CN103941684A - Dispatching optimization method for electroless copper plating process of multiple layers of circuit boards - Google Patents
Dispatching optimization method for electroless copper plating process of multiple layers of circuit boards Download PDFInfo
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- CN103941684A CN103941684A CN201410140873.2A CN201410140873A CN103941684A CN 103941684 A CN103941684 A CN 103941684A CN 201410140873 A CN201410140873 A CN 201410140873A CN 103941684 A CN103941684 A CN 103941684A
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- 238000000034 method Methods 0.000 title claims abstract description 122
- 238000005457 optimization Methods 0.000 title claims abstract description 49
- 238000007747 plating Methods 0.000 title claims abstract description 37
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title abstract description 4
- 229910052802 copper Inorganic materials 0.000 title abstract description 4
- 239000010949 copper Substances 0.000 title abstract description 4
- 238000012163 sequencing technique Methods 0.000 claims description 20
- 230000035772 mutation Effects 0.000 claims description 11
- 230000008901 benefit Effects 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 6
- 230000006978 adaptation Effects 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 239000000203 mixture Substances 0.000 claims description 5
- 238000004519 manufacturing process Methods 0.000 abstract description 8
- 238000012545 processing Methods 0.000 abstract description 4
- 238000011161 development Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000002028 premature Effects 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to a dispatching optimization method for the electroless copper plating process of multiple layers of circuit boards and belongs to the technical field of intelligent dispatching optimization in a production workshop. The dispatching optimization method comprises the steps that a dispatching model and an optimization objective of the electroless copper plating process are determined, and the optimization objective is optimized through a dispatching optimization method based on the differential evolution algorithm; the dispatching model is established according to processing finishing time of each circuit board on each process device, and meanwhile the optimization objective is obtained by minimizing the earliest finishing time. By means of the dispatching optimization method, the algorithm can be better guided to conduct global search; historical information of superior individuals can be fully utilized, and it can also be guaranteed that the global search of the algorithm has a certain width; as a result, the search field of the algorithm is wider, the local development capability of the algorithm is remarkably improved, and the solving quality is remarkably improved.
Description
Technical field
The present invention relates to a kind of Optimization Scheduling of chemical-copper-plating process process of multilayer circuit board, belong to workshop intelligent optimization dispatching technique field.
Background technology
Printed-wiring board (PWB) (Printed Circuit Board, PCB) is the integrated carriers of electronic devices and components, is one of most important parts of electronic industry.Almost every kind of electrical equipment, in order to realize the electric interconnection between different components and parts, all will use printed board.On the product structure of PCB, multilayer circuit board has occupied most output value ratio, and the manufacturing capacity of multilayer circuit board has become the most important standard of weighing PCB industry technology level.Along with being growing more intense of market competition, how effectively to improve the efficiency of each link in multilayer circuit board production run, be the key that improves Business Economic Benefit and the market competitiveness.
In the manufacture process of PCB system, chemical-copper-plating process process is a wherein the most key ring.Chemical-copper-plating process process comprises oil removing, washing-1, acidleach, electro-coppering and washing-2 totally 5 stages, and these 5 stages need to be by said sequence at different process equipment
(
) on complete.In the printing process of whole wiring board, chemical-copper-plating process process occupies the main time.Therefore, chemical-copper-plating process process reasonably being dispatched, is to shorten the production cycle, improves the key of PCB system production capacity.In manufacture multilayer circuit board process, the every increase one deck of sheet material to be processed, will be through chemical-copper-plating process process once.Specifically, print the circuit board of multilayer, this sheet material need to repeat through 5 process equipments in chemical-copper-plating process process repeatedly, can complete processing by same sequence.The feature of chemical-copper-plating process process is: the number of plies of every circuit version is not quite similar, and the every increase one deck of wiring board will be according to
order process once, and on every machine, the processing sequence of each circuit version is identical.Chemical-copper-plating process process belongs to the reentried line flow procedure of a class complexity, because the processing sequence of each circuit version on every process equipment is identical, academia defines this class streamline for displacement streamline (the Reentrant Permutation Flow-shop that can reentry, RPFS), already proved that two above RPFS scheduling problems of machine belong to np hard problem, cannot try to achieve its exact solution in polynomial time.Obviously, number of machines
m=5 RPFS scheduling problem (being chemical-copper-plating process process scheduling problem), also belongs to the difficult category of NP.This problem is reasonably dispatched, can obviously improve the production efficiency of PCB system.
