CN111062552A - Scheduling method of intelligent scheduling system - Google Patents

Abstract

The invention provides a scheduling method of an intelligent scheduling system, which comprises the steps of (a) receiving basic data provided by a user on a user interface, (b) establishing an initialization model based on the basic data, (c) carrying out simulation operation based on the initialization model, and (d) outputting a result of the simulation operation. Therefore, the intelligent dispatching system can establish a virtual factory model which accords with the real situation in a digital computer, solves the problem that the conventional dispatching system can not calculate the dispatching which completely accords with the actual situation, and assists a user to be used as decision support, and is quicker and more accurate compared with the conventional method.

Description

Scheduling method of intelligent scheduling system

Technical Field

The present invention relates to a scheduling method, and more particularly, to a scheduling method of an intelligent scheduling system.

Background

Generally, a factory is faced with many unexpected emergency situations during practical operation, such as rapid order insertion, unexpected product yield, equipment breakdown, shortage of raw materials, etc., which are all related to the scheduling of factory production, however, in the past known production scheduling methods, because the factors of the real environment are too complex, it is often difficult to calculate by mathematical modeling, most of the available planning methods are calculation methods using capacity stack and adding constraints to calculate and solve, and the results obtained by such methods are far from the real situation and time consuming.

Disclosure of Invention

In view of the above, the present invention provides a scheduling method for an intelligent scheduling system, which can establish a virtual factory model conforming to the real situation in a digital computer, and solve the problem that the conventional scheduling system cannot calculate the scheduling completely conforming to the actual situation.

To achieve the above object, the present invention provides a scheduling method of an intelligent scheduling system, which comprises the following steps: the method comprises the steps of (a) receiving basic data provided by a user on a user interface, (b) establishing an initialization model based on the basic data, (c) performing simulation operation based on the initialization model, and (d) outputting a simulation operation result.

The scheduling method of the intelligent scheduling system belongs to an object-oriented modular development mode, can quickly establish a user-defined virtual factory model for a user, assists the user in decision support, and is quicker and more accurate compared with the conventional method.

The details of the present invention will be described in the following detailed description. However, it will be understood by those skilled in the art that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention as defined by the appended claims.

Drawings

FIG. 1 is a flow chart of a scheduling method of the intelligent scheduling system of the present invention;

FIG. 2 is a schematic flow chart illustrating a scheduling method of the intelligent scheduling system according to the present invention;

fig. 3 to fig. 10 are schematic views illustrating the operation of the interface of the intelligent scheduling system of the present invention.

[ Main element ]

S1-step (a); s2-step (b); s3-step (c); s4-step (d).

Detailed Description

To illustrate the implementation of the present invention in more detail, a semiconductor package and test example will be described, however, for other possible embodiments, the scheduling method of the intelligent scheduling system is also applicable to other industries, such as semiconductor manufacturing, led panel, metal processing assembly, etc. Referring to fig. 1, a flowchart of a scheduling method of an intelligent scheduling system according to a preferred embodiment of the present invention is shown, where the scheduling method of the intelligent scheduling system includes the following steps: (a) receiving basic data provided by a user in a user interface, establishing an initialization model based on the basic data in step (b), performing a simulation operation based on the initialization model in step (c), and outputting the result of the simulation operation in step (d).

Referring to fig. 2, in the present embodiment, the step (a) includes the step (a1) of inputting the basic data, the step (a2) of adjusting the basic data, and the step (a3) of collating the basic data. In more detail, the step (a1) is that the user inputs basic data in an interface of the intelligent scheduling system, the basic data includes equipment information as shown in tables 1 to 5, product route information as shown in tables 6 to 7, and order information as shown in table 8.

The following table 1 is a work center group table, and the required data is field settable parameters of machine name, processing time, maintenance time, work center name, replaceable work center name, interval upper limit, interval lower limit, key index assignment and priority index assignment, and the use priority of the machine is determined.

TABLE 1 work center group form

TABLE 1 work center group form (continuation)

Upper limit of interval	Lower limit of interval	Key index dispatching	Priority index assignment
						2	1
		2	1
						2	1
		2	1
						2	1
		2	1
						2	1

The following table 2 is a table of the internal structure of a machine, which can set the machine name, machine type, loading size, loading lock, manufacturing slot, and processing lot of the machine.

