JPH10277500A - Multistage weight sorter and method therefor as well as memory medium recorded with multistage weight sorting program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make it possible to satisfy the total number of pieces and total weights in respective ranks with respect to the objects to be weighed which have variations in weighed values and are subjected to multistage sorting and to approximate the total weights after the sorting to the regulated designation weights. SOLUTION: When the total weights and total numbers of pieces are inputted from an operating means 10, a processing means 12 calculates the average weights of the respective ranks, calculates the limit values of the respective ranks in accordance with the adjacent average weights and set distribution ratios and sets these values in a rank sorting means 14. This rank sorting means 14 judges which ranks are the weighed values of the objects to be weighed which are weighed by the weighing means by referencing the limit values. The means discharges the objects to be weighed from the discharge chutes of the corresponding ranks. The objects to be weighed are continuously discharged and boxed until the total weights and the total number of pieces are satisfied.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a multi-stage weight selecting apparatus and method for selecting objects to be weighed according to multi-stage ranks based on weighed values of objects to be weighed, and to control multi-stage weight selection by a programmed computer. To a device that

[0002]

2. Description of the Related Art A multi-stage weight sorter is configured so that an object to be weighed is set in advance into a plurality of ranks, and a discharge process is performed to a corresponding rank according to a weighed value of the supplied object to be weighed. I have. The configuration of this multi-stage weight sorting apparatus is disclosed in Japanese Patent Publication No. 2-16978 filed by the same applicant.

[0003] An example in which the apparatus is applied to multi-stage selection of fresh fish will be described with reference to the schematic diagram of FIG. Each rank is packed in a box so as to uniformly fill the indicated weight of 7.5 kg.
The number of tails in each rank is 40, 45,
It is assumed that the number of tails is set to 50, 55, 60, etc. For example, the average target mass of one fish is 136 g in the rank of 55 7.5 kg, and the average target mass of one fish is 125 g in the rank of 60 7.5 kg.

In order to rank the objects to be weighed after weighing, an intermediate value (ratio of 5: 5) between the average target masses of adjacent ranks is set as a limit value L, and weighing is performed based on the limit value L. A method of allocating to any rank by value is widely used. For example, the limit value L for ranking 55 and 60 tails is 136 g and 125
g is set as the median value, i.e., 130.5 g, and the fresh fish with a weighing value of 130 g is sorted to a rank of 60 fishes,
40 g of fresh fish is sorted to a rank of 55 fish.

[0005]

However, setting the limit value as described above is effective when the probability distribution of the weighing value of the weighing object is a uniform distribution, but it is effective for natural catching and harvesting. For fresh fish or the like, the distribution of the measured values varies depending on factors such as the timing of the harvest and the location of the catch.

For example, assuming that the weighing value is normally distributed between 40 and 60 fishes as shown in the figure, if many fresh fish near the limit value are weighed, for example, when the limit value is 130.5 g, When about 130 g of fresh fish are continuously weighed, the weight of the box at the rank of 60 fishes will be shipped as a weight greater than 7.5 kg.
At the same time, the rank of 55 fish weighs less than 7.5 kg.

[0007] It is not preferable that the weight after packing is not less than the specified notation weight. Generally, a shipping company handling a sorting device calculates the boxing weight as notation weight (7.5 kg) + insertion amount (about 100 g). We ship with the standard which we did. With the conventional setting of the limit value, it is impossible to approach this entry to the specified notation weight, and even if the entry is provided, it is shipped with a weight heavier than this entry, and unnecessary loss The minutes remained unresolved.

[0008] In particular, when the multi-stage weight sorting device is installed in a shipping company that needs to sort and ship a large amount of fresh fish in a multi-stage manner in a short time, the extra loss generated in each box becomes large. Become. As described above, although there is a demand to make the boxing weight as close as possible to the indicated weight (7.5 kg or the like) as much as possible at any rank, there is no specific solution.

It is also conceivable to manually adjust the limit values to vary the ratio between the average target masses of adjacent ranks. However, in this manual adjustment, each of the plurality of limit values must be individually adjusted. Misconfiguration is easy to occur.
Further, in order to reduce the number of insertions, it is necessary to adjust each of the plurality of limit values after grasping the distribution constant of the weighing value of the object to be weighed. If an incorrect setting is made here, the weight of the box in the adjacent rank may be lower than or substantially higher than the indicated weight.

Further, the distribution constant (variation of the measured values) described with reference to the above-mentioned figure moves in the direction of the dotted line in the figure, etc.
Each time the distribution constant itself changes (such as a change in the height of the distribution curve), the limit value must be manually adjusted each time, which is complicated. The distribution constant changes due to factors such as a difference in the timing and location of fresh fish.

In the above description, an example has been described in which the objects to be weighed are fresh fish to be caught. However, the present invention is not limited to this. A similar problem arises when weight sorting is performed.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems, and satisfies the total number and the total weight in each rank for an object to be weighed which has a scattered weighing value and is selected in multiple stages. It is an object of the present invention to provide a multi-stage weight sorting apparatus and method capable of bringing the total weight after sorting close to a specified notation weight, and a storage medium storing a multi-stage weight sorting program.

[0013]

In order to achieve the above-mentioned object, a multi-stage weight sorting apparatus according to the present invention is a multi-stage weight sorting apparatus which sorts a plurality of stages according to a weighing value of an object. Weighing means for measuring the weight of the weighing object, and a limit value defining a weight range of a plurality of ranks are set. An indicator that outputs a rank designation signal, and a discharge chute that is provided in accordance with the plurality of ranks and discharges the weighed object to a corresponding rank based on the rank designation signal output from the indicator,
The indicator has input means for inputting the total weight of the objects to be weighed discharged from each rank, the total number of objects to be weighed for each rank, and the total input from the input means. A process of determining an average weight for each rank based on the weight and the total number, and setting a limit value defining the weight range between adjacent ranks according to the average weight for each rank and a preset distribution ratio. And means are provided.

According to a second aspect of the present invention, a distribution constant is input to the input means as a variation in the weighing value of the object to be weighed, and the processing means sets a limit based on the average weight and the distribution constant for each rank. A configuration for setting a value may be adopted.

According to the multi-stage weight sorting method of the present invention, in a multi-stage weight sorting method for sorting in a plurality of stages according to the weighing value of an object, a total weight of the object to be weighed at each input rank and a plurality of weights are selected. Calculating an average weight for each rank based on the total number of objects to be weighed for each rank, according to an average weight between adjacent ranks among the calculated average weights, and a predetermined distribution ratio set in advance; Calculating a limit value defining the weight range of each rank, weighing the weight of the object to be weighed, and determining the rank of the object to be weighed based on the limit value of each rank. It is characterized by:

According to a fourth aspect of the present invention, in the step of calculating the limit value, each rank limit value is calculated based on an average weight of adjacent ranks among the calculated average weights and an input distribution constant. May be calculated.

The storage medium storing the multi-stage weight selection program of the present invention is a storage medium storing a multi-stage weight selection program for selecting an object to be weighed into a plurality of stages according to a weighing value by a computer, The sorting program allows the computer to calculate the average weight of each rank by inputting the total weight of the objects to be weighed in each rank and the total number of the objects to be weighed in each of a plurality of ranks. The method is characterized in that a limit value that defines a weight range of each rank is calculated according to an average weight between adjacent ranks and a predetermined distribution ratio set in advance.

Further, the distribution ratio may be configured to be individually input and set for each rank in accordance with the type of the object to be weighed and the like.

According to a seventh aspect of the present invention, there is provided a storage medium storing a multi-stage weight selection program for selecting an object to be weighed into a plurality of stages in accordance with a weighing value by a computer. The computer calculates the total weight of the objects to be weighed in each rank and the total number of the objects to be weighed in each of a plurality of ranks to calculate the average weight of each rank. And a limit value that defines the weight range of each rank is calculated based on the average weight and the distribution constant indicating the variation in the input weighing value of the object to be weighed.

Further, the distribution constant is stored in advance as an actual value selected by the apparatus in the past for each type of the object to be weighed, and the actual value is read and input. You can also.

When the total weight common to each rank and the total number of individual ranks are input by operating the indicator 5 of the apparatus, the processing means 12 calculates the average weight Cn for each rank based on the total weight and the total number. , The average weight C of adjacent ranks
A boundary value (limit value) between ranks is calculated according to n and a preset distribution ratio α. The object to be weighed is weighing means 3
, The rank of the measured value is determined by a plurality of limit values, and the measured value is discharged from the discharge chute 4 of the corresponding rank.

