondoes notrequireuserswithstrongsourcecodereadabilityasthecodingrequiredisoftenshorterthan otherprogrammingsoftware.Duetotheextensivelibraryandhigh-builtdatastructures,Python abletoidentifyEnglishkeywords thatallowusersto easilyunderstandthecode interpretation by shortening the code, which other programming software unable to achieve. Even though Python might not be lacking in speed, they are versatile and broadly adopted in every major operatingsystem.

AsPythonlibrariesinclude ApplicationProgrammingInterface(API)services, Pythoncanbe easilyintegratedintomostoftheoperatingsystemstoimprove overallworkefficiency.Being oneofthetopprogramminglanguages,Pythonismostlyusedtoautomatetheworkprocesses,

which involves repetitive and time-consuming tasks. Python can be applied to all industries which require coding as it supports cross-platform operating systems. Python's main applications include web development, game development, machine learning and artificial intelligence,datavisualisation,andComputer-AidedDesigning(CAD).

3.0DEVELOPMENTOFSOLUTION

3.1Preparationofcriticalassetsinformationandbuildingmodel

Critical assets information needs to be developed before developing an automated programming solutionfor integrating theassetsinformation intothedeveloped3Dmodel. An automated AIR generator solution for populating critical asset information from PDF document, developed by Ng and Fadeyi (2020), is shown in Figure 3. A 3D view of the 8storey building used for this study showing some of its floors is shown in Figure 4. A typical MEPfloorplanofthe8-StoreybuildingisshowninFigure 5.

The 8-storey building have a total of 448 critical assets. There are two extra critical assets information in the generated AIR, CTMUPMP-RF-04, and DB-06-03, which the developed solution in this project will need to identify. Thus, the developed building model used in this studycontainsapproximately450criticalassetsrangingfromACMV,plumbingandSanitary, electrical,andfireprotectionsystems.TheassetsinformationfromthegeneratedAIRtemplate will be imported into the BIM model MEP file, which contains all the critical assets of the developedbuilding.

3.2AssetInformationRequirement(AIR)Generator

Assetinformationrequirement(AIR)wasgeneratedwiththeautomatedAIRgeneratorsolution developedbyNgandFadeyi(2020)withminorchangesinthe templateforthiscurrentstudy. The initial AIR was neatly organised, with all the system information being separated clearly with blank spaces. However, one ofthelimitations of Dynamo was the inabilityto readExcel information when empty spaces found between the lines. Hence, the AIR developed for automatingtheprocessofimportingcriticalassetsinformationintheAIRtemplateintoaBIM 3Dmodelshouldnothave blankspacesinbetweentheinformation.

Figure3:AssetInformationRequirement(AIR)Generator

Figure4:A3Dviewofthe8-Storeybuildingusedforthisstudyshowingsomeofitsfloors

Figure5:TypicalMEPfloorplanofthe8-Storeybuilding

3.3ProgrammingofPrototype

ThescriptinginDynamoisinnodesthatmadeiteasierforuserstousethanotherprogramming tools. In this study,Pythoncodingwasusedtocreatethenodeswhichperforms the command – see Figure 6. Users will not be required to create their source code for the script, as all the nodes are available in the Dynamo library, as shown in Figure 7. Dynamo is used to develop theautomatedsolutiontoimportassetsinformationfromAIRExcelintoRevitModelwiththe followingpackages:Data-Shapes,Clockwork,BimorphNodesandarchilab.

Thefollowingarethebasicworkingprinciplesofthedevelopedsolution:

Step 1: UploadingofAIRExcelfileandextracttheinformationintheExcelfile.

Step 2: Revitelementsareselectedbyidentifyingthroughthe“Mark”parameter.

Step 3: Create sharedprojectparametersaccordingtotheAIRExcelheader.  Check if the parameters had been created in Revit model to avoid duplication

Step 4: InformationinAIRExcelwillbeimportedintoRevitElements  They are matching of Revit elements “Mark” parameter with AIR Excel“Equipmentlabel.”  IdentifywhichcolumnofAIRExcelbelongstotheRevitparameters.

Step 5: Create ProjectSchedulesaccordingtoAIRExcel.

Step 6: ImportAIRExceltoverifyinformationwiththeRevitmodel.  Identify differences in the information and users are able to export resultsintoExcelformat.

