Fault Diagnosis for an Industrial High Pressure Leaching Process with a Monitoring Dashboard Article Swipe
Adriaan Haasbroek
,
Johannes Jacobus Strydom
,
John T. McCoy
,
Lidia Auret
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2018.09.402
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2018.09.402
Although fault detection and diagnosis are extensively studied and demonstrated on synthetic benchmarks, very few demonstrations of industrial application exist. In this paper, an investigation of faulty conditions in an industrial base metal refinery is conducted using standard statistical fault detection and diagnosis methods, and the IntelliSenzo™ monitoring dashboard. A workflow for offline fault investigation is described, and demonstrated on the industrial data, highlighting the need for careful record keeping, a structured approach, and iterative investigative steps. Potential propagation paths established links between the identified fault, process variables of interest, and engineering hypotheses, guiding the investigation and leading to recommendations of corrective action to the operating plant. The root cause of the fault (leaking and choked feed valves) were identified as potential causes in the investigation. Plant personnel confirmed that this structured approach, using process data, statistical techniques, and engineering knowledge, could speed up fault investigations, and reduce the costs of production losses and plant downtime.
Related Topics
Concepts
Downtime
Workflow
Fault detection and isolation
Process (computing)
Reliability engineering
Root cause analysis
Dashboard
Work in process
Root cause
Engineering
Statistical process control
Fault (geology)
Computer science
Automotive engineering
Database
Artificial intelligence
Operations management
Actuator
Seismology
Operating system
Geology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ifacol.2018.09.402
- OA Status
- diamond
- Cited By
- 2
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2897532420
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2897532420Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.ifacol.2018.09.402Digital Object Identifier
- Title
-
Fault Diagnosis for an Industrial High Pressure Leaching Process with a Monitoring DashboardWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-01-01Full publication date if available
- Authors
-
Adriaan Haasbroek, Johannes Jacobus Strydom, John T. McCoy, Lidia AuretList of authors in order
- Landing page
-
https://doi.org/10.1016/j.ifacol.2018.09.402Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.ifacol.2018.09.402Direct OA link when available
- Concepts
-
Downtime, Workflow, Fault detection and isolation, Process (computing), Reliability engineering, Root cause analysis, Dashboard, Work in process, Root cause, Engineering, Statistical process control, Fault (geology), Computer science, Automotive engineering, Database, Artificial intelligence, Operations management, Actuator, Seismology, Operating system, GeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2020: 1Per-year citation counts (last 5 years)
- References (count)
-
18Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2897532420 |
|---|---|
| doi | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| ids.doi | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| ids.mag | 2897532420 |
| ids.openalex | https://openalex.org/W2897532420 |
| fwci | 0.19064887 |
| type | article |
| title | Fault Diagnosis for an Industrial High Pressure Leaching Process with a Monitoring Dashboard |
| biblio.issue | 21 |
| biblio.volume | 51 |
| biblio.last_page | 122 |
| biblio.first_page | 117 |
| topics[0].id | https://openalex.org/T10876 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2207 |
| topics[0].subfield.display_name | Control and Systems Engineering |
| topics[0].display_name | Fault Detection and Control Systems |
| topics[1].id | https://openalex.org/T12282 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9972000122070312 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2210 |
| topics[1].subfield.display_name | Mechanical Engineering |
| topics[1].display_name | Mineral Processing and Grinding |
| topics[2].id | https://openalex.org/T11443 |
| topics[2].field.id | https://openalex.org/fields/18 |
| topics[2].field.display_name | Decision Sciences |
| topics[2].score | 0.9797000288963318 |
| topics[2].domain.id | https://openalex.org/domains/2 |
| topics[2].domain.display_name | Social Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1804 |
