JP2006512628A5 - - Google Patents

Description

Design support method for multi-variable variable production line

  The present invention relates to a design support method for a multi-variable variable production line comprising a combination of a job type layout and a flow type layout.

(Flow type, job type production, and multi-variable variable production line)
Conventional concepts related to production methods and physical distribution related to the production methods can be summarized into flow type and job type categories.

  Flow type: The workpieces are conveyed one by one on the conveyor, and each workpiece is sequentially delivered from one device corresponding to each production process to another device. This transfer can be performed at high speed. The slowest device in the line determines the productivity tact. Therefore, in order to improve productivity, the slower and cheaper device (s) are operated in parallel to catch up with the productivity tact of expensive systems. (For example, workflow represented by Ford)

  Job type: In a job shop type production method (hereinafter referred to as “job type”), production progresses as the transfer movement follows the order of the processes. This requires a long transfer time, so the system normally performs batch processing by keeping workpieces in stock. In order to improve the productivity of this production method, it is essential to increase the number of workpieces to be processed per badge. In addition, it is essential to increase the processing speed of a device with a heavy work load and to operate a plurality of devices in parallel. (For example, work flow represented by semiconductor factories)

  These two production methods are highly compatible not only with manual operations and manual transfer systems, but also with automated production lines and automated transfer systems.

  On the other hand, the U-shaped production line maximizes the use of human labor, and is particularly effective in a multi-variable variable production line. The U-shaped production line has a flow-type layout, where an operator transports a workpiece from one device to another and performs specific work using each device (usually a simple jig). The product is completed after going through the U-shaped production line.

  In addition to the above, as a multi-variety variable production line, there is a method in which the operator moves the apparatus toward the work body and performs production without moving the main work such as a Volvo method.

  In order to improve productivity by the flow type or job type production method described above, increasing the output (output) is a practical means.

  On the other hand, in the U-shaped production line, the improvement in productivity is realized not by increasing the production volume but by reducing the investment in factory equipment. That is, (1) make the operator work more efficiently, increase the work load per operator, and directly reduce the expenditure expense on the equipment, and (2) switch the equipment model, or a different model To reduce the total amount of factory capital investment by reducing the loss caused by inadequate planning and logistics, by operating the devices in parallel.

  Even if additional processes of batch processing are necessary to solve problems related to high costs, machinery or production tacts, operators can easily operate and operate job-type automated guided vehicles. As long as the transport distance is short, it is possible to partially incorporate the job type concept into the work flow of the U-shaped production line. It is of course possible to combine the advantages of both flow-type and job-type production methods.

  Further, the hardware necessary for the transport operation for the U-shaped production line is almost the same as that required for the job type. Nevertheless, it is known that the transport route cannot be planned in advance, so U-shaped production line software generally differs from job types, and this layout requires sophisticated software algorithms. It is thought.

  The present invention has been made in view of the above points, and an object of the present invention is to provide a production line design support method capable of planning a conveyance path in advance.

  In order to solve the above-mentioned problems, the present invention provides a design support method for a multi-variable production line comprising a combination of a job-type layout and a flow-type layout, while conveying a workpiece using an automatically guided pallet. An input process that accepts input of basic information such as equipment information necessary for the design of a variety-variable production line, and a model / unit determination process that determines the model and number of equipment required for the multi-variable production line are determined. A device array extraction step for extracting a plurality of device arrays based on a flow-type layout based on the model and number of devices, and a branch path for job-type layout is added to the transport paths of the extracted plurality of device arrays. Simulate the cost, space, and production volume of the branch path addition process and each device arrangement and transfer path candidate with the branch path added. Deployment to the simulation results, characterized by comprising a simulation step of providing as the determination information to determine the final device arrangement and the conveying path.

  In the present invention, first, the operator inputs the system design requirements of the production line such as the processing time, operation rate, factory facility cost, etc. of each process, and further, the weight (importance) of each of the above requirements is input. Second, the support system outputs several optimal production line candidates. And a support system performs a simulation about a candidate, respectively. Finally, an optimal production line is constructed by simulation.

In the present invention, the basic information in the input step includes the following information (1) to (4):
(1) Necessary steps (2) List of all devices required for each step (3) Production amount, space, investment amount required for each step (4) Processes that can be processed by a device having multiple functions It is preferable to include a list.

  In the present invention, the model / number determination step is executed by a step of receiving information regarding installation space, investment amount, and production capacity of the multi-variety variable production line, and a necessary number of devices and a plurality of functions of one device. A step of calculating the number of possible steps, a step of calculating a plurality of results generally satisfying the requirements regarding the installation space, the investment amount, and the production capacity from the calculation results of the step, and the production Preferably, the method includes calculating the amount, the investment amount, the standby time of each device, and the investment amount for the standby time of each device.

