Aluminium Melting Process Optimization with SmartMelt, a Digital Tool for Real-Time Operational Guidance View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2022-02-05

AUTHORS

A. Rostamian , M. Rappaz , M. Bertherat , J.-L. Desbiolles , M. A. Salgado Ordorica

ABSTRACT

Every year, about 70 million tonnes of Aluminium (Al) scrap is remelted worldwide in gas fired reverberatory furnaces. The efficiency of the melting process in such furnaces is strongly influenced by human-driven decisions and some furnace issues. SmartMelt is a novel IoT-based platform that combines real-time collection of sensor data, load data, and operator input in a dedicated interface, and a very efficient physical model of the melting process to provide on-line guidance to execute operations at optimal timings while detecting furnace issues and improving operator safety. Integrated into the daily operations of two furnaces of 30 and 70 tonnes capacity for periods of 16 and 6 months, respectively, the system has yielded an increase of productivityProductivity of up to 12% and a reduction of gas consumption of about 11%. SmartMelt successfully detects in real-time deviations of burners performance while also monitoring and recording delays influenced by external factors. More... »

PAGES

713-722

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-92529-1_94

DOI

http://dx.doi.org/10.1007/978-3-030-92529-1_94

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1145300449


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rostamian", 
        "givenName": "A.", 
        "id": "sg:person.016322173613.34", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016322173613.34"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rappaz", 
        "givenName": "M.", 
        "id": "sg:person.013657516157.10", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013657516157.10"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Constellium. Rue de l\u2019industrie 15, Chippis, Switzerland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Constellium. Rue de l\u2019industrie 15, Chippis, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bertherat", 
        "givenName": "M.", 
        "id": "sg:person.010414503013.20", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010414503013.20"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Desbiolles", 
        "givenName": "J.-L.", 
        "id": "sg:person.012746010777.26", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012746010777.26"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Salgado Ordorica", 
        "givenName": "M. A.", 
        "id": "sg:person.012117711513.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012117711513.23"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "2022-02-05", 
    "datePublishedReg": "2022-02-05", 
    "description": "Every year, about 70 million tonnes of Aluminium (Al) scrap is remelted worldwide in gas fired reverberatory furnaces. The efficiency of the melting process in such furnaces is strongly influenced by human-driven decisions and some furnace issues. SmartMelt is a novel IoT-based platform that combines real-time collection of sensor data, load data, and operator input in a dedicated interface, and a very efficient physical model of the melting process to provide on-line guidance to execute operations at optimal timings while detecting furnace issues and improving operator safety. Integrated into the daily operations of two furnaces of 30 and 70 tonnes capacity for periods of 16 and 6\u00a0months, respectively, the system has yielded an increase of productivityProductivity of up to 12% and a reduction of gas consumption of about 11%. SmartMelt successfully detects in real-time deviations of burners performance while also monitoring and recording delays influenced by external factors.", 
    "editor": [
      {
        "familyName": "Eskin", 
        "givenName": "Dmitry", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-030-92529-1_94", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-030-92528-4", 
        "978-3-030-92529-1"
      ], 
      "name": "Light Metals 2022", 
      "type": "Book"
    }, 
    "keywords": [
      "melting process", 
      "burner performance", 
      "such furnaces", 
      "real-time deviation", 
      "reverberatory furnace", 
      "aluminum scrap", 
      "process optimization", 
      "ton capacity", 
      "gas consumption", 
      "furnace", 
      "load data", 
      "operator safety", 
      "IoT-based platform", 
      "physical model", 
      "sensor data", 
      "real-time collection", 
      "operator input", 
      "efficient physical models", 
      "daily operations", 
      "operation", 
      "dedicated interface", 
      "scrap", 
      "line guidance", 
      "operational guidance", 
      "gas", 
      "interface", 
      "tons", 
      "process", 
      "optimization", 
      "digital tools", 
      "efficiency", 
      "performance", 
      "consumption", 
      "platform", 
      "capacity", 
      "input", 
      "system", 
      "deviation", 
      "model", 
      "reduction", 
      "detects", 
      "guidance", 
      "issues", 
      "delay", 
      "external factors", 
      "increase", 
      "safety", 
      "data", 
      "tool", 
      "collection", 
      "decisions", 
      "productivityProductivity", 
      "factors", 
      "timing", 
      "period", 
      "years", 
      "optimal timing", 
      "months"
    ], 
    "name": "Aluminium Melting Process Optimization with SmartMelt, a Digital Tool for Real-Time Operational Guidance", 
    "pagination": "713-722", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1145300449"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-030-92529-1_94"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-030-92529-1_94", 
      "https://app.dimensions.ai/details/publication/pub.1145300449"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-11-24T21:16", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/chapter/chapter_34.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-3-030-92529-1_94"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-92529-1_94'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-92529-1_94'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-92529-1_94'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-030-92529-1_94'