| topics[2].subfield.display_name | Statistics, Probability and Uncertainty |
| topics[2].display_name | Advanced Statistical Process Monitoring |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C180591934 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8159466981887817 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1253369 |
| concepts[0].display_name | Downtime |
| concepts[1].id | https://openalex.org/C177212765 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6224929094314575 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q627335 |
| concepts[1].display_name | Workflow |
| concepts[2].id | https://openalex.org/C152745839 |
| concepts[2].level | 3 |
| concepts[2].score | 0.5715956687927246 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q5438153 |
| concepts[2].display_name | Fault detection and isolation |
| concepts[3].id | https://openalex.org/C98045186 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5131400227546692 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[3].display_name | Process (computing) |
| concepts[4].id | https://openalex.org/C200601418 |
| concepts[4].level | 1 |
| concepts[4].score | 0.508738100528717 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2193887 |
| concepts[4].display_name | Reliability engineering |
| concepts[5].id | https://openalex.org/C130963320 |
| concepts[5].level | 2 |
| concepts[5].score | 0.49503961205482483 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1401207 |
| concepts[5].display_name | Root cause analysis |
| concepts[6].id | https://openalex.org/C33499554 |
| concepts[6].level | 2 |
| concepts[6].score | 0.4673251211643219 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1417134 |
| concepts[6].display_name | Dashboard |
| concepts[7].id | https://openalex.org/C174998907 |
| concepts[7].level | 2 |
| concepts[7].score | 0.45088326930999756 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q357662 |
| concepts[7].display_name | Work in process |
| concepts[8].id | https://openalex.org/C84945661 |
| concepts[8].level | 2 |
| concepts[8].score | 0.44981318712234497 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q7366567 |
| concepts[8].display_name | Root cause |
| concepts[9].id | https://openalex.org/C127413603 |
| concepts[9].level | 0 |
| concepts[9].score | 0.4268098473548889 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[9].display_name | Engineering |
| concepts[10].id | https://openalex.org/C113644684 |
| concepts[10].level | 3 |
| concepts[10].score | 0.41418182849884033 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q1356717 |
| concepts[10].display_name | Statistical process control |
| concepts[11].id | https://openalex.org/C175551986 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4106161892414093 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q47089 |
| concepts[11].display_name | Fault (geology) |
| concepts[12].id | https://openalex.org/C41008148 |
| concepts[12].level | 0 |
| concepts[12].score | 0.40816158056259155 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[12].display_name | Computer science |
| concepts[13].id | https://openalex.org/C171146098 |
| concepts[13].level | 1 |
| concepts[13].score | 0.1623876690864563 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q124192 |
| concepts[13].display_name | Automotive engineering |
| concepts[14].id | https://openalex.org/C77088390 |
| concepts[14].level | 1 |
| concepts[14].score | 0.13576918840408325 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q8513 |
| concepts[14].display_name | Database |
| concepts[15].id | https://openalex.org/C154945302 |
| concepts[15].level | 1 |
| concepts[15].score | 0.11165767908096313 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[15].display_name | Artificial intelligence |
| concepts[16].id | https://openalex.org/C21547014 |
| concepts[16].level | 1 |
| concepts[16].score | 0.10637053847312927 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q1423657 |
| concepts[16].display_name | Operations management |
| concepts[17].id | https://openalex.org/C172707124 |
| concepts[17].level | 2 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q423488 |
| concepts[17].display_name | Actuator |
| concepts[18].id | https://openalex.org/C165205528 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q83371 |
| concepts[18].display_name | Seismology |
| concepts[19].id | https://openalex.org/C111919701 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[19].display_name | Operating system |
| concepts[20].id | https://openalex.org/C127313418 |
