JPH06266735A - Information processing method/device - Google Patents

Abstract

PURPOSE:To easily and objectively decide an optimum remedy for the users to instantaneously and accurately grasp and analyze a large quantity of data on the state of a control subject, to decide the presence of problems and their factors, and to eliminate these problems. CONSTITUTION:The data are retrieved in relation to a certain state (101), and the information turned into a visible form or an index are prepared and transmitted (102). Then the result of analysis is supplied (103) and the state to be analyzed is decided (104). If the state to be analyzed is confirmed, this state is specified to repeat a series of preceding processings (105). If the state to be analyzed is not confirmed, a plan is supplied for improvement of the state (106). Then a virtual state is generated in response to execution of the supplied remedy (107) and then converted into the quantitative evaluation value (108). This value is transmitted (109) and a series of preceding processings are repeated for evaluation of the remedies as long as any unevaluated remedy exists.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION The present invention is centered on physical distribution systems.
Like an administrator who is responsible for integrated management (logistics) of a wide range of corporate activities from production to sales, many sites such as factories, distribution centers, and sales offices are simultaneously controlled from the perspective of overall management optimization. A person who has to do it accurately and efficiently grasps / analyzes all the site conditions from a large amount of data, discovers the hidden problem behind it, finds the cause, and decides an appropriate improvement plan. TECHNICAL FIELD The present invention relates to an information processing method and an apparatus for supporting the process.

[0002]

2. Description of the Related Art Conventionally, management of factories, distribution centers, sales offices, etc. has often been carried out on a site-by-site basis. There, though local, an information system for collecting / analyzing the necessary data was in place. on the other hand,
Recently, some advanced companies have finally established a manager who is responsible for integrated management of all corporate activities centered on logistics, and promote activities to realize overall optimization of management. It's starting to happen. However, the activity has just begun, and it goes without saying that the collection / management of data on a large number of target site situations will be in the future, not to mention the development / operation of the information processing system that supports it.

[0003]

In order to comprehensively manage all corporate activities, it is premised on the unified management of a large amount of data regarding each field situation. However, the above-mentioned integrated management cannot be realized by that alone. This is because the ultimate decision maker of integrated management is a human, and there are limits and individual differences in information processing ability. Up to now, although there has been recognition of the problem of excessive human information processing work required for integrated management of all corporate activities and individual differences in abilities, no solution has been proposed. The present invention is
This was done based on the recognition of such issues.

An object of the present invention is to provide a user with an optimal improvement plan for immediately and accurately grasping / analyzing a large amount of data regarding the condition of an object to be managed, determining the presence / absence and cause of the problem, and solving the problem. An object is to provide an information processing method and apparatus capable of assisting in easily and objectively determining.

Other objects of the present invention can be easily inferred by those skilled in the art from the present specification and the accompanying drawings.

[0006]

The above object is to retrieve data relating to a certain situation from a storage device, create visualized or indexed information from the retrieved data, output it to an output device, and output it. The analysis result for the information is inputted from the input device, the situation to be analyzed next is judged from the inputted analysis result, and when it is judged that the situation to be analyzed exists, the situation is specified and the above series of Repeatedly, the process is repeated, and when it is determined that the situation to be analyzed does not exist, the plan for improving the analyzed situation is input from the input device, and the input improvement plan is executed. Then, a virtual situation that is assumed to be generated is generated, the generated virtual situation is converted into a quantitative evaluation value, the converted evaluation value is output to the output device, and the series of the improvement plan evaluation processes is performed. Repeating as long as there remains a counter scheme unevaluated is achieved by.

[0007]

The above-mentioned means visualizes or indexes the data related to the situation to be analyzed and outputs it, so that the user can grasp / analyze the situation immediately and accurately. Further, the user only sequentially inputs the analysis result for the output information, and the means controls the output etc. by judging the situation to be analyzed next, so that the difference between the users is large. The location and cause of problems can be mechanically determined without using analysis know-how. Further, since the above-mentioned means quantitatively evaluates the implementation effect of the improvement plan created by the user in advance, the optimum one can be objectively extracted from the plurality of improvement plans.

As is apparent from the above, the present invention is not limited to the diagnosis of physical distribution systems, but is applied to other diagnosis in which information processing using a large amount of data is indispensable because it covers a wide range of objects, and industrial engineering. It is highly desired. From this specification and the accompanying drawings, it is extremely easy for a person skilled in the art to infer that the present invention is applicable to many fields that are industrially and engineeringly desired.

[0009]

Embodiments of the present invention will now be described in detail with reference to the drawings.

FIG. 1 is a processing flow chart showing an embodiment of the present invention. FIG. 2 is a device configuration diagram for realizing the present embodiment.

