{"id":"https://openalex.org/W2892982276","doi":"https://doi.org/10.1109/indin.2018.8471933","title":"Development of a Mobile App for Fault Detection Assessment based on Information Fusion","display_name":"Development of a Mobile App for Fault Detection Assessment based on Information Fusion","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2892982276","doi":"https://doi.org/10.1109/indin.2018.8471933","mag":"2892982276"},"language":"en","primary_location":{"id":"doi:10.1109/indin.2018.8471933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2018.8471933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109405456","display_name":"F. Arevalo","orcid":null},"institutions":[{"id":"https://openalex.org/I3130920692","display_name":"South Westphalia University of Applied Sciences","ror":"https://ror.org/04t5phd24","country_code":"DE","type":"education","lineage":["https://openalex.org/I3130920692"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fernando Arevalo","raw_affiliation_strings":["Department of Automation Technology, South Westphalia University of Applied Sciences, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Automation Technology, South Westphalia University of Applied Sciences, Germany","institution_ids":["https://openalex.org/I3130920692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090859316","display_name":"Enzo Oestanto","orcid":null},"institutions":[{"id":"https://openalex.org/I3130920692","display_name":"South Westphalia University of Applied Sciences","ror":"https://ror.org/04t5phd24","country_code":"DE","type":"education","lineage":["https://openalex.org/I3130920692"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Enzo Oestanto","raw_affiliation_strings":["Department of Automation Technology, South Westphalia University of Applied Sciences, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Automation Technology, South Westphalia University of Applied Sciences, Germany","institution_ids":["https://openalex.org/I3130920692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025397538","display_name":"Andreas Schwung","orcid":"https://orcid.org/0000-0001-8405-0977"},"institutions":[{"id":"https://openalex.org/I3130920692","display_name":"South Westphalia University of Applied Sciences","ror":"https://ror.org/04t5phd24","country_code":"DE","type":"education","lineage":["https://openalex.org/I3130920692"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Schwung","raw_affiliation_strings":["Department of Automation Technology, South Westphalia University of Applied Sciences, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Automation Technology, South Westphalia University of Applied Sciences, Germany","institution_ids":["https://openalex.org/I3130920692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109405456"],"corresponding_institution_ids":["https://openalex.org/I3130920692"],"apc_list":null,"apc_paid":null,"fwci":0.2464,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63908363,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"635","last_page":"640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9883999824523926,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6316737532615662},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6286736726760864},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.6140798926353455},{"id":"https://openalex.org/keywords/idle","display_name":"Idle","score":0.5593217611312866},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5301103591918945},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4619003236293793},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.41165655851364136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4018106758594513},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.3934321403503418},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.37653404474258423},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2921657860279083},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07997706532478333}],"concepts":[{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6316737532615662},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6286736726760864},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.6140798926353455},{"id":"https://openalex.org/C16320812","wikidata":"https://www.wikidata.org/wiki/Q1812200","display_name":"Idle","level":2,"score":0.5593217611312866},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5301103591918945},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4619003236293793},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.41165655851364136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4018106758594513},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.3934321403503418},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37653404474258423},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2921657860279083},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07997706532478333},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin.2018.8471933","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2018.8471933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 16th International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W22229905","https://openalex.org/W611021884","https://openalex.org/W767201593","https://openalex.org/W1572517243","https://openalex.org/W1977471222","https://openalex.org/W1990561005","https://openalex.org/W1997113291","https://openalex.org/W1999393241","https://openalex.org/W2101234009","https://openalex.org/W2118978333","https://openalex.org/W2480645619","https://openalex.org/W2547344027","https://openalex.org/W2548532043","https://openalex.org/W2779622286","https://openalex.org/W2785530950","https://openalex.org/W2789904726","https://openalex.org/W3017312168","https://openalex.org/W4239808474","https://openalex.org/W6675354045","https://openalex.org/W6748919945"],"related_works":["https://openalex.org/W3121841074","https://openalex.org/W2901018557","https://openalex.org/W2055572829","https://openalex.org/W1894159578","https://openalex.org/W4297796115","https://openalex.org/W4285600173","https://openalex.org/W3125086856","https://openalex.org/W2913388591","https://openalex.org/W3007653948","https://openalex.org/W1957831838"],"abstract_inverted_index":{"Machine":[0,9],"faults":[1,10],"cause":[2],"high":[3],"financial":[4],"losses":[5],"for":[6,46,100,110,126],"industrial":[7,106],"companies.":[8],"stop":[11],"the":[12,31,33,47,61,101,111,116,123,127,151,161,166,169,176],"process":[13,68],"flow,":[14],"and":[15,21,113],"are":[16],"associated":[17],"with":[18,175],"idle":[19,34,50],"time":[20,35,40,51],"additional":[22],"expenses":[23],"due":[24],"to":[25,42,84,89],"unexpected":[26],"corrective":[27],"maintenance.":[28,93],"Depending":[29],"on":[30],"fault,":[32],"can":[36,52],"span":[37],"from":[38],"short":[39],"actions":[41],"long":[43],"inactivity":[44],"periods":[45],"machine.":[48],"This":[49,94,146],"risk":[53,60],"a":[54,97,142],"customer":[55,62],"shipment,":[56],"subsequently":[57],"putting":[58],"at":[59],"trust.":[63],"A":[64,108],"complex":[65],"interaction":[66],"between":[67],"variables":[69],"cannot":[70],"be":[71],"easily":[72],"traced":[73],"using":[74,137],"conventional":[75],"condition":[76,91],"monitoring":[77],"approaches.":[78],"There":[79],"is":[80,118,135],"an":[81],"increasing":[82],"trend":[83],"use":[85],"machine":[86,138],"learning":[87,139],"methods":[88],"assess":[90],"based":[92],"paper":[95],"proposes":[96],"mobile":[98,117],"App":[99],"fault":[102,128,132,170],"detection":[103,129,133,171],"assessment":[104,134,172],"of":[105,115,153,168],"machinery.":[107],"proposal":[109],"design":[112],"implementation":[114],"presented,":[119],"as":[120,122],"well":[121],"methodology":[124],"followed":[125],"assessment.":[130],"The":[131,157],"adressed":[136],"techniques,":[140],"specifically":[141],"majority":[143,147,162],"voting":[144,148,163],"classifier.":[145],"classifier":[149],"combines":[150],"predictions":[152],"three":[154],"classification":[155,178],"methods.":[156,179],"results":[158],"show":[159],"that":[160],"approach":[164],"improves":[165],"performance":[167],"in":[173],"comparison":[174],"invidual":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}