Scripts in Steps 1 and 6 are action-based, which meansuserswill be prompted toperforman actionbeforeproceedingtothenextstep.UsersarerequiredtoactivatetheDynamoPlayerin the Revit application to run the Dynamo scripts. The developed solution will fulfill the followingthreemainfunctions:(1)UserstouploadAIRExcelandcopyinformationfromAIR into the Revit BIM 3D model, (2) Create project schedules, and (3) Compare Revit BIM 3D modelelementsinformationwithAIRExceltoidentifythedifferences.

3.4Function1–ImportingofAIRExcelandcopyinformationintotheRevitmodel

The scripting for the first function consists of four steps of the basic working principles, as mentionedpreviously. The Dynamo scriptof thisfunctionis designed to allow the solutionto readandidentifytheinformationfromanExcelfile,whichactivatesthecopyingfunctioninto the Revit elements. There is a mixture of action-based and backend scripting to prevent the developedsolutionfrombeinghardcodedinthisfunction.Theoverviewofthe Dynamoscript forthisfunctionisshowninFigure8.Adetailedbreakdownofthescriptswillbeexplainedin thefollowingsections.

3.4.1

Step 1 – Uploading of AIR Excel file and extract the information in the Excel file.

Thescriptinginthefirststepisseparatedintotwoways.Onefocusesonaction-based;another willbethebackend,asshown inFigure9.Thefirstportionwillneedtopromptuserstoselect thedesiredfilepathtoidentifytheAIRExcelfile.TheDynamoscriptofthisportionisshown in Figure 10, which will first appear as the pop-up message to prompt users to select the file path, as shown in Figure 11. The “MultipleInputForm++” node is from an external library package, Data-Shapes, which containsa setof nodes thathave the capability of providing the interactive action-based script. This node helps make the scriptmoreflexible in terms of how userscanselecttheirfilepath.

In the second portion of the scripting in Figure 12, the “Read Excel” node will extract the information from AIR Excel. The information will be separated into two different lists. One containstheinformationoftheAIRExcelheaders,andanotherlistcontainingthecriticalassets information.TheListcontainingcriticalassetsinformationwillneedtobemappedtotheRevit elements to detect the same critical asset code and mapped the information to the elements. Thereisatotalof7376informationtobeimportedintotheRevitmodel.

3.4.2

Step 2 – Selecting of Revit elements by identifying through “Mark” parameter

Inthisstep,thescriptingneedstoallowthedevelopedsolutiontoidentifyRevitelementsfrom mechanicalequipment,electricalequipment,andelectricalfixturesthrough“Markparameters,” asshowninFigure13.ThescriptusesnodesinthestandardDynamolibrary,whichallowsthe system to identify the desired categories and extract the “Mark” information of the Revit elementsshowninFigure14.

Figure6:Pythoncodingtocreatenode

Figure7:DynamoLibraryPackages

Figure1:Function1DynamoScriptOverview

Figure5:ScriptforextractinginformationfromAIRExcel

Step2:SelectingofRevitelements

START

1.Identifywhich categoriesofassets tobeselected

2.Set"Mark"as theparameterto identifytheassets

SelectallRevit Elementsunder Mechanical Equipment,Electrical Equipment,Electrical Fixtures

Figure6:Step2WorkProcess

Figure7:ScriptforselectingofRevitelementsandidentifyingthrough“Mark”parameter

3.4.3 Step 3 – Create shared project parameters according to AIR Excel header

The information highlighted in yellow in Table 1 is the project parameters that need to be created in the Revit model. When the node detected that the parameters do not exist in the system, the solution will proceed to create shared parameters using the "Parameter.CreateSharedParameter” node – see Figure 15. The solution will need to identify the parameter group and parameter type first before completing the creation of the shared parameterprocess.

Users are required to ensure that the working Revit model does not have any existing shared parameters created. The script for this step will need to achieve the ability to check the existence of the parameters in the initial Revit model and only create the project parameters when there is no similar parameter found. See Figure 16 for steps in the work process. The “CheckifParameterexists”nodeisfromanexternallibrarypackage.

3.4.4 Step 4 – Importing of AIR Excel information into Revit Model

Theworkprocessforstep4(seeFigure17)involvestwomainobjectives:(1)IdentifytheAIR ExcelinformationbelongingtothecriticalassetsintheRevitmodel,and(2)CopyAIRExcel informationtothespecificcriticalassetsinRevitModel.Thedesignofthescriptistoachieve the objectives are separated into four portions. Firstly, the script is designed to identify what arethecriticalassetsintheRevitmodelmatcheswithAIRExcelbymappingthe“Mark”with “EquipmentLabel”(seeFigure18).