Because the chemical-copper-plating process process scheduling problem of multilayer circuit board is NP difficulty, make traditional mathematic programming methods can only solve problem on a small scale, and the optimization of heuristic constructive method is second-rate.Therefore, the present invention designs a kind of Optimization Scheduling based on differential evolution algorithm, can obtain the good solution of the electroless copper process scheduling problem of multilayer circuit board within a short period of time.
Summary of the invention
Technical matters to be solved by this invention is the problem that obtains the good solution of the chemical-copper-plating process process scheduling problem of multilayer circuit board within a short period of time, and a kind of Optimization Scheduling of chemical-copper-plating process process of multilayer circuit board is provided.
Technical scheme of the present invention is: a kind of Optimization Scheduling of chemical-copper-plating process process of multilayer circuit board, by determining scheduling model and the optimization aim of chemical-copper-plating process process, and use the Optimization Scheduling based on differential evolution algorithm to be optimized optimization aim; Wherein the machine time of every wiring board of scheduling model foundation on every process equipment sets up, and optimization aim is for minimizing completion date the earliest simultaneously
c max :
In formula:
mrepresent 5 process equipments of copper-plating technique process,
sumRrepresent all
nthe number of plies sum of individual wiring board to be processed,
nrepresent the quantity of wiring board to be processed,
wiring board Operation Sequencing to be processed,
(
j=1 ...,
sumR) represent to sort
πin
jthe wiring board of individual position,
represent wiring board
?
in the number of times that repeats,
it is wiring board
the
inferiorly enter
kthe process time of platform process equipment,
it is wiring board
the
inferiorly enter
kthe completion date of platform process equipment,
represent all formable rankings
the set of composition; Optimization aim be
in find an optimal sequencing
, make corresponding completion date the earliest
c max minimum.
The concrete steps of the described Optimization Scheduling based on differential evolution algorithm are as follows:
A, coded system: adopt, based on random code mode, wiring board Operation Sequencing is carried out to real coding, then utilize LOV rule to set up the mapping relations one by one between real coding and integer coding, and then realize the conversion from real coding to wiring board Operation Sequencing;
B, initialization of population: adopt random device to produce initialization population, until the quantity of initial solution reaches the requirement of population scale, wherein population scale is M;
C, operative norm DE operation: previous generation population order is carried out to variation, intersects and select operation, produce candidate population;
D, based on "
insert" mutation operation: according to variation probability 0.3 to candidate population carry out based on "
insert" mutation operation, obtain variation after candidate population;
E, based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: using individual as " choosing individuality " the front 5 ﹪ advantages of adaptation value minimum in the candidate population after variation, to each execution of " choosing individuality " based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: if the individuality that Local Search obtains is better than " choosing individuality ", replaced, and using current population as population of new generation;
F, end condition: the maximum iteration time of setting end condition is 200, if met, output " optimum individual "; Otherwise go to step C, iterate, until meet end condition.
Described population scale is set to 50.
Principle of work of the present invention is:
Step 1: chemical-copper-plating process process scheduling model and the optimization aim of setting up multilayer circuit board.
The machine time of every wiring board of scheduling model foundation on every process equipment sets up, and optimization aim is for minimizing completion date the earliest simultaneously
c max :
；
,
k?=2,…
m；
；
,?
；
In formula:
mrepresent 5 process equipments (completing respectively oil removing, washing-1, acidleach, electro-coppering and washing-2 operation) of copper-plating technique process,
sumRrepresent all
nthe number of plies sum of individual wiring board to be processed,
nrepresent the quantity of wiring board to be processed,
wiring board Operation Sequencing to be processed,
(
j=1 ...,
sumR) represent to sort
πin
jthe wiring board of individual position,
represent wiring board
?
in the number of times that repeats,
it is wiring board
the
inferiorly enter
kthe process time of platform process equipment,
it is wiring board
the
inferiorly enter
kthe completion date of platform process equipment,
represent all formable rankings
the set of composition; Optimization aim be
in find an optimal sequencing
, make corresponding completion date the earliest
c max minimum.
Step 2: the expression of solution.
The coding of separating is the prerequisite of algorithm iteration optimizing.By setting up the rational mapping of solution space and algorithm solution space, not only can effectively reflect the architectural characteristic of problem self, also facilitate decode operation simultaneously and then form feasible schedule.For scheduling problem, classical coded system mainly comprises the coding based on machine, the coding based on workpiece and the coding based on random by key etc.For the feature of the chemical-copper-plating process process of multilayer circuit board, the present invention proposes the coding based on random by key.