First, the apparatus configuration diagram shown in FIG. 2 will be described. The device configuration is the output device 20 in the computer 201.
2, the storage device 203 and the input device 204 are connected. It is needless to say that the output device 202 is preferably a color display device, particularly a high-definition color graphic display in implementing the present invention. The storage device 203 is not limited to a magnetic storage device, but may be an optical disk or a semiconductor memory. In short, it is sufficient to have sufficient capacity for executing programs and storing data. As the input device 204, a keyboard and a mouse are shown in FIG. 2, but other input devices may be used, or a combination thereof may be used. As can be easily inferred by those skilled in the art from the above description, the device configuration for implementing the present invention is
What is generally called a computer or a computer system may be used. Specifically, it may be a large-scale computer, a workstation, or a personal computer. As a matter of course, even the special-purpose device manufactured in order to carry out the present invention only needs to satisfy the functions of the peripheral devices as described above.

The processing operation in this embodiment will be described with reference to FIG. 2 and according to the processing flow chart of FIG.

The storage device 20 stores data relating to a certain situation.
3 is searched (step 101). An output device 20 that creates information visualized or indexed from the retrieved data
2 (step 102). The analysis result for the output information is input from the input device 204 (step 1
03). From the input analysis result, the situation to be analyzed next is determined (step 104). When it is determined that there is a situation to be analyzed, the situation is specified and the process returns to step 101 (step 105). On the other hand, when it is determined that there are no more situations to be analyzed, a proposal for improving the analysis result up to now is input from the input device 204 (step 106). A virtual situation assumed to occur when the inputted improvement plan is implemented is generated (step 107). The generated virtual situation is converted into a quantitative evaluation value (step 108). The converted evaluation value is output to the output device 202 (step 109).

Steps 106 to 109 described above
This is repeated as long as there is an unevaluated improvement proposal (step 110). The above-mentioned processing flow consisting of 10 steps shows the most basic case, and some steps may be omitted in practice. For example, when step 102 is processed simultaneously with step 101, step 101 is apparently omitted. Also, in step 104, if there is only one option and certainly exists, step 104 and step 105
May be skipped and the process may jump directly to step 101.

As described above, according to the present embodiment, the user is presented with the visualized or indexed information related to a certain situation, so that the situation can be grasped accurately and immediately. Also,
The location and cause of the problem can be determined by simply repeating the input of the analysis result for the output information. Furthermore, the user can quantitatively obtain the expected effects of each by inputting a plurality of improvement plans for the investigated cause. Therefore, it is possible to objectively compare and consider the improvement plans and easily find a better improvement plan. You can

Consider a case where the present invention is applied to the physical distribution system diagnosis of company X. Now, an executive of Company X makes a request to consulting company Y, saying, "There seems to be a problem with the logistics system, but can you somehow find the cause and present an improvement plan?" I was in charge.
The following is an overview of company X.

Company X is a maker that handles two types of product groups A and B and has an annual sales of several tens of billion yen. Here, the product group is a group of products having similar physical distribution characteristics such as transportation and storage. Figure 4
FIG. 4 is a diagram showing the development of bases (factory and distribution center) of company X involved in each distribution by product group. Company X has eight major regions in Japan (Hokkaido 401, Tohoku 402,
Kanto 403, Chubu 404, Kinki 405, China 406, Shikoku 407, Kyushu 408) to manage sales and customers,
And plans to expand bases accordingly.

In the case of product group A, there are four plants in Narashino.
We have 09, and we deliver directly to customers in the Kanto region from this Narashino factory 409. One distribution center is set up in each of the remaining seven regions and is responsible for delivery to customers throughout the region.

On the other hand, the product group B has a factory 410 in Hiroshima. However, until now, the handling volume was small overall, so we did not set up distribution centers in the six regions west of the Kanto region, but instead delivered directly from Hiroshima Factory 410 to customers. However, since there are two regions, Hokkaido 401 and Tohoku 402, which are far from the Hiroshima factory 410, from the perspective of guaranteeing customer service levels such as delivery times, we have set up distribution centers to serve customers in all regions. I am in charge of delivery to.

At the time of starting the physical distribution diagnosis, the person in charge K decides to obtain / edit the actual data of the company X and the like and prepare the following basic file.

(1) Monthly total results file by location 5
01 (Fig. 5) Monthly sales 504, monthly average inventory 505, delivery cost 506, warehouse cost 507 (breakdown: storage cost 5071, loading and unloading cost 5072, repackaging cost 5073) using the base code 502 and the year / month 503 as keys. , Transportation cost 50
8 is a file that has packaging cost 509 (factory only) as data. In general, a distribution center is responsible for managing delivery costs when a product is shipped from itself, but is not responsible for shipping cost when a product comes in from an upstream (production) site. However, changing the operation method of the distribution center, such as the method of inventory management, also has a great influence on the transportation cost. Therefore, for the purpose of facilitating comparative consideration of expected effects of improvement plans, which will be described later, the transportation cost is managed for each site, while being aware of overlapping management data.

(2) Shipment detailed file 60 for each site and for each product
1 (FIG. 6) With the site code 602, the product code 603, and the shipping date 604 as keys, the shipping type 605 and the shipping destination code 6
This file has 06, the number of shipments 607, and the proportional fare 608 as data. The shipment type is U when the product is shipped to the customer (sales shipment), and Y otherwise. If the shipping type is U, the customer code is entered in the shipping destination code 606. If the shipping type is Y, the site code is entered in the shipping destination code 606. Actually, since a plurality of products are mixed and carried, it is impossible to actually measure how much the transportation cost (freight) was incurred for each product. Therefore, the fare paid to one truck is proportionally calculated for each mixed product according to the weight or volume. This is the apportioning fare 608.