The nodes in Figure 19 and Figure 20 will identify which information belongs to individual Revitelements.ThescriptinFigure21willrequirethe“Element.SetParameterbyName”node tohaveinformationinputintoindividualelementsaccordingtothesharedparameterscreated earlierontoachievethecopyingfunction.The“Passthrough”nodeisanindicationtoholdthe entire step 4d process on hold until all shared parameters had been created. In Figure 22, all the informationhadbeenimportedfrom the AIR Excelfile to the respective parametersfield under“IdentityData”foralltheRevitelements.

Figure18:MapAIREquipment LabelwithMarkParameter

Figure19:FilterAIRinformationaccordingtotheRevitelements

Figure20:MapAIRinformationwithRevitelements

Figure21:CopyingofinformationfromExceltoRevitmodel

Figure22:InformationimportedfromAIRExceltotheRevitmodel

3.5Function2–CreateProjectSchedulesaccordingtoAIRExcel

Thescriptforthesecondfunctionwillcoverstep5ofthebasicworkingprinciples,as mentionedpreviously.Thescriptofthisfunctionisdesignedtocreateaprojectscheduleand addschedulablefieldsaccordingtothesharedparameterscreated.

3.5.1Step5–CreateProjectSchedulesaccordingtoAIRExcel

Theworkprocessforstep5involvesidentifyingwhichRevitelementstocreateaproject scheduleaccordingtotheAIRExcelfile.InFigure23,the“ScheduleView.CreateSchedule” nodewillallowthedevelopedautomatedsolutiontocreateprojectschedulesformechanical equipment,electricalequipment,andelectricalfixtures.Thescriptwillproceedtofilterthe schedulablefieldsaccordingtothesharedparameterscreatedpreviously.The “ScheduleView.AddFields”nodewillretrievethedatafromtheschedulablefieldsandaddit totheprojectschedule,asshowninFigure24.

3.6Function3–IdentifydifferencesbetweentheinformationinExcelandRevitelements

The third function script will cover step 6 (see Figure 25) of the basic working principles, as mentionedpreviously. Thisfunction'sscriptisdesignedtoallowuserstoimportAIRExcelto compare the information with Revit elements and identify the differences in the information. Inthisfunction,thereisamixtureofaction-basedandbackendnodestopreventthedeveloped solutionfrombeinghardcoded.TheoverviewoftheDynamoscriptforthisfunctionwasshown in Figure26.Adetailedbreakdownofthescriptwillbeexplainedinthefollowingsection.

3.6.1 Step 6 – Users to import AIR Excel to verify information with the Revit model

The main objectives of this step require the developed automated solution to allow users to importAIRExcelandcomparetheinformationtoidentifythedifferences,asshowninFigure 25. After identifying the differences, the results will beexported to an Excel file accordingto where users wanted to export. The design of the script is separated into four main steps. In ordertomakea comparison betweeninformation,thedevelopedautomatedsolutionwillneed to retrieve the information from the project schedule, shown in Figure 24, by using the “Schedule.GetData”node,asshowninFigure 27.

The script will need to act by prompting users to import the desire Excel file to make comparisonsbyusingthe“MultipleInputForm++” and“ReadExcel”nodes(Figure 28).After retrieving the information from both sources, the script will activate comparing information andidentifyingthedifferencesbyusing“List.SetDifference”node(Figure29).Finally,apopup message will appear to prompt users to select which Excel file to export the results using the “Data.ExportExcel” (Figure 30). The missing critical assets in the Revit model are identified in Figure 31 as the preparation of the AIR had intentionally added two more assets informationtotestthefunctionalityof thisscript.

Figure28:ImportationofAIRExcelFile

Figure29:Compareofinformationandidentifydifferences

Figure30:ExportresultstoExcel

Figure31:MissingAssetsfoundonRevit

4.0METHODOLOGYFORTESTINGSOLUTIONEFFECTIVENESS

Anautomatedprocesscouldsignificantlyreducethetimeneededtoimportassetsinformation from the previously developed automated AIR Excel file into a BIM 3D model. The users would only need to upload their standardised AIR Excel file. The developed automated solutionissoftware-based.TheprogrammingexplainedinSection3willallowthedeveloped automated solution to retrieve information from the AIR Excel file and assign it to specific assets by automatically detecting the asset code. Even though the process is shortened, the accuracy of the information should not be compromised, and it should be 100% accurate. Accuracyisuncompromisable.

