Optimization of Assembly Sequence Plan Using Digital Prototyping and Neural Network. (2016)

• Record Type: Journal Article
• Authors: Dalvi, Santosh D.
• Is Part Of: Procedia technology. Volume 23(2016)
• Page Start: 414
• Page End: 422
• Publication Date: 2016
• Subjects: Assembly -- Sequence -- Digital prototyping -- Hinge Assembly; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.03.045
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Carrying out assembly process planning tasks manually is both time-consuming and requires a lot of effort. To gain an insight into the processes that occur during a design and assembly task, time and motion study methods are utilized in both digital prototyping and assembly sequence programming to carry out the investigation. In addition, a brief investigation has been carried out to examine the time savings of using the virtual tools in comparison with the traditional manual method. The whole process comprised of three steps viz. digital prototyping, assembly representation i.e. assembly part relationships and generating optimized assembly sequence plans. The process resulted in 60% saving in time, 63% saving in assembly cost and 150% improvement in the productivity.