JPH04230573A - Method for planning production line - Google Patents

Abstract

PURPOSE:To prepare basic data for managerial judgment of a investment in plant and equipment etc., without requiring particular experience by classifying work time concerning a processor into process waiting time, processing time with operator intervention and processing time without operator intervention, and planning the production line based on the classification. CONSTITUTION:The planning method for the production line consists of a personnel operation system selection processing part 8, a personnel operation system-1 9 in a queue calculation part which assumes the personnel are those specialized operators who can operate only one sort of device and calculates the number of personnel and devices, and a personnel operation system-2 10 in a queue calculation part which assumes the personnel are those skilled operators who can operate plural sorts of devices and calculates the numbers of personnel and devices. The systems '1' and '2' both calculate the queue for the personnel and the queue for the number of devices. An equipment/personnel prediction data output part 11 specifies an output form and outputs information concerning the material for planning the production line.

Description

[Detailed description of the invention]

0001

[Industrial Application Field] The present invention relates to a manufacturing line planning method that allows estimation of the amount of equipment and number of operators in accordance with an annual production plan in a manufacturing factory by combining multiple processes. .

0002

[Prior Art] Estimating the amount of equipment and number of operators at a manufacturing factory is used to determine equipment investment plans and personnel allocation plans. Conventionally, this type of estimation method was based on the experience of each company. It was decided based on. In that case, it is normal to make a decision using a deductive method based on conventional experience. Therefore, when planning production facilities for new products using such a method, the method has not been established, and the planning decision has been extremely intuitive.

[0003] Furthermore, as a conventionally known prediction method using a computer, a calculation method based on a Markov process has been used.

0004

[Problems to be Solved by the Invention] However, in the conventional method using the Markov process, when used for planning general manufacturing equipment, it is necessary to define the chain of each processing step. When the manufacturing process involves hundreds of steps, such as planning production equipment, there is a problem in that a huge amount of computer resources are required.

[0005] The present invention has been made to solve the above-mentioned problems, and the purpose of the present invention is to make it possible to create basic materials for business decisions such as capital investment plans without requiring any particular experience. Our goal is to provide the technology that is possible.

[0006] Another object of the present invention is to provide a technique that makes it possible to predict equipment plans through extremely simple statistical calculations.

The above and other objects and novel features of the present invention will become apparent from the description of this specification and the accompanying drawings.

[0008]

[Means for Solving the Problems] In order to achieve the above object, the means (1) of the present invention includes a computer-based production line planning method, in which a series of processes related to a production line are
It is characterized by classifying according to the processing equipment, classifying the work time related to the processing equipment into processing waiting time, processing time with operator intervention, and processing time without operator intervention, and planning the production line based on this. shall be.

The invention (2) of the present invention is a computer-based manufacturing line planning method that uses a queuing method based on an annual throughput plan related to manufacturing equipment and each time element.
The method is characterized by determining the required number of personnel and required number of devices, and planning the production line based on this.

[0010] The invention (3) of the present invention uses a computer-based manufacturing line planning method to first calculate the annual throughput plan, operator intervention processing time, and allowable operator waiting time.
Determine the required number of operators and average operator waiting time,
Based on the results, predict the device exclusive time that the target object will use, and based on the device exclusive time, allowable processing waiting time, and annual throughput plan, calculate the required number of devices and the amount of time required for the device. It is characterized by determining the average working time involved and planning the production line based on this.

[0011]

[Operation] According to the above-mentioned means, it becomes possible to apply a queuing model based on mathematical analysis. Therefore, by showing the procedure for applying the work time analysis method and the queuing method when applying the queuing model, a logical method as a manufacturing equipment planning method can be achieved. This makes it possible to create basic materials for business decisions such as capital investment plans without requiring any particular experience. Furthermore, it is possible to predict equipment plans through extremely simple statistical calculations.

0012

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 is a block diagram showing a schematic functional configuration of a computer-based equipment/personnel prediction system according to an embodiment of the present invention.

