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Data mining in manufacturing: a review based on the kind of knowledge
In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emer...
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| Format: | Default Article |
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2009
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| Online Access: | https://hdl.handle.net/2134/9795 |
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| _version_ | 1818174714631159808 |
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| author | Alok Choudhary Jennifer Harding Manoj K. Tiwari |
| author_facet | Alok Choudhary Jennifer Harding Manoj K. Tiwari |
| author_sort | Alok Choudhary (1251471) |
| collection | Figshare |
| description | In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques. |
| format | Default Article |
| id | rr-article-9566138 |
| institution | Loughborough University |
| publishDate | 2009 |
| record_format | Figshare |
| spelling | rr-article-95661382009-01-01T00:00:00Z Data mining in manufacturing: a review based on the kind of knowledge Alok Choudhary (1251471) Jennifer Harding (1258389) Manoj K. Tiwari (7197308) Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified Knowledge discovery Data mining Manufacturing Text mining Literature review Mechanical Engineering not elsewhere classified Artificial Intelligence and Image Processing In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques. 2009-01-01T00:00:00Z Text Journal contribution 2134/9795 https://figshare.com/articles/journal_contribution/Data_mining_in_manufacturing_a_review_based_on_the_kind_of_knowledge/9566138 CC BY-NC-ND 4.0 |
| spellingShingle | Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified Knowledge discovery Data mining Manufacturing Text mining Literature review Mechanical Engineering not elsewhere classified Artificial Intelligence and Image Processing Alok Choudhary Jennifer Harding Manoj K. Tiwari Data mining in manufacturing: a review based on the kind of knowledge |
| title | Data mining in manufacturing: a review based on the kind of knowledge |
| title_full | Data mining in manufacturing: a review based on the kind of knowledge |
| title_fullStr | Data mining in manufacturing: a review based on the kind of knowledge |
| title_full_unstemmed | Data mining in manufacturing: a review based on the kind of knowledge |
| title_short | Data mining in manufacturing: a review based on the kind of knowledge |
| title_sort | data mining in manufacturing: a review based on the kind of knowledge |
| topic | Mechanical engineering not elsewhere classified Artificial intelligence not elsewhere classified Knowledge discovery Data mining Manufacturing Text mining Literature review Mechanical Engineering not elsewhere classified Artificial Intelligence and Image Processing |
| url | https://hdl.handle.net/2134/9795 |