  In the present invention, the device array extraction step includes a step of calculating all combination permutations of device arrays based on the model and number of the devices calculated in the model / number determination step, and a transport distance weighted by transport efficiency. A step of receiving an input of an index; a step of measuring a transport distance index for each of the combinations of the apparatus arrangements calculated based on the input transport distance index; and a transport distance based on the measured transport distance index It is preferable to include a step of selecting a plurality of device arrangements from the side where the index is high.

  In the present invention, it is preferable that the branch path addition step is a step of adding a branch path to a combination result of a plurality of device arrays selected in the device array extraction step at a location that is not a flow-type conveyance path.

  In the present invention, it is preferable to perform a bolt neck analysis on the simulation result.

  In the present invention, first, the operator inputs the system design requirements of the production line such as the processing time, operation rate, factory facility cost, etc. of each process, and further, the weight (importance) of each of the above requirements is input. Second, the support system outputs several optimal production line candidates. And a support system performs a simulation about a candidate, respectively. Finally, an optimal production line is constructed by simulation.

(About multi-variable variable production line)
The work flow of the U-shaped production line as a multi-variable variable production line is very effective for production by various production apparatuses and production of products having a short product life.

  In addition, our previous PCT International Application No. 02-03229 (PCT / JP02 / 03229) proposes an ultra-compact precision production line called a desktop factory (hereinafter referred to as DTF) that is small and can be placed on a table. is doing. This DTF is one of the multi-variable variable production lines, and it is a production line where human work should be avoided as much as possible.

  Usually, the term “productivity” means the throughput per hour. In practical terms, the amount processed per “money value” is more important. In modern times, “productivity” should be defined as a production cost with respect to “total management cost” (hereinafter referred to as TCO) from the viewpoint of management. Here, the monetary value is the sum of factory capital investment and running cost, and includes indirect costs such as investment cost, education and training cost, environmental infrastructure construction, maintenance cost and scrap value, and is the final value of the product. .

  The above-mentioned U-shaped production line has many excellent points from the viewpoint of TCO. The plant capital investment consists of desks, equipment parts storage shelves, simple jigs and minimal stand-alone equipment. The energy preparation for the equipment is likewise minimal. In particular, the apparatus conforms to the standard, and has a great advantage in terms of the scrap value of the system. However, the U-shaped production line has higher education and training costs, personnel management costs, and clean environment maintenance costs compared to general production lines. Compared to automated production lines, quality assurance costs are also high.

  Nevertheless, it is generally known that U-shaped production lines offer very good productivity from a TCO perspective. The biggest advantage seems to be that the U-shaped production line greatly reduces management risks associated with production fluctuations and product life cycles.

(Policy for building a multi-variable variable production line)
When analyzing productivity based on TCO, an equilibrium must be sought for the following factors while making tradeoffs.

1) Realize flow-type movement and job-type movement (conveyance cost optimization).
2) Share expensive equipment across multiple product lines (costs to be shared and productivity tact).
3) Increase the operating time of expensive equipment and do not increase the number.
4) Reduce the total cost of factory equipment needed to manufacture the product.
5) Minimize the site area, factory operation cost, and environmental infrastructure construction cost (shortening the work flow).
6) Maximize productivity per hour for a given production volume.
7) Equipment reusability, disposal costs and product scrap value.
8) Eliminate wasteful movements and layouts that degrade product quality (technical choices such as contamination and vibration).

  Items 3), 4), 5), and 6) must be balanced by comprehensively evaluating the predicted production volume, product life strategy, scrap value, and existing equipment.

  Based on the above, (1) productivity improvement and improvement not dependent on volume expansion, and (2) production line design support method capable of analyzing factory equipment cost based on TCO, for example, design support system and design support program Is to provide.

(Request for transfer operation)
From the viewpoint of a multi-variable variable production line (U-shaped production line) that combines a job-type layout and a flow-type layout, there are the following requirements for the transfer operation.

1) The process sequence proceeds to the next process based on a flow type work flow.
2) If necessary from the viewpoint of factory equipment cost and production volume, carry out job type conveyance.
3) An interactive random access transfer operation is performed separately from the basic transfer operation.

  Among the above, at least the step 3) is not described in the prior art. However, an automatic guidance type pallet (hereinafter referred to as AGP) is used so as to skillfully interrupt the main work flow as an auxiliary conveyance operation whenever necessary, by loading machine parts and auxiliary members. If the equipment is fully automated, a device for picking up the component elements is required. However, in the U-shaped production line, the cost of the picking device is zero.