Theresultsfromtheexperimentwould serve asevidence ontheefficiencyandeffectiveness of the developed automated solution to perform the required function stated above. The experiment examines the total time taken to complete the importation and accuracy of importingcriticalassetsinformationfromanautomatedAIRExcelfileintoaBIM3Dmodel for manual and automated processes. 10 participants were involved in the experiment as showninFigure32.TherequiredfacilitiesforthisexperimentarelaptopwithAutodeskRevit 2019, Dynamo 2.0.3 and Zoom application, screen recording application, AIR Excel file, architecturalandMEPmodel,twotimerdevices,andexperimentalguide.

4.1ExperimentPreparation

Itisimportanttoensurethedevelopedautomatedsolutionisingoodworkingconditionbefore testing it. Hence, preliminary testing was done on the developed automated solution before theactualexperimentaltestingtoensurethatcriticalassetsinformationintheAIR Excelfile can be imported into the Revit model and any surfaced technical issues can be minimised. Preliminary testing of the prototype helped to ensure the efficiency and effectiveness of the experiment.

Figure32:Experimentalsetupforparticipantsinvolvedinthestudy

Duetotimeconstraints,thisexperiment'ssamplesizewasten.Thereisaneedtocaterbuffer timefortheloadingofthemodelastheRevitfile'sfilesizemightbetoobigforthecomputer system to run at full speed. The 5 of the 10 participants regarded as having experience in importing AIR informationintoBIM3Dmodelswereeithercurrentlyworkingor workedin thecompanyprovidingDFM services(see Figure32). Theother5participantswerewithout anyexperienceinimportingAIRinformationintoBIM3Dmodels.

All the participants were involved in the two sets of experiments. The first set involves the manual import of information from AIR Excel to the Revit model. The second set uses the automatedprocessforimportinginformationintotheBIM3DModelsolution.Atotalof450 critical assets were used for this study. A briefing was conducted before the experiment for eachparticipant,whichtookupapproximately10minutes.

Eachparticipantwasbriefedontheexperimentinstructionsandobjectivesbeforeconducting the experiment. Short training, as required for the experiment, on importing of information from AIR Excel file to Revit Model was also provided for all the participants. The training includes creating project shared parameters, project schedules, and using of automated processforimportinginformationintoBIM3DModelsolutionaregiventoeachparticipant.

4.2Actualexperimentfortheimportationofinformation

The experiment'sduration consistsoffifteenminutes ofexperimentbriefing, anhourforthe experimentusingmanualdataentryintotheRevitmodel,andfifteenminutesforexperiment using automated process for importing information into BIM 3D Model solution. The experiment was conducted at the agreed time by each of the participants through a video conferencewiththeZoomapplicationduetoCOVID-19restrictions.

Duringthe experiment, there were two sets of time beingrecorded by the two differenttime devices. Time taken for the whole experiment duration, which includes the time needed for openingtheRevitmodelandcreatingprojectparametersandscheduleswererecordedbyone of the devices. Another timer device recorded the actual time spent by a participant in importinginformation.Theactualtimetakenexcludesthetimeneededforbreaksorquestions ontheimportingofinformation.

4.3ActualExperimentforcheckingofinformation

TheimportanceofaccuracyintheRevitmodeliscriticalinmanagingfacilitiesmanagement. Hence, the developed solution was tested several times to ensure all information from AIR ExcelhadbeenimportedintotheRevitmodelaccuratelyandavoidtechnicalissuesthatmight be missed out during the development of the prototype. Thus, the second portion of the experiment aimed to verify that the developed solution aid in the error-free automatic importationofassetinformationintotheBIM3DModel.

Figure 35showsthe process of how the Revit model information willbecheckedduringthe experiment. All Revit models submitted by each participant were checked three times for possibleerrors.Theprocessofcheckingtheinformationisdescribedasfollows.Afull100% checkonallRevitmodelsweredonetoidentifyvisibleerrors.Whentherewasnoerrorfound, the second round of checks on the models was done to avoid human error during the first roundofthecheck.

Duringthesecondroundofchecking,50%oftheRevitelementsfromeachservicetypewere randomlychecked. When there were noerrors spotted duringthe second round of checking, thefinalroundofcheckingwasdoneontheRevitmodel.Inthefinalroundofchecking,25% ofthe Revitelementsfromeachservicetype were selectedrandomlyforchecking. Whenan error is found inany checking, the types and quantity of errors were documented. Checking ofinformationshouldnotproceedtothenextstage,withoutcorrectingtheidentifiederror(s).