(3) Logistics performance file 701 by site and by product by day (FIG. 7): Base code 702, product code 703, and date 70
It is a file having the number of arrivals 705, the number of shipments 706, and the number of stocks 707 as data with 4 as a key. Note that daily management is not an essential condition. Depending on the required accuracy of the data,
You may manage by a coarser unit, for example, weekly.

(4) Order / arrival details file 801 for each product by site (FIG. 8) The number of orders 805 and the date of arrival 80 are keyed by the site code 802, the product code 803, and the order date 804.
6 is a file having the number of arrivals 807 as data.

(5) Product master file 901 (FIG. 9) Using the product code 902 as a key, product name 903, product group name 904, original unit price 905, selling unit price 906, volume 9
This file has 07 and weight 908 as data.

(6) Location attribute file 1001 (see FIG. 1
0) With the base code 1002 as a key, a base name 1003, a product group name 1004, a base type 1005, and a location 10
This is a file having 06, area 1007 in charge, and contracted floor area 1008 as data. The site type 1005 is
It is a code that distinguishes between a factory and a distribution center, and is represented by I and S, respectively.

(7) Customer attribute file 1101 (see FIG. 1
1) Customer name 1103, customer address 1104, area code 1105, area code 11 with the customer code 1102 as a key
It is a file having 06 as data.

By combining or re-editing the above basic files, the data required for the following processing can be obtained at any time. The processing flow when the present invention is applied to the physical distribution system diagnosis of Company X will be described in detail with reference to FIG.

<Step 301> Creation / output of distribution cost occurrence status for each product group Output status 202 of distribution cost occurrence status for each product group (FIG. 12) using table 1201 and line graph 1202
Output to. There are various ways to capture the logistics cost 1203,
You can set it freely. Here, warehouse cost 1203
1, the transportation cost 12032 and the packaging cost 12033 will be taken up. The warehouse cost 12031 is the sum of the storage cost as the warehouse rent and the cargo handling cost as the storage / delivery work cost. The transportation and delivery cost 12032 is a truck fare required for transportation between bases and delivery to customers. The packaging cost 12033 is a labor cost required for the packaging work in the factory. This is because, in general, the packing work only occurs in the factory. If packing (repacking) work also occurs at the distribution center, the personnel cost will be included in the warehouse cost.

In addition to distribution cost 1203, table 1201 shows sales 1204 and inventory 120 by product group.
5, the inventory level 1206, and the distribution cost rate 1207 are shown. Logistics costs by product group 1
203, sales 1204, and inventory 1205 can be easily obtained by collecting the total of the data in the monthly total actual results file 501 for each base for each product group while eliminating the duplication of costs (without adding the transportation cost). can get. The inventory level 1206 is obtained by dividing the inventory 1205 by the sales 1204, and the unit is months. Logistics cost rate 1207
Is obtained by dividing the distribution cost 1203 by the sales 1204 and expressing it as a percentage.

A line graph 1202 shows the trend of the distribution cost rate for the last three years by product group.

<Step 302> Input of Product Group Name Having Problem in Distribution Cost Generation Person in charge K has a high possibility that the product group having a high distribution cost rate or increasing in recent years is a problem product group. It analyzes and inputs the group name from the input device 204. Here, the column 1208 of the product group A
Click with the mouse. In addition, the latest month, February 1993, is input as the analysis target month.

<Step 303> Creating / outputting the actual distribution of the problem product group The actual distribution of the problem product group is expressed separately for each site, inter-site, and customer (regional), and the output device 202 is provided for each. Output to. Of these, the table 1301 (FIG. 13) is used to display the actual condition by site, and the map 1401 (FIG. 14) is used to display the actual condition between sites and by customer.

Table 1301 shows basic data 13 for each base.
03, physical distribution cost 1304, and analysis index 1305 are shown. As basic data 1303, sales 1303
1, inventory amount 13032, inventory occupied area 13033, inventory volume 13034, and shipping volume 13035. The distribution cost 1304 includes a delivery cost 13041, a warehouse cost 13042 (breakdown: storage cost 130421, cargo handling cost 130422, repackaging cost 130423), transportation cost 13043 (reference value), and packaging cost 1304.
4 (factory only). As the analysis index 1305, an inventory level 13051, a storage efficiency 13052, and a cargo handling work efficiency 13053 are shown. The storage efficiency is 130
52 is the inventory volume 13034 and the inventory occupied area 13033.
Divided by, the cargo handling work efficiency is the cargo handling cost 13042
2 divided by the shipping volume 13035. Of the above, the sales amount 13031 and the inventory amount 13032 are obtained from the monthly total achievement file 501 for each base. As the inventory occupied area 13033, the contract basis weight 1008 of the site attribute file 1001 is used. The stock volume 13034 is obtained by multiplying the stock quantity 707 in the daily distribution record file 701 by site by the volume 907 in the product master file 901.
This can be obtained by taking the average of the analyzed months for all products in the base and adding them. The shipping volume 13035 is
Number of shipments 607 in the shipment detail file 601 for each site and product
Is multiplied by the volume 907 of the product master file 901, and this is added to all items of all products (months to be analyzed) in the site.