In FIG. 1, 1 is the main control unit of the database management system, 2 is the process sheet editing processing unit, and 3 is the main control unit of the database management system.
is a data conversion processing unit that converts a database file into text, and each unit is controlled by a database management system. The creation and editing of this process chart database and the conversion of data file formation include:
Commercially available database software (eg, DB3) is used. The output data of the data converter 3 is stored on a floppy disk 4.

5 is a text EWS (Engineer
ing, Work, Station),
Reference numeral 6 indicates a text data reading processing unit, and reference numeral 7 indicates an information processing unit, which reorganizes process charts, organizes repeatedly used devices, etc. (that is, groups processes).

Reference numeral 8 denotes a staff operation method selection processing unit, and 9 represents staff operation methods 1 and 10 of a queue calculation unit that calculates the number of personnel and the number of devices assuming a specialized worker who can handle only one type of equipment. This is the staff operation method 2 of the queue calculation unit that calculates the number of personnel and the number of devices assuming that workers can handle many types of devices. In both of these personnel utilization methods 1 and 2, as shown in FIG. 5 or 6, queue calculations are first performed for personnel, and then queue calculations are performed for the number of devices. Reference numeral 11 denotes an equipment/personnel prediction data output unit, which specifies the output format and outputs material information used for manufacturing line planning. Reference numeral 12 denotes a main control unit for the program of the equipment/personnel prediction system of this embodiment.

In this embodiment, first, a series of manufacturing steps are classified according to each processing device. At the stage of formulating a manufacturing equipment investment plan, it is assumed that the series of manufacturing processes for the product in question are, in principle, clearly known, and it is not possible to create a configuration plan for the manufacturing line without this process being clarified. do not have. Therefore, it is possible to classify a series of manufacturing processes.

Furthermore, in a series of manufacturing processes, the same apparatus may be used in different manufacturing processes. For such processing apparatuses, it is common that the setup time and processing time are different depending on the processing method. If there is a large variation in the setup time or processing time, the time may be divided into groups and considered as separate devices, but in the case of this example, the variation is small for each device. Furthermore, it is assumed that the frequency distribution functions of setup time and processing time in each device are the same for all devices. Furthermore, the throughput of each device based on the annual manufacturing plan is determined by the product of the amount of input into the manufacturing line and the number of times the same device is used in a series of manufacturing processes.

Similarly, in order to obtain various products on the same production line, it is conceivable to manufacture them using different manufacturing processes. In this case, the throughput of each device is
It is defined by the sum of the products of the input amount for each product and the number of times the device is used at that time.

FIG. 2 is an example of a classification table for manufacturing processes.

Each manufacturing process is classified according to the equipment used. The basic setup method and usage conditions for each device are as follows:
It is desirable that they be the same. As already mentioned, the number of times the equipment is used for each manufacturing process is investigated. The information processing unit 7 in FIG. 1 investigates the number of times each device is used during the process, and reorganizes each time element. In other words, for processing times (T-2, T-3, T-5), the average value of processing times used in the process chart is equal to the allowable waiting time (T-5).
-1, T-4), the minimum value in the process chart is determined, and the table shown in FIG. 2 is created in the computer as a processing result of the information processing section 7 shown in FIG. Here, the processing time and operator intervention time will be described later. The price of each device has been investigated,
Used to calculate capital investment.

When the same type of manufacturing equipment is used in multiple types of manufacturing processes, the number of times the equipment is used is redefined as the sum of the times it is used in all manufacturing process types, ie, N=Σni. i is the manufacturing process type. Furthermore, the processing time and operator intervention time are defined as average values for each manufacturing process type. Specific calculations are provided separately.
This will be explained in detail when explaining FIG.

FIG. 3 is a diagram showing an example of a classification method of time management elements for one-step work time analysis according to the present invention.

As shown in FIG.
Break down into different types of time elements.

