Research on Data Generation Method in Cloud Manufacturing Simulation Platform

2017 ◽  
Author(s):  
Chun Zhao ◽  
Lin Zhang
Keyword(s):  
Cloud Manufacturing ◽  
Simulation Platform ◽  
Data Generation ◽  
Manufacturing Environment ◽  
Simulation Data ◽  
Simulation Accuracy ◽  
Manufacturing Simulation ◽  
The Real ◽  
Actual Environment ◽  
Resource Characteristics

Cloud manufacturing simulation platform is used to simulate the collaboration and evolution, which among the resources, services, tasks, participants in cloud manufacturing environment. As an important part of the platform of simulation, simulation data generation method can effectively support the simulation accuracy. Data in cloud manufacturing environment are not completely random, and are closely related to the actual environment and resource characteristics. The workload of traditional random generate method or artificial method is very heavy and cannot completely rebuild the simulation environment. In this paper, Using clustering method to extract characteristics from an actual environment, and then extend the characteristics to generate new simulation data. To build a similar environment to the real environment used in the simulation. The result is shown that compared with the method to generate random data. This method can generate the reference data similar environment, the simulation can reflect the real effect in the process.

Development of the Picking Manipulator Simulation Platform Based on Multi-Domain System

2010 ◽  
Vol 102-104 ◽  
pp. 292-296
Author(s):  
Yin Le Chen ◽  
Xiang Jun Zou ◽  
Hai Xin Zou ◽  
Quan Sun ◽  
Jing Li ◽  
...  
Keyword(s):  
Inverse Kinematics ◽  
Intelligent Design ◽  
Simulation System ◽  
Simulation Platform ◽  
Research Needs ◽  
Motion Simulation ◽  
Motion Model ◽  
Simulation Accuracy ◽  
The Real ◽  
Analysis Tools

In order to reduce the research and experimental cost of hand-picking machine, to make the design of manipulator more reasonable, and to provide more optimized program for the design, an agricultural picking manipulator simulation system based on intelligent design was designed. Firstly ,based on the research needs, to simplify the real picking manipulator under the premise of that the simulation accuracy reach the requirement, the model of picking manipulator had been simplified. Secondly, the finished model was put into EON Studio to build the virtual procedure, and movement properties were added to the manipulator to realize the function of motion simulation. Thirdly, the picking manipulator mathematics motion model of 4 freedoms was established, and the inverse kinematics of the picking manipulator was analyzed by MATLAB analysis tools, and the reverse solution program was written. Finally, Microsoft Visual C++ was used to complete the design of simulation platform, in order to realize the calling of various functions of the manipulator.

Agent-based simulation platform for cloud manufacturing

2017 ◽  
Vol 08 (03) ◽  
pp. 1742001 ◽  
Author(s):  
Chun Zhao ◽  
Lin Zhang ◽  
Yongkui Liu ◽  
Zhiqiang Zhang ◽  
Gengjiao Yang ◽  
...  
Keyword(s):  
Business Models ◽  
Cloud Manufacturing ◽  
Simulation Platform ◽  
Agent Based Simulation ◽  
Manufacturing Environment ◽  
Agent Based ◽  
Open Environment ◽  
Platform Architecture ◽  
Key Technologies

Cloud manufacturing is a new manufacturing paradigm which creates an open environment for transactions among the enterprises. Research on transaction modes and regularities in a cloud manufacturing environment is important for promoting the applications of cloud manufacturing. To this end, we design and implement a simulation platform according to the typical transaction processes of enterprises in the cloud manufacturing environment. In the simulation platform, enterprises are encapsulated into Service Agents, and thus the activities of service agents can be used to describe enterprise behaviors. By defining different rules, simulations for different business models can be conducted. Detailed descriptions of the platform architecture, functions, and key technologies are presented. The feasibility of the simulation platform is verified through a case study.

Trust Model Based on Feedback Evaluation in Cloud Manufacturing Environment

2011 ◽  
Vol 308-310 ◽  
pp. 1740-1745 ◽  
Author(s):  
Xiao Lan Xie ◽  
Liang Liu ◽  
Ying Zhong Cao
Keyword(s):  
Cloud Manufacturing ◽  
Trust Model ◽  
Human Society ◽  
Manufacturing Environment ◽  
Trust Mechanism ◽  
Model Based ◽  
Service Behavior ◽  
Relationship Of ◽  
Dynamic Adaptability ◽  
Feedback Evaluation

Aiming at the existing trust issues under manufacturing environment. This paper proposes a trust model based on feedback evaluation, TMBFCM, from the characteristics of human of trust relationship of human society. The model proposed a set of evaluation indicators of cloud manufacturing services properties, introduced the dynamic trust mechanism for attenuation by time,established the service which cloud manufacturing services providers provided and the feedback evaluation and incentive mechanism given by the user of cloud manufacturing service, improved the dynamic adaptability of the model. The results show that, compared with the existing trust model, the evaluation results are closer to the true service behavior of cloud manufacturing services provider, it can resist all kinds of malicious attacks acts effectively, demonstrated good robustness and recognition.

An OSGi-Based Adaptation Access of Machine Tools in the Cloud Manufacturing Environment

2021 ◽  
Author(s):  
Xiaobin Li ◽  
Chao Yin
Keyword(s):  
Information Acquisition ◽  
Machine Tools ◽  
Universal Access ◽  
Cloud Manufacturing ◽  
Manufacturing Environment ◽  
Access Method ◽  
Manufacturing Enterprises ◽  
Cloud Application ◽  
Key Enabling Technologies ◽  
Manufacturing Mode

Abstract Machine tools (MTs) are the core manufacturing resources for discrete manufacturing enterprises. In the cloud manufacturing environment, MTs are massive, heterogeneous, widely dispersed and highly autonomous, which makes it difficult for cloud manufacturing mode to be deeply applied to support the networked collaboration operation among manufacturing enterprises. Realizing universal access and cloud application of various MTs is an essential prerequisite to solve the above problem. In this paper, an OSGi-based adaptation access method of MTs is proposed. First, the MTs information description model in the cloud manufacturing environment is built. Then, an OSGi-based adaptation access framework of MTs is constructed, and key enabling technologies, including machine tool information acquisition and processing, Bundle and Subsystem construction, are studied. Finally, an application case is conducted to verify the effectiveness and feasibility of the proposed method.

scholarly journals Application of Extreme Learning Machine in GPS Positioning Process

2018 ◽  
Vol 176 ◽  
pp. 01034
Author(s):  
Chengxin Li ◽  
Jing Peng ◽  
Lv Zhicheng ◽  
Mengli Wang ◽  
Gang Ou
Keyword(s):  
Extreme Learning Machine ◽  
Experimental Simulation ◽  
Data Generation ◽  
Simulation Experiments ◽  
Simulation Data ◽  
Gps Positioning ◽  
Network Training ◽  
Generation Network ◽  
Network Prediction ◽  
Learning Machine

In the positioning process of GPS, the linear least squares algorithm and Kalman filtering algorithm are widely used but still have shortcomings. Application of extreme learning machine in this area is proposed in this paper, which breaks through the limitations of the traditional method of positioning based on mathematical models. Two simulation experiments of ELM in GPS positioning process are presented in this paper while the latter is a supplement to the former. Each one contains three phases, including simulation data generation, network training and network prediction, each of which is considered carefully. The feasibility of extreme learning machine is verified through experimental simulation. A more accurate positioning result can be obtained.

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