Chatswood to Sydenham Environmental Impact Statement Summary
Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.
-
date post
19-Dec-2015 -
Category
Documents
-
view
214 -
download
0
Transcript of Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.
![Page 1: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/1.jpg)
An integrated scheduling problem of PCB components on sequential pick-
and-place machines: Mathematical models and heuristic solutions
Authors:
William Ho and Ping Ji
Published Date:
April 2009
Presented by:
Mark Sydenham
![Page 2: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/2.jpg)
ReferencesAltinkemer, K., Kazaz, B., Köksalan, M., & Moskowitz, H. (2000).
Optimization of printed circuit board manufacturing: integrated modeling and algorithms. European Journal of Operational Research, 124, 409–421.
Ball, M. O., & Magazine, M. J. (1988). Sequencing of insertions in printed circuit board assembly. Operations Research, 36, 192–201.
Broad, K., Mason, A., Rönnqvist, M., & Frater, M. (1996). Optimal robotic component placement. Journal of the Operational Research Society, 47,1343–1354.
Crama, Y., Flippo, O. E., Klundert, J. V. D., & Spieksma, F. C. R. (1997). The assembly of printed circuit boards: A case with multiple machines and multiple board types. European Journal of Operational Research, 98, 457–472.
Ellis, K. P., Vittes, F. J., & Kobza, J. E. (2001). Optimizing the performance of a surface mount placement machine. IEEE Transactions on Electronics Packaging Manufacturing, 24, 160–170.
Foulds, L. R., & Hamacher, H. W. (1993). Optimal bin location and sequencing in printed circuit board assembly. European Journal of Operational Research, 66,279–290.
Francis, R. L., Hamacher, H. W., Lee, C. Y., & Yeralan, S. (1994). Finding placement sequences and bin locations for Cartesian robots. IIE Transactions, 26, 47–59.
Gen, M., & Cheng, R. (1997). Genetic algorithms and engineering design. New York: Wiley.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. New York: Addison-Wesley.
Ji, Z., Leu, M. C., & Wong, H. (1992). Application of linear assignment model for planning of robotic printed circuit board assembly. Journal of Electronic Packaging, 114, 455–460.
Kumar, R., & Li, H. (1995). Integer programming approach to printed circuit board assembly time optimization. IEEE Transactions on Components, Packaging, and Manufacturing Technology – Part B, 18, 720–727.
Leu, M. C., Wong, H., & Ji, Z. (1993). Planning of component placement/insertion sequence and feeder setup in PCB assembly using genetic algorithm. Journal of Electronic Packaging, 115, 424–432.
Loh, T. S., Bukkapatnam, S. T. S., Medeiros, D., & Kwon, H. (2001). A genetic algorithm for sequential part assignment for PCB assembly. Computers & Industrial Engineering, 40, 293–307.
Magyar, G., Johnsson, M., & Nevalainen, O. (1999). On solving single machine optimization problems in electronics assembly. Journal of Electronics Manufacturing, 9, 249–267.
Ong, N. S., & Khoo, L. P. (1999). Genetic algorithm approach in PCB assembly. Integrated Manufacturing Systems, 10, 256–265.
Ong, N. S., & Tan, W. C. (2002). Sequence placement planning for high speed PCB assembly machine. Integrated Manufacturing Systems, 13, 35–46.
Osman, I. H., & Kelly, J. P. (1996). Meta-heuristics: Theory & applications. Boston: Kluwer Academic Publishers.
Wilhelm, W. E., & Tarmy, P. K. (2003). Circuit card assembly on tandem turret-type placement machines. IIE Transactions, 35, 627–645.
![Page 3: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/3.jpg)
Function of Paper Process planning issues
Setup optimization○ Line assignment○ Machine grouping○ PCB grouping○ PCB sequencing
Process optimization○ Component allocation○ Feeder arrangement○ Component sequencing
The purpose of this paper is to integrate the feeder arrangement and component sequencing for sequential pick-and-place (PAP) machines. In other words, optimize these problems simultaneously. By using two methods Mathematical modeling A hybrid genetic algorithm
![Page 4: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/4.jpg)
Why is optimizing these problems simultaneously important?
If, for example, the arrangement of components in the feeders is not made carefully and the sequencing is optimized, the over-all system performance can be very poor.
So to maximize performance by minimizing production time, these two problems must be solved simultaneously.
![Page 5: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/5.jpg)
Is this paper related to the technical area in the course?
Yes, it is related. In class we have discussed electronics assembly and pick and place machines. And this paper is attempting to optimize this pick and place process.
![Page 6: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/6.jpg)
Design of Pick and Place Machines The machine The process
![Page 7: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/7.jpg)
Design principle or purpose Minimize the distance the placing head
travels, which in turn, reduces the take needed to place all the components
![Page 8: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/8.jpg)
Definition of parameters for the mathematical models
![Page 9: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/9.jpg)
The different mathematical models formulatedM3 (non-linear – contain both binary and integer values)
M4 (linear version of M3)
M5 (simplified version of M3)
M6 (M5 made linear)
![Page 10: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/10.jpg)
Experimental equipment for the mathematical models These equations were optimized by
two software packagesCPLEX
○ A integer linear programming solver○ Used to solve M4
BARON ○ A computational system for solving non-
convex optimization problems○ Used to solve M5
![Page 11: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/11.jpg)
Results of mathematical models Mathematical models are too complex
and require too much time to solve.
![Page 12: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/12.jpg)
The hybrid genetic algorithm method (HGA) The basic idea of
this method is to maintain a population of possible solutions that evolve as the process proceeds
![Page 13: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/13.jpg)
Method
![Page 14: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/14.jpg)
Method continued
![Page 15: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/15.jpg)
Results of the HGA method Solved in 9 seconds versus 11 hours or
15 days
![Page 16: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/16.jpg)
Results Summary
Mathematic MethodVery accurate but takes to long to perform
HGA MethodReaches a good, but not perfect,
optimization very quickly.
![Page 17: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/17.jpg)
Technical advancement?
Authors boast that their results constitute a reduction of about 2.2 seconds in cycle time per PCB.
![Page 18: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/18.jpg)
Is this advancement practical for industrial use? There is the potential for this study to
benefit industry but the explanation on how to perform the proposed HGA method is difficult to understand
![Page 19: Authors: William Ho and Ping Ji Published Date: April 2009 Presented by: Mark Sydenham.](https://reader036.fdocuments.us/reader036/viewer/2022062714/56649d2c5503460f94a01eb9/html5/thumbnails/19.jpg)
Which industries would benefit from this study? Manufacturers of PCB Manufacturers of machines that are
used to produce PCB