T-1 is a processing start waiting time, and within this time element, the objects to be processed are stored in the work-in-progress storage. According to the procedure of this embodiment described later, this time element is initially set as an allowable processing waiting time. And finally, it will be calculated as the average processing waiting time. Naturally, the calculated average waiting time is shorter than the allowable processing waiting time.

T-2 is the time for operator intervention for preprocessing. This is the time it takes for the product to be processed to be placed in the device and for the operator to leave the device. This time also includes setup time if necessary.

T-3 is the time when the device is automatically operated and does not require operator intervention. In other words, it is the time from when the processed product leaves the operator's intervention until the automatic processing ends.

[0027] T-4 is an operator waiting time, which is the time from when the automatic processing of the item to be processed ends until the operator starts post-processing. That is, during this time, the processed product remains in the device.

T-5 is the time for operator intervention for post-processing. This is the time when items to be processed are taken out of the equipment and handed over to storage for the next processing step.

[0029] Whether the processing time mentioned in the discussion of Figure 2 refers to the time of T-3 or the time of T-2 and T-3 will be clarified when creating the table in Figure 2. It is necessary to keep it.

As shown in FIG. 3, the time for exclusive use of the device is the sum of T-2, T-3, T-4, and T-5. In addition, the operator intervention time is the sum of T-2 and T-5, and in normal cases, after completing the work at T-5, the operator continuously shifts to work at T-2 on the newly processed product. It is normal to do so.

FIG. 4 is a diagram showing planning elements (production planning data) for the annual input amount of each product type for each manufacturing process.

[0032] Generally, a plurality of types are manufactured by the same manufacturing process. The total number of annual inputs is summarized according to the manufacturing process. In other words, the annual total input amount is Li
=ai+bi+... is defined as the sum of input amounts of each product type manufactured in the same manufacturing process.

FIG. 5 is a flow chart for determining the number of devices and personnel according to the present invention, and FIG. 6 is a flow chart for determining the number of devices, the number of personnel, storage space, etc.

First, production planning data is defined. Device operational data is then defined. Since the device exclusive time depends on the operator waiting time at T-4 in FIG. 3, first, the required number of operators is estimated. At this time, the operator's allowable waiting time is specified. The important point of the present invention is that, as shown in FIG. 5, queue calculation is first performed for the operator (step 102), and then queue calculation is performed for the processing in the device. (Step 103). Here, the reason why we first perform queue calculation for operators is that, as already mentioned, the allowable waiting time of operators is longer than the average waiting time of operators determined as a result of queue calculation. This is because when estimating the time during which a person will occupy the equipment, this exclusive time T-4 will be overestimated, which is inconvenient when considering a production line configuration with a short delivery time.

The queue calculation method will be further explained with reference to FIG.

First, production plan data, equipment operation data, allowable operator waiting time, and allowable processing waiting time are input (steps 201 to 204).

[0037] The arrival rate of work-in-progress (products processed in the device) is calculated by Σni×Li/Y for the annual total number of working hours Y.
(Step 205). In other words, the arrival rate of work-in-progress at the processing device is considered for all manufacturing process types produced on the manufacturing line (step 2).
06).

Queue calculation is already an established mathematical technique. For example, by using an M/M/n type queuing model (here, Kendall's representation format is used), a window (in the case of the present invention) that enables service to be provided within the operator's allowable waiting time (number of operators) can be statistically predicted (step 207)
. This calculation also recalculates the operator's average waiting time and also calculates the operator's service rate. As a general property of the queuing calculation results, the number of operators can be reduced by increasing the allowable waiting time of operators. Since an increase in the operator's allowable waiting time means a longer production period, this can provide material for management judgment in determining the balance between the operator's labor costs and the production period.

Queue calculation for processing in the device will be performed in substantially the same manner (step 208). As already explained in connection with FIG. 3, the device exclusive time is T
-2, T-3, T-4, and T-5. This time corresponds to the service time in the queuing model.