Regarding the above indexes 13051 to 13053, the suitability is judged based on the average value of all distribution centers and the standard value which can be preset from the product characteristics. It is displayed in a mode different from other specific colors such as red and yellow, blinking, and the like. As a result, the user can immediately and accurately analyze whether or not there is a problem.

On the other hand, in the map 1401, the distribution flow between the bases is shown by the arrow 1402 connecting the two bases, and the movement of the goods can be grasped at a glance. The direction of the arrow represents the direction of flow, and the thickness (or color) represents the amount. Further, the loading rate of the transportation truck can be represented by numeral 1403 attached to the arrow. The distribution flow between the bases is obtained by adding the shipment detailed file 601 for each product for each base to the analysis target month for each shipment destination for each base.

In order to show the actual situation by customer (region), the delivery amount (amount) by delivery source is shown by a pie chart 1404 for each region on the same map 1401. In this case, the pie chart 1404
The total area of the area corresponds to the demand amount of the whole region, to be precise, the shipping amount to the region.

As shown in the legend 1405, the distribution center 14 that is originally in charge of the region as the delivery source.
051, other distribution center 14052, factory 140
It distinguishes the three of 53. The delivery amount by delivery source for each region is obtained by multiplying the number of shipments in the item-by-site shipment detail file 601 by the unit selling price 906 of the product master file 901, and referring to the customer attribute file 1101 and the site attribute file 1001. It can be easily obtained by adding up.

Also, the individual diagnosis menu (FIG. 15) for narrowing down to individual problems is displayed at the same time as the output device 20 together with the table 1301 and the map 1401 showing the physical distribution of the problem product group.
Output to 2.

<Step 304> Input of Diagnosis Function Name of Individual Problem In the individual diagnosis menu, a diagnosis function of an individual problem corresponding to the output information is registered / prepared in advance. Person K
Selects a desired diagnostic function based on its analysis result and inputs the function name. For example, when a distribution center with a very high inventory level is found, the center name and the function name “stock management diagnosis” 1502 are input device 204.
Enter from. Or, even if the demand in a certain region has increased significantly, it can be handled only by direct delivery from the factory, or even if a distribution center in charge of that region is installed, If you receive a great deal of support from the distribution center, the region name and "base development diagnosis"
The function name 1503 is input from the input device 204.

Generally, in the former case, it is necessary to consider the establishment of a new distribution center, and in the latter case, it is necessary to consider the consolidation or abolishment of the distribution center. In addition to the above, "storage efficiency diagnosis" for distribution centers with small inventory volume per unit area (storage efficiency) 1
504 and cargo handling cost per unit receipt / shipment volume (work cost)
"Work efficiency diagnosis" for large distribution centers 150
5. "Transportation and delivery efficiency diagnosis" between bases with low loading rate 1506
Individual diagnostic functions such as Here, it is assumed that “stock management diagnosis” 1502 is selected as the function name and the input is performed by clicking the button 1402 with the mouse.

The steps up to here (301 to 30)
5) will be called basic diagnosis, and the following steps will be called individual diagnosis.

<Step 305> Execution of Individual Problem Diagnosis Function In the following, the processing flow of the individual problem diagnosis function will be described first with reference to FIG.
Will be described in detail. Here, the "inventory management diagnosis" function is to determine whether an inventory is held properly for each product and support formulation of an improvement plan.

<Step 1601> Creation / Output of Inventory Management Status by Product Rank All products handled at the distribution center are ranked according to the size of shipment. ABC analysis may be applied to this. ABC analysis is a generally well-known analysis method.
Here, when all the commodities are arranged in descending order of the shipment amount and the shipment amounts are added in order from the higher rank commodities, one rank is given to the commodity group occupying a predetermined ratio of the total shipment amount. For example, a product group occupying 70% of the total shipping amount is an A rank product, a product group occupying 90% of the total shipping amount is a B rank product other than the A rank product, and some of the remaining products have a shipping amount. A product group is called a C-rank product, and a product group with no shipment is called a Z-rank product.

The horizontal axis is a product list (the number of items) arranged in descending order of shipment, and the vertical axis is the composition ratio.
Line graph 1701 showing the relationship between cumulative shipments and cumulative inventory
(FIG. 17) and output to the output device 202. At this time, if the boundaries of the ranks are clearly indicated, the person in charge K can easily grasp "how much stock in which shipping rank product is in stock".

In the ABC analysis based on the above-mentioned shipment amount, the number of shipments 607 of the shipment detailed file 601 for each product by site is multiplied by the selling unit price 906 of the product master file 901, and this is totaled for each analysis target month for each product. Can be used. Further, the inventory amount is, for example, the number of stocks at the end of the month 707 of the analysis target month of the distribution log file 701 for each product by site and each day.
The product unit price 906 of the product master file 901 may be multiplied by the product price, and the product price obtained for each product may be used.

<Step 1602> Input of Problem Product Rank Name It is understood that the greater the difference between the cumulative shipment value curve 1702 and the cumulative inventory value curve 1703, the greater the variation in the inventory turnover ratio between products. For example, the slopes of the cumulative curves of shipments and inventories are compared for each shipping rank, and if the slope of the cumulative curve of shipments for a certain rank is less than the slope of inventory, the inventory turnover rate for that rank is averaged. You can see that it exceeds the value. When excess inventory is a problem, as in this “inventory management diagnosis,” attention should be paid to a product group with a high inventory turnover ratio, and the corresponding rank name is input from the input device 204. Here, C rank is input. <Step 1603> Output of Inventory Management Status by Product It is necessary to more precisely grasp the inventory management status for each product centered on the input product rank and analyze the presence / absence of a problem individually.

The average stock quantity of products is given by the sum of the safety stock quantity and half of the average order quantity, and is independently affected by both. Here, inventory management status by product (Fig. 1
8) is divided into a safety stock quantity-dependent portion 1803 and an average order quantity-dependent portion 1804, which is output to the output device 202 using the table 1801 and the distribution chart 1802.

Since the distribution center handles a large number of products, it is difficult for the person in charge K to analyze them all in detail. Therefore, for safety stock quantity and average order quantity,
In addition to the current value, a numerical value that will be described later as a reference value is introduced. The reference value is merely a reference value, and does not guarantee the optimality during operation as an ideal value. A distribution chart 1802 for each product is displayed on a plane in which the horizontal axis represents the ratio between the current value and the reference value and the vertical axis represents the current value. This allows
For example, a product whose current value is large and which exceeds the standard value can be displayed near a specific area (upper right) of the distribution map as a product with excessive inventory and a large problem, so it can be grasped at a glance. it can. Also, by enclosing the product group of interest on this distribution map with the area line 1807,
Since detailed data of the corresponding product is output on the table 1801, the problem product can be easily narrowed down.

The current value 18041 of the average order quantity may be calculated by taking the average of the number of orders 805 in the order / incoming delivery detailed file 801 for each site. On the other hand, the current value of the average inventory quantity can be obtained by averaging the inventory quantity 707 of the daily physical distribution file 701 for each site and product. Therefore, the current value 18031 of the inventory that can be regarded as a safety stock can be easily obtained by subtracting half the current value of the average order quantity from the current value of the average stock quantity.

The method for obtaining the reference value will be described below.

(1) Calculation of standard value of safety stock quantity Safety stock is a stock that is held as a margin in order to avoid out of stock due to variations in demand during the procurement period of goods. The calculation of the standard value 18032 of the safety stock essentially depends on the ordering method in detail. Here, a safety factor (corresponding to the allowable limit of the out-of-stock rate, which is an inventory policy, is determined from the statistically calculated demand fluctuation (standard deviation) within the average procurement period from the site-specific product-specific order receipt detailed file 801 ( By multiplying by (1 to 2), I decided to roughly calculate.

(2) Calculation of the standard value of the average order quantity It is difficult to obtain the standard value 18042 of the average order quantity independently for each product. Here, the concept of "basic ordering cycle" is introduced, and the model is adopted in which the timing of the arrival of goods, that is, the transportation is synchronized by adopting an integer multiple of the ordering cycle of all products. This is a fairly realistic model that simulates the actual field operation that "I want to pack as many procured trucks as possible to maximize transportation efficiency so that there is no difference in delivery date." Can be said. Needless to say, the ordering cycle for products that sell well and the ordering cycle for products that sell poorly are lengthened.

Under this model, some order plans are created internally. This processing flow is shown in FIG. First, an ABC analysis is performed on the shipment amount for all products (step 1901). Next, the basic ordering cycle is determined (step 1902). Select a product and select its ABC
Ordering cycle is set according to rank (Step 1
903). For example, the basic ordering cycle is set as it is for the A-rank products, and the ordering cycles twice or three times the basic ordering cycle are set for the B-ranked products and the C-ranked products, respectively. As the order quantity, the expected demand quantity during the order cycle cycle is set (step 1904). The above process is repeated for all products in one basic ordering cycle (step 1905). Further, the above processing is repeated while changing the basic ordering cycle (step 190).
6). The distribution cost simulation described later is executed for each of the created ordering plans. At this time,
It is considered that the order quantity specified in the order plan that realizes the minimum cost is the standard value of the order quantity.

<Step 1604> Input of improvement plan for inventory management by product With reference to the current value and the standard value for some products, the safety stock amount set value 18033 in the inventory management status table 1801 is set. The order quantity set value 18043 is input from the input device 204 as an improvement plan.

