04000nam 2201105z- 450 991055749150332120220111(CKB)5400000000042916(oapen)https://directory.doabooks.org/handle/20.500.12854/76899(oapen)doab76899(EXLCZ)99540000000004291620202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvanced Process Monitoring for Industry 4.0Basel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (288 p.)3-0365-2073-2 3-0365-2074-0 This book reports recent advances on Process Monitoring (PM) to cope with the many challenges raised by the new production systems, sensors and "extreme data" conditions that emerged with Industry 4.0. Concepts such as digital-twins and deep learning are brought to the PM arena, pushing forward the capabilities of existing methodologies to handle more complex scenarios. The evolution of classical paradigms such as Latent Variable modeling, Six Sigma and FMEA are also covered. Applications span a wide range of domains such as microelectronics, semiconductors, chemicals, materials, agriculture, as well as the monitoring of rotating equipment, combustion systems and membrane separation processes.Technology: general issuesbicsscartificial generation of variabilityauto machine learningclassificationcombustioncondition monitoringconstruction industrycontinuous castingcontrol chart patternconvolutional neural networkcurve resolutiondata augmentationdata miningdata reconciliationdecision support systemsdigital processingdiscriminant analysisdisruption managementdisruptionsexpert systemsfailure mode and effects analysis (FMEA)failure mode effects analysisfault detectionfault diagnosishigh-dimensional dataimbalanced dataIndustry 4.0latent variables modelsload identificationmembranemonitoringmulti-mode modelmulti-phase residual recursive modelmultiscalemultivariate data analysisn/aneural networksnon-intrusive load monitoringonlineoptical sensorsOPTICSpasting processPCAplaster productionPLSprincipal component analysisprocess controlprocess imageprocess monitoringquality controlquality predictionreal-timerisk priority numberrolling bearingsemiconductor manufacturingsignal detectionSix Sigmaspatial-temporal dataspectroscopy measurementsstatistical process controlstatistical process monitoringtime series classificationyield improvementTechnology: general issuesReis Marco Sedt1325356Gao FurongedtReis Marco SothGao FurongothBOOK9910557491503321Advanced Process Monitoring for Industry 4.03036793UNINA