Model for Developing a Feature Recogntion System for A Reconfigurable Bending Press Machine

E. Murena, K. Mpofu, J. Trimble, N. Gwangwava

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

Sheet metal products are often designed without a systematic consideration of downstream product development requirements, such as process planning, manufacturability, production scheduling and manufacturing optimization. This can often result in a lot of expensive and time consuming reworks. Consequently, it affects the quality, cost and delivery time of the product. In this paper, a framework for developing a web - based feature recognition system (FRS) has been proposed to recognise bending features on a reconfigurable bending press machine (RBPM). The research explores the current literature and design approaches used to develop feature recognition systems in the current manufacturing industries. This model will help to offer a suitable method for designing a web based feature recognition system for sheet metal bending using RBPMs. This model will be applied to feature recognition systems in other manufacturing industries. The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model. The proposed models will aid the designer right at the design stage with useful design and the feature recognition system. The designer will be able to relate process technology to product design instead of specifying the geometric definition alone. Design of these models will provide a more convenient design environment and an easier way to integrate CAD/CAM activities. After developing the model the designer will be able to use the CAD software to develop patterns, interpret drawings and transfer dimensions to sheet materials and sections to meet the required specification. © 2017 Published by Elsevier B.V.
Original languageEnglish
Pages533-538
Number of pages6
DOIs
Publication statusPublished - 2017

Fingerprint

Sheet metal
Computer aided design
Process planning
Computer aided manufacturing
Product design
Product development
Industry
Information systems
Scheduling
Specifications
Costs

Cite this

@conference{cf6588ce580b4171ad634f043c4b00c3,
title = "Model for Developing a Feature Recogntion System for A Reconfigurable Bending Press Machine",
abstract = "Sheet metal products are often designed without a systematic consideration of downstream product development requirements, such as process planning, manufacturability, production scheduling and manufacturing optimization. This can often result in a lot of expensive and time consuming reworks. Consequently, it affects the quality, cost and delivery time of the product. In this paper, a framework for developing a web - based feature recognition system (FRS) has been proposed to recognise bending features on a reconfigurable bending press machine (RBPM). The research explores the current literature and design approaches used to develop feature recognition systems in the current manufacturing industries. This model will help to offer a suitable method for designing a web based feature recognition system for sheet metal bending using RBPMs. This model will be applied to feature recognition systems in other manufacturing industries. The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model. The proposed models will aid the designer right at the design stage with useful design and the feature recognition system. The designer will be able to relate process technology to product design instead of specifying the geometric definition alone. Design of these models will provide a more convenient design environment and an easier way to integrate CAD/CAM activities. After developing the model the designer will be able to use the CAD software to develop patterns, interpret drawings and transfer dimensions to sheet materials and sections to meet the required specification. {\circledC} 2017 Published by Elsevier B.V.",
author = "E. Murena and K. Mpofu and J. Trimble and N. Gwangwava",
note = "Export Date: 18 June 2018",
year = "2017",
doi = "10.1016/j.procir.2017.04.029",
language = "English",
pages = "533--538",

}

Model for Developing a Feature Recogntion System for A Reconfigurable Bending Press Machine. / Murena, E.; Mpofu, K.; Trimble, J.; Gwangwava, N.

2017. 533-538.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Model for Developing a Feature Recogntion System for A Reconfigurable Bending Press Machine

AU - Murena, E.

AU - Mpofu, K.

AU - Trimble, J.

AU - Gwangwava, N.

N1 - Export Date: 18 June 2018

PY - 2017

Y1 - 2017

N2 - Sheet metal products are often designed without a systematic consideration of downstream product development requirements, such as process planning, manufacturability, production scheduling and manufacturing optimization. This can often result in a lot of expensive and time consuming reworks. Consequently, it affects the quality, cost and delivery time of the product. In this paper, a framework for developing a web - based feature recognition system (FRS) has been proposed to recognise bending features on a reconfigurable bending press machine (RBPM). The research explores the current literature and design approaches used to develop feature recognition systems in the current manufacturing industries. This model will help to offer a suitable method for designing a web based feature recognition system for sheet metal bending using RBPMs. This model will be applied to feature recognition systems in other manufacturing industries. The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model. The proposed models will aid the designer right at the design stage with useful design and the feature recognition system. The designer will be able to relate process technology to product design instead of specifying the geometric definition alone. Design of these models will provide a more convenient design environment and an easier way to integrate CAD/CAM activities. After developing the model the designer will be able to use the CAD software to develop patterns, interpret drawings and transfer dimensions to sheet materials and sections to meet the required specification. © 2017 Published by Elsevier B.V.

AB - Sheet metal products are often designed without a systematic consideration of downstream product development requirements, such as process planning, manufacturability, production scheduling and manufacturing optimization. This can often result in a lot of expensive and time consuming reworks. Consequently, it affects the quality, cost and delivery time of the product. In this paper, a framework for developing a web - based feature recognition system (FRS) has been proposed to recognise bending features on a reconfigurable bending press machine (RBPM). The research explores the current literature and design approaches used to develop feature recognition systems in the current manufacturing industries. This model will help to offer a suitable method for designing a web based feature recognition system for sheet metal bending using RBPMs. This model will be applied to feature recognition systems in other manufacturing industries. The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model. The proposed models will aid the designer right at the design stage with useful design and the feature recognition system. The designer will be able to relate process technology to product design instead of specifying the geometric definition alone. Design of these models will provide a more convenient design environment and an easier way to integrate CAD/CAM activities. After developing the model the designer will be able to use the CAD software to develop patterns, interpret drawings and transfer dimensions to sheet materials and sections to meet the required specification. © 2017 Published by Elsevier B.V.

U2 - 10.1016/j.procir.2017.04.029

DO - 10.1016/j.procir.2017.04.029

M3 - Paper

SP - 533

EP - 538

ER -