A multiple view product model for reflector and lens in automotive headlamps with reconfigurable tooling for manufacture

2011 ◽  
Vol 3 (2) ◽  
pp. 138
Author(s):  
Haris Naduthodi ◽  
Prakasan Kalakkath
Keyword(s):  
Product Model ◽  
Multiple View

scholarly journals A Collaborative Framework for Integrated Part and Assembly Modeling

2002 ◽  
Vol 2 (4) ◽  
pp. 256-264 ◽  
Author(s):  
Rafael Bidarra ◽  
Niels Kranendonk ◽  
Alex Noort ◽  
Willem F. Bronsvoort
Keyword(s):  
Feature Modeling ◽  
Product Modeling ◽  
Product Model ◽  
Team Members ◽  
Assembly Modeling ◽  
Distributed Development ◽  
Assembly Design ◽  
Multiple View ◽  
Actual Design ◽  
Collaborative Sessions

An ideal product modeling system should support both part modeling and assembly modeling, instead of just either of them as is the case in most current CAD systems. A good basis for such integration is multiple-view feature modeling, as it allows focusing on different aspects of the product, while at the same time maintaining consistency of all model views. This paper presents a framework that supports synchronous collaborative sessions via Internet, among members of a distributed development team, with such a modeling system. The framework provides facilities for creating a hierarchical product structure, with single and compound components, and meanwhile assigning tasks to team members. The actual design of a single component is supported by a web-client specialized in part design, whereas the specification of assembly relations among components is supported by a web-client specialized in assembly design. All clients make use of the same server, which runs a multiple-view feature modeling system and maintains the complete product model, guaranteeing consistency of the part design and the assembly design views.

scholarly journals Coupling Engineering Knowledge With Product Design Knowledge by the Means of Multiple View Product Model

2012 ◽  
Author(s):  
Golnoosh Rasoulifar ◽  
Guy Prudhomme ◽  
Daniel Brissaud
Keyword(s):  
Product Development ◽  
Product Design ◽  
Design Knowledge ◽  
Product Model ◽  
Engineering Knowledge ◽  
Multiple View ◽  
Collaborative Tool ◽  
Development Processes ◽  
Product Development Processes

Product design involves a multitude of actors who have complementary knowledge and responsibility about the product under development. Coupling together their views-points, particularly these of product designers and engineering designers in the upstream phases of the design, has the objectives to make the collaboration easier and to improve the product from both of their expertises. The Product/Process multi-view model is a collaborative tool which supports engineering designers during product development processes. It allows the structuring and tracing of relative knowledge of engineering designers on the product. We make the assumption that Product/Process multi-view model could also be used to create relationships with the product designer’s representation. The paper deals with this product model and illustrates the possible connection between engineering knowledge and product design knowledge.

Automatic Model Adjustment in Form Feature Conversion

1999 ◽  
Author(s):  
Alex Noort ◽  
Willem F. Bronsvoort
Keyword(s):  
Product Development ◽  
Feature Model ◽  
Development Phase ◽  
Product Model ◽  
Multiple View ◽  
Feature Modelling ◽  
Model Adjustment ◽  
Feature Conversion ◽  
Form Feature ◽  
New View

Abstract A problem with multiple-view form feature modelling is that, sometimes, a feature model cannot be derived for some view of a product. This indicates that the product, as it is, is not appropriate seen from the product development phase related to that view. In such a case, the product model should be adjusted such that a feature model for the view becomes possible. A method is presented in which, if possible, the product model is automatically adjusted. The adjustment is based on information on the importance of properties of the model, and on information on the dependencies between the shape faces. After the model has been adjusted, a feature model of the new view is derived.

PENGEMBANGAN MEDIA VIDEO PEMBELAJARAN RIAS KARAKTER PADA PROGRAM STUDI PENDIDIKAN TATA RIAS

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Irmiah Nurul Rangkuti ◽  
Harun Sitompul ◽  
Naeklan Simbolon
Keyword(s):  
Student Learning ◽  
Learning Outcomes ◽  
Student Learning Outcomes ◽  
University Education ◽  
State University ◽  
Product Model ◽  
Significance Level ◽  
Material Development ◽  
Learning Development ◽  
Media Learning