  In addition, the conveyance system using AGP is a new tracked automatic conveyance system. This aims to provide the flexibility of the automated guided vehicle and the high speed of the conveyor line and feed rod conveyance. These elements are described in Japanese patent applications 2002-113660 and 2002-150750.

  The purpose of Japanese Patent Application No. 2002-113660 is to reduce weight and to be compact, and this AGP can stably transport a work, and the AGP mechanism generates dust and the like while maintaining the cleanliness of the work area environment. And can be easily charged.

  This application describes one best embodiment of a self-guided pallet. As shown in FIG. 1 of Japanese Patent Application No. 2002-113660, the main components of AGP2 are wheels 6 on two parallel tracks, a motor that drives wheel 2, a battery that can be charged and that operates the motor, a workpiece 4 is a member 9 that can be loaded and removed from the AGP 2, a non-contact charging unit 11 a, and a control circuit. The non-contact charging unit 11b is disposed between the tracks 3 and faces the non-contact charging unit 11a of the AGP2.

  With regard to Japanese Patent Application No. 2002-150750, its purpose is to make it easier to change the trajectory arrangement or system.

  This application explains that the system has a station controller 6 corresponding to the station 5. The AGP 2 provides communication means for connecting to the station controller 6 via the station 5. The station 5 is arranged between the station controller 6 and the AGP 2 in order to ensure the communication. The station controller 6 can communicate with other station controllers. Further, the station controller 6 is a data transport means capable of transporting (receiving and transmitting) data, a communication means for communicating with the AGP 2 via the station 5, and a storage means for storing a step (routine) program for controlling the AGP 2. And an execution means for executing a process (routine) program.

  A transport system using AGP combines the advantages of two conventional transport systems on the production line. In other words, the flow type (so-called “assembly line”) is suitable for mass production and has the advantage of minimizing the transfer distance between each process in the system, and the job type (many batch processes are required). Is advantageous in that it enables transfer (round trip) between the school processes. The proposed system can be used in a flexible manufacturing system with a relatively small production volume and a wide range of product types.

(Design support method)
Before explaining the design support method of the multi-variable variable production line of the present invention, the possibility of using both job type and flow type functions as a production line will be considered based on the drawings.

(Fusion of flow type and job type random access)
FIG. 1 shows a flow-type transport topology. This is a very typical transport system found in free flow conveyors and the like. In FIG. 1, a so-called “return path” is provided.

  In flow layout, the overall productivity tact is dominated by the slowest process. As a result, the system must be adjusted to obtain a uniform productivity tact distribution throughout the process. Nevertheless, productivity tact can be well balanced. In addition, if “(slow process cost) << (high cost process)”, ie (slow process cost) is much smaller than (high cost process), it is necessary to run the slow processes in parallel. . There are two ways to do so. That is, (1) a parallel line is formed by a complete branch shop, and (2) a “multiple-intake” operation (see FIG. 2) is applied.

  Conversely, a job-type layout requires a topology in which processing devices are connected to the path in parallel. FIG. 3 shows an arrangement in which processing devices are connected in parallel to one transport path, and a workpiece can be transported from any processing device to another arbitrary processing device. In order to increase the throughput of the system, that is, in order to efficiently handle the request for simultaneous transport, a plurality of transport paths are provided, or the transport paths are formed in a loop shape (see FIG. 4).

  The job type transport system has a topology composed of a common passage and a branch line for carrying the work body to the apparatus. However, a plurality of transport vehicles are included in the topology by restricting one way on the common passage. Can be released. In this way, fused random access is provided to the job-type layout.

(Fusion or combination of job type layout and flow type layout)
FIG. 5 shows the topology of the conveyance path using both the conveyance path of the job type layout and the conveyance path of the flow type layout. 5 are rearranged as white circular conveyance paths in the order of A to F in FIG. The gray conveyance path (conveyance path G) in FIG. 5 is the conveyance path itself in FIG.

  Here, it is assumed that the work body moves along each conveyance path as indicated by an arrow. The workpiece is basically sent from the transport path A-E to the next adjacent process. As a result, the transport operation cannot differ from a given destination. However, the conveyance path G can provide a selective conveyance operation from an arbitrary process to another arbitrary process.

  Therefore, since the conveyance path G can provide the same function as the conveyance path F, the conveyance path F is omitted, and the function shares the same conveyance path when the two steps are shown in the topology of FIG. This is accomplished by an alternative means. In other words, this topology indicates that branching and merging have been added to obtain a random access function using a return path in a flow-type layout (see FIG. 7).

(Optimization layout-conventional way of thinking)
A specific example will be described regarding a method of mapping a layout that optimizes productivity by using a conveyance path having both a random access conveyance function and a flow conveyance function.

  An explanation will be given assuming an example of the following processing.

Device A: Assembly (3 hands for 3 parts)
Cost 0.5, tact 10
Device B: Application (Adhesion application is possible at a predetermined position)
Cost 0.5, tact 15
Device C: First-in first-out oven (adhesion annealing for a predetermined time is possible)
Cost 1.0, tact 5
Device D: Cooling (cooling after annealing)
Cost 0.5, tact 5
Device E: Dimension measurement cost 3.5, tact 3
Transport time tact 1
(Cost: million yen; tact: seconds)

  Assume that the above five devices assemble three mechanical parts (b, c, d) in order on the main work body (a). Of these, two mechanical parts (b, c) require adhesive coating, annealing and cooling processes. In addition, it is assumed that dimension measurement is necessary for the intermediate workpiece and the final product after being assembled to the main workpiece. To briefly explain this, assume that all parts are supplied in a predetermined arrangement. Table 1 shows the arrangement of the steps.

表２は、従来の手法のフロー型レイアウトで実行された処理工程の結果を示す。

Table 2 shows the results of processing steps performed with a conventional flow-type layout.

  Under this condition, dimension measurement accounts for 71% of the total cost of 19.5 million yen, and the operation rate of the dimension measurement process is 20%. The value obtained by multiplying the equipment cost by the operating rate (hereinafter referred to as “investment operating amount”) is 5.8 million yen in total. This means that only 5.8 million yen of the 19.5 million yen investment is used.

  The following formula shows the rate at which the investment amount is used (hereinafter referred to as the “investment amount utilization rate”).

(Σ (MT / Ct * device cost)) / total cost

  The above formula is an index representing the investment amount per unit time when the investment worked effectively. This indicator counts the cost of the device when the total availability cannot fully represent time. Even if the operating rate of low-priced equipment increases, the value of this index does not increase. If the operating rate of high-priced equipment increases, the index greatly improves.

  In the setting in which the devices are arranged in the order of the process processing, the numerical value of this index is less than 30%. This calculation is based on the assumption of 24-hour operation. In the case of operation for 8 hours, it becomes 10%. This means that the effective investment amount is only 10%.

  In order to increase the “investment amount utilization rate” to 90% or more, it is necessary to install additional devices and balance the tact of each device. That is, the actual problem here is that the productivity tact of each device cannot be balanced unless the production volume is increased.

  In addition, the numbers in this table assume a line length of 34 units per 19 units, which is assumed here as the basis for calculating cleanroom investments. The size of one unit is 500 mm × 1000 mm, and the clean room construction cost is 40 million yen / square meter.

  “Amount of play” is another unique index that we decided independently, and is shown as follows.

(1-Investment amount utilization rate) x Equipment cost

  This measure may be useful when trying to find a bottleneck for each unit cost of the device. However, when the entire line is considered, “play amount” has almost the same meaning as “investment amount utilization rate”.

  “Equipment price per product” is the equipment cost per product assuming annual production.

  As mentioned above, the optimization of the production line of the conventional technology has been evaluated based on a new index “investment rate of investment amount”. As mentioned above, it has been understood that productivity will not improve unless the production volume is increased in the conventional sense. (As long as the equipment specifications are fixed, if the production is small, the productivity tact must be balanced. Is impossible.)

(Process layout optimization-DTF concept)
Next, let us consider a production line that functions without depending on the expansion of production volume.

  It should be noted that expressing the number of necessary devices as a ratio is important as a means of improving the “investment amount utilization rate”.

  If this concept (that is, 1/2 or 1/3) is accepted, the investment amount utilization rate of mass production can be applied to small-quantity production. By the way, if you use 0.85 devices A, 1.25 devices B, 0.44 devices C, 0.44 devices D, and 0.25 devices E, 100% investment The simulation shows that a monetary occupancy rate, that is, a 100% occupancy rate for all devices is obtained.

  Here, it is verified whether the idea of counting with the condition that the number of devices is not an integer is feasible. Assume that a job type function using a flow type layout in which one apparatus described above is used in different processes is applied. In addition, the number of apparatuses necessary for executing one process is assumed to be 1/2 and 1/3 for convenience. The equipment used in the above example process may be represented in a non-integer form as follows:

Device A: 1/3, 2/3, 1, 4/3
Device B: 1/2, 1, 3/2
Device C: 1/2, 1, 3/2
Device D: 1/2, 1, 3/2
Device E: 1/4, 2/4, 3/4

  It should be noted here that the same device requires different tooling and different machine hands (the tooling choices are different in the following cases).

