scholarly journals Intelligent Manufacturing: a Way to Upgrade Manufacturing Industry

2018 ◽  
Vol 439 ◽  
pp. 032020
Author(s):  
Yin Du ◽  
Gengbao Huang
Keyword(s):  
Manufacturing Industry ◽  
Intelligent Manufacturing

Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry
Keyword(s):  
Internet Of Things ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
The Internet ◽  
Resource Assignment ◽  
Industrial Internet Of Things ◽  
Assignment Method ◽  
Industrial Internet

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

The Methods for Increasing of the Efficiency in the Intelligent Assembly Cell

2013 ◽  
Vol 470 ◽  
pp. 729-732 ◽  
Author(s):  
Radovan Holubek ◽  
Roman Ruzarovsky
Keyword(s):  
Manufacturing Industry ◽  
Production Systems ◽  
Process Analysis ◽  
Intelligent Manufacturing ◽  
Time Data ◽  
Flexible Assembly ◽  
Manufacturing Efficiency ◽  
Assembly Cell ◽  
Visualization And Simulation ◽  
Product Assembly

Efficiency of industrial production lines is crucial as it results in an improved production and utilization of available resources. Industry companies are constantly looking for new ways to improve workplace efficiency. Manufacturing industry trends to employ more flexible assembly cells with changes in programs and configurations for robots, and to achieve a high manufacturing efficiency. The various problems inherent in current mechanized product assembly are outlined, and potential organizational, technological, and engineering measures aimed at increasing the efficiency of product assembly are examined. Future developments in automated assembly are predicted. In order to improve the effectiveness of the cell, it is important to recognize measure and reduce losses in the assembly cell. The most effective method is to analyze the OEE (Overall Equipment Effectiveness) of the cell. It is developed design of assembly system under the project an intelligent assembly cell at the Institute of Production Systems and Applied Mechanics where after process running and debugging, based on the process analysis was evaluated, it is necessary to increase the efficiency of the cell. Deployment of monitoring, visualization and simulation are predicted defects that reduce overall system effectiveness. The project is aiming to develop an efficient intelligent manufacturing system integrating real time data collection, simulation, optimization and synthesis.

Bot-X: An AI-based virtual assistant for intelligent manufacturing

2021 ◽  
Vol 17 (1) ◽  
pp. 1-14
Author(s):  
Chen Li ◽  
Hong Ji Yang
Keyword(s):  
Manufacturing Industry ◽  
Design Principle ◽  
Intelligent Manufacturing ◽  
Order Processing ◽  
Architecture Model ◽  
Key Issues ◽  
Recent Trends ◽  
Machine Interface ◽  
Framework System ◽  
Industrial Company

In light of recent trends toward introducing Artificial Intelligence (AI) to enhance the Human Machine Interface (HMI), companies need to identify the key issues of the communication between operator and production machines. Despite the fact that the industrial company starts to introduce chatbots to assist the communication between humans and machines, the virtual assistant (or digital assistant) by using human natural language is still widely required in the manufacturing domain. In this paper, we introduce an AI-based virtual assistant, Bot-X, for the manufacturing industry to handle a variety of complex services, e.g., order processing, production execution. This work expands the idea in three directions. Firstly, we introduce the design motivation of Bot-X, e.g., knowledge boundary in the manufacturing context. Secondly, the design principle of Bot-X is presented, including the framework, system architecture, model architecture, and the core algorithm. Then, three scenarios are presented to test the Bot-X usability and flexibility regarding the manufacturing environment.

scholarly journals An Evaluation of the Yangtze River Economic Belt Manufacturing Industry Level of Intelligentization and Influencing Factors: Evidence from China

2021 ◽  
Vol 13 (16) ◽  
pp. 8913
Author(s):  
Decai Tang ◽  
Luxia Wang ◽  
Brandon J. Bethel
Keyword(s):  
Index System ◽  
Yangtze River ◽  
Manufacturing Industry ◽  
Manufacturing Sector ◽  
Regional Scale ◽  
Intelligent Manufacturing ◽  
Entropy Method ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
The Yangtze River