TABLE 2 Table of the internal structure of the machine

Name of machine	Class of machine	Carrying size	Load lock	Manufacturing tank	Processing batches
						SOR_1	Limited	3	2	6	1
SOR_2	Limited	3	2	4	1
						SOR_3	Limited	3		3	1
STH_1	Limited	3		3	1
						STH_2	Limited	2		3	1
SCRA_1	Limited	3		3	1
						SCRA_2	Limited	3		3	1
MIC_1	Limited	3		3	1
						MIC_2	Limited	3		3	1
DESD_1	Limited	2	2		4
						DESD_2	Limited	2	2		4

The following table 3 is a table of machine production time, which can set the machine number, production item name, processing stage, processing technology, processing parameter, production rate, production line classification, production lot, production line personnel group, production line personnel number, production line personnel man-hour, LP _ man-hour calculation mode, PT _ man-hour calculation mode, DL _ man-hour calculation mode, LP _ production time, PT _ production time, DL _ production time, and other relevant settings for each machine. Taking FV-4 in Table 3 as an example, when the item PD _1 is produced to the processing technology of the serial number 125, it takes 36 seconds to process one PD _ 1; in the production of the item PD _1 to the processing of the reference numeral 130, it takes 60 seconds to process one PD _ 1.

TABLE 3 production time table

Machine station number	Name of production item	Stage of processing	Processing technology	Processing parameters	Production rate
						FV_4	PD_1	P11	125	Recipe 12	1
FV_4	PD_1	P11	130	Recipe 13	1
						FV_4	PD_1	BPFV	590	Recipe 60	1
FV_4	PD_10	BPFV	540	Recipe 124	1
						FV_4	PD_11	BPFV	540	Recipe 188	1
FV_4	PD_12	P11	115	Recipe 208	1

TABLE 3 production time table of machine (continue)

Production line classification	Mass production	Production line personnel group	Number of production line personnel
				F	1
F	1
				F	1
F	1
				F	1
F	1

TABLE 3 production time table of machine (continue)

TABLE 3 production time table of machine (continue)

The following table 4 is a table of the production time of the machine, which can set the related settings of the machine name, the cycle start time, the cycle shutdown time, the absolute start time, the absolute shutdown time, etc. for each machine. Taking the machine SOR-1 in table 4 as an example, the machine SOR-1 will automatically start up at 8 am 00 min 05 sec every day, and the machine can perform production until it automatically shuts down at 5 pm 00 min, and the machine cannot perform production.

TABLE 4 production time chart of machine

The following table 5 is a table of machine tool crashes, which may set the machine name, routine, interval, In _ P1, In _ P2, upper limit of crashes, lower limit of crashes, duration, upper limit of crashes, lower limit of crashes, etc.

TABLE 5 Table of machine crash

Name of machine	Routine nature	Crash interval	In_P1	In_P2
					ACE01	TRUE	normal	2:00:39:30.0300	1:09:31:31.1400
ACE01-PM1	TRUE	normal	51:13.4	06:37.1
					ACE01-PM2	TRUE	normal	5731.8	29:28.2
ACE01-PM3	TRUE	normal	13:39.9	13:53.0

TABLE 5 Table crash form (continue)

Upper limit of crash	Lower limit of crash	Duration of time	P1_ duration
				09:01.0	12:07:14:09.0000	normal	28:47.6
19:16.0	8:04:07:23.0000	normal	26:53.4
				08:34.0	4:03:46:13.0000	normal	34:02.0
19:53.0	3:23:21:39.0000	normal	27:24.1

TABLE 5 Table crash form (continue)

P2_ duration	Upper limit of crash	Lower limit of crash
			53:35.4	06:51.0	24:24.0
13:35.2	06:30.0	20:21.0
			41:21.0	07:15.0	13:38.0
13:34.3	06:30.0	03:19.0

Because the scheduling method of the intelligent scheduling system is an object-oriented modular development mode, when the machine table form data of tables 1 to 5 is filled, the machine object is also built in the model, and then the machine parameters are included in the production decision when the user performs the scheduling simulation.

The data required by the item route form shown in the following table 6 is information such as item name, process serial number, work center, processing stage, process name, rework rate, workpiece retention time, sampling rate, material quantity per minute, transfer lot, waiting quantity (>), waiting quantity (<), waiting time (seconds) (>), waiting time (seconds) (<), standard man-hour (seconds), sub-part name, sub-part quantity, etc.