If there were errors found in the information imported using the developed solution, the software would be deemed as failed, and rectification of the solution will need to be done based on the documented observations during the experiment. After the rectification, the process will need to restart from checking all information, as shown in Figure 33, to ensure the developedsolution able to retrieve and assign information to the corresponding Revit elementaccurately.However.Thissituationdidnotoccurinthisstudy.

5.0RESULTSANDDISCUSSION

The demonstration of the developed automated solution can be found in the link in the supplementary information section. The demonstration videos are provided for better

appreciation,visualization,andunderstandingofthedevelopedautomatedsolution.

5.1 Impactofmanualandautomatedmethodsontimetakentoimportinformation

Theactualtimetaken byparticipantsto completethe importation ofcriticalassetinformation intoaRevitmodelbyusingbothmanualandautomatedmethodsisshowninTable2.Thereis anaverage timesavingsof 3mins7secsforonecompletedasset whenthe automatedmethod wasadoptedinsteadofthemanualmethod.

This means there is a 99% reduction in the time needed to import the information from AIR excel into the Revit model with the use of the developed automated solution. 100% of the participants could not complete their tasks within the allowable 60 minutes (1 hour) for the manual method. On average, participants were only able to complete importation of 5.5% of the total critical assets within an hour given for the manual method of importing the information.Participantswereabletocompletetheirtasksinnomorethan6minsbyusingthe developedautomatedsolution.

Although thebenefitprovided,intermsoftimesavings,bythedevelopedautomatedsolution, issignificant,thetimetakenwasunexpectedasthetimerequiredtousethedevelopedsolution toimporttheinformationfromAIRExcelintoRevitwasinitiallyplannedtobewithin4mins. The difference between the expected and obtained results for the developed solution may be due to the computer's operating system used in the experiment. The experiment should have beenconductedface-to-facetoensurethatallparticipantswillusethesameapparatustoavoid inconsistency in the results obtained. However, due to COVID-19 stay home restriction, the experimentcouldonlybedonethroughavideoconferenceinwhichparticipantswererequired to use their personal computer. Ascomputerswith different operating systems were used, the requiredtimeneededtoruntheRevitandDynamofilewillbedifferent.

Thecurrentworkprocessofimportingtheinformationistime-consuming,whichoftencauses theneedformoremanpoweracquisitiontomeettheprojectdeadline.Withtheadoptionofthe developed automated solution in the industry, the time takento import informationfrom AIR excel to the Revit model and the number of manpower required to complete the task will be significantlyreduced.

(a)

(b)

Figure33:Theprocessforensuringaccuracyofimportingcriticalassetsinformationintoa3Dmodelusingtheautomatedmethod(a)andmanualmethod(b).

Table2:ThetimetakentocompletetheimportationofcriticalassetinformationintoaRevitmodelbyusingboththemanualandautomatedmethods

ImportingofinformationusingMANUALmethod

Revit loading time (mins)

Time neededfor creatingof parameter (mins)

Experiment duration (mins)

Actual timetaken fordata entry (mins)

Noof assets completed

Time takenfor each asset (mins)

ImportingofinformationusingAUTOMATEDmethod

Revit loading time (mins)

Experiment duration (mins)

Actual timetaken fordata entry (mins)

Noof assets completed

Time takenfor each asset (mins)

Participant1 5 10 60 45 20 2.25 4.50 9.00 4.5 448 0.01

Participant2 3 7 60 50 31 1.61 2.50 8.50 6 448 0.01

Participant3 2.5 8 60 49.5 62 0.80 1.50 3.00 1.5 448 0.01

Participant4 1.5 9 60 49.5 52 0.95 1.50 7.00 5.5 448 0.01

Participant5 6 6.5 60 47.5 34 1.40 2.00 7.00 5 448 0.01

Participant6 2 15 60 43 10 4.30 1.50 3.00 1.5 448 0.01

Participant7 6.5 12.5 60 41 9 4.56 7.00 10.50 3.5 448 0.01

Participant8 4 17 60 39 10 3.90 3.00 5.00 2 448 0.01

Participant9 4.5 14 60 41.5 6 6.92 4.00 9.00 5 448 0.01

Participant10 1 9 60 50 12 4.17 2.00 6.00 4 448 0.01

Minimumtimetaken(mins) 0.80

Minimumtimetaken(mins) 0.01

Maximumtimetaken(mins) 6.92 Maximumtimetaken(mins) 0.01

Averagetimetaken(mins) 3.08 Averagetimetaken(mins) 0.01

5.2Impactofexperienceontimetakentoimportinformation

Table 3 shows the comparison of the time taken between experienced and non-experienced participants. On average, participants with experience in importing information from AIR to Revitmodelthroughmanualmethodtooklessthan2minspercriticalasset,asshowninTable 3.Whileparticipantswithnoexperience,onaverage,tookabout5minspercriticalasset.There is a difference of 3 mins in the time taken between the experienced and non–experienced participants.