In standard difference evolution algorithm, individuality shows with real number string list, adopt, based on random code mode, wiring board Operation Sequencing is carried out to real coding in this profit, then utilize LOV rule to set up the mapping relations one by one between real coding and integer coding, and then realize from algorithm solution space (real coding) conversion of (wiring board Operation Sequencing) to solution space;
Step 3: initialization of population: adopt random device to produce initialization population, until the quantity of initial solution reaches the requirement of population scale;
Step 4: operative norm DE operation: previous generation population order is carried out to variation, intersects and select operation, produce candidate population, and use candidate population to substitute previous generation population;
Step 5: based on "
insert" mutation operation: according to variation probability 0.3 to candidate population carry out based on "
insert" mutation operation, obtain variation after candidate population.Differential evolution algorithm has stronger overall exploring ability, but in algorithm evolution process, is easily absorbed in local optimum, thereby causes the Premature Convergence of algorithm, therefore, adds effective Local Search mechanism very important in differential evolution algorithm.Use "
insert" operate the individuality in population (being the solution of problem) is carried out to disturbance, be conducive to algorithm and jump out local optimum, and then make the more zones of different of algorithm search.The present invention propose based on "
insert" mutation operation, be conducive to improve the global search performance of algorithm, and then improve the quality of separating.
Step 6: based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: using individual as " choosing individuality " the front 5 ﹪ advantages of adaptation value minimum in the candidate population after variation, to each execution of " choosing individuality " based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: if the individuality that Local Search obtains is better than " choosing individuality ", replaced, and using current population as population of new generation;
Step 7: end condition: the maximum iteration time of setting end condition is 200, if met, output " optimum individual "; Otherwise go to step 4, iterate, until meet end condition.
The invention has the beneficial effects as follows: proposed scheduling model and the optimization aim of the chemical-copper-plating process process of multilayer circuit board, it is clear accurate to make to express; Adopt " optimum individual " renewal individuality of future generation that obtains current population according to algorithm steps, better bootstrap algorithm carries out global search; In the renewal process of population, adopt the cross and variation in algorithm and select the modes such as operation, not only can make the historical information of advantage individuality be fully used, can also ensure that the global search of algorithm has certain width; In global search, utilize "
insert" operate disturbance is carried out in current region of search, be conducive to algorithm and jump out local optimum, and then make the search field of algorithm more extensive; In conjunction with "
interchange" neighborhood search and front end abridged Local Search, the local development ability of algorithm is significantly improved, the quality of solution be improved significantly.
Brief description of the drawings
Fig. 1 is the chemical-copper-plating process process schematic diagram of multilayer circuit board in the present invention;
Fig. 2 is algorithm flow chart of the present invention;
Fig. 3 is the expression schematic diagram of solution in the present invention;
Fig. 4 be of the present invention based on "
insert" variation schematic diagram;
Fig. 5 be of the present invention "
interchange" operation chart.
Embodiment
Embodiment 1: as Figure 1-5, a kind of Optimization Scheduling of chemical-copper-plating process process of multilayer circuit board, by determining scheduling model and the optimization aim of chemical-copper-plating process process, and use the Optimization Scheduling based on differential evolution algorithm to be optimized optimization aim; Wherein the machine time of every wiring board of scheduling model foundation on every process equipment sets up, and optimization aim is for minimizing completion date the earliest simultaneously
c max :
In formula:
mrepresent 5 process equipments of copper-plating technique process,
sumRrepresent all
nthe number of plies sum of individual wiring board to be processed,
nrepresent the quantity of wiring board to be processed,
wiring board Operation Sequencing to be processed,
(
j=1 ...,
sumR) represent to sort
πin
jthe wiring board of individual position,
represent wiring board
?
in the number of times that repeats,
it is wiring board
the
inferiorly enter
kthe process time of platform process equipment,
it is wiring board
the
inferiorly enter
kthe completion date of platform process equipment,
represent all formable rankings
the set of composition; Optimization aim be
in find an optimal sequencing
, make corresponding completion date the earliest
c max minimum.
The concrete steps of the described Optimization Scheduling based on differential evolution algorithm are as follows:
A, coded system: adopt, based on random code mode, wiring board Operation Sequencing is carried out to real coding, then utilize LOV rule to set up the mapping relations one by one between real coding and integer coding, and then realize the conversion from real coding to wiring board Operation Sequencing;
B, initialization of population: adopt random device to produce initialization population, until the quantity of initial solution reaches the requirement of population scale, wherein population scale is M;
C, operative norm DE operation: previous generation population order is carried out to variation, intersects and select operation, produce candidate population;
D, based on "
insert" mutation operation: according to variation probability 0.3 to candidate population carry out based on "
insert" mutation operation, obtain variation after candidate population;
E, based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: using individual as " choosing individuality " the front 5 ﹪ advantages of adaptation value minimum in the candidate population after variation, to each execution of " choosing individuality " based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: if the individuality that Local Search obtains is better than " choosing individuality ", replaced, and using current population as population of new generation;
F, end condition: the maximum iteration time of setting end condition is 200, if met, output " optimum individual "; Otherwise go to step C, iterate, until meet end condition.