TABLE 6 item route sheet

Name of item	Process number	Work center	Stage of processing	Name of art
					Part_1	020.000	TGSOR	IQA	TDATA
Part_1	030.000	TGSTH	IQA	TTKMA
					Part_1	040.000	TGSCRA	IQA	TSCRA
Part_1	050.000	TGMIC	IQA	TINSA

TABLE 6, item route form (continuation)

TABLE 6, item route form (continuation)

TABLE 6, item route form (continuation)

Standard man-hour (seconds)	Name of sub-part 1	Number of sub-parts 1	Name of sub-part 2
				15.6
36
				11.1
36

The following table 7 shows an item single-time feeding form, in which the required data are information such as client name, object name, item name, starting process, ending process, quantity, priority parameter, customer requirement date, scheduling delivery date, etc.

TABLE 7 single item feed form

Name of customer	Name of object	Name of item	Starting process	Finishing process
						29GA6008.1	PD_1	050.000
	CFG95612.1	PD_1	630.000
						CFG95613.1	PD_1	630.000
	CFG95614.1	PD_1	640.000

TABLE 7 single item feed form (continue)

Number of	Priority order parameter	The day of customer's request	Scheduling delivery period
				25	6	2017/10/1 07:00:00	2017/10/5 23:00:00
25	3	2017/10/1 07:00:00	2017/10/5 06:00:00
				25	3	2017/10/1 07:00:00	2017/10/5 06:00:00
25	3	2017/10/1 07:00:00	2017/10/5 06:00:00

After the basic data required in step (a1) is filled by the user, the user can proceed to step (a2), i.e., modify or adjust the specific individual or batch data, such as adding or deleting data, adding new tools and product items, etc. After the step (a2) is completed, the intelligent dispatching system starts to perform the step (a3), i.e. standardizing the imported data, and loading the standardized data into the intelligent dispatching system for operation.

First, step (b1) is performed: establishing a virtual factory, i.e. the intelligent scheduling system first establishes a virtual factory framework, and then proceeds to step (b 2): creating a group of devices, the intelligent scheduling system grouping according to the functions or characteristics of the devices, such as non-contact surface measurement devices, being put together in the virtual factory, and then performing step (b 3): establishing an equipment model, namely establishing specific characteristics, functions and connection relations with other machines of the individual machine, and then performing the step (b 4): establishing a product model, loading information such as the product item, the name, the processing path, the process and the like of the product, and then performing the step (b 5): receiving the equipment parameters and product parameters, such as processing time, etc. set by the user, and importing these parameters into the system, and then proceeding to step (b 6): the simulation starting time point set by the user is received, so that the current condition of the factory can be simulated to the future production condition.

Then the intelligent dispatching system starts to proceed the step (c1) in sequence: determining the product type, step (c 2): confirm route number, step (c 3): selecting usable equipment, and step (c 4): and (5) simulating production. In this embodiment, the step (c1) can be returned to for recycling after the step (c4) is finished.

After the operation of the simulation production is finished, the intelligent scheduling system carries out the step (d): and outputting the result of the simulation operation, wherein the result comprises the daily information of the equipment, the information of the simulated station passing and the information of the simulated batch. The user can make a decision based on the result.

In practical operation, referring to fig. 3 to 5, a user first opens the top page of the intelligent scheduling system shown in fig. 3, clicks the lower left button (Download Template), downloads the sample files of excel basic data forms, which are shown in tables 1 to 7, fills up the required data, clicks the lower right button (Upload) of the top page to Upload the data to be scheduled, and jumps out of the Upload screen shown in fig. 4, selects the filled excel file and clicks the button (Upload) to Upload, and jumps out of the other screen shown in fig. 5, if the basic data content format is correct, the lower right button (RUN) appears, and starts to execute the simulation scheduling, i.e., execute steps (b) to (d).

When the user inputs data, trial calculation can be carried out according to different unit roles such as purchasing, production management, business and the like. For purchasing personnel, the main use requirements are planning and issuing of the feeding schedule; for production management personnel, the main requirements are order trial calculation, material planning, the total production number target of the machine group and trial calculation of the capacity; the order delivery trial calculation and the order production progress inquiry are the most important use requirements for business personnel. Therefore, for the buyer, the data import includes material information, such as feed planning and inventory information, in addition to the basic data; for production management personnel, besides basic data, machine parameters and a process machine group are further required to be input; in addition to the basic data, the business personnel further need to input order items and order quantity.

