Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/11357
Title: DECISION SUPPORT SYSTEM FOR THE SELECTION OF RAPID PROTOTYPING PROCESSES
Authors: Rao, Vennamaneni Venkateshwar
Keywords: MECHANICAL INDUSTRIAL ENGINEERING;DECISION SUPPORT SYSTEM;RAPID PROTOTYPING PROCESSES;SELECTION METHODOLOGY
Issue Date: 2006
Abstract: In this report discussed details of selection methodology for RP processes. Selecting the right prototyping process can be difficult, but it is critical to the success of your product development programs. Picking a solution requires experience, in formation and understanding of a broad set of processes technologies This is a skill that few possess, when large no of processes are available. While some individuals can look at a design and quickly identify the best options, most of us don't have this ability. Often, the selection is based on familiarity and past experience. However, this is not the most. effective way to select a process that delivers a suitable prototype in the time allowed and within the budget constraints. This methodology has considered total 15 processes in the selection process. This includes 5 liquid based RP systems (e.g. SLA, SGC, SOUP, SCS, SOLIFORM), 5 solid based RP systems (e.g. LOM, FDM, MJM, IBM, KINERGY), 5 powdered based RP systems (e.g., DSPC, EOSINT, 3DP, BPM). The proposed methodology uses a ranking strategy. • In the present report CARPPSS software is used to implement RP processes in the form of interactive, user friendly software. The software has been developed using Microsoft Access and Visual Basic. The developed software collects the required input information through interactively through pull down menus. This includes information about the nature of work material, part size, operational requirements, economical aspects and environmental aspects. Material based reclassification, part size reclassification, reclassification based on operational requirements and of economic and environmental aspects reclassification was used to development of CARPPSS. In this report considered two real life examples, for selection methodology.
URI: http://hdl.handle.net/123456789/11357
Other Identifiers: M.Tech
Research Supervisor/ Guide: Jain, N. K.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (MIED)

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