[0022]

FIG. 1 is a side view showing a multi-stage weight sorter. The apparatus includes a sorting unit 1 for sorting objects to be weighed in multiple stages by weight, a weighing unit 3 provided in the middle of the transfer of the transfer conveyor 2 in the sorting unit 1, and a plurality of discharge chutes 4 (4a to 4n, n ) And an indicator 5 for controlling each part of the apparatus.

An introduction unit 6 into which an object to be weighed is introduced is provided on the sorting unit 1. The introduced object to be weighed is conveyed in the direction A while being leveled on the introduction unit 6, and inverted at a point C. At the same time, it is transferred onto the conveyor 2 of the sorting unit 1. The sorting unit 1 is driven to be conveyed in the direction shown in the figure by the driving means 7, and the weighing means 3 provided in the middle of the conveyance measures the measured value of the object to be weighed. The measured weight value is output to the indicator 5, and the indicator 5 determines which of a plurality of preset ranks corresponds to which rank. The configuration of this ranking is omitted because it has been described above.

When the object reaches the discharge chute 4n of the corresponding rank, the indicator 5 selectively activates a sorting gate provided at the discharge chute,
The object to be weighed is discharged to the discharge chute 4n of this rank. At the end of the discharge chute 4, storage boxes of the same size are prepared, and the boxes are packed until the total weight reaches a preset value. Here, the indicator 5 adds the measured values of the objects to be weighed discharged from the respective discharge chutes 4 and discharges them until the total weight of the boxes is reached.

FIG. 2 is a diagram showing a hardware configuration provided in the indicator 5, showing a main part of the apparatus of the present invention. An operation means 1 including a keyboard and the like is provided on the indicator 5.
0, processing means 12 comprising a CPU, RAM, ROM
And a rank selecting means 14 for rank-selecting the objects to be weighed based on the processing results of the processing means 12. The operating means 10 is provided on the housing of the indicator 5 and can be operated externally.
2. The storage unit 13 and the rank selection unit 14 are provided in a circuit unit in the housing.

First, the first embodiment will be described with the above-described configurations as configurations common to the respective embodiments. From the operating means 10, the total weight Wt (boxed weight) common to each rank, the total number Bn for each rank, the upper limit value Lu,
The lower limit value Ld is input. The total number Bn is plural (B1 to Bn) corresponding to the variation of the weight value of the object to be weighed.
Is set. The processing unit 12 calculates a plurality of limit values Ln (n = 1 to n) for each rank selection based on the total number Bn input and the total number Bn for each rank.

In the storage means 13, a plurality of files for calculating the plurality of limit values are temporarily created. The created files are a Wt storage file, a Bn storage file, an average weight Cn storage file (n = 1 to n),
This is a limit value Ln storage file (n = 1 to n). Further, the storage means 13 stores a fixed distribution ratio α (for example, α =
0.5) is provided. The distribution ratio α is input in advance by operating the operation unit 10. In addition, the input upper and lower limit value L
u and Ld are stored in the Lu and Ld storage files. The upper and lower limit values Lu and Ld are used in order to exclude an underweight or an overweight object Wk from the rank classification process and discharge it from the discharge chutes 4 of the discharge chutes 4 assigned as defective ranks during multi-stage sorting. Used.

The rank selecting means 14 determines, based on the plurality of limit values Ln calculated by the processing means 12, which of the plurality of ranks the weighing value Wk inputted for each weighing of the weighing object belongs to. , And outputs a rank designation signal R. On the basis of the rank designation signal R, the multi-stage weight sorting apparatus selectively operates the corresponding sorting gate when the object reaches the discharge chute 4n of the corresponding rank as described above, thereby moving the object to be weighed. Rank discharge chute 4
to n.

Next, the process of calculating the limit value Ln for each rank will be described with reference to the flowchart of FIG. First, the total weight Wt (boxed weight) common to each rank and the total number Bn for each rank are input from the operating means 10 (SP).
1). The input Wt and Bn are temporarily stored in the Wt storage file and the Bn storage file, respectively. Here, the total weight Wt is the total value of the notation weight Wh and the notch Wi of the box of the size common to each rank, and the object to be weighed is added to the box by the notch weight in addition to the notation weight. Is input as a goal. In addition, the total number Bn is different for each rank-based box, and the total number of objects to be weighed put in each rank-based box is input.