<Step 1605> Generation of virtual situation associated with implementation of improvement plan In order to determine an accurate improvement plan, its quantitative expected effect is calculated in advance so that the improvement plans can be objectively compared with each other. There is a need to. This time, the expected effect is calculated from the viewpoint of distribution cost. As described above, the distribution cost that occurs in connection with the operation of the distribution center is composed of the delivery cost, the warehouse cost (the sum of the storage cost, the cargo handling cost and the repackaging cost), and the transportation cost. The definition and calculation method of each cost are shown below as a physical distribution cost calculation model.

(1) Delivery cost As a general rule, delivery is performed by a special pile-up service (common name: courier service). The fare for delivery in this case can be obtained by searching the “reference fare table” 2001 (FIG. 20) using the “weight” 2003 of the article to be delivered and the “distance” 2002 from the delivery source to the delivery destination as keys. Of the above, "weight" and "distance" are called operating conditions, and "standard fare table" is called operating conditions. If the demand does not change, the “weight” and the delivery destination do not change, and if the position of the delivery source does not change, the “distance” does not change, and as a result, the operation status does not change at all. Therefore, it can be seen that the delivery cost remains unchanged without calculation even under the assumption that the operating conditions do not change. However, if the location of the delivery source changes, as in the case of “base deployment diagnosis”, the “distance” also changes, and naturally the delivery cost also changes.

(2) Warehouse cost (a) Storage cost It is assumed that a rented warehouse is rented at a "unit price per tsubo". At this time, the cost of storing the products can be calculated by the product of the “inventory occupying area (unit: tsubo)” and the “unit price per tsubo” of all products. Of the above, the "inventory occupied area (unit: tsubo)" is called the operating status, and the "unit price per tsubo" is called the operating condition. As described above, the average stock amount of a product is given by the sum of the safety stock amount and half of the average order amount, so that if either one of them is changed, the average stock amount changes. If the storage efficiency is constant, the “inventory occupancy area” also changes in proportion to the change in the average stock amount.

(B) Cargo Handling Cost In the case of a logistics center that has been operating for a long time, a "cargo handling fee per unit work amount (example: 1 case)" is determined,
It is often paid according to "total work (eg total number of incoming and outgoing cases)". On the other hand, in the case of a new base, it is often possible to understand it only by roughly multiplying the "required number of people" with "personnel cost per person", such as one person per 100 tsubo.
Of the above, "total work volume" and "required personnel" are called operating status, and "loading fee per unit work volume" and "labor cost per person"
Will be referred to as operating conditions. The “total work” is considered to be almost proportional to the quantity (flow) passing through the distribution center, and the quantity passing is almost proportional to the demand. That is,
If the demand does not change, the “total work” may not change. Therefore, it can be seen that the cargo handling cost is unchanged without calculation even under the assumption that the operating conditions are not changed.

(C) Repacking cost It is assumed here that there is no repacking work at the distribution center, so there is no need to consider it.

(3) Transportation cost As a general rule, transportation shall be performed by charter flights that rent out trucks. The fare for transportation in this case is obtained by multiplying the "classification number" and the "classification fee" of the trucks to be driven within a predetermined period (for example, one month). Among the above, the "number of types" will be referred to as the operating status, and the "type fee" will be referred to as the operating condition. Here, the type refers to the type of track capacity, such as 4 tons or 10 tons.

Generally, a large truck is cheaper, but it should be noted that this may not always be the case depending on the loading rate. For example, when carrying 4 tons of material, a 4 ton truck (loading rate: 100%)
However, it is cheaper than a 10-ton truck (loading ratio: 40%). If the ordering cycle or the order quantity of the products handled by the distribution center is changed, the transportation pattern of the products, and thus the "type number", changes even if the total quantity of goods received does not change.

Specifically, it is obtained as follows. First,
For products for which the ordering cycle is synchronized,
Create a daily arrival pattern for 30 days. This is nice to sync and easy to create. Next, the remaining commodities are uniformly stacked in the created arrival pattern by the ordered quantity. For example, the order quantity of the remaining products is 2
If there is a break, the created arrival pattern will be uniform on 10/8
You can double it.

In this step 1605, the above-mentioned model is used to generate the operation status based on the inputted improvement plan.

<Step 1606> Calculation of expected effect of improvement plan The distribution cost is calculated by adding the current value of each operation condition to the operation status generated in step 1605.

<Step 1607> Expected Effect Output The expected effect (FIG. 21) of the improvement plan is grasped as a change in physical distribution cost and is output to the output device 202 using the table 2101 and the graph 2102. At this time, the inventory occupied area 2103 is also output as a reference value.

<Step 1608> Repeated determination of improvement plan evaluation The above steps 1604 to 1607 are repeated as long as there is an unevaluated improvement plan.

Next, in the case of executing the "base deployment diagnosis" function for the product group B, the processing flow of the individual problem diagnosis function will be briefly described with reference to FIG. Here, the "base deployment diagnosis" function is to judge the good or bad of the position of the base and the distribution of distribution between the bases, and support the formulation of the improvement plan. This time, we will especially explain the case of planning the establishment of a new base. In the following, the method of obtaining the reference value and the simulation cost is basically the same as in the case of "stock management diagnosis".

