scholarly journals Computer aided design of sequencing problem – the concept of Paint Shop 4.0

Mechanik ◽  
2018 ◽  
Vol 91 (7) ◽  
pp. 529-531
Author(s):  
Jolanta Krystek ◽  
Sara Alszer ◽  
Szymon Bysko
Keyword(s):  
Automotive Industry ◽  
Computer Aided Design ◽  
Industry 4.0 ◽  
Paint Shop ◽  
Actual Structure ◽  
New Approach ◽  
Digital Factory ◽  
Sequencing Problem ◽  
Car Body ◽  
Aided Design

Presented is the concept of paint shop operation for the automotive industry – Paint Shop 4.0, based on the ideas of Industry 4.0 and Digital Factory. A new approach to the issue of car body sequencing, taking into account the actual structure of the paint shop department with buffers, has been presented. In the created application, proprietary car body sequencing algorithms were implemented.

scholarly journals Contemporary aspects of car sequencing problem in a paint shop

Mechanik ◽  
2017 ◽  
Vol 90 (7) ◽  
pp. 527-529 ◽  
Author(s):  
Jolanta Krystek ◽  
Sara Alszer
Keyword(s):  
Production Line ◽  
Paint Shop ◽  
Organization Of Work ◽  
Actual Structure ◽  
New Approach ◽  
Sequencing Problem ◽  
Car Sequencing ◽  
Car Sequencing Problem ◽  
Production Orders ◽  
Industrial Solutions

The article presents a problem of car sequencing from the perspective of the paint shop requirements. The issue of determining production orders depending on a color, on which a body is painted, has been considered in the literature several times. However, the assumptions proposed by scientists simplified greatly the analyzed problem in relation to the existing industrial solutions and requirements. The purpose of conducted analysis is to demonstrate a need for a completely new approach to sequencing problem, taking into account an actual structure of a car production line and organization of work in a paint shop.

Advantages of Implementing Virtual Reality Tools in Design and Technological Preparation of Production

2021 ◽  
pp. 44-52
Author(s):  
V.V. Yakhrichev
Keyword(s):  
Computer Aided Design ◽  
Industry 4.0 ◽  
Industrial Revolution ◽  
Design System ◽  
Data Presentation ◽  
Fourth Industrial Revolution ◽  
Digital Modeling ◽  
Virtual And Augmented Reality ◽  
Aided Design ◽  
Modern Technologies

Along with digital modeling, the key modern technologies include virtual (VR) and augmented (AR) reality, the use of which is a prerequisite for the implementation of the fourth industrial revolution, also known as Industry 4.0. However, at Russian enterprises, these tools have not become widespread yet. The paper analyzes the possibility of using the tools of virtual and augmented reality and introduces the available Russian instruments. Practical examples consider the application in this area of — one of them — the VRConcept system — in detail. The availability of support in the VRConcept system for the data presentation format of the domestic computer-aided design system Compass-3D simplifies its implementation and use at the enterprise.

Computer Implementation of an Optimal Conformal Mapping for Gear Tooth Stress Analysis

1989 ◽  
Vol 111 (2) ◽  
pp. 297-305 ◽  
Author(s):  
M. J. Richard ◽  
D. Pare ◽  
A. Cardou
Keyword(s):  
Conformal Mapping ◽  
Stress Analysis ◽  
Computer Aided Design ◽  
Gear Tooth ◽  
Spur Gear ◽  
Concentrated Load ◽  
New Approach ◽  
Gear Teeth ◽  
Aided Design ◽  
Mapping Theory

This paper describes a computerized version of the complex potential approach which is a comprehensive mathematical model for the stress analysis of spur gear teeth. The entire procedure is a basic application of Hirano’s conformal mapping theory in which laws of elasticity have been combined. The main concepts of the method have been explained in previous publications but the work described herein is an appreciable extension of this relatively new approach. The algorithm is eminently well-suited for computer-aided-design of gear teeth; it serves as the basis for an interactive computer program which can model a gear tooth and can calculate the stresses and displacements within the tooth when subjected to a concentrated load. Results are compared with AGMA’s and other published values.

Computer Aided Automotive Interior Design for Kansei Engineering

2011 ◽  
Vol 130-134 ◽  
pp. 504-507 ◽  
Author(s):  
Li Hong Zhu ◽  
Han Zhao ◽  
Xiao Chen Yin ◽  
Li Jun Zhu ◽  
Liang Zhang
Keyword(s):  
Interior Design ◽  
Automotive Industry ◽  
Computer Aided Design ◽  
Design Parameters ◽  
Kansei Engineering ◽  
Computer Aided ◽  
Quantitative Analysis Method ◽  
Aided Design ◽  
Industry Trends ◽  
Automotive Interior

Nowadays, the development of automotive industry trends more personalized and profuse product alternatives. Kansei Engineering has been applied to interior design for customer satisfaction based on ergonomic technology in the paper. The computer aided design automotive interior system includes two subsystems: one is Computer-aided Sensation Survey Subsystem and the other is Computer-aided Automobile Interior Design Subsystem. Mathematical statistics and quantitative analysis method are adopted to establish quantified relationship between product perceptual image and design parameters.

Curvature Estimation for Metrology of Non-Rigid Parts

2013 ◽  
Author(s):  
Ali Aidibe ◽  
Souheil-Antoine Tahan
Keyword(s):  
Residual Stresses ◽  
Manufacturing Process ◽  
Computer Aided Design ◽  
Cad Model ◽  
New Approach ◽  
Profile Deviation ◽  
Defect Area ◽  
Computer Aided ◽  
Curvature Estimation ◽  
Aided Design

At the end of the manufacturing process, engineers need to know if a manufactured part fits its computer-aided design (CAD) model and how is the amplitude of inherent variation of manufacturing process. Non-rigid parts, at free state condition, may have a significant different form than their CAD model due to gravity loads; residual stresses induced distortion and/or assembly load. Today, a complicated and expensive specialized fixture is needed to conform these parts. To tackle the above challenges, we present in this paper a new approach for metrology of fixtureless non-rigid parts. This approach combines the curvature properties of manufactured parts with the extreme value statistic test as identification method to distinguish profile deviation due to the manufacturing process from part’s deformation due to the flexibility of the part and to determine whether the tolerance fits the CAD model or no. This approach is tested on simulated typical industrial sheet metal giving satisfying results in terms of percentage of errors in defect area and in peak profile deviation estimated.

scholarly journals Designing learning-skills towards industry 4.0

2020 ◽  
Vol 11 (2) ◽  
pp. 150-161
Author(s):  
Giovana del Gaudio ◽  
Craig N. Refugio ◽  
Igor Jurcic ◽  
Valentina Della Corte ◽  
Debra Ferdinand James ◽  
...  
Keyword(s):  
Computer Aided Design ◽  
Industry 4.0 ◽  
Raw Material ◽  
Lifelong Learners ◽  
Material Development ◽  
Value Stream ◽  
Communication Space ◽  
Digital Learners ◽  
Aided Design ◽  
Cultural World

The world is shrinking now more than ever due to new scientific and technological breakthroughs that expand the boundaries of human knowledge, resulting in improvements in transportation, communication, space exploration and educational technologies. Today’s students will compete in a technological, diverse, multi-cultural world and must be prepared to thrive in this futuristic environment. Therefore, it is vital that today’s pedagogy produce lifelong learners, who can succeed in a global pulpit. To ensure our educational technology progresses at the rate demanded by today’s ubiquitous digital learners, we review emerging technologies and traditional teaching methods and propose desirable changes. Future companies will need employees with specific Internet of Things connected additive manufacturing skills across the value stream, including computer-aided design, machine operation, raw material development, robotics and supply chain management; but these are only island of excellence in industry 4.0 and not the consummate requirement of the manufacturing process.Keywords: Industry 4.0, IoT, smart teaching, future skills.

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