The processing means 12 stores the Wt storage file, B
Wt and a plurality of Bn are read from the n storage files, and an average weight Cn for each rank is calculated (SP2). The average weight Cn for each rank is based on the total weight Wt common to each rank and the total number Bn for each rank, and an arithmetic expression of Cn = Wt / Bn (1) (where n is 1 to n) is executed. It is obtained by doing. Obtained C
n is temporarily stored in the average weight Cn storage file (SP3).

The above equation (1) shows the average weight Cn at a certain rank, and the processing means 12 repeatedly processes the above equation (1) until the average weights C1 to Cn of all ranks are obtained (SP4). ). Specifically, initially, after C1 is obtained from the Bn storage file based on the value of rank 1 (B1), the value of B2 of the next rank is read from the Bn storage file to change the rank, and Obtaining the average weight C2 in the rank is repeated.

After the average weight Cn of all ranks is obtained, the limit value Ln for each rank is calculated. First, the average weight C1 to Cn of the reference rank and the rank adjacent to this rank are read from the average weight Cn storage file (SP5). For example, based on rank 1, the average weights C1 (Cn) and C2 of rank 1 and rank 2 respectively.
(Cn + 1) is read. The fixed distribution ratio α is read from the distribution ratio α storage file (SP6).

Next, the processing means 12 calculates the limit value Ln in the reference rank based on the read average weights Cn and Cn + 1 of the rank and the fixed distribution ratio α (SP).
7). Ln = Cn + ((Cn + 1) −Cn) × α) (2) (where n is 1 to n) The obtained Ln is temporarily stored in the limit value Ln storage file (SP8).

The above equation (2) indicates the upper limit value Ln of a certain rank as a reference.
2 repeatedly performs the above equation (2) until the limit values C1 to Cn of all ranks are obtained (SP9). Specifically, after initially obtaining the limit value L1 of rank 1 (C1), the process of reading the value of the next rank C2 to change the rank and repeating the process of obtaining the limit value L2 for the next rank is repeated. .

By the above series of processing, a plurality of ranks C1
To Cn and the limit values L1 to Ln for each rank are obtained and set in the rank selection means 14. FIG. 4 shows each rank C1 to C5 with the horizontal axis representing weight and each limit value L1.
It is a figure which shows the setting state of L4. Here, the distribution ratio α
Is set to 0.5, an intermediate value between the average weights Cn of the adjacent ranks is set as the limit value Ln.

To explain using a specific example, when sorting fresh fish as multi-stage weights as objects to be weighed, the total weight Wt packed in each box is assumed to be 7.5 kg, and the total number Wt of each rank (total Number of tails) are 60, 55, ..., 40 respectively
A description will be given of a case where five ranks are defined such as tails and the set distribution ratio α is 0.5. In this case, by inputting Wt and each Bn, the average weight Cn in each rank is C1 = 125 g as shown in FIG.
Calculated as C2 = 136 g,..., C5 (Cn) = 188 g. Also, the limit value L1 in the rank of C1
Is the weight of the intermediate value of these C1 and C2, 130.5 g, and L2 of the rank of C2 is 143 g,.
(Ln) becomes 177.5 g.

By setting the limit values L1 to Ln of each rank in the rank selecting means 14, it is possible to perform multi-stage weight selection by the multi-stage weight selecting device. And
Fresh fish as an object to be weighed is leveled on the introduction unit 6 and then transferred to the sorting unit 1. When the fresh fish is weighed by the weighing means 3, the measured value Wk is output to the indicator 5.

The rank selecting means 14 in the indicator 5 determines which rank the measured weight Wk is. For example, when the weighing value Wk is 134 g, the limit value L1
(130.5g), limit value L2 (143g)
The fresh fish is determined to be of rank 2 (55 fish) based on the result of (1), and the corresponding rank designation signal is output to the sorting unit 1. As a result, the sorting unit 1 sets the discharge chute 4 of the rank corresponding to the fresh fish.
Is reached, the corresponding sorting gate is selectively operated to discharge the object to be discharged to the discharge chute 4 of this rank.

Incidentally, the rank selecting means 14 determines whether the upper limit value Lud is exceeded or the lower limit value Ld is exceeded.
When a weighing value Wk that is lower than the above is input, it is determined to be a defective rank and discharged to the corresponding discharge unit 4 portion.

In the configuration for automatically calculating the limit value L as in the above configuration, the limit value is changed when the type of the weighing object is changed (for example, when the size of the weighing object is changed). At the time of the fluctuation of the weighed value), a. When the size of the box changes and the indicated weight changes, b. The case where the insertion has changed (including when the weight of the box is changed), the time when the total number (number of tails) for each rank is changed, and the like.

