Cloud manufacturing service combination optimal selection method giving consideration to regional logistics service capability

A technology of service combination and service capability, which is applied in the optimal field of cloud manufacturing service combination considering regional logistics service capability

Inactive Publication Date: 2018-01-16
袁宏斌
View PDF3 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The networked manufacturing model has become a new choice for the manufacturing industry, but there are many problems in the networked manufacturing models such as manufac

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Cloud manufacturing service combination optimal selection method giving consideration to regional logistics service capability
  • Cloud manufacturing service combination optimal selection method giving consideration to regional logistics service capability
  • Cloud manufacturing service combination optimal selection method giving consideration to regional logistics service capability

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0181] The present invention takes the logistics cloud service in a certain region as an example to illustrate the method for determining the weight of the service index by using the neural network.

[0182] Step 1 Determine the input and output matrix of the neural network

[0183] The input and output matrices of the neural network are the QoS index description and service comprehensive score of the service sample respectively.

[0184] Suppose there are 10 logistics cloud service samples S in a region R A -S J , its QoS index description and the comprehensive score of each service sample given by evaluation experts are shown in Table 2,

[0185] Table 2 QoS indicators and comprehensive scores of regional R logistics cloud service samples

[0186] S

C

T

P sreq

P spro

P dpro

P dint

P fpro

P fcor

G

S A

13.4

23

0.43

0.72

0.74

0.88

0.52

0.48

7.4

S B

12.6

30

0.57

0.61

0.78

0.83...

Embodiment 2

[0202] The present invention takes the processing of a certain equipment part as an example to illustrate the optimization process of cloud manufacturing service combination from the candidate service set.

[0203] Assuming that on the cloud manufacturing service platform, the user submits a processing request for a certain equipment part, the cloud manufacturing platform will automatically decompose the manufacturing demand into five manufacturing sub-parts based on the historical business process data in the manufacturing field and the cloud manufacturing services that the platform can provide. Task, 3 logistics sub-tasks, its business logic structure is as follows Figure 7 shown. The set of candidate cloud manufacturing services and logistics cloud services are shown in Table 4 and Table 5.

[0204] Table 4 Cloud manufacturing service candidate service set

[0205]

[0206] Table 5 Logistics cloud service candidate service set

[0207]

[0208]

[0209] In this...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a cloud manufacturing service combination optimal selection method giving consideration to regional logistics service capability, and the method comprises the steps: S1, constructing a logistics cloud service evaluation system framework and describing a logistics cloud service QoS index; S2, determining an index weight through a neural network; S3, calculating a combined service comprehensive index through a subjective and objective comprehensive weight method; S4, solving a cloud manufacturing service combination optimal selection problem through a genetic algorithm. The invention aims at carrying out the cloud manufacturing service combination based on the QoS comprehensive index, and an index weight employed in the combination process is determined through the neural network. Moreover, the logistics cloud service and regional logistics capability are considered in the combination process, thereby enabling the obtained comprehensive evaluation index to be moreaccurate and enabling the logistics cloud evaluation to be adaptive.

Description

technical field [0001] The invention relates to the field of information technology; in particular, it relates to a cloud manufacturing service combination optimization method considering regional logistics service capabilities. Background technique [0002] The manufacturing industry occupies an important position in the national economy, and the traditional manufacturing industry is facing great challenges and new opportunities in the information age. The networked manufacturing model has become a new choice for the manufacturing industry, but there are many problems in the networked manufacturing models such as manufacturing grid and agile manufacturing in terms of service model, manufacturing resource sharing and allocation, physical terminal equipment access, and information security. In this context, cloud manufacturing came into being. Cloud manufacturing connects manufacturing resources to the network through embedded, Internet of Things and other technologies, orga...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06Q10/08G06Q10/06H04L29/08
Inventor 袁宏斌
Owner 袁宏斌
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap