Name
Abstract | ||
|---|---|---|
In a continuing quest to decrease the time interval between conceptualisation of a product and its first production, the use of information technology in design, analysis and manufacturing practice has been actively researched. The design engineer designs a part and sends the final design to the manufacturing engineer, who re-interprets the design and plans the manufacturing activities to produce the part. These two sections generally work in isolation from each other, resulting in high lead-time, duplication of data, inconsistent product data and sometimes redesign of a product. Feature recognition is a process of reinterpreting a design model database for automating downstream manufacturing activities. Active research in this field has developed numerous techniques such as syntactic pattern recognition, graph theory, volume decomposition, artificial intelligence and hint-based, and neural network-based systems. This paper presents a critical review of strengths and weaknesses of these approaches. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1080/09511921003642121 | Int. J. Computer Integrated Manufacturing |
Keywords | DocType | Volume |
feature recognition,inconsistent product data,design engineer,machining feature recognition methodology,manufacturing activity,downstream manufacturing activity,syntactic pattern recognition,final design,manufacturing engineer,design model database,manufacturing practice | Journal | 23 |
Issue | ISSN | Citations |
4 | 0951-192X | 7 |
PageRank | References | Authors |
0.51 | 55 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arvind Kumar Verma | 1 | 8 | 0.86 |
| Sunil Rajotia | 2 | 8 | 0.86 |
| VermaArvind Kumar | 3 | 7 | 0.51 |