 

This table displays all metadata directly associated to this object as RDF triples.

147 TRIPLES      22 PREDICATES      82 URIs      75 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-030-92529-1_94 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nf12fdab6e12e404a82830fb79bd8a231
4 schema:datePublished 2022-02-05
5 schema:datePublishedReg 2022-02-05
6 schema:description Every year, about 70 million tonnes of Aluminium (Al) scrap is remelted worldwide in gas fired reverberatory furnaces. The efficiency of the melting process in such furnaces is strongly influenced by human-driven decisions and some furnace issues. SmartMelt is a novel IoT-based platform that combines real-time collection of sensor data, load data, and operator input in a dedicated interface, and a very efficient physical model of the melting process to provide on-line guidance to execute operations at optimal timings while detecting furnace issues and improving operator safety. Integrated into the daily operations of two furnaces of 30 and 70 tonnes capacity for periods of 16 and 6 months, respectively, the system has yielded an increase of productivityProductivity of up to 12% and a reduction of gas consumption of about 11%. SmartMelt successfully detects in real-time deviations of burners performance while also monitoring and recording delays influenced by external factors.
7 schema:editor N63057bef1aa843a1b0dbbc5fc8869ef1
8 schema:genre chapter
9 schema:isAccessibleForFree false
10 schema:isPartOf Nc6d0f1cc842e4fae8d19ca5e9c10f210
11 schema:keywords IoT-based platform
12 aluminum scrap
13 burner performance
14 capacity
15 collection
16 consumption
17 daily operations
18 data
19 decisions
20 dedicated interface
21 delay
22 detects
23 deviation
24 digital tools
25 efficiency
26 efficient physical models
27 external factors
28 factors
29 furnace
30 gas
31 gas consumption
32 guidance
33 increase
34 input
35 interface
36 issues
37 line guidance
38 load data
39 melting process
40 model
41 months
42 operation
43 operational guidance
44 operator input
45 operator safety
46 optimal timing
47 optimization
48 performance
49 period
50 physical model
51 platform
52 process
53 process optimization
54 productivityProductivity
55 real-time collection
56 real-time deviation
57 reduction
58 reverberatory furnace
59 safety
60 scrap
61 sensor data
62 such furnaces
63 system
64 timing
65 ton capacity
66 tons
67 tool
68 years
69 schema:name Aluminium Melting Process Optimization with SmartMelt, a Digital Tool for Real-Time Operational Guidance
70 schema:pagination 713-722
71 schema:productId N1ed22885baec4927bb10055896371948
72 Nd24168e612414fd8a49a6f0031e710b3
73 schema:publisher Nc4596f6dd859410a9cfe48096e50e083
74 schema:sameAs https://app.dimensions.ai/details/publication/pub.1145300449
75 https://doi.org/10.1007/978-3-030-92529-1_94
76 schema:sdDatePublished 2022-11-24T21:16
77 schema:sdLicense https://scigraph.springernature.com/explorer/license/
78 schema:sdPublisher N8d76dbf09e794bdb8148b25678f9926e
79 schema:url https://doi.org/10.1007/978-3-030-92529-1_94
80 sgo:license sg:explorer/license/
81 sgo:sdDataset chapters
82 rdf:type schema:Chapter