The intelligent dispatching system is realized by simulating a real planning method in a computer simulation operation way, after the intelligent dispatching system converts data input by a user into a virtual factory, after the virtual material, the virtual manpower and the virtual machine are put into operation, the simulation production is carried out to generate a simulation planning result, the data initialization is to establish all the required virtual objects including equipment, manpower, material, orders and the like, and restore the objects to the state at the scheduled time point, e.g., want to start scheduling at 2018/8/18:00, then all current data, such as equipment, equipment status, material in use, order in process, manpower attendance, manpower status …, etc. need to be collected 2018/8/18:00, which facilitates the initialization of the model and the more accurate the result will be when the data can be collected; after all the data models are initialized, planning production is started, and capacity planning is performed according to the current conditions of the factories, the conditions of the materials and the manpower, and the dispatching logics of the factories, wherein if the data cannot be completely collected, the average value or the estimated value can be used as an input parameter.

After the virtual scheduling is finished, a detailed work execution plan is generated, the content of which includes start time, end time, work order code, cycle time, whether to reach the delivery … on time, etc., and these data become reference bases for user, company or enterprise decision, so as to know the usage planning of factory resources, forecast work order production data and machine statistics, etc. For example, as shown in fig. 6, the service personnel may query the detailed information of the customer order from the output information of the order list, and may query information such as a predicted start date (FeedDate), an expected completion date (SOD), and an earliest completion date (FinishingTime). For example, as shown in fig. 7 and 8, the production manager can use the cluster dispatching record and the scheduling planning output information to know and record the output targets of each day, such as the Machine group Name (ToolGroup _ Name), the Target completion date (DueDate), the Target Quantity (Target _ Quantity), etc., and the Machine dispatching plan, the real-time order production schedule, such as the work order number (LotID), the work order start time (TrackIn), the work order end time (trackouttime), the processing Machine (Machine), etc. If the delivery period of a certain factory is too long on average, the production manager can utilize the bottleneck cluster production data, such as cluster utilization rate (UTIL) in fig. 9, find the bottleneck station machine group, on the one hand, monitor, and on the other hand, can perform production simulation after adding machines in the virtual factory, and can check whether the capacity bottleneck is solved without actually purchasing new machines, thereby avoiding the factory from bearing unnecessary investment loss, and even if a new machine is added in the virtual factory, the connection relationship between the new machine and other sites or machines does not need to be established on the system in additional time, so that a lot of time can be saved for users. Finally, the buyer can use the output information of the material planning to know the information of the amount of stock (Inventory _ Qty), the Status of stock (Status), the amount of stock change (modification _ Qty), etc., as shown in fig. 10.

It should be noted that the detailed description provided above with reference to the drawings is only an embodiment provided for illustrating the technical contents and features of the present invention, and those skilled in the art of the present invention should be able to make various simple modifications, substitutions or component reductions without departing from the spirit of the present invention after understanding the technical contents and features of the present invention, and therefore, the present invention should fall within the claims of the present disclosure.

Claims (6)

1. a scheduling method of an intelligent scheduling system, is characterized in that, comprises the following steps: (a) accept basic data provided by the user in a user interface; (b) establishing an initialization model based on the basic data; (c) performing simulation operations based on the initialization model; and (d) The result of the simulation operation is output. 2. The scheduling method of the intelligent scheduling system according to claim 1, wherein the step (a) comprises the step (a1) inputting basic data, the step (a2) adjusting the basic data, and the step (a3) sorting basic data. 3. scheduling method according to claim 1 is characterized in that, wherein the establishment initialization model of this step (b) comprises step (b1) establishes virtual factory, step (b2) establishes equipment group, step (b3) establishes For the equipment model, step (b4) establishes a product model, step (b5) accepts the equipment parameters and product parameters set by the user, and step (b6) accepts the simulation start time point set by the user. 4. The scheduling method according to claim 1, wherein the simulation operation of the step (c) includes the step (c1) determining the product category, the step (c2) confirming the route number, and the step (c3) selecting the available equipment, and step (c4) simulates production. 5 . The scheduling method according to claim 1 , wherein the result of the step (d) includes the daily information of the equipment, the information of the simulated passing station, and the information of the simulated batch. 6 . 6 . The scheduling method according to claim 4 , wherein after the step (c4) is completed, the step (c1) can be returned to repeat the cycle. 7 .

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