Although the distribution ratio α in the above configuration is a numerical value that is 0.5, it is treated as a constant in the calculation process in the above equation (2). According to this configuration, each rank C
Limit values L1 to Ln of 1 to Cn are set to intermediate weight values of average weights C1 to Cn of adjacent ranks. That is, since the distribution ratio α means that the limit value Ln distributes the weight range of each rank Cn to X: Y (5: 5), the distribution ratio α is not limited to the above equation (2), and is not limited to the above equation (2). : Y
Can calculate the limit value Ln with the same distribution ratio α even in other calculation processes. Since the distribution ratio α is applied to all ranks, it is effective when the variation in the measured values of the objects to be weighed has a uniform distribution.

The distribution ratio α can be variably set to a different distribution ratio α, for example, a distribution state of 4: 6, by operating the operation means 10 (operation input of the distribution ratio setting means). At this time, the numerical value of the distribution ratio α used in the above equation (2) is 0.4. This change of the distribution ratio can shift the limit value Ln to the heavier side when the variation in the weighing value of the object to be weighed has a predetermined distribution constant (for example, a normal distribution). The weight of the box can be brought closer to the indicated weight. In addition, a different distribution ratio α can be used for each rank, and an appropriate limit value can be set in accordance with the degree of variation in the measured values of the objects.

Next, a second embodiment of the present invention will be described. FIG. 5 is a diagram showing a hardware configuration of the second embodiment. In the figure, description of the same components as in the first embodiment will be omitted. In this embodiment, a general constant is used for the distribution constant of the object to be weighed, that is, the average value X bar (the bar is described as a bar for convenience of the format, but a so-called X head is drawn) and the standard deviation S. In this configuration, a limit value Ln suitable for the leverage distribution constant is obtained. For this reason, in the present embodiment, the operating means 10 is provided with a distribution constant setting means so that the average value X bar and the standard deviation S can be input and set, and the storage means 13 stores the input distribution constant. Create a storage file.

FIG. 6 is a diagram showing the distribution of the objects to be weighed (fresh fish). The horizontal axis is weight, and the vertical axis is probability density. For example, when the distribution constant of the fresh fish is a normal distribution as shown in the figure, the distribution curve has a target curve on the light side and the heavy side with respect to the average value X bar.

In this embodiment, when calculating the limit value Ln for each rank, first, any one of the limit values Ln is calculated based on the fixed distribution ratio α described in the above-described embodiment by using the above equation ( It is obtained by performing the operation of 2). For example, to obtain the limit value L1 as a reference, the following is executed: L1 = C1 + ((C2−C1) × α). The distribution ratio α at this time is a value set in the distribution ratio α storage file. The limit value L1 obtained by the above calculation is temporarily stored in a limit value Ln storage file.

Thereafter, after each other limit value L2, the reference limit value Ln (L1), the value of Cn stored in the average weight Cn storage file, and the average value stored in the distribution constant storage file It is obtained by executing the following equation (3) with reference to the X bar and the standard deviation S.

[0047]

(Equation 1)

The value of w when the following condition is satisfied is set as the limit value L (n + 1) of the next rank. This limit value L (n + 1) is stored in the limit value Ln storage file.

FIG. 7 is a flowchart of a limit value Ln calculation process in the second embodiment. SP1-SP
Each process of calculating the average weight Cn of each rank shown in FIG. 4 is the same as in the first embodiment. Also, SP5 to SP
8, the same processing as in the first embodiment is performed in that only the limit value L1 for rank 1 is calculated.

Thereafter, all subsequent limit values Ln are sequentially calculated, and each limit value Ln (L2 to L4) is obtained based on the above equation (3). Explaining the specific processing contents of this equation (3), first, the limit value L1 of rank 1 is read from the limit value Ln storage file (SP
9). Also, virtual variable parameters Y, X, w are used in the limit calculation process. (W is added and adjusted by a fixed amount when necessary by a w increasing means 12a provided in the processing means 12 as described later.) These Y, X and w are cleared to 0 in the initial state (SP10).

Next, an operation is performed using the operation result of (w−C (n + 1)) × K (w) (4) as a parameter X (SP1).
1). The probability density K (w) at this time is obtained by reading the average value X bar and the standard deviation S from the distribution constant file and executing the processing of the following equation (5).

[0052]

(Equation 2)

The parameter X is replaced with a new parameter Y as Y = Y + X, and is temporarily stored in a parameter file (SP12). Next, it is determined whether or not Y is 0 or more (SP13). As a result, if Y> 0, it is determined that the above expression (3) is satisfied, and the parameter w stored in the parameter file at that time is set to the limit value L (n + 1 ) Is stored in the limit value Ln storage file (SP14).

On the other hand, if Y ≦ 0, w is increased by a predetermined amount by the w increasing means 12a (SP15). The increment is set in advance as w0. Since w0 affects the accuracy in calculating the limit value, it is set to, for example, 0.1 (g). After that, the process proceeds to SP11 and the same processing is performed. In this way, w when the parameter w is increased to satisfy the condition of SP13 can be obtained as the limit value L (n + 1) of this rank.

In the above processing, this rank 2, that is, rank 1
Is n, the limit value L2 at the rank of (n + 1), that is, L (n + 1) is obtained. After this, all ranks L1 to L
It is determined whether each of the limit values L1 to Ln up to n has been obtained (SP16). Thereafter, since the limit value L3 in the next rank 3 is obtained by referring to the limit value L2, Ln is changed to L.
After updating to (n + 1) (SP17), the process proceeds to SP9, and the calculation processing of the equation (4) is repeatedly executed in the same manner, to obtain the limit values Ln of all ranks, and the processing ends.

For example, the limit value L2 is calculated by the equation (3).
Based on

[0057]

(Equation 3)

The value of w when the following condition is satisfied is taken as the limit value L2 of rank 2.

The limit values Ln for all ranks are set in the rank selecting means 14, and, as in the previous embodiment, the limit values Ln
The objects to be weighed are sorted in multiple stages for each rank based on n.
According to this embodiment, when the weighing values of the objects to be weighed vary in a normal distribution, the limit value of each rank can be automatically set to a distribution ratio corresponding to the average weight Cn based on this distribution. . In this way, when the weighing objects are continuously weighed, if the weighing value of each weighing object occurs within the range of this normal distribution variation, the box after being assigned to each rank The packing weight can be made as close as possible to the target weight.

In the above description, the reference limit value Ln is described as the limit value L1 of rank 1. However, the lower limit value Ld is used as the reference limit value Ln.
The configuration may be such that the limit value L1 of rank 1 is obtained by executing the calculation with reference to the lower limit value Ln.

As a modified example of the above configuration, a general value is used for the standard deviation S of the distribution constant and the average value X bar. , A distribution constant can be used. For example, when the object to be weighed is a fresh fish, a past actual value can be obtained for the distribution constant depending on the catch timing, the catch location, and the like.
The distribution constant (standard deviation S,
And the average value X bar) in the distribution constant storage file,
ROM of the storage means 13 or HDD of the external storage means separately,
By storing the past history in a storable means so as not to be erased, it is also possible to adopt a configuration in which the limit calculation processing is executed by reading out the relevant weighing target when multistage sorting is performed. In this case, a more optimal limit value can be calculated with respect to the dispersion of the weighing values of the objects to be weighed, so that the package weight at each rank can be made closest to the target weight. Further, the present invention is not limited to the example described in the above-described embodiment, and may be configured to calculate the probability density of Expression (5) based on the frequency distribution of the past measured values.

[0062]

According to the present invention, the limit value can be set only by inputting the total weight of the objects to be weighed for each rank and the total number of objects for each rank, so that the limit value setting operation can be easily performed. In addition, even if the objects to be weighed vary in the weighing value, the total number and the total weight in each rank can be satisfied and the objects can be sorted in multiple stages. Further, even if the type of the object to be weighed is changed, it can be easily handled by a simple operation, and erroneous setting of limit values can be prevented. The limit value is determined according to a predetermined distribution ratio set after the average weight of each rank is determined based on the input total weight and total number. If the configuration is such that the distribution ratio is input and set, the total weight at each rank can be brought close to the set total weight. Further, if a configuration is adopted in which a distribution constant indicating the variation of the objects to be weighed is input instead of the distribution ratio, the total weight in each rank can be made closer to the set value. If a configuration is used in which a past actual value is used as the distribution constant, the total weight at each rank can be made closest to the set value. As a result, it is possible to reduce extra insertions while satisfying the notation weight specified when the objects to be weighed are packaged and shipped, so that the loss of the shipping company can be reduced.