However, through the adoption of the developed solution, there isnotimedifferencebetween the experiencedandnon-experiencedparticipants. Allparticipantstook, onaverage,1 sec per criticalasset.Thisisimportantbecausenewstaffwithnoexperienceoftheoperationcaneasily getthejobdoneinaveryshortperiod.Additionally, thecostimplicationfromtrainingstaffto doingthejobcanalsobeavoided.

One of the main issues faced in the digital facility management industry is the shortage of qualified and skilled. The importation of information from AIR Excel to the Revit model for an entire building often requires three to four people for the data entry only. The verification of the information would require another three to four people. From the results gathered, importing information through the manual method would require more manpower to reduce the time needed to complete the importation, especially if non-experienced employees are involved.

The findings suggest that regardless of experience, each participant was able to complete the importation of information for the entire building within 10 minutes by using the developed automatedsolution. Ifthe developedautomated solutionisintegrated intothe currentpractice in the digital facility management industry, the importation of information in AIR Excel into the Revit model will only require one person, leaving rooms for other staff to handle other projects. The company will be more efficient andproductive as it couldhandle more projects atthesametime.

5.3. Accuracyofinformation

The information in the completed Revit model by the participants were verified against

informationintheautomaticgeneratedAIR.TheaccuracycheckontheRevitmodelusingthe manualmethodwasbasedonthetotalnumberofcriticalassetscompleted.Figure34shows thetypesoferrorsfoundwhileconductingthefirstroundofcheckingontheimported information.Themostcommonerrorfoundwaswronginformationandcopyingofinformation towrongcriticalassets.Duringthefirst100%accuracycheck,anaverageof34errorswas foundintheinformationdonemanually.

Figure34:Typesoferrorsfoundintheinformationduringthechecks

Forthefirstcheck,allparticipantshadmadeerrorsinthemanualimportationofinformation. Thenon-experiencedtestgroupmademoreerrorsthantheexperiencedgroup.After conductingthe50%accuracycheck,2ofthefiveexperiencedparticipantsand4ofthefive non-experiencedstillmadesomeerrorsintheimportationofinformation,asshowninTable 4.Someerrorsfoundonthesecondroundofcheckswereundiscoveredduringthefirst100% checkandwerediscoveredinthe50%check.Theinterestingpointisthateventheexperienced participantsmadenumerouserrorswiththemanualmethodofimportinginformationintothe Revitmodel.Thismeanserrorscanstillbecommittedregardlessofexperience,mainlydueto

humanerror.IfhumaninvolvementintheimportationofinformationintoRevitmodelcanbe reducedsignificantly,errorsduetohumanswillbereducedsignificantly.

The two errors found during the first 100% accuracy of information importation with the developedautomatedsolutionisthesameforallparticipants.Surplusassetswereplacedinthe generatedAIRintentionally.Theobservationmeansthedevelopedautomatedsolutioncanhelp identifiederrorseasily.Thetwoadditionalcriticalassetswereexcludedinthenexttworounds ofchecking.Thus,therewerenoadditionalerrorsfoundwhenconductingthesubsequent50% and 25% of accuracy checks. After conducting the three stages of the check, no errors were found. The adoption of the developed automated solution could ensure the accuracy of information being imported from the AIR Excel file into the Revit model within a very short time.Themainobjectiveofthedevelopedautomatedsolutionwastoensure100%accuracyin the information imported. Thus, the obtained results fulfilled the main objective of the developedautomatedsolution.

Based onexperience gained in the digitalfacilitymanagement industry, errors willalways be found in the imported information, which was done manually. Companies will conduct the threestagesofcheckinginthecurrentindustrytoensurethatnoerrorswerefoundintheRevit model. However, the process of checking was usually done with three to four people. When differentpeopleworkonthesamesetofinformation,therewillbeinconsistenciesinthequality of information. As the importation of information was done manually in the industry, employees are being pressured, which might cause them to lose focus that causes errors to occur. If the developed automated solution in this study is integrated into the current digital facility management industry, the contact between the information and the employee will be minimised,causingtheimportedinformationtonoerrorsintheimportationofverifiedcritical assetinformationintheAIRintoa3Dmodel.