<Step 2201> Creation / Output of Demand / Delivery Status by Region Demand / Delivery Status by Region indicating how much demand is in total and how much is delivered from each base (FIG. 23) ) Is output to the output device 202 using the table 2301.

<Step 2202> Input of problem area name For example, if there is an area where the demand is extremely large and all the delivery is covered by direct delivery from the factory, sufficient customer service cannot be guaranteed in terms of delivery time, or You can easily analyze what you can't do. New logistics centers should be established in such regions. Here, assuming that the Kanto region corresponds to this, the region name is input device 20.
Enter from 4.

<Step 2203> Output of detailed demand situation of problem area The demand amount (FIG. 24) by prefecture (can be by municipality) of the Kanto region,
Output to the output device 202 using the Kanto map 2401. At the same time, a history table 2501 of the site new design drawing (Fig. 25)
Is also output to the output device 202.

<Step 2204> Input of new site design image Input the first plan (“plan 1”). First, a candidate site for a new distribution center is input from the input device 204 using the map 2401 as an interface. Here, the vicinity of Atsugi is picked up with a mouse to instruct, and a specific place name (city / town / village name) is input by selecting it from the pull-down menu 2402. The input result is displayed in the cell 2502 at the base position of “plan 1” in the history table. By specifying the position of the new center on the map, the distance between the new center and an arbitrary area can be calculated at any time using the inter-coordinate distance in the map and the scale. This is used when calculating shipping costs. Next, if you pick the cell 2503 in the delivery area of "Plan 1" with the mouse, the candidates for the area to be assigned to the new center will be output in a pull-down menu by prefecture or by municipality. input. Here, by selecting all prefectures in Kanto,
Specify the entire Kanto region. As a result, the actual shipment data to the Kanto region is cut out from the site-specific product-specific shipment detail file 601 and transferred as new center management.

At the new establishment center, it is necessary to newly set up an inventory management plan indicating which products and how many items to have. When the cell 2504 of the inventory management plan of “Plan 1” is picked up with the mouse, the inventory management plan table 2601 (FIG. 26)
Is output. In this inventory management plan table, the result of executing the ABC analysis based on the shipment amount is output for all the products in the shipment record which have been managed by the new center. Here, for example, we have stock only for A rank products and B rank products,
For C-ranked products, enter the plan such as direct delivery from the factory as before. For A-ranked products and B-ranked products that have inventory, it is necessary to determine how much safety stock quantity and average order quantity should be held respectively. Therefore, the actual value of Atsugi set as the base position is used as a reference value of the operating condition. In addition, if the cell 2505 of the operation condition of “plan 1” is picked up with the mouse, the operation condition table 27
Since 01 is output to the output device 202, the user can set operating conditions by himself using this as an interface.

<Step 2205> Generation of Virtual Situation Accompanied by Implementation of New Site Design Image In this step 2205, operating conditions are respectively generated based on the input new site design image using the above model.

<Step 2206> Expected effect calculation of new site design image The distribution cost is calculated by adding the set value of the operation condition to the operation status generated in step 2205.

<Step 2207> Expected Effect Output The expected effect of the new site design is grasped as a change in physical distribution cost and is output to the physical distribution cost column 2506 of the history table. For reference, the physical distribution status 2507 is also output.

<Step 2208> Repetition determination of site new design image evaluation The above steps 2204 to 2207 are repeated as long as there is an unevaluated site new design image proposal.

<Step 2208> Output of Evaluation Value Changes in physical distribution costs are reflected in the plan history table 2501.

<Step 2209> Repetition Judgment The above steps 2205-2208 are repeated as long as there is an unevaluated plan.

As described above, according to the detailed description of the present embodiment, it is possible to obtain an effect that even a user who does not have much diagnostic know-how can accurately and efficiently carry out a physical distribution system diagnosis.

Next, the embodiment for realizing the information processing method and apparatus according to the present invention will be described with reference to FIG. 2 on the apparatus configuration diagram shown in FIG.
This will be described using 8. Since the outline of the device configuration is the same as that of FIG. 2, description thereof will be omitted. The present embodiment will be described in correspondence with the functions described with reference to FIG.

First, data relating to a certain situation is retrieved from the storage device 203, information is created by the visualization and indexing function 2801, and then output to the output device 202. The user sees this, grasps / analyzes the situation, and inputs the analysis result from the input device 204. The input analysis result is transmitted to the analysis control function 2803 via the situation determination function 2802, and the visualization and indexing function 2801 is controlled so as to output the situation to be grasped / analyzed next.

When the analysis is completed and the location and cause of the problem have been clarified, the user inputs the improvement plan into the input device 204.
Enter from. The situation generation function 2804 generates a virtual situation that is considered to occur with the implementation of the input improvement plan. The generated virtual situation is evaluated value conversion function 2
The output device 202 converts the quantitative evaluation value by 805 or visualizes / indexes by the visualization and indexing function 2801.
Is output to.