The value of the fraction which can obtain the investment amount utilization rate of 100% as described above is as follows.

A0.85 units 1 unit B1.25 units 3/2 units (3 units in 2 processes)
C0.44 units 1/2 units (1 unit in 2 processes)
D0.44 units 1/2 units (1 unit in 2 processes)
E0.25 unit 1/4 unit (1 unit in 4 processes)

  If the investment amount utilization rate is recalculated using the number of units in the above fraction, an utilization rate of 90% or more is required.

Investment amount utilization rate 91%
Equipment cost 8 million yen Production volume 133,000 products CR investment amount 1.6 million yen Play amount 650,000 yen Equipment amount 5 yen per product

  This calculation result shows that 133,000 product production can be realized in 2/3 area at a cost of 1/2, in other words, the same rate optimized for about 4 times production is applied to this case. (This prediction does not assume the effect of DTF technology, whose technical objective is minimization of the device itself, and assumes that existing conventional devices will be used for all the criteria to be compared. If the effect of DTF is taken into consideration, a higher effect is expected).

  Although not specifically described here, another advantage of using equipment per product by fraction is also a significant reduction in inventory on the production line.

The production line according to the present embodiment described above has the following problems.
1) How many steps can one device handle?
2) To what extent can the workpiece be transported flexibly?
Both the means 1) and 2) can be logically pursued, but this limits costs, process adjustments, maintenance, etc. In other words, the device design limits the possibility of providing the functions of 1) and 2). As a result, it is necessary to evaluate in advance the possibilities and risks associated with performing the steps listed in Table 1.

  In the present embodiment, a DTF robot is proposed as a solution to the problem 1), and an AGP transport system is proposed as an answer to the problem 2).

(DTF type robot)
DTF type robots are less expensive than robots provided in prior art automated assembly lines. The DTF robot under development is characterized by the following.

(1) Configuration that can realize significant cost reduction
(2) Enhanced tooling freedom of orthogonal robot
(3) Enhanced linearity of orthogonal robot (in one direction)
(4) High cleanliness of joint robot
(5) Securing the ratio of the installation area to the work area of the joint robot
(6) Possibility of direct drive of XY positioning mechanism to ensure absolute accuracy

  Here, (2) and (5) are very important when a plurality of functions are to be given to the robot, and more important for a DTF robot that reduces the size of the product.

(About AGP)
Next, AGP (advantage list: small intelligent transport vehicle) will be described with reference to FIG.

  In the design support method of the multi-variable variable production line of the present invention having the advantages of the flow-type layout and the job-type layout production line method, the automatic guided pallet system using AGP has the production tact, locus, operation rate, equipment cost, etc. It can be optimized using various parameters. Specifically, it is as follows.

1) An efficient production line can be constructed while minimizing line inventory.
2) There is no need to arrange the devices in the order of the processes.
3) Concentrate work on expensive high-speed devices. (For example, in the demonstration, one laser scanning precision measuring instrument provides measurement work for three steps in random order.)
4) Production tact can be balanced by arranging devices that require long-term cleaning work in parallel.
5) The main work body and the machine part pallet can be transported on the same transport path.
6) Clean transfer is ensured by non-contact power supply = power supply at each station arranged in a distributed manner.
7) With reference position recognition accuracy of ± 0.5mm, no special positioning for marking, manual or image inspection is required.
8) A read-write type nonvolatile memory capable of reading and writing the pallet ID.
9) Ability to monitor a transport vehicle that takes a complicated transport path based on Windows ( registered trademark ).
10) Conveyance and layout design support tool that matches various optimizations

(About the flow to generate a production line)
Based on the above, the production line design support method of the present invention will be described with reference to FIG. A flow chart for generating a production line is outlined as follows.

(Step 1: Clarification of input process, technical seeds and needs)
1) Clarify the necessary steps.
2) List all equipment required for each process.
3) Specify the production volume, space, and investment amount required for each process.
4) List processes that can be processed by an apparatus having multiple functions.

(Step 2: Model / unit number determination process)
1) Enter the size of space, investment, production capacity, etc.
2) Calculate the required number of devices and the number of processes that can be executed by a plurality of functions of one device.
3) Calculate multiple trials and multiple results that generally meet the requirements of 1). The production amount, the investment amount, the standby time for each device, and the investment amount for the standby time for each device are listed.

(Step 3: Device sequence extraction process)
1) Enter a weighted transport distance index.
2) All the combinations of the arrangements of the devices selected in step 2 are calculated in a permutation, all the transport distance indices are measured, and a plurality of combinations having a high transport distance index are selected.

(Step 4: branch path addition process)
1) A route to the job is added to the result selected in step 3 at a location that is not a conveyance path of the flow type layout.

(Step 5: Simulation process)
1) Simulate with different transport times, transport costs, etc.
2) Simulate to estimate how many transport vehicles can be put in.
3) Calculate cost, space and production volume.

(Step 6: Create program)
1) Create a program for the production line selected by simulation.

(Step 7: Analysis of equipment used for actual production)
1) Produce products on selected production lines.
2) Check the transport vehicle via the monitor screen and collect data for the equipment used in the actual production line.
3) The bottleneck is analyzed based on the data collected as described above.
4) Feed back analysis results and improve production lines.

  Decisions are made according to the above procedure. A plurality of candidates are selected for each step, and an apparatus is selected in which the interactive designer “starts the process” by his / her decision and “reedits” the work flow and layout using his personal experience.

  In order to roughly screen candidates that are almost infinite from the permutation, a large amount of data often has to be processed. In order to increase the efficiency of sieving, it is necessary to introduce a genetic algorithm (hereinafter referred to as “GA”) below. In the next step 4, a branch path is set. FIG. 6 shows an example of a “branch path”, that is, a black transport path. In FIG. 6, a transport route that is not required for actual processing is deleted. The layout at this stage is adjusted to some extent by further simulation to ensure the analysis. By performing the simulation, the designer can further improve the efficiency of the system, and finally an actual layout and transport control program is created.

  After that, the program is downloaded to the equipment, the final adjustment is made by comparing the difference between the simulation result and the result of the production equipment used for actual production, and the bottleneck is analyzed using the equipment in the production line .

  Next, each step will be described.

(Step 1: Clarification of input process, technical seeds and needs)
As described in (Process layout optimization-DTF concept), in DTF, processing steps are assigned with a focus on productivity only, and overlapping steps are independent of the arrangement of devices and the transfer operation between devices. By designing as a phase that has been made, it is assigned to one device (multifunctional device).

(Step 2: Model / unit number determination process)
In order to select a desired device model and the number of devices, tentative proposals for parameters such as production volume (operation time), device design, space, and allowable investment amount must be generated. At this stage, the parameters are selected independently of the transport system and device arrangement. That is, if this work is to be performed by software, the software must include both analytical and integrated tools.

  It can be said that the analysis-type tool is characterized in that the operator can easily calculate the investment amount, the investment amount operating rate, and the operating rate of each device by manually inputting the required number of devices for each model. As a result, the analysis suggests the necessity of a plurality of functions or a plurality of apparatuses for balancing productivity tact.

  On the other hand, for the integrated tool, the operator inputs data relating to the device model, device function recognition, and the cost of each device. The data is processed according to the following instructions.

(1) Minimum space
(2) Minimum cost
(3) Optimal investment amount; variable production volume
(4) Guaranteed production volume; variable investment amount As an instruction, (1) The minimum space temporarily determines the number of required devices and the type of device that incorporates all possible multiple functions.

  As an instruction, (2) cost minimum compares the cost of giving a plurality of possible functions to one device with the cost of using the single function of the device. This comparison is performed for all combinations thereof. And the model and number of apparatuses are determined using the combination of the configuration and the lowest cost.

  As instructions, (3) To optimize the investment amount, reduce the number of devices as much as possible by using multiple functions until the cost of the combination matches the given investment amount. Reduced). The combination (s) that provide the maximum output is extracted.

  As an instruction, (4) in the case of optimizing the number of productions, a combination that guarantees the required production amount and investment amount is searched, and a combination that matches the required production amount is specified. A plurality of combinations with the lowest cost are extracted. In addition, when a plurality of devices are required for all models, an alternative production method is also presented in which two production lines are operated in parallel, resulting in production that is ½ of the initial requirement.

  At first glance, it seems difficult to generate software that performs (3) and (4) above. However, the elements used in this permutation combination are the device type and the possibility that the device has multiple functions. Since the number of combinations is very small, almost all combinations can be evaluated. Table 3 shows the result of this permutation combination for the specific example shown in (Optimized layout-conventional concept).

(Step 3: Device sequence extraction process)
To determine the tentative arrangement order of the device arrangement based on the model and number of devices obtained as described above, the arrangement order of the device arrangement is changed, the fastest and least expensive method is extracted, and the designer is informed. Present. However, it is difficult even with a computer to calculate the transport time and the cost of the transport device in real time for all combinations resulting from the “permutation combination”. Further, this “permutation combination” includes contents beyond mathematics. In other words, if there are multiple devices with multiple functions, a simulation of all combinations must be performed to determine the desired device, and which device is best suited for the intended process. Don't be. This calculation requires an enormous amount of time.

  In order to eliminate wasteful conveyance operation without relying on simulation, it is necessary to roughly estimate a desired arrangement in the initial stage. In order to accomplish this work, a new index called the transport distance index is introduced. In this process, the transport distance index is obtained for all arrays resulting from a permutation of combinations including a multi-function device. Finally, the combination having the highest conveyance distance index is extracted.

  The transport distance index is given by the following simple rule. Here, the expected sequence is compared with the actual sequence. A score is given for each shift that must be moved from the original or assumed sequence. The total sum of the obtained scores becomes the transport distance index of the device arrangement.

  The following is an example of the scoring rules.

1 shift from right to left 5 / n
One shift from left to right -5 / n
Shift 3 or more from left to right 3 / n
Shift 2 left, then right 30
4 shifts left, then shifts right 50

  The scoring system under the concept shown in FIG. 7 is based on knowledge. (1) The path passing through the device is added in the case of a left shift. (2) The highest transfer efficiency can be obtained especially by one shift. (3) When the workpiece is returned by the return line, the longer the distance, the more advantageous the score. (The score is set based on the idea that a higher score is better. A shift from right to left and vice versa will produce the same result.)

  The score calculated in this manner is statistically analyzed, and the highest score is extracted. (For example, a score higher than 3σ)

  Thus, sequences that are not worthy of evaluation are excluded by this rough sieving.

(Step 4: branch path addition process)
The sequence candidates obtained above are arranged in a ring shape. Here, the sequence of steps is assumed to be ABCDBCE, and the sequence candidate is assumed to be ABCDE (see FIG. 9).

  When the route diagram of the line shown in FIG. 9 is prepared, a route to the job is added at a place that is not a flow type conveyance route, and the conveyance network shown in FIG. 10 is determined.

(Step 5: Simulation process)
At this stage, a program for necessary operations for the transport network is generated, and the program is simulated.

  The outline of the automation programming of each station is as follows. “Check the availability of the next station. Based on the availability check of the next station, declare“ occupied ”of both the seated station and the target station. As soon as the work body starts the seated station, the occupation of the seated station is released. "

  Nevertheless, in the case of a transport network that requires a reciprocating motion at a dead end where there is no place for the robot to travel, the number of devices (number of branches) that can be inserted into the “dead end / bag path” is calculated in advance. In addition to the target station, several stations can be secured in the bag path.

  Similar programs are generated for all stations.

  All of the sequence candidates obtained above are simulated, where we get the actual productivity tact for each sequence. Each sequence candidate is simulated for actual work tact and transport time and the data is further processed to extract a few candidates. The average output period is an evaluation function, and the highest average output period array is extracted as a final candidate.

  This simulation simultaneously calculates the following parameters as average values.

Module utilization rate Waiting time after completion of work due to an automatic guided pallet (hereinafter referred to as “AGP”) in the discharge queue Ratio of AGP passing through the module without receiving work

  This result is used for the bottleneck analysis described below.

(Step 6: Create AGP program)
Create a program for the production line selected by simulation.

(Manual program correction)
Here, as a bottleneck improvement by simulation, manual program correction is performed as shown in FIG. As a result of the above results, modules with low availability are classified into the following categories 3 and 4 based on the cause of the low availability.

1) Modules with many AGPs passing through them without any work 2) Modules with many queues that need to be discharged 3) Modules with many queues due to lack of ingestion 4) Assigned to one rail Module with many queues due to excessive bi-directional operation

  To solve the problems 1) and 2), it is proposed to add a dummy station for the module following the problem process. In this way, AGP of 1) passes quickly and waits for discharge. The queue of 2) does not need to be synchronized with other processes, so that the module data processing is accelerated.

  For 3), it is proposed to connect the previous process to the branch path. In this way, AGP can be taken from the branch path.

  With regard to 4), it is proposed that one route has three lanes, and the throughput of the entire transportation can be increased.

  Based on these proposals, the designer himself / herself makes judgments and interactively executes changes in accordance with the proposals. The designer optimizes the final shape of the transport network and its productivity by calculating the number of AGPs that can be put into the production line.

(Change by manual mode)
When it is considered that the layout should be changed in the simulation process, the layout is changed in the manual mode, and the productivity and cost of the new layout are confirmed. A complete layout has not yet been obtained by automatic layout using automatic programming. Therefore, human thought is indispensable for the change and improvement in this manual mode.

(Main effects of this embodiment)
In DTF as a multi-variety variable production line, first, the operator inputs the system design requirements of the production line such as the processing time, operation rate, factory equipment cost, etc. of each process, ) Is entered. Second, the support system outputs several optimal production line candidates. And a support system performs a simulation about a candidate, respectively. Finally, an optimal production line is constructed by simulation.

  In addition, introduction of an automatic guidance pallet (hereinafter referred to as AGP) enables transfer between processes in a production line by combining a flow-type layout and a job-type layout that are merged or “joined”. This method can balance the productivity tact of the apparatus without depending on the expansion of the production amount. Flexible layout that meets various requirements, such as when expensive equipment needs to be accessed multiple times, equipment installation is limited in area, and for low production, prioritizing minimum over investment optimization Can be created.

  It is difficult to determine a layout that meets this requirement by human thought alone because the process sequence and work flow do not match each other. The computer provides “brute force” evaluation data. Nevertheless, the amount of data that must be evaluated “brute force” is enormous, and even a computer cannot provide an accurate evaluation in the form of a simulation. To solve this problem, a basic evaluation is provided to provide initial candidates, which are then evaluated by simulation.

  Furthermore, the computer-assisted layout is incomplete and may require some improvement, such as the addition of a transport path. For this reason, it is essential that this production layout design method includes the interaction between humans and computers. In order to realize this new concept, it is important to provide analysts to diagnose where bottlenecks are in the process.

  The above description and drawings disclose the present invention, but it will be apparent to those skilled in the art that modifications can be made without departing from the spirit and scope of the present invention.

The basic flow type production system of the prior art is shown. A plurality of prior art flow type productions are shown. 1 shows a conventional job-type conveyance path. A double common conveyance path system is shown. 1 illustrates a transport system having both flow and job transport paths. 1 illustrates a transport system having both flow and job transport paths. 7 shows an alternative embodiment of the embodiment shown in FIG. 2 shows a flowchart of the system of the present invention. Sequence candidates are shown. The final transport network is shown. It is an illustration of a flow. It is an illustration of an automatic guidance type pallet (AGP). Orbit change unit.

Claims (6)

A design support method for a multi-variable variable production line consisting of a combination of job-type layout and flow-type layout, while conveying workpieces using an automatic guided pallet,
An input process for receiving input of basic information such as device information necessary for designing the multi-variable variable production line;
A model / unit determination step for determining the model and number of devices required for the multi-variable variable production line;
A device array extraction step for extracting a plurality of device arrays based on a flow-type layout based on the determined model and number of devices;
A branch path addition step of adding a branch path for job type layout to the transport paths of the plurality of extracted device arrangements;
Simulation for simulating cost, space, and production volume for each device array and transport path candidate to which the branch path is added, and providing simulation results as decision information for determining the final device array and transport path A design support method for a multi-variety variable production line characterized by comprising a process. The basic information in the input step includes the following information (1) to (4):
(1) Necessary steps (2) List of all devices required for each step (3) Production amount, space, investment amount required for each step (4) Processes that can be processed by a device having multiple functions 2. The design support method for a multi-variety variable production line according to claim 1, further comprising a list. The model / number determination process is as follows:
A step of receiving input of information relating to an installation space, an investment amount, and a production capacity of the multi-variable variable production line;
Calculating the number of necessary devices and the number of processes that can be executed by a plurality of functions of one device;
Among the calculation results of this step, calculating a plurality of results that generally satisfy the requirements for the installation space, the investment amount, and the production capacity;
The design of the multi-variable variable production line according to claim 1 or 2, further comprising a step of calculating an investment amount for the production amount, the investment amount, a standby time of each device, and a standby time for each device. Support method. The apparatus sequence extraction step includes:
Based on the model and number of the devices calculated in the model / number determination step, a step of calculating all the device array combination permutations;
Receiving an input of a transport distance index weighted by the transport efficiency;
Measuring the transport distance index for each of the calculated combinations of the device arrangements based on the input transport distance index;
4. The multi-variety variable production line according to claim 1, further comprising a step of selecting a plurality of device arrangements from the side with a high transport distance index based on the measured transport distance index. Design support method.   The branching path adding step is a step of adding a branching path to a combination result of a plurality of apparatus arrays selected in the apparatus array extracting process at a location that is not a flow-type conveyance path. 5. A design support method for a multi-variable variable production line according to any one of 4 above.   6. The design support method for a multi-variable variable production line according to claim 1, wherein the simulation result is subjected to bolt neck analysis.