Component mounting and dispatching optimization method for chip mounter on basis of quantum neural network

A technology of quantum nerves and optimization methods, which is applied to the biological neural network model and the assembly of printed circuits with electrical components, can solve problems such as the complexity of the placement scheduling mathematical model and the increase in the optimization solution time, so as to shorten the placement time and improve the efficiency of the placement process. The effect of production efficiency

Inactive Publication Date: 2013-01-16
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
View PDF0 Cites 27 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The technical effect of this patented technology lies on optimizing part assembly processes by predicting how well parts are going where they will be placed next based upon their location within an installation area or queue. This helps reduce downtime while improving productivity.

Problems solved by technology

This patented describes how optimizing the placements during printing processes helps increase manufacturing efficacy while reducing costs associated with defects caused by poorly placed parts. Specifically, it suggests improving the placer's order assignment based upon its grip pattern and position relative to the substrate being assembled onto. Additionally, there are proposals about quantifying the impact of placing machines over their lifespan. These improvements aimed at increasing the overall performance of the printer itself through improved plaque dispensation accuracy and shorter cycle times.

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
  • Component mounting and dispatching optimization method for chip mounter on basis of quantum neural network
  • Component mounting and dispatching optimization method for chip mounter on basis of quantum neural network
  • Component mounting and dispatching optimization method for chip mounter on basis of quantum neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0013] The quantum neural network-based placement scheduling optimization method for placement machine components of the present invention will be described in detail below with reference to the accompanying drawings.

[0014] as attached figure 1 , in the quantum neural network-based component placement scheduling optimization method of the present invention, the working principle of component placement is: first, the placement head moves to the position of the component intelligent feeder, and absorbs the component device; then the placement head moves to the position of the first component to complete the placement of component 1, and then moves to the position of the second device to complete the placement of device 2, and repeats the cycle of placement until the PCB on the All components are mounted.

[0015] An optimization method for placement scheduling of placement machine components based on quantum neural network, the specific process is as follows:

[0016] Step ...

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 provides a component mounting and dispatching optimization method for a chip mounter on basis of a quantum neural network. The component mounting and dispatching optimization method comprises the steps of establishing a mathematical model of the sum of paths required by the operation of mounting all components on a printed circuit board (PCB) according to an operating principle of mounting the components by a suction nozzle of the chip mounter, wherein the distances between all the mounted components and different feed tanks are taken as input vectors of the quantum neural network, and all weighting values are set as small random numbers, and given input vectors and target output vectors of a training set are provided; and calculating overall optimal solution of the established mathematical modeling by adopting a three-layer quantum neural network algorithm, thus obtaining an optimized component mounting and dispatching scheme corresponding with the sum of the shortest mounting patches of all the components, the optimal mounting order of all the components, and the arrangement positions of feeders of the components in the feed tanks. The component mounting and dispatching optimization method constructs the component mounting and dispatching mathematical model which takes both the component mounting order and the feeder arrangement positions into consideration, obtains the optimal control on the mounting and dispatching of the components in the PCB, shortens the mounting time of single-end arch components, and enhances the mounting and production efficiency of the components of the chip mounter.

Description

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

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
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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