Over recent decades, the application of artificial intelligence methods in manufacturing has led to new spheres of research such as the Internet of Things, Cyber–Physical Systems, and Cloud Computing and Big Data, leading to the so-called Industry 4.0. However, to date, little research has been geared towards assessing the factors that influence intelligent manufacturing on a regional scale. Addressing this problem, this paper constructs an evaluation index system for the Yangtze River Economic Belt (YREB) intelligent manufacturing sector using eleven years (2008–2018) of provincial panel data. The entropy method is applied to three evaluation criteria, namely intelligent innovation, equipment, and profit, to construct an evaluation index system. An analysis of the results revealed that the level intelligentization of the manufacturing industry of the YREB increases yearly, and that intelligent innovations are notably occurring at a faster rate than profits. Disproportional enterprise returns on investment have occurred, which decreases enterprise motivation to be innovative in the first place. Additionally, it was also observed that FDI, financial development, government intervention, and the level of opening-up were the primary factors modulating regional intelligent manufacturing levels.

scholarly journals CAx Integration and Its Design Application Based on Feature Extension of Sensor Components

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yaohong Tang ◽  
Mengmeng Song ◽  
Shungen Xiao ◽  
Xiangui Liu ◽  
Guoxiang Liang
Keyword(s):  
Manufacturing Industry ◽  
Management Information Systems ◽  
Intelligent Manufacturing ◽  
Sensor Technology ◽  
Framework Structure ◽  
Management Information ◽  
Integration Framework ◽  
Whole Process ◽  
Application Mode ◽  
Effective Path

In order to improve the information and product originality level of intelligent manufacturing industry based on sensor technology, this paper summarizes the current situation of CAx integration based on sensor technology and its design application and analyzes the shortcomings of existing CAx integration, aiming at accurate, complete, timely, and barrier-free transfer of sensor product data and information between CAx system and MRPII/ERP management information system. The concept and information model of feature extension of sensor components oriented to the whole process of sensor intelligent manufacturing is presented. Taking feature extension of sensor components as the integration link, CAx integration framework structure and its design application mode based on feature extension are established, while key technologies and implementation ideas to realize the integration and the design application are put forward, which provides an effective path to realize the sensor integration of CAx and management information systems such as MRPII/ERP.

scholarly journals Key Course Group Construction of Intelligent Manufacturing for Applied

2021 ◽  
Vol 3 (4) ◽  
pp. 110-115
Author(s):  
Zhuqiao Ma
Keyword(s):  
Manufacturing Industry ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
Practical Application ◽  
New Era ◽  
Teaching Content ◽  
Core Courses ◽  
Group Construction ◽  
Technology Foundation

This article mainly expounds the intelligent manufacturing theory basis and technology foundation course group construction in the important role of applied undergraduate professional curriculum system, combining the reform of the new round of intelligent industry, on theoretical knowledge taught content at the same time, the core courses and practical application of the teaching content to construct, and explore the construction conform to the concept of the new era of smart manufacturing key lessons Cheng Qun, the introduction of cognition and reconstruction of the teaching theory, make full use of various platforms to help students better meet the requirements of intelligent manufacturing industry talent.

Research on Evaluation of Intelligent Manufacturing Capability and Layout Superiority of Supply Chain by Big Data Analysis

2022 ◽  
Vol 30 (7) ◽  
pp. 0-0
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Manufacturing Industry ◽  
Cost Model ◽  
Intelligent Manufacturing ◽  
Research On Evaluation ◽  
Manufacturing Capability ◽  
Enterprise Collaboration ◽  
Manufacturing Mode ◽  
Internet Of Things Technology

With the rise of cloud computing, big data and Internet of Things technology, intelligent manufacturing is leading the transformation of manufacturing mode and industrial upgrading of manufacturing industry, becoming the commanding point of a new round of global manufacturing competition. Based on the literature review of intelligent manufacturing and intelligent supply chain, a total factor production cost model for intelligent manufacturing and its formal expression are proposed. Based on the analysis of the model, 12 first-level indicators and 29 second-level indicators of production line, workshop/factory, enterprise and enterprise collaboration are proposed to evaluate the intelligent manufacturing capability of supply chain. This article also further studies the layout superiority and spatial agglomeration characteristics of intelligent manufacturing supply chain, providing useful reference and support for enterprises and policy makers in the decision-making.

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