83 N1ed22885baec4927bb10055896371948 schema:name doi
84 schema:value 10.1007/978-3-030-92529-1_94
85 rdf:type schema:PropertyValue
86 N2914a4c70c4e45508ec1970c1b833e6f rdf:first sg:person.012746010777.26
87 rdf:rest N32ce2e712e454475ae12abb274bbaa0a
88 N32ce2e712e454475ae12abb274bbaa0a rdf:first sg:person.012117711513.23
89 rdf:rest rdf:nil
90 N35ddbaefeab14bebaa251de0fe9716af schema:familyName Eskin
91 schema:givenName Dmitry
92 rdf:type schema:Person
93 N63057bef1aa843a1b0dbbc5fc8869ef1 rdf:first N35ddbaefeab14bebaa251de0fe9716af
94 rdf:rest rdf:nil
95 N8d76dbf09e794bdb8148b25678f9926e schema:name Springer Nature - SN SciGraph project
96 rdf:type schema:Organization
97 Nc4596f6dd859410a9cfe48096e50e083 schema:name Springer Nature
98 rdf:type schema:Organisation
99 Nc6d0f1cc842e4fae8d19ca5e9c10f210 schema:isbn 978-3-030-92528-4
100 978-3-030-92529-1
101 schema:name Light Metals 2022
102 rdf:type schema:Book
103 Nd24168e612414fd8a49a6f0031e710b3 schema:name dimensions_id
104 schema:value pub.1145300449
105 rdf:type schema:PropertyValue
106 Nd650f9c187c44139a7b64b324a3a5d93 rdf:first sg:person.013657516157.10
107 rdf:rest Nfb93b5b886de4e0aa6c3b154793f69dc
108 Nf12fdab6e12e404a82830fb79bd8a231 rdf:first sg:person.016322173613.34
109 rdf:rest Nd650f9c187c44139a7b64b324a3a5d93
110 Nfb93b5b886de4e0aa6c3b154793f69dc rdf:first sg:person.010414503013.20
111 rdf:rest N2914a4c70c4e45508ec1970c1b833e6f
112 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
113 schema:name Information and Computing Sciences
114 rdf:type schema:DefinedTerm
115 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
116 schema:name Artificial Intelligence and Image Processing
117 rdf:type schema:DefinedTerm
118 sg:person.010414503013.20 schema:affiliation grid-institutes:None
119 schema:familyName Bertherat
120 schema:givenName M.
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010414503013.20
122 rdf:type schema:Person
123 sg:person.012117711513.23 schema:affiliation grid-institutes:None
124 schema:familyName Salgado Ordorica
125 schema:givenName M. A.
126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012117711513.23
127 rdf:type schema:Person
128 sg:person.012746010777.26 schema:affiliation grid-institutes:None
129 schema:familyName Desbiolles
130 schema:givenName J.-L.
131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012746010777.26
132 rdf:type schema:Person
133 sg:person.013657516157.10 schema:affiliation grid-institutes:None
134 schema:familyName Rappaz
135 schema:givenName M.
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013657516157.10
137 rdf:type schema:Person
138 sg:person.016322173613.34 schema:affiliation grid-institutes:None
139 schema:familyName Rostamian
140 schema:givenName A.
141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016322173613.34
142 rdf:type schema:Person
143 grid-institutes:None schema:alternateName Constellium. Rue de l’industrie 15, Chippis, Switzerland
144 Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland
145 schema:name Constellium. Rue de l’industrie 15, Chippis, Switzerland
146 Novamet. Route de Vallaire 4a, St. Sulpice, Switzerland
147 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...