| concepts[20].level | 0 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[20].display_name | Geology |
| keywords[0].id | https://openalex.org/keywords/downtime |
| keywords[0].score | 0.8159466981887817 |
| keywords[0].display_name | Downtime |
| keywords[1].id | https://openalex.org/keywords/workflow |
| keywords[1].score | 0.6224929094314575 |
| keywords[1].display_name | Workflow |
| keywords[2].id | https://openalex.org/keywords/fault-detection-and-isolation |
| keywords[2].score | 0.5715956687927246 |
| keywords[2].display_name | Fault detection and isolation |
| keywords[3].id | https://openalex.org/keywords/process |
| keywords[3].score | 0.5131400227546692 |
| keywords[3].display_name | Process (computing) |
| keywords[4].id | https://openalex.org/keywords/reliability-engineering |
| keywords[4].score | 0.508738100528717 |
| keywords[4].display_name | Reliability engineering |
| keywords[5].id | https://openalex.org/keywords/root-cause-analysis |
| keywords[5].score | 0.49503961205482483 |
| keywords[5].display_name | Root cause analysis |
| keywords[6].id | https://openalex.org/keywords/dashboard |
| keywords[6].score | 0.4673251211643219 |
| keywords[6].display_name | Dashboard |
| keywords[7].id | https://openalex.org/keywords/work-in-process |
| keywords[7].score | 0.45088326930999756 |
| keywords[7].display_name | Work in process |
| keywords[8].id | https://openalex.org/keywords/root-cause |
| keywords[8].score | 0.44981318712234497 |
| keywords[8].display_name | Root cause |
| keywords[9].id | https://openalex.org/keywords/engineering |
| keywords[9].score | 0.4268098473548889 |
| keywords[9].display_name | Engineering |
| keywords[10].id | https://openalex.org/keywords/statistical-process-control |
| keywords[10].score | 0.41418182849884033 |
| keywords[10].display_name | Statistical process control |
| keywords[11].id | https://openalex.org/keywords/fault |
| keywords[11].score | 0.4106161892414093 |
| keywords[11].display_name | Fault (geology) |
| keywords[12].id | https://openalex.org/keywords/computer-science |
| keywords[12].score | 0.40816158056259155 |
| keywords[12].display_name | Computer science |
| keywords[13].id | https://openalex.org/keywords/automotive-engineering |
| keywords[13].score | 0.1623876690864563 |
| keywords[13].display_name | Automotive engineering |
| keywords[14].id | https://openalex.org/keywords/database |
| keywords[14].score | 0.13576918840408325 |
| keywords[14].display_name | Database |
| keywords[15].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[15].score | 0.11165767908096313 |
| keywords[15].display_name | Artificial intelligence |
| keywords[16].id | https://openalex.org/keywords/operations-management |
| keywords[16].score | 0.10637053847312927 |
| keywords[16].display_name | Operations management |
| language | en |
| locations[0].id | doi:10.1016/j.ifacol.2018.09.402 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2898405271 |
| locations[0].source.issn | 2405-8963, 2405-8971 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2405-8963 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | IFAC-PapersOnLine |
| locations[0].source.host_organization | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_name | Elsevier BV |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320990 |
| locations[0].source.host_organization_lineage_names | Elsevier BV |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | IFAC-PapersOnLine |
| locations[0].landing_page_url | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5075407790 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Adriaan Haasbroek |
| authorships[0].affiliations[0].raw_affiliation_string | Stone Three Mining, Somerset West, South Africa |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Adriaan Haasbroek |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Stone Three Mining, Somerset West, South Africa |
| authorships[1].author.id | https://openalex.org/A5009063748 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Johannes Jacobus Strydom |
| authorships[1].countries | ZA |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I26092322 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| authorships[1].institutions[0].id | https://openalex.org/I26092322 |
| authorships[1].institutions[0].ror | https://ror.org/05bk57929 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I26092322 |
| authorships[1].institutions[0].country_code | ZA |