Described population scale is set to 50.
Embodiment 2: as Figure 1-5, a kind of Optimization Scheduling of chemical-copper-plating process process of multilayer circuit board, by determining scheduling model and the optimization aim of chemical-copper-plating process process, and use the Optimization Scheduling based on differential evolution algorithm to be optimized optimization aim; Wherein the machine time of every wiring board of scheduling model foundation on every process equipment sets up, and optimization aim is for minimizing completion date the earliest simultaneously
c max :
In formula:
mrepresent 5 process equipments of copper-plating technique process,
sumRrepresent all
nthe number of plies sum (the every required copper-plated number of plies of wiring board is not quite similar) of individual wiring board to be processed,
nrepresent the quantity of wiring board to be processed,
wiring board Operation Sequencing to be processed,
(
j=1 ...,
sumR) represent to sort
πin
jthe wiring board of individual position,
represent wiring board
?
in the number of times that repeats,
it is wiring board
the
inferiorly enter
kthe process time of platform process equipment,
it is wiring board
the
inferiorly enter
kthe completion date of platform process equipment,
represent all formable rankings
the set of composition; Optimization aim be
in find an optimal sequencing
, make corresponding completion date the earliest
c max minimum.
The concrete steps of the described Optimization Scheduling based on differential evolution algorithm are as follows:
A, coded system: adopt, based on random code mode, wiring board Operation Sequencing is carried out to real coding, then utilize LOV rule to set up the mapping relations one by one between real coding and integer coding, and then realize the conversion from real coding to wiring board Operation Sequencing; Be as shown in Figure 3 the solution of a problem;
B, initialization of population: adopt random device to produce initialization population, until the quantity of initial solution reaches the requirement of population scale, wherein population scale is M;
C, operative norm DE operation: previous generation population order is carried out to variation, intersects and select operation, produce candidate population;
D, based on "
insert" mutation operation: according to variation probability 0.3 to candidate population carry out based on "
insert" mutation operation, obtain variation after candidate population;
E, based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: using individual as " choosing individuality " the front 5 ﹪ advantages of adaptation value minimum in the candidate population after variation, to each execution of " choosing individuality " based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: if the individuality that Local Search obtains is better than " choosing individuality ", replaced, and using current population as population of new generation;
F, end condition: the maximum iteration time of setting end condition is 200, if met, output " optimum individual "; Otherwise go to step C, iterate, until meet end condition.
Described population scale is set to 50.
Table 1 has provided the method for the present invention's proposition and the comparative result of classical NEH method.The method that the present invention proposes as shown in Table 1 can obtain being better than the result of classical NEH method, therefore can be used for the scheduling problem of the chemical-copper-plating process process that effectively solves multilayer circuit board.
The target function value comparison that the method that table 1 the present invention proposes is tried to achieve in different problem scale situations from classical NEH method
Note:
sumRfor
nthe number of plies sum of individual wiring board to be processed, the number of plies of each wiring board is between 2 to 5.
By reference to the accompanying drawings the specific embodiment of the present invention is explained in detail above, but the present invention is not limited to above-mentioned embodiment, in the ken possessing those of ordinary skill in the art, can also under the prerequisite that does not depart from aim of the present invention, make various variations.
Claims (3)
1. the Optimization Scheduling of the chemical-copper-plating process process of a multilayer circuit board, it is characterized in that: by determining scheduling model and the optimization aim of chemical-copper-plating process process, and use the Optimization Scheduling based on differential evolution algorithm to be optimized optimization aim; Wherein the machine time of every wiring board of scheduling model foundation on every process equipment sets up, and optimization aim is for minimizing completion date the earliest simultaneously
c max :
In formula:
mrepresent 5 process equipments of copper-plating technique process,
sumRrepresent all
nthe number of plies sum of individual wiring board to be processed,
nrepresent the quantity of wiring board to be processed,
wiring board Operation Sequencing to be processed,
(
j=1 ...,
sumR) represent to sort
πin
jthe wiring board of individual position,
represent wiring board
?
in the number of times that repeats,
it is wiring board
the
inferiorly enter
kthe process time of platform process equipment,
it is wiring board
the
inferiorly enter
kthe completion date of platform process equipment,
represent all formable rankings
the set of composition; Optimization aim be
in find an optimal sequencing
, make corresponding completion date the earliest
c max minimum.