[Brief description of the drawings]

FIG. 1 is a side view showing a multi-stage weight sorter of the present invention.

FIG. 2 is a diagram illustrating a hardware configuration according to the first embodiment.

FIG. 3 is a flowchart showing a limit value calculation process by the device.

FIG. 4 is a diagram showing a setting state of each rank and each limit value.

FIG. 5 is a diagram showing a hardware configuration according to a second embodiment.

FIG. 6 is a diagram showing a distribution state of measurement values of an object to be weighed (fresh fish).

FIG. 7 is a flowchart of a limit value calculation process according to the second embodiment.

FIG. 8 is a schematic diagram of multi-stage sorting.

[Explanation of symbols]

1 ... sorting unit, 2 ... conveyor, 3 ... weighing means,
4 (4a to 4n): discharge chute, 5: indicator, 6: introduction unit, 10: operating means, 12: processing means, 13 ...
Storage means, 14 ... Rank selection means.

Claims (8)

[Claims] 1. A multi-stage weight sorting apparatus for sorting a plurality of stages according to a measured value of an object to be weighed, wherein a weighing means for weighing the object to be weighed and a limit value defining a weight range of a plurality of ranks are set. An indicator that determines the rank of the object to be weighed according to the weighing value of the object to be weighed output from the weighing unit and outputs a corresponding rank designation signal, and a plurality of indicators are provided according to the plurality of ranks, A discharge chute that discharges the weighed object to a corresponding rank based on a rank designation signal output from the indicator,
The indicator has input means for inputting the total weight of the objects to be weighed discharged from each rank, the total number of objects to be weighed for each rank, and the total weight and the total number input from the input means. Processing means for determining an average weight for each rank based on the average weight for each rank, and setting a limit value that defines the weight range between adjacent ranks according to the average weight for each rank and a preset distribution ratio. A multi-stage weight sorter provided. 2. The apparatus according to claim 1, wherein the input unit receives a variance in the weighing value of the object as a distribution constant, and the processing unit sets a limit value based on the average weight and the distribution constant for each rank. The multi-stage weight sorter according to claim 1. 3. A multi-stage weight sorting method for sorting in a plurality of stages according to a weighing value of an object to be weighed, comprising: Calculating an average weight for each rank based on the total number; defining an average weight of adjacent ranks among the calculated average weights and a weight range of each rank according to a predetermined distribution ratio set in advance. Calculating a limit value to be measured, a step of weighing the weight of the object to be weighed, and a step of determining the rank of the object to be weighed based on the limit value of each rank. Sorting method. 4. In the step of calculating the limit value, each rank limit value is calculated based on an average weight of adjacent ranks among the calculated average weights and an input distribution constant. The multi-stage weight sorting method according to claim 3. 5. A storage medium storing a multi-stage weight sorting program for sorting an object to be weighed into a plurality of stages in accordance with a weighing value by a computer, wherein the sorting program stores the object to be weighed in each rank in a computer. The total weight of the items and the total number of objects to be weighed for each of the plurality of ranks are input to calculate the average weight of each rank, and the average weight of adjacent ranks among the calculated average weights is set in advance. A storage medium storing a multi-stage weight selection program for a multi-stage weight selection device, wherein a limit value defining a weight range of each rank is calculated according to a predetermined distribution ratio. 6. The multi-stage weight sorting program for a multi-stage weight sorting apparatus according to claim 5, wherein the distribution ratio can be individually set and set for each rank according to the type of the object to be weighed. The storage medium on which it was recorded. 7. A storage medium storing a multi-stage weight sorting program for sorting an object to be weighed into a plurality of stages in accordance with a weighing value by a computer, wherein the sorting program stores the object to be weighed in each rank in a computer. The average weight of each rank is calculated by inputting the total weight of the items and the total number of objects to be weighed by each rank, and the average weight of adjacent ranks among the calculated average weights is input. A storage medium storing a multi-stage weight selection program for a multi-stage weight selection device, wherein a limit value defining a weight range of each rank is calculated based on a distribution constant indicating a variation in weighed values of objects to be weighed. 8. The distribution constant is stored in advance as an actual value selected in the past by the apparatus for each type of the object to be weighed, and the like.
8. A storage medium storing a multi-stage weight selection program for a multi-stage weight selection device according to claim 7, wherein the actual value is read and input.