Vermontpanel1
panel1 时间:2021-01-06 阅读:()
PHM4SMSWorkshopPanel1WEKNOWWHATHAPPENSNEXTDavidSiegel(siegel@predictronics.
com)OverviewofManufacturingSectorsandExamplePHMApplications2PHMManufacturingApplicationsAutomotiveManufacturing‐IndustrialRobots,StampingMachines,ProcessLinesAerospaceManufacturing:MachineTools,ProductQualityPrediction,LaserDrilling/MachiningSemiconductorManufacturing:EtchingTools,VirtualMetrology,WaferSlicingProcessIndustry:steel/aluminummanufacturing,paper,consumergoods,food/beverageExampleMachineLevelPHMApplicationsforAutomotiveManufacturing3IndustrialRobotsServo-motortorquemonitoringMachineToolsNon-intrusiveperformancemonitoringToolconditionmonitoringSpindleperformancemonitoringBallscrewhealthassessment&lifepredictionBearinganalysis&diagnosisStampingMachinesProcessfaultdetectionCentrifugalAirCompressorData-drivensurgemapmodelingMiningforAlarmCorrelationPatternsFleet-basedhealthassessmentPastSuccessinManufacturingApplications"…theIMSCenterhasgeneratedover$855Mofeconomicimpacttoitsmemberswithabenefitcostratioof238:1.
"GrayDO,RiversDandVermontG.
"MeasuringtheEconomicImpactsofNSFI/UCRCProgram:AFeasibilityStudy"(May2012)PreparedforNSFI/UCRCunderEEC-0631414.
Accessedthrough:http://www.
ncsu.
edu/iucrc/PDFs/IUCRC_EconImpactFeasibilityReport_Final.
pdfHighlightsfrompastcasestudies:ToyotaandIMS(2007):Data-DrivenSurgeMapModelsandSurgeDetectionforCentrifugalAirCompressorso6.
5MsavingestimatedforextendedapplicationinwholefactoryConsumerGoodsManufacturerandIMS(2009):AutonomousProductionAnomalyDetectionAgentbyDataMiningMethodsoDramaticimprovementonproductqualityandmillionsinsavingsondowntimereductionAerospaceManufacturerandIMS(2011):MachineToolHealthAssessmentbyFixedCycleFeatureTextoAppliedonmultipleassetmonitoringintwofactoriesandseveremachinebreakdownwasdetectedtwoweeksinadvance.
4ChallengesMachinelevelPHM(MachineTools)oMultitudeofoperatingsettings(differentspeeds,depthsofcut,feedrates)–Howtonormalizethesefactorsinordertohaverobusthealthmonitoringmethods.
oHowtodealwiththehumanfactors(howwellwasmaintenanceperformed,howpeopleoperatethemachine(frompersontopersonandshifttoshift).
ObtainingtherightdatatododiagnosticsandprognosticsoManyheterogeneousdatasourcesfrommultipleplaces.
oObtaininginformationfrommachinecontrollersiseasiernowthen5yearsago,butcanstillbeabarrier.
oMaintenancerecordsareincomplete,sometimesmanuallyentered,andcanbeunstructured–Thisinaccuracycouldmakeitmoredifficulttousehistoricaldatatodevelopandvalidatediagnosticandprognosticsystems.
Systemlevel/ProductionLinePHMNeedsmoreResearchoManystudiesonmachineorcomponentlevelPHM;veryfewonmultiplemachinesinaproductionline.
oHowtodealwithchangesinsystemconfigurationandunitsbeingreplacedwithrespecttotypicalPHMapproachesbasedonabaseline/referencecondition.
oDatadrivenmodels+systemlevelinteractionmodelcouldbeneeded.
oPreviouscasestudywithconsumergoodsmanufacturerusedadata-drivenmethodthatcouldlearnovertime;theapproachworkedverywellbuttook3yearstodevelopandimplement.
5CurrentandFuturePerspectives6Forcertainapplications,Ifeelthatthetechnologyismatureenough(industrialrobots,machinetools,rotatingmachinery).
PHMapplicationsattheprocessorsystemlevelrequiremoreR&Dwork,andcreatingageneralapproachforbothmachinesandsystemsrequiresimprovementinthescienceandalsostandardstohelpgeneralizethemethodsandapproaches.
https://www.
youtube.
com/watchv=wb7iiEbIgHw&feature=youtu.
beVideoofrobothealthmonitoringsoftware:
com)OverviewofManufacturingSectorsandExamplePHMApplications2PHMManufacturingApplicationsAutomotiveManufacturing‐IndustrialRobots,StampingMachines,ProcessLinesAerospaceManufacturing:MachineTools,ProductQualityPrediction,LaserDrilling/MachiningSemiconductorManufacturing:EtchingTools,VirtualMetrology,WaferSlicingProcessIndustry:steel/aluminummanufacturing,paper,consumergoods,food/beverageExampleMachineLevelPHMApplicationsforAutomotiveManufacturing3IndustrialRobotsServo-motortorquemonitoringMachineToolsNon-intrusiveperformancemonitoringToolconditionmonitoringSpindleperformancemonitoringBallscrewhealthassessment&lifepredictionBearinganalysis&diagnosisStampingMachinesProcessfaultdetectionCentrifugalAirCompressorData-drivensurgemapmodelingMiningforAlarmCorrelationPatternsFleet-basedhealthassessmentPastSuccessinManufacturingApplications"…theIMSCenterhasgeneratedover$855Mofeconomicimpacttoitsmemberswithabenefitcostratioof238:1.
"GrayDO,RiversDandVermontG.
"MeasuringtheEconomicImpactsofNSFI/UCRCProgram:AFeasibilityStudy"(May2012)PreparedforNSFI/UCRCunderEEC-0631414.
Accessedthrough:http://www.
ncsu.
edu/iucrc/PDFs/IUCRC_EconImpactFeasibilityReport_Final.
pdfHighlightsfrompastcasestudies:ToyotaandIMS(2007):Data-DrivenSurgeMapModelsandSurgeDetectionforCentrifugalAirCompressorso6.
5MsavingestimatedforextendedapplicationinwholefactoryConsumerGoodsManufacturerandIMS(2009):AutonomousProductionAnomalyDetectionAgentbyDataMiningMethodsoDramaticimprovementonproductqualityandmillionsinsavingsondowntimereductionAerospaceManufacturerandIMS(2011):MachineToolHealthAssessmentbyFixedCycleFeatureTextoAppliedonmultipleassetmonitoringintwofactoriesandseveremachinebreakdownwasdetectedtwoweeksinadvance.
4ChallengesMachinelevelPHM(MachineTools)oMultitudeofoperatingsettings(differentspeeds,depthsofcut,feedrates)–Howtonormalizethesefactorsinordertohaverobusthealthmonitoringmethods.
oHowtodealwiththehumanfactors(howwellwasmaintenanceperformed,howpeopleoperatethemachine(frompersontopersonandshifttoshift).
ObtainingtherightdatatododiagnosticsandprognosticsoManyheterogeneousdatasourcesfrommultipleplaces.
oObtaininginformationfrommachinecontrollersiseasiernowthen5yearsago,butcanstillbeabarrier.
oMaintenancerecordsareincomplete,sometimesmanuallyentered,andcanbeunstructured–Thisinaccuracycouldmakeitmoredifficulttousehistoricaldatatodevelopandvalidatediagnosticandprognosticsystems.
Systemlevel/ProductionLinePHMNeedsmoreResearchoManystudiesonmachineorcomponentlevelPHM;veryfewonmultiplemachinesinaproductionline.
oHowtodealwithchangesinsystemconfigurationandunitsbeingreplacedwithrespecttotypicalPHMapproachesbasedonabaseline/referencecondition.
oDatadrivenmodels+systemlevelinteractionmodelcouldbeneeded.
oPreviouscasestudywithconsumergoodsmanufacturerusedadata-drivenmethodthatcouldlearnovertime;theapproachworkedverywellbuttook3yearstodevelopandimplement.
5CurrentandFuturePerspectives6Forcertainapplications,Ifeelthatthetechnologyismatureenough(industrialrobots,machinetools,rotatingmachinery).
PHMapplicationsattheprocessorsystemlevelrequiremoreR&Dwork,andcreatingageneralapproachforbothmachinesandsystemsrequiresimprovementinthescienceandalsostandardstohelpgeneralizethemethodsandapproaches.
https://www.
youtube.
com/watchv=wb7iiEbIgHw&feature=youtu.
beVideoofrobothealthmonitoringsoftware:
弘速云20.8元/月 ，香港云服务器 2核 1g 10M
弘速云元旦活动本公司所销售的弹性云服务器、虚拟专用服务器（VPS）、虚拟主机等涉及网站接入服务的云产品由具备相关资质的第三方合作服务商提供官方网站：https://www.hosuyun.com公司名：弘速科技有限公司香港沙田直营机房采用CTGNET高速回国线路弹性款8折起优惠码:hosu1-1 测试ip:69.165.77.50地区CPU内存硬盘带宽价格购买地址香港沙田2-8核1-16G20-...
HostRound：美国达拉斯/洛杉矶/纽约/荷兰大硬盘服务器,1TB NVMe+4TB HDD,$179/月
hostround怎么样?大硬盘服务器，高防服务器。hostround，美国商家，2017年成立，正规注册公司(Company File #6180543)，提供虚拟主机、VPS云主机、美国服务器、荷兰服务器租用等。现在有1款特价大硬盘独服，位于达拉斯，配置还不错，本月订购时包括免费 500Gbps DDoS 保护，有兴趣的可以关注一下。点击直达：hostround官方网站地址美国\荷兰独立服务器...
妮妮云（43元/月 ） 香港 8核8G 43元/月 美国 8核8G
妮妮云的来历妮妮云是 789 陈总 张总 三方共同投资建立的网站 本着“良心 便宜 稳定”的初衷 为小白用户避免被坑妮妮云的市场定位妮妮云主要代理市场稳定速度的云服务器产品，避免新手购买云服务器的时候众多商家不知道如何选择，妮妮云就帮你选择好了产品，无需承担购买风险，不用担心出现被跑路 被诈骗的情况。妮妮云的售后保证妮妮云退款 通过于合作商的友好协商，云服务器提供2天内全额退款，超过2天不退款 物...
panel1为你推荐
-
服务器空间租用个人网络域名空间租用网站空间租赁网站空间租用好一些还是云主机好一些？域名注册公司找家正规的中文域名注册公司域名空间代理哪里的域名空间商比较好?cm域名注册cm域名是什么含义？价格是多少？注册地址是多少？有什么投资价值？美国主机空间哪个美国ASP的主机空间最稳定，最好使!!中国域名注册中国十大域名注册服务商有哪些?域名服务域名服务器是什么？有什么作用域名服务域名系统主要是什么？免费网站域名申请哪里可以申请到免费网站域名？