The findings from this study have shown that the importation of information using the developed automated solution will ensure the accuracyof the information, which iscrucialas it affects the management and maintenance ofcritical assets. The accuracyin the information imported into the Revit model by the developed automated solution has shown its feasibility andreliabilitytoreducethetimetakenwhileenhancingquality.

Table3:ThetimetakentocompletetheimportationofcriticalassetinformationintoaRevitmodelbyexperienceandnon-experienceparticipants

MANUALmethod

AUTOMATEDmethod

With experience?

Actualtime takenfordata entry(mins)

Noofassets completed Timetakenfor eachasset (mins)

Actualtime takenfordata entry(mins)

Ableto complete? Noofassets completed Timetakenfor eachasset (mins)

Participant1 Yes 45 20 2.25 4.5 Yes 448 0.01

Participant2 Yes 50 31 1.61 6 Yes 448 0.01

Participant3 Yes 49.5 62 0.80 1.5 Yes 448 0.01

Participant4 Yes 49.5 52 0.95 5.5 Yes 448 0.01

Participant5 Yes 47.5 34 1.40 5 Yes 448 0.01

Minimumtimetaken(mins) 0.80

Maximumtimetaken(mins) 2.25

Minimumtimetaken(mins) 0.01

Maximumtimetaken(mins) 0.01

Averagetimetaken(mins) 1.40 Averagetimetaken(mins) 0.01

Participant6 No 43 10 4.30 1.5 Yes 448 0.01

Participant7 No 41 9 4.56 3.5 Yes 448 0.01

Participant8 No 39 10 3.90 2 Yes 448 0.01

Participant9 No 41.5 6 6.92 5 Yes 448 0.01

Participant10 No 50 12 4.17 4 Yes 448 0.01

Minimumtimetaken(mins) 3.90

Maximumtimetaken(mins) 6.92

Averagetimetaken(mins) 4.77

Minimumtimetaken(mins) 0.01

Maximumtimetaken(mins) 0.01

Averagetimetaken(mins) 0.01

Table4:Numberoferrorsrecordedbytheparticipantswhenusingmanualandautomatedmethods

ImportingofinformationusingMANUALmethod

Noof assets completed

Totalasset information tobe imported

Errors foundon 100% accuracy check

Errors foundon 50% accuracy check

Errors foundon 25% accuracy check

ImportingofinformationusingAUTOMATED method

Noof assets completed

Totalasset information tobe imported

Errors foundon 100% accuracy check

Errors foundon 50% accuracy check

Errors foundon 25% accuracy check

Participant1 Yes 20 320 5 0 0 448 7376 2 0 0

Participant2 Yes 31 496 7 0 0 448 7376 2 0 0

Participant3 Yes 62 992 8 2 0 448 7376 2 0 0

Participant4 Yes 52 832 8 3 0 448 7376 2 0 0

Participant5 Yes 34 544 9 0 0 448 7376 2 0 0

Participant6 No 10 160 12 3 0 448 7376 2 0 0

Participant7 No 9 144 9 5 0 448 7376 2 0 0

Participant8 No 10 160 13 3 0 448 7376 2 0 0

Participant9 No 6 96 7 0 0 448 7376 2 0 0

Participant10 No 12 192 15 4 0 448 7376 2 0 0

The developed automated solution eliminated the root cause of the problem caused by the manual method of importing verified critical asset information from AIR into a 3D model. The root cause is inherent inconvenience and discomfort. The automated solution provided both experienced and non-experienced participants convenience and comfort in the importationwithoutcompromisingquality.

5.4 FutureImplementation

Eventhoughthedevelopedautomatedsolutioncaneliminatethecauseoftheproblemcurrently experiencedinthedigitalfacilitymanagementindustry,thereisstillaneedtocontinuelooking outforcontinuousimprovement.

5.4.1 Integration of AIR generator with developed solution

The integration of the automatic AIR generator, developed earlier by Ng and Fadeyi (2020) andusedinthisstudyforautomaticdocumentationofcriticalassetsandtheirinformation,and the automated process for importing information into BIM 3D Model will reduce the time neededfor the overall work processto 4mins. This caneven be true forverylarger buildings withthousandsofcriticalassetswiththousandsofinformation.Eventhoughtheintegrationof bothsolutionswillreducethetimeneeded,thereisstillaneedtofurtherincreaseconvenience and comfort provided to users in doing the importing of critical assets information. In the current developed automated solution, users will still need to select the Excel and open Revit modeltorunthe Dynamo script.