2. the Optimization Scheduling of the chemical-copper-plating process process of multilayer circuit board according to claim 1, is characterized in that: the concrete steps of the described Optimization Scheduling based on differential evolution algorithm are as follows:
A, coded system: adopt, based on random code mode, wiring board Operation Sequencing is carried out to real coding, then utilize LOV rule to set up the mapping relations one by one between real coding and integer coding, and then realize the conversion from real coding to wiring board Operation Sequencing;
B, initialization of population: adopt random device to produce initialization population, until the quantity of initial solution reaches the requirement of population scale, wherein population scale is M;
C, operative norm DE operation: previous generation population order is carried out to variation, intersects and select operation, produce candidate population;
D, based on "
insert" mutation operation: according to variation probability 0.3 to candidate population carry out based on "
insert" mutation operation, obtain variation after candidate population;
E, based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: using individual as " choosing individuality " the front 5 ﹪ advantages of adaptation value minimum in the candidate population after variation, to each execution of " choosing individuality " based on "
interchange" neighbour structure and improve and jump out the Local Search of principle first: if the individuality that Local Search obtains is better than " choosing individuality ", replaced, and using current population as population of new generation;
F, end condition: the maximum iteration time of setting end condition is 200, if met, output " optimum individual "; Otherwise go to step C, iterate, until meet end condition.
3. the Optimization Scheduling of the chemical-copper-plating process process of multilayer circuit board according to claim 1 and 2, is characterized in that: described population scale is set to 50.
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| CN201410140873.2A CN103941684A (en) | 2014-04-10 | 2014-04-10 | Dispatching optimization method for electroless copper plating process of multiple layers of circuit boards |
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| CN201410140873.2A CN103941684A (en) | 2014-04-10 | 2014-04-10 | Dispatching optimization method for electroless copper plating process of multiple layers of circuit boards |
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Cited By (7)
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|---|---|---|---|---|
| CN104503381A (en) * | 2014-11-20 | 2015-04-08 | 昆明理工大学 | Optimizing scheduling method of handset in production assembly process |
| CN104571007A (en) * | 2014-11-20 | 2015-04-29 | 昆明理工大学 | Optimizing dispatching method for producing assembly process of general assembly line in production and manufacturing of cars |
| CN108845499A (en) * | 2018-07-06 | 2018-11-20 | 昆明理工大学 | A kind of Optimization Scheduling of steel smelting procedure |
| CN108873850A (en) * | 2018-09-05 | 2018-11-23 | 昆明理工大学 | A kind of Optimization Scheduling of automation of machinery manufacture production process |
| CN108873835A (en) * | 2018-06-12 | 2018-11-23 | 昆明理工大学 | The Optimization Scheduling of photoetching process in a kind of manufacture of semiconductor integrated circuit |
| CN109164763A (en) * | 2018-07-25 | 2019-01-08 | 昆明理工大学 | A kind of Optimization Scheduling of industrial robot automatic production line |
| CN109213094A (en) * | 2018-07-25 | 2019-01-15 | 昆明理工大学 | A kind of Optimization Scheduling based on multiplexing inter-plant steel smelting-continuous casting production steel billet process |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104503381A (en) * | 2014-11-20 | 2015-04-08 | 昆明理工大学 | Optimizing scheduling method of handset in production assembly process |
| CN104571007A (en) * | 2014-11-20 | 2015-04-29 | 昆明理工大学 | Optimizing dispatching method for producing assembly process of general assembly line in production and manufacturing of cars |
| CN104571007B (en) * | 2014-11-20 | 2018-11-27 | 昆明理工大学 | The Optimization Scheduling of general assembly line production assembling process in a kind of automotive manufacture |
| CN108873835A (en) * | 2018-06-12 | 2018-11-23 | 昆明理工大学 | The Optimization Scheduling of photoetching process in a kind of manufacture of semiconductor integrated circuit |
| CN108845499A (en) * | 2018-07-06 | 2018-11-20 | 昆明理工大学 | A kind of Optimization Scheduling of steel smelting procedure |
| CN109164763A (en) * | 2018-07-25 | 2019-01-08 | 昆明理工大学 | A kind of Optimization Scheduling of industrial robot automatic production line |
| CN109213094A (en) * | 2018-07-25 | 2019-01-15 | 昆明理工大学 | A kind of Optimization Scheduling based on multiplexing inter-plant steel smelting-continuous casting production steel billet process |
| CN108873850A (en) * | 2018-09-05 | 2018-11-23 | 昆明理工大学 | A kind of Optimization Scheduling of automation of machinery manufacture production process |
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