Abstrak: Penelitian ini bertujuan untuk: (1) menghasilkan media video pembelajaran rias karakter yang layak digunakan, mudah dipelajari mahasiswa dan dapat dipakai untuk pembelajaran individual, (2) mengetahui keefektivitasan media video pembelajaran rias karakter yang dikembangkan pada materi rias karakter. Penelitian pengembangan yang menggunakan model produk Borg dan Gall yang dipadu dengan model pengembangan pembelajaran Dick dan Carey. Hasil penelitian menunjukkan: (1) media video pembelajaran layak digunakan dalam pembelajaran rias karakter pada program studi pendidikan tata arias universitas negeri medan, (2) terdapat perbedaan yang signifikan antara hasil belajar mahasiswa yang dibelajarkan dengan menggunakan media video pembelajaran rias karakter dengan hasil belajar mahasiswa yang dibelajarkan dengan menggunakan media belajar buku teks. Hal ini ditunjukkan dengan hasil pengolahan data (thitung=3,285 )pada taraf signifikansi ɑ = 0,05 dengan dk 56 diperoleh (ttabel = 1,67 ), sehingga (thitung > ttabel), efektivitas penggunaan media video pembelajaran rias karakter = 80,46%. Hasil belajar kelompok mahasiswa yang dibelajarkan tanpa menggunakan media video pembelajaran rias karakter sebesar 71,72%. Dari data ini membuktikan bahwa penggunaan media video pembelajaran rias karakter lebih efektif dalam meningkatkan kompetensi dan pengetahuan mahasiswa pada pembelajaran rias karakter dari pada tanpa menggunakan media video pembelajaran. Kata Kunci: media video pembelajaran, rias karakte, pendidikan tata rias Abstract: This study aims to: (1) produce a suitable use of character makeup learning video media, easy for students to learn and can be used for individual learning, (2) to find out the effectiveness of media character makeup learning videos developed in character makeup material. Development research using the Borg and Gall product model combined with the learning development model of Dick and Carey. The results of the study showed: (1) learning video media is feasible to use in character makeup learning in the field state university education education program, (2) there are significant differences between student learning outcomes learned using the character makeup video learning media with student learning outcomes which was learned by using media learning textbooks. This is indicated by the results of processing data (tcount = 3.285) at the significance level ɑ = 0.05 with dk 56 obtained  (ttable = 1.67), so that (tcount> t table), effectiveness of using media character makeup learning videos = 80.46%. The learning outcomes of the group of students who were taught without using the character makeup learning video media amounted to 71.72%. From these data prove that the use of character makeup learning video media is more effective in increasing students' competence and knowledge in character makeup learning than without using learning video media. Keywords: learning video media, character makeup, makeup education

DECISION-MAKING ON INVESTMENT OF IT-INNOVATION BASED ON FUZZY EXPERT INFORMATION

2018 ◽  
pp. 103-111
Author(s):  
Olga Olegovna Eremenko ◽  
Lyubov Borisovna Aminul ◽  
Elena Vitalievna Chertina
Keyword(s):  
Decision Making ◽  
Individual Characteristics ◽  
Production Model ◽  
Investment Management ◽  
It Projects ◽  
Product Model ◽  
Project Cost ◽  
Reasoning System ◽  
Managerial Decisions ◽  
The Individual

The subject of the research is the process of making managerial decisions for innovative IT projects investing. The paper focuses on the new approach to decision making on investing innovative IT projects using expert survey in a fuzzy reasoning system. As input information, expert estimates of projects have been aggregated into six indicators having a linguistic description of the individual characteristics of the project type "high", "medium", and "low". The task of decision making investing has been formalized and the term-set of the output variable Des has been defined: to invest 50-75% of the project cost; to invest 20-50% of the project cost; to invest 10-20% of the project cost; to send the project for revision; to turn down investing project. The fuzzy product model of making investment management decisions has been developed; it adequately describes the process of investment management. The expediency of using constructed production model on a practical example is shown.

scholarly journals Neural methods for effective, efficient, and exposure-aware information retrieval

2021 ◽  
Vol 55 (1) ◽  
pp. 1-2
Author(s):  
Bhaskar Mitra
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Large Scale ◽  
Web Search ◽  
Real Life ◽  
Inverted Index ◽  
Information Need ◽  
Product Model ◽  
Performance Improvements ◽  
Deep Model

Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion.

Sign in / Sign up

Export Citation Format

Share Document