AdvancedfeaturessuchasusingPythoncodingthatcanensurethesmoothintegrationbetween the two solutions – automated AIR generator and automated solution for importing asset informationinto3Dmodel,isstillneeded.Itisenvisagedthatinthefuture,userswilljustneed to upload the equipment list, and generation of asset information in the AIR and importation of asset information into the Revit model will occur automatically without the need to select therequiredExcelandopenRevit modeltoruntheDynamo script.

One of the possible future implementations will be integrating the developed automated solution with Python. As Python has the capability of machine learning and artificial intelligence, advanced features could be integrated into the solution to improve the overall

work process. Image reading is important in the digital facility management industry, which couldbe done with Python. With the image reading ability, users are not limitedto importing PDForExcelfilesandimageformattedinformation.

5.4.2 Challenges

Theexperimentwasinitiallyplannedtobeconductedface-to-facetoavoidfactorsthatmight introduce uncertainty into the experiment results. However, the experiment was changed to be conducted through an online conference due to COVID-19 restrictions. Extra measures suchaspreparingexperimentbriefs, videoguides, andscreenrecordingwereused toreduce the possibility of misjudgment that could contribute to uncertainty in the data collected and presentedresults.

6.0CONCLUSION

Thereportedprojectaimstodevelopautomatedsolutiontoaidthedigitalfacilitymanagement professionals in effectively and efficiently importing critical assets information into a Revit BIM3Dmodel.Thisisacontinuationoftheearlierworkbytheauthors,NgandFadeyi(2020), inwhichanautomaticAIRgeneratorwascreated.Thefirstobjective ofthiscurrentstudywas todevelopanautomatedsolutionthatcouldhelpfulfilltheproject'saim.Thesecondobjective was to examine the efficiency (time-saving) and effectiveness of the developed automated solutioninimportingassetinformationintoa3Dmodel.

There was a 99% reduction in time reduction when the developed automated solution was adopted instead of the manual method prevalent in the industry to import critical assets information into a 3D model. Additionally, the use of the automated solution ensures all participantsinthestudywereabletocompletetheimportationoftheinformationof448assets into a 3D model in no more than 6 mins. This contrasts with participants completing importationof only 6to62assetseven whengiven upto 60minsto completetheimportation manually.

The adoption of the developed automated solution makes the experience in importing critical assets information into a 3D model irrelevant. Each of the experienced and non-experienced participants spent an average of less than 1 sec per asset importation into a 3D model. When

participants were required to use the manual method for the importation, experienced participantsspentanaverageof1.40minswhilenon-experiencedparticipantsspentanaverage of4.77mins.

ThecomparisonmadebetweenassetsinformationintheAIRandassetsinformationmanually imported into a 3D model reveals an average of 34 errors in the imported information during the first round of checking. This is in contrast to no error found in the imported information done with the developedautomated solution, except for the twoerrors intentionally placed in theAIRforalltheparticipants.

The automated solution developed and reported in this paper is essential to improving the comfort and convenience of importing asset information in AIR into a 3D model with one person irrespective of the number of assets in less than a second without compromising the work'saccuracy. Theimplicationofthisisthatadditionalmanpowercanbedeployedtoother works where usefulness can be delivered. The developed automated solution reported in this paper is relevant to productivity improvement in the facility management industry. The adoption of the developed solution in the digital facility management industry, and documentation of the benefits inherent in it is essential. Efforts tocontinuously improve how automatedsolutionsareprovidedtoenhancetheconvenienceandcomfortofimportingcritical assetsinformationintothe 3Dmodelareencouraged.

ACKNOWLEDGEMENT

The Singapore Institute of Technology funds this project through a SEED grant (R-MOEA403-G008). Ms. Ng Hui Min did the project work and writing of this paper as part of her Master of Engineering Technology in Sustainable Infrastructure Engineering (Building Services) degree. Dr. Moshood Olawale Fadeyi guided the development of the developed automatedsolution andexperimentaldesignand execution. Dr. Fadeyi also contributedto the developmentofthisarticle.

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SUPPLEMENTARYINFORMATION

Thevideosofthedevelopedautomatedsolutioncanberetrievedfromthelinkprovidedbelow.

Theauthorsreservedtherighttothevideos.

Developed Automated Solution

https://www.dropbox.com/sh/n4cvccwxam2l01z/AAAk0n5oQ2zO1vNF1f-SQhvTa?dl=0