Data and knowledge modeling for design–process planning integration of sheet metal components

Ramana, K. V.; Rao, P. Venkateswara

doi:10.1023/b:jims.0000037711.00532.38

Cited by 26 publications

(17 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These intermediate state workpiece models are referred to as in-process model. In the full three-dimensional digital process planning, the three-dimensional process model as a carrier of the process information, eventually guides the parts' formatting [4].…”

Section: The Concept Related With In-process Model and Idea Of Currenmentioning

confidence: 99%

Technology of WAVE and Feature Cutter volume of manufacturing

Jialiang¹,

Chen²,

Xu³

et al. 2016

MATEC Web of Conferences

View full text Add to dashboard Cite

Abstract.A forward and automatic method for in-process model generation is proposed and integrated with three-dimensional computer aided process planning (CAPP) system. The method based on feature cutter volume of manufacturing drives the in-process model to evolve from blank to part, which is coincident with the manufacturing process and ideology of process design. At the same time, technology of What-if Alternative Value Engineering (WAVE) is implanted in the generation to establish the relationship of in-process models, which supports function of the automatic update for models. The paper introduces a theory of the solution to demonstrate the connection between manufacture feature and feature cutter volume, and detailedly presents the technological process in applying the WAVE technology. Examples are completed in a commercial CAPP system to illustrate the feasibility of this approach.

show abstract

Section: The Concept Related With In-process Model and Idea Of Currenmentioning

confidence: 99%

Technology of WAVE and Feature Cutter volume of manufacturing

Jialiang¹,

Chen²,

Xu³

et al. 2016

MATEC Web of Conferences

View full text Add to dashboard Cite

show abstract

“…On the conceptual level, data and knowledge models are integrated into the design and process planning of sheet metal components [14]. The design data model consists of a classification of forming features; the design knowledge model comprises rules to determine forming feature attributes and the associated forming operations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Hence, it is necessary to identify important attributes which are going to influence the estimated values and are required for the downstream processes. Based on [12,14,22], typical sheet metal forming features and operations can be hierarchically classified as illustrated in Fig. 3.…”

Section: B Data Model For Sheet Metal Forming Processmentioning

confidence: 99%

Cost estimation of automotive sheet metal components using knowledge-based engineering and case-based reasoning

Karadgi

Müller

Metz

et al. 2009

2009 IEEE International Conference on Industrial Engineering and Engineering Management

View full text Add to dashboard Cite

Responding quickly to a customer's request with a sufficiently precise offer is one of the challenges faced by almost every manufacturing enterprise. Currently, necessary information is passed from department to department and in many cases this information is waiting to be processed. Further, number of offers that are converted into orders is small making the process of preparing an offer relatively costly. Research has been carried out to automatically determine process plans and estimate cost of simple sheet metal components. Unfortunately, this research has not been extended to simultaneously determine process plan and cost of complex deep drawn components. To overcome these drawbacks and to substantially improve the efficiency and precision of the time consuming process of offer preparation, a new methodology is presented which utilizes knowledge-based engineering and case-based reasoning. Inputs obtained to create an offer can be used to generate basic tool structure for the downstream processes.Keywords -Case-based reasoning, cost estimation, deep drawn sheet metal component, knowledge-based engineering 978-1-4244-4870-8/09/$26.00 ©2009 IEEE

show abstract

“…Tremendous effort has been put into developing an automated process planner as documented in a number of past studies. Those works evolved around feature recognition [12][13][14][15][16][17][18], knowledge representation [19][20][21][22][23][24][25] and inference engine [26,27], and integration of process planning, and upstream or downstream processes [28,29]. Some researchers applied different methods/technologies such as OPPS-PRI 2.0 system [30], genetic algorithms (GA) [31][32][33][34][35][36], imperialist competitive algorithm [37], energy-efficient oriented method [38], neural network-based system [39][40][41], fuzzy set theory/fuzzy logic method [39,42,43], agent-based methodology [44,45], Internet-based technology [46,47], functional blocks [48,49], Petri net model [50] and STEP-compliant method [51][52][53][54], just to name a few, f...…”

Section: Introductionmentioning

confidence: 99%