Performance measurement based on machines data: Systematic literature review
Abstract Industry 4.0 driven by the internet of things (IoT) is changing the way of producing and has been offering smart manufacturing systems with support technologies for the digital transformation of manufacturing plants seeking improvements in productivity, in control over the process, and cust...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-06-01
|
| Series: | IET Collaborative Intelligent Manufacturing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cim2.12051 |
| _version_ | 1818203422709514240 |
|---|---|
| author | Gleison Hidalgo Martins Fernando Deschamps Silvana Pereira Detro Pablo Deivid Valle |
| author_facet | Gleison Hidalgo Martins Fernando Deschamps Silvana Pereira Detro Pablo Deivid Valle |
| author_sort | Gleison Hidalgo Martins |
| collection | DOAJ |
| description | Abstract Industry 4.0 driven by the internet of things (IoT) is changing the way of producing and has been offering smart manufacturing systems with support technologies for the digital transformation of manufacturing plants seeking improvements in productivity, in control over the process, and customisation of production, among others. Due to these technological developments, small and medium‐sized industries have been identified as a weak link in adapting their processes and resources, where they are usually the biggest victims in the transition to industry 4.0. The evidence points out that the excess data inserted in the databases of the manufacturing system of the industries influences the decision‐making process of managers, making the process more complex and dynamic. This research focuses on a systematic literature review to assess how data‐based performance measurements for machines are being handled in the context of industry 4.0. The methodological approach follows the application of the PROKNOW‐C (Knowledge Development Process‐Constructivist) method used to build a Bibliographic Portfolio in a structured way in line with the research theme. The results presented in the Bibliometric Analysis enabled the construction of a performance measurement model based on the sources of the researched articles. |
| first_indexed | 2024-12-12T03:25:06Z |
| format | Article |
| id | doaj.art-846f5a3e4ec94442beb9b77f1942e647 |
| institution | Directory Open Access Journal |
| issn | 2516-8398 |
| language | English |
| last_indexed | 2024-12-12T03:25:06Z |
| publishDate | 2022-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Collaborative Intelligent Manufacturing |
| spelling | doaj.art-846f5a3e4ec94442beb9b77f1942e6472022-12-22T00:40:04ZengWileyIET Collaborative Intelligent Manufacturing2516-83982022-06-0142748610.1049/cim2.12051Performance measurement based on machines data: Systematic literature reviewGleison Hidalgo Martins0Fernando Deschamps1Silvana Pereira Detro2Pablo Deivid Valle3Manufacturing Engineering Graduate Program (PPGEM) Federal University of Paraná (UFPR) Curitiba BrazilManufacturing Engineering Graduate Program (PPGEM) Federal University of Paraná (UFPR) Curitiba BrazilProduction Engineering Department (DEP) Federal University of Paraná (UFPR) Curitiba BrazilManufacturing Engineering Graduate Program (PPGEM) Federal University of Paraná (UFPR) Curitiba BrazilAbstract Industry 4.0 driven by the internet of things (IoT) is changing the way of producing and has been offering smart manufacturing systems with support technologies for the digital transformation of manufacturing plants seeking improvements in productivity, in control over the process, and customisation of production, among others. Due to these technological developments, small and medium‐sized industries have been identified as a weak link in adapting their processes and resources, where they are usually the biggest victims in the transition to industry 4.0. The evidence points out that the excess data inserted in the databases of the manufacturing system of the industries influences the decision‐making process of managers, making the process more complex and dynamic. This research focuses on a systematic literature review to assess how data‐based performance measurements for machines are being handled in the context of industry 4.0. The methodological approach follows the application of the PROKNOW‐C (Knowledge Development Process‐Constructivist) method used to build a Bibliographic Portfolio in a structured way in line with the research theme. The results presented in the Bibliometric Analysis enabled the construction of a performance measurement model based on the sources of the researched articles.https://doi.org/10.1049/cim2.12051connected manufacturingdata analyticsintelligent manufacturingperformance measurement |
| spellingShingle | Gleison Hidalgo Martins Fernando Deschamps Silvana Pereira Detro Pablo Deivid Valle Performance measurement based on machines data: Systematic literature review IET Collaborative Intelligent Manufacturing connected manufacturing data analytics intelligent manufacturing performance measurement |
| title | Performance measurement based on machines data: Systematic literature review |
| title_full | Performance measurement based on machines data: Systematic literature review |
| title_fullStr | Performance measurement based on machines data: Systematic literature review |
| title_full_unstemmed | Performance measurement based on machines data: Systematic literature review |
| title_short | Performance measurement based on machines data: Systematic literature review |
| title_sort | performance measurement based on machines data systematic literature review |
| topic | connected manufacturing data analytics intelligent manufacturing performance measurement |
| url | https://doi.org/10.1049/cim2.12051 |
| work_keys_str_mv | AT gleisonhidalgomartins performancemeasurementbasedonmachinesdatasystematicliteraturereview AT fernandodeschamps performancemeasurementbasedonmachinesdatasystematicliteraturereview AT silvanapereiradetro performancemeasurementbasedonmachinesdatasystematicliteraturereview AT pablodeividvalle performancemeasurementbasedonmachinesdatasystematicliteraturereview |