[0040] It is also possible to calculate the queue by inputting the allowable time from the time the product arrives at the work-in-process storage (storage location) until it is taken out from the work-in-process storage, that is, the allowable processing waiting time ( Step 209). This makes it possible to predict the number of required devices, average processing waiting time, etc. It is also possible to predict the required work-in-process storage space based on the average processing waiting time and the arrival rate of work-in-progress. As in the case of operators, if the number of devices increases, that is, if the amount of capital investment increases, the manufacturing period will be shortened and the storage space will also be reduced. Consideration of these factors can be used as a material for management decisions, as in the case of operators. In step 210, the processing time for each device type is calculated.

The above-described procedure provides an equipment planning method when there are constraints on both operators and equipment, such as difficulty in hiring operators or restrictions on equipment investment. However, if only one of the constraints is extremely strong, it is only natural that the queue calculation should be performed only for the one with the strongest constraint.

As can be seen from the above explanation, conventionally, the estimation of the amount of equipment and the number of operators in a manufacturing factory required basic knowledge based on past manufacturing experience, but according to this embodiment, No particular experience is required, and you can create basic materials for business decisions such as capital investment plans.

Furthermore, for example, an LSI manufacturing process is a collection of several hundred processing steps. Analyzing the movement of each work-in-progress with respect to such processing steps using mathematical means such as Markov chain requires an extremely large amount of computer resources. By applying the classification method of the present invention, it is possible to predict equipment plans through extremely simple statistical calculations. By the way, this calculation method can be applied to LS of about 300 processes.
When used to predict I manufacturing equipment, it was possible to predict all equipment within 5 minutes using a personal computer.

[0044] The present invention has been specifically explained above based on examples, but it goes without saying that the present invention is not limited to the above-mentioned examples and can be modified in various ways without departing from the gist thereof. Nor.

[0045]

[Effects of the Invention] As explained above, according to the present invention, basic materials for business decisions such as capital investment plans can be created without requiring any particular experience.

[0046]Furthermore, it is possible to predict the equipment plan by extremely simple statistical calculations.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing a schematic functional configuration of a computer-based equipment/personnel prediction system according to an embodiment of the present invention.

FIG. 2 is a diagram showing an example of a manufacturing process classification table (equipment operation data).

FIG. 3 is a diagram showing an example of a classification method of time management elements for work time analysis according to the present invention.

FIG. 4 is a diagram showing an example of planning elements (production planning data) of annual total input amount.

FIG. 5 is a diagram showing an example of a method for determining the number of devices, number of personnel, storage space, etc. according to the present invention.

FIG. 6 is a diagram showing detailed procedures for determining the number of devices, number of personnel, storage space, etc. according to the present invention.

[Explanation of symbols]

1 Main control section of the database management system 2 Work schedule editing processing section 3 Data conversion processing section 4 Floppy disk 5 Transmission processing section 6 Data reading processing section 7 Information processing section 8 Personnel operation method selection processing section 9 Personnel operation method 1 10 Personnel Operation method 2 11 is the equipment/personnel prediction data output unit 12 Main control unit of the program

Claims (3)

[Claims] Claim 1: In a manufacturing line planning method using a computer, a series of processes related to the manufacturing line are classified according to processing equipment, and the work time related to the processing equipment is divided into processing waiting time, operator intervention processing time, A manufacturing line planning method characterized by classifying processing time without operator intervention and planning the manufacturing line based on this. [Claim 2] In a manufacturing line planning method using a computer, the number of required personnel and the number of required equipment are determined by a queuing method based on an annual throughput plan related to manufacturing equipment and each time element, A manufacturing line planning method characterized by planning a manufacturing line based on this. 3. In a computer-based production line planning method, first, the required number of operators,
Determine the average operator waiting time, and based on the results, predict the equipment exclusive time that the relevant workpiece will occupy, and based on the equipment exclusive time, allowable processing waiting time, and annual throughput plan, A manufacturing line planning method characterized by determining the required number of devices and the average working time associated with the devices, and planning the manufacturing line based on this.