JP2015014911A - Order quantity calculating system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a component order quantity calculating system capable of optimizing an inventory for not holding an excessive stock.SOLUTION: A component order quantity calculating system includes means of: specifying demand-forecast parameters (a supply rate, a procurement rate, a contract rate, a demand forecast method, a result acquisition period, a unit time period, and an index) for every kind; calculating a demand forecast and requirement of a supply center and a supply base using the parameters; and comparing a demand forecast value with an actual result, and applying (automatically updating) an optimal demand forecast method for every kind.

Description

  The present invention relates to an order quantity calculation system suitable for application to, for example, an organization that manages ordering of maintenance parts, base supply, emergency delivery, and the like and a parts base (hereinafter referred to as a logistics center).

  As background art of this technical field, there is JP-A-2006-155365. This gazette states that “additional ordering requirement is required for the materials used in the manufacture of products, stored in association with the time when the materials are used, which is the quantity that has to be delivered from the supplier but has not yet been ordered. A quantity storage means, a surplus data receiving means for receiving a surplus data representing the amount of surplus capacity as a quantity that the supplier can supply the material in association with the time period, in a time series for a plurality of times, and received by the receiving means. The surplus data storage means for storing the surplus power data and the additional order required quantity at a certain time are read from the additional order required quantity storage means, and the surplus data at the certain time included in the latest surplus data is read from the surplus data storage means. Based on the read-out additional order requirement amount and the read-out latest surplus amount, the read-out additional order amount is read out. "Material order quantity calculation system with additional order quantity calculation means to calculate the additional order quantity as the quantity to be ordered among the required quantity" Suppress the occurrence of excess inventory of materials ”(see abstract).

  Further, in the order quantity calculation system, for example, a replenishment center that replenishes and manages a part from a factory that is a parts supply source or a replenishment base that receives a part supply from the replenishment center and replenishes the part at a lower level base. , The required amount of required parts, that is, the replenishment rate of the replenishment center (= replenishment rate) is calculated. Something that calculates is proposed.

  More specifically, the conventional parts order quantity calculation system only calculates the order quantity from uniform demand forecasting methods and parameters. The supply center calculates the required amount when the probability of supply immediately to the supply base (replenishment rate) is the optimal fulfillment rate (≈100%) when consumption occurs throughout the country, and purchases / deploys parts. The replenishment base calculates the necessary amount when the probability (procurement rate) that can be immediately accommodated in the territory of the replenishment base is the optimum fulfillment rate (≈100%) in the territory of the replenishment base. The replenishment base also has parts for non-contractors in order to calculate the required amount from the predicted consumption coefficient.

JP 2006-155365 A

  The above-mentioned patent publication describes a mechanism of a material order quantity calculation system that suppresses the occurrence of surplus stock of materials due to a shift in demand forecast while preventing breakage of material orders. However, the former order quantity calculation system does not take into account that stocks that can always be dealt with at the replenishment centers and replenishment bases when parts are consumed at the bases scattered throughout Japan.

Further, according to the latter order quantity calculation system, when parts are consumed at each base, it is possible to have a stock that can always be dealt with at the supply center and the supply base. However, the order quantity calculation system is a method for calculating the order quantity from uniform demand forecasting methods and parameters, and in such a method, it is a mechanism for calculating the optimum order quantity according to the characteristics of the product type. As a result, it is necessary to keep inventory that can always be dealt with at both the replenishment center and the replenishment base, even if the exhaustion occurs at any base. Therefore, the efficiency of inventory management was poor.
In addition, since the order quantity is calculated from the required quantity at each replenishment base, if the supply chain to the end customer is multi-staged, inventory will be held at each stage, and the number of inventory Overall optimization cannot be achieved. In addition, there was a problem that the inventory cost increased.
In addition, with the diversification of service levels, there is an increasing need to manage the stock quantity for each product type using parameters such as contract rate.

  Therefore, the present invention provides a parts order quantity calculation system that can optimize inventory and does not need to have excessive inventory.

  In order to achieve the above object, the present invention designates a demand prediction parameter (supply rate, procurement rate, contract rate, demand prediction method, performance acquisition period, unit period, index) for each product type, and uses the parameter. Then, the demand forecast and the required amount of the replenishment center and the replenishment base are calculated, and the demand forecast value and the actual result are compared for each type, and an optimum demand forecast method is applied (automatic update). As a result, the order quantity is optimized.

For example, the order quantity calculation system of the present invention is an order quantity calculation system in a system for supplying parts to a supply center and supplying parts from the supply center to a supply base.
Demand forecasting means for forecasting demand at the replenishment center and the replenishment base;
A required amount calculating means for calculating the required amount of the replenishment center and the replenishment base;
Order quantity calculation means for calculating the order quantity based on the calculation result and inventory information of the order quantity calculation means, and the order lot;
Have
The demand prediction means includes a processing unit that predicts the number of consumptions that will occur in the future based on past consumption results and demand prediction parameters specified for each type.
The required amount calculation means is based on the number of consumptions by the demand prediction means and the required quantity calculation parameter specified for each product type, from the supply rate indicating the supply rate of the supply center