As described above, according to this embodiment, as in the embodiment described with reference to FIG. 1, the user is presented with the visualized or indexed information related to a certain situation, so that the situation can be accurately identified. You can understand immediately. In addition, the location and cause of the problem can be determined by simply repeating the input of the analysis result for the output information. Furthermore, the user can quantitatively obtain the expected effects of each by inputting a plurality of improvement plans for the investigated cause. Therefore, it is possible to objectively compare and consider the improvement plans and easily find a better improvement plan. You can

[0085]

As described in detail above, according to the present invention, a user can immediately and accurately grasp / analyze a large amount of data regarding the condition of an object to be managed, determine the existence and the cause of the problem, and solve the problem. The optimal improvement plan to solve
It is possible to provide an information processing method and apparatus that can easily and objectively support the determination.

[Brief description of drawings]

FIG. 1 is a process flow chart showing an embodiment according to the present invention.

FIG. 2 is a diagram showing an example of a device configuration for carrying out the present invention.

FIG. 3 is a processing flow chart of physical distribution diagnosis.

[Figure 4] Location map of each product group.

[Fig. 5] Layout diagram of total achievement file by site.

FIG. 6 is a layout diagram of a shipping detail file for each product by location.

FIG. 7 is a layout diagram of a distribution result file by product by day and by site.

FIG. 8 is a layout diagram of an order / arrival item file for each site and for each product.

FIG. 9 is a layout diagram of a product master file.

FIG. 10 is a layout diagram of a base attribute file.

FIG. 11 is a layout diagram of a customer attribute file.

FIG. 12 is an output diagram of the distribution cost occurrence status by product group.

FIG. 13 is an output diagram of physical distribution using a table.

FIG. 14 is an output diagram of physical distribution using a map.

FIG. 15 is a view showing a diagnosis function menu of an individual problem.

FIG. 16 is a processing flow chart of inventory management diagnosis.

FIG. 17 is an output diagram of ABC analysis.

FIG. 18 is an output diagram of inventory management status by product.

FIG. 19 is a diagram illustrating a method of setting an order plan.

FIG. 20 is a diagram illustrating a standard fare table.

FIG. 21 is an output diagram of expected effects of improvement plans.

FIG. 22 is a processing flow chart of a site new design drawing.

FIG. 23 is an output diagram of demand / delivery status by region.

FIG. 24 is an output diagram of a detailed demand situation in a problem area.

FIG. 25 is an output diagram of a base new design history table.

FIG. 26 is an output diagram of an inventory management plan table.

FIG. 27 is an output diagram of an operation condition table.

28 is a configuration diagram of an embodiment for realizing the information processing method and the device according to the present invention on the device configuration diagram shown in FIG. 2 in correspondence with the function described with reference to FIG.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Mitsutaka Kosaka 1099, Ozenji Temple, Aso-ku, Kawasaki City, Kanagawa Prefecture, Hitachi Systems Development Laboratory, Ltd. Hitachi Ltd. Information Systems Division (72) Inventor Takao Sato 12 890 Kashimada, Sachi-ku, Kawasaki-shi, Kanagawa Hitachi Business System Development Center 12 (72) Inventor Hiromichi Kimura 890 Kashimada, Saiwai-ku, Kawasaki-shi, Kanagawa Address No. 12 Hitachi, Ltd. Information Systems Division (72) Inventor Tetsuji Sekiyama 3-6-3 Shibuya, Shibuya-ku, Tokyo Inside Hitachi Logistics (72) Inventor Takahiro Tajima 4-chome Kanda Surugadai, Chiyoda-ku, Tokyo Address 6 Hitachi, Ltd.

Claims (4)

[Claims] 1. A data storage device that retrieves data relating to a certain situation, creates visualized or indexed information from the retrieved data, outputs the information to an output device, and outputs an analysis result of the output information to an input device. From the input analysis result, determine the situation to be analyzed next, if it is determined that there is a situation to be analyzed, specify the situation, repeat the series of processes, on the other hand, If it is determined that the situation to be analyzed does not exist, a proposal for improving the analyzed situation is input from an input device, and a virtual situation assumed to occur when the input improvement plan is implemented is Generate, convert the generated virtual situation into a quantitative evaluation value, output the converted evaluation value to the output device, the series of the improvement plan evaluation process, un-evaluated improvement plan remains Repeated as long as that information processing method characterized by. 2. The information processing method according to claim 1, wherein the situation is a situation indicating stock or flow of goods. 3. Data relating to at least one situation
A storage device to store, and the related data is retrieved from the storage device to perform the retrieval.
The visualized or indexed information from the collected data
Means, an output device for outputting the created information, an input device for inputting an analysis result for the output information, and a situation to be analyzed next is determined from the input analysis result
And means for controlling the visualization or indexing according to the judgment.
Means, an input device for inputting a plan for improving the analyzed situation, and assumed to occur when the input improvement plan is implemented.
Means for generating a virtual situation, and a means for converting the generated virtual situation into a quantitative evaluation value.
And a means for outputting the converted evaluation value to the output device.
An information processing device comprising: 4. The information processing apparatus according to claim 3, wherein the status is a status indicating stock or flow of goods.