A process planning system with feature based neural network search strategy for aluminum extrusion die manufacturing

Aluminum extrusion die manufacturing is a critical task for productive improvement and increasing potential of competition in aluminum extrusion industry. It causes to meet the efficiency not only consistent quality but also time and production cost reduction. Die manufacturing consists first of die design and process planning in order to make a die for extruding the customer's requirement products. The efficiency of die design and process planning are based on the knowledge and experience of die design and die manufacturer experts. This knowledge has been formulated into a computer system called the knowledge-based system. It can be reused to support a new die design and process planning. Such knowledge can be extracted directly from die geometry which is composed of die features. These features are stored in die feature library to be prepared for producing a new die manufacturing. Die geometry is defined according to the characteristics of the profile so we can reuse die features from the previous similar profile design cases. This paper presents the CaseXpert Process Planning System for die manufacturing based on feature based neural network technique. Die manufacturing cases in the case library would be retrieved with searching and learning method by neural network for reusing or revising it to build a die design and process planning when a new case is similar with the previous die manufacturing cases. The results of the system are dies design and machining process. The system has been successfully tested, it has been proved that the system can reduce planning time and respond high consistent plans

DFM synthesis approach based on product-process interface modelling. Application to the peen forming process.

Engineering design approach are curently CAD-centred design process. Manufacturing information is selected and assessed very late in the design process and above all as a reactive task instead of being proactive to lead the design choices. DFM appraoches are therefore assesment methods that compare several design alternatives and not real design approaches at all. Main added value of this research work concerns the use of a product-process interface model to jointly manage both the product and the manufacturing data in a proactive DFM way. The DFM synthesis approach and the interface model are presented via the description of the DFM software platform

DFM synthesis approach based on product-process interface modelling. Application to the peen forming process.

International audienceEngineering design approach are curently CAD-centred design process. Manufacturing information is selected and assessed very late in the design process and above all as a reactive task instead of being proactive to lead the design choices. DFM appraoches are therefore assesment methods that compare several design alternatives and not real design approaches at all. Main added value of this research work concerns the use of a product-process interface model to jointly manage both the product and the manufacturing data in a proactive DFM way. The DFM synthesis approach and the interface model are presented via the description of the DFM software platform

Functional architecture and specifications for Tolerancing Data and Knowledge Management

Part 1: Knowledge ManagementInternational audienceThe paper deals with the Computer-Aided Tolerancing and Product Data Management. It is especially focus on data and knowledge management system to support and improve the tolerancing tasks in product development process. The first part of the paper introduces an overview about the recent developments related to tolerancing supports and data management systems. Based on a literature survey and industrial issues, the second part proposes a functional architecture and specifications of the data and knowledge manage-ment system addressing the numerous needs clarified by tolerancing experts

European-wide Formation and Certification for the Competitive Edge in Integrated Design

Organised by: Cranfield UniversityCompetitive Product Design is more and more linked to mastering the challenge of the complexity and multidisciplinary nature of modern products in an integrated fashion from the very earliest phases of product development. Design Engineers are increasingly confronted with the need to master several different engineering disciplines in order to get a sufficient understanding of a product or service. Industrialists demand for the certification of these skills, as well as for their international recognition and exchangeability. This paper describes the approach that EMIRAcle takes together with the ECQA in order to define and establish job roles, curricula and certifications in the domain of Integrated Engineering on a European level.Mori Seiki – The Machine Tool Compan

Dynamic Learning Organisations Supporting Knowledge Creation for Competitive and Integrated Product Design

Organised by: Cranfield UniversityThis paper shows that learning strategies and a structured approach to turn organisations into learning organisms have a major influence on the success of engineering programs in general, and on integrated design activities in particular. It points out the important relationship between dynamic learning organisations and the successful integrated development of complex mechatronic products using the topical and typical example of safety engineering in automotive development. It points out the key properties of learning organisations and reports about a way in which they have been successfully applied to the showcase example in close collaboration with a car manufacturing company.Mori Seiki – The Machine Tool Compan

Case-based reasoning for adaptive aluminum extrusion die design together with parameters by neural networks

Global Product Development 2011, Part 13, 491-496, DOI: 10.1007/978-3-642-15973-2_50 ISBN 978-3-642-15972-5International audienceNowadays Aluminum extrusion die design is a critical task forimproving productivity which involves with quality, time and cost. Case-Based Reasoning (CBR) method has been successfully applied to support the die design process in order to design a new die by tackling previous problems together with their solutions to match with a new similar problem. Such solutions are selected and modified to solve the present problem. However, the applications of the CBR areuseful onlyretrievingprevious features whereas the critical parameters are missing. In additions, the experience learning to such parameters are limited. This chapter proposes Artificial Neural Network(ANN) to associate the CBR in order to learning previous parameters and predict to the new die design according to theprimitive die modification. The most satisfactory is to accommodate the optimal parameters of extrusion processes

Integration to Face Modern Quality Challenges in Automotive

International audienc