| authorships[1].institutions[0].display_name | Stellenbosch University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Johannes J. Strydom |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| authorships[2].author.id | https://openalex.org/A5036512617 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | John T. McCoy |
| authorships[2].countries | ZA |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I26092322 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| authorships[2].institutions[0].id | https://openalex.org/I26092322 |
| authorships[2].institutions[0].ror | https://ror.org/05bk57929 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I26092322 |
| authorships[2].institutions[0].country_code | ZA |
| authorships[2].institutions[0].display_name | Stellenbosch University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | John T. McCoy |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| authorships[3].author.id | https://openalex.org/A5066835493 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-2129-4971 |
| authorships[3].author.display_name | Lidia Auret |
| authorships[3].countries | ZA |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I26092322 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| authorships[3].institutions[0].id | https://openalex.org/I26092322 |
| authorships[3].institutions[0].ror | https://ror.org/05bk57929 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I26092322 |
| authorships[3].institutions[0].country_code | ZA |
| authorships[3].institutions[0].display_name | Stellenbosch University |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Lidia Auret |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Department of Process Engineering, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Fault Diagnosis for an Industrial High Pressure Leaching Process with a Monitoring Dashboard |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10876 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2207 |
| primary_topic.subfield.display_name | Control and Systems Engineering |
| primary_topic.display_name | Fault Detection and Control Systems |
| related_works | https://openalex.org/W2030594396, https://openalex.org/W2754538212, https://openalex.org/W2490884653, https://openalex.org/W4200610016, https://openalex.org/W2183996497, https://openalex.org/W129587375, https://openalex.org/W4385832900, https://openalex.org/W2559147525, https://openalex.org/W4382407621, https://openalex.org/W2132554038 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2023 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2020 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1016/j.ifacol.2018.09.402 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2898405271 |
| best_oa_location.source.issn | 2405-8963, 2405-8971 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2405-8963 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | IFAC-PapersOnLine |
| best_oa_location.source.host_organization | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | IFAC-PapersOnLine |
| best_oa_location.landing_page_url | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| primary_location.id | doi:10.1016/j.ifacol.2018.09.402 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2898405271 |
| primary_location.source.issn | 2405-8963, 2405-8971 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2405-8963 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | IFAC-PapersOnLine |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | IFAC-PapersOnLine |
| primary_location.landing_page_url | https://doi.org/10.1016/j.ifacol.2018.09.402 |
| publication_date | 2018-01-01 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W2092627382, https://openalex.org/W2011968922, https://openalex.org/W2146641221, https://openalex.org/W4254621538, https://openalex.org/W2417644542, https://openalex.org/W2757109865, https://openalex.org/W6740872288, https://openalex.org/W2020405858, https://openalex.org/W2078678611, https://openalex.org/W2080303547, https://openalex.org/W2524294401, https://openalex.org/W2169347809, https://openalex.org/W1966863755, https://openalex.org/W2729884040, https://openalex.org/W2125849052, https://openalex.org/W2800817460, https://openalex.org/W2005051528, https://openalex.org/W2734575787 |
| referenced_works_count | 18 |
| abstract_inverted_index.A | 49 |
| abstract_inverted_index.a | 70 |
| abstract_inverted_index.In | 20 |
| abstract_inverted_index.an | 23, 29 |
| abstract_inverted_index.as | 120 |
| abstract_inverted_index.in | 28, 123 |
| abstract_inverted_index.is | 34, 55 |
| abstract_inverted_index.of | 16, 25, 88, 100, 110, 150 |
| abstract_inverted_index.on | 10, 59 |
| abstract_inverted_index.to | 98, 103 |
| abstract_inverted_index.up | 143 |
| abstract_inverted_index.The | 107 |
| abstract_inverted_index.and | 3, 8, 41, 44, 57, 73, 90, 96, 114, 138, 146, 153 |
| abstract_inverted_index.are | 5 |
| abstract_inverted_index.few | 14 |
| abstract_inverted_index.for | 51, 66 |
| abstract_inverted_index.the | 45, 60, 64, 83, 94, 104, 111, 124, 148 |
| abstract_inverted_index.base | 31 |
| abstract_inverted_index.feed | 116 |
| abstract_inverted_index.need | 65 |
| abstract_inverted_index.root | 108 |
| abstract_inverted_index.that | 129 |
| abstract_inverted_index.this | 21, 130 |
| abstract_inverted_index.very | 13 |
| abstract_inverted_index.were | 118 |
| abstract_inverted_index.Plant | 126 |
| abstract_inverted_index.cause | 109 |
| abstract_inverted_index.costs | 149 |
| abstract_inverted_index.could | 141 |
| abstract_inverted_index.data, | 62, 135 |
| abstract_inverted_index.fault | 1, 39, 53, 112, 144 |
| abstract_inverted_index.links | 81 |
| abstract_inverted_index.metal | 32 |
| abstract_inverted_index.paths | 79 |
| abstract_inverted_index.plant | 154 |
| abstract_inverted_index.speed | 142 |
| abstract_inverted_index.using | 36, 133 |
| abstract_inverted_index.action | 102 |
| abstract_inverted_index.causes | 122 |
| abstract_inverted_index.choked | 115 |
| abstract_inverted_index.exist. | 19 |
| abstract_inverted_index.fault, | 85 |
| abstract_inverted_index.faulty | 26 |
| abstract_inverted_index.losses | 152 |
| abstract_inverted_index.paper, | 22 |
| abstract_inverted_index.plant. | 106 |
| abstract_inverted_index.record | 68 |
| abstract_inverted_index.reduce | 147 |
| abstract_inverted_index.steps. | 76 |
| abstract_inverted_index.between | 82 |
| abstract_inverted_index.careful | 67 |
| abstract_inverted_index.guiding | 93 |
| abstract_inverted_index.leading | 97 |
| abstract_inverted_index.offline | 52 |
| abstract_inverted_index.process | 86, 134 |
| abstract_inverted_index.studied | 7 |
| abstract_inverted_index.valves) | 117 |
| abstract_inverted_index.(leaking | 113 |
| abstract_inverted_index.Although | 0 |
| abstract_inverted_index.keeping, | 69 |
| abstract_inverted_index.methods, | 43 |
| abstract_inverted_index.refinery | 33 |
| abstract_inverted_index.standard | 37 |
| abstract_inverted_index.workflow | 50 |
| abstract_inverted_index.Potential | 77 |
| abstract_inverted_index.approach, | 72, 132 |
| abstract_inverted_index.conducted | 35 |
| abstract_inverted_index.confirmed | 128 |
| abstract_inverted_index.detection | 2, 40 |
| abstract_inverted_index.diagnosis | 4, 42 |
| abstract_inverted_index.downtime. | 155 |
| abstract_inverted_index.interest, | 89 |
| abstract_inverted_index.iterative | 74 |
| abstract_inverted_index.operating | 105 |
| abstract_inverted_index.personnel | 127 |
| abstract_inverted_index.potential | 121 |
| abstract_inverted_index.synthetic | 11 |
| abstract_inverted_index.variables | 87 |
| abstract_inverted_index.conditions | 27 |
| abstract_inverted_index.corrective | 101 |
| abstract_inverted_index.dashboard. | 48 |
| abstract_inverted_index.described, | 56 |
| abstract_inverted_index.identified | 84, 119 |
| abstract_inverted_index.industrial | 17, 30, 61 |
| abstract_inverted_index.knowledge, | 140 |
| abstract_inverted_index.monitoring | 47 |
| abstract_inverted_index.production | 151 |
| abstract_inverted_index.structured | 71, 131 |
| abstract_inverted_index.application | 18 |
| abstract_inverted_index.benchmarks, | 12 |
| abstract_inverted_index.engineering | 91, 139 |
| abstract_inverted_index.established | 80 |
| abstract_inverted_index.extensively | 6 |
| abstract_inverted_index.hypotheses, | 92 |
| abstract_inverted_index.propagation | 78 |
| abstract_inverted_index.statistical | 38, 136 |
| abstract_inverted_index.techniques, | 137 |
| abstract_inverted_index.demonstrated | 9, 58 |
| abstract_inverted_index.highlighting | 63 |
| abstract_inverted_index.investigation | 24, 54, 95 |
| abstract_inverted_index.investigative | 75 |
| abstract_inverted_index.demonstrations | 15 |
| abstract_inverted_index.investigation. | 125 |
| abstract_inverted_index.IntelliSenzo™ | 46 |
| abstract_inverted_index.investigations, | 145 |
| abstract_inverted_index.recommendations | 99 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5066835493, https://openalex.org/A5075407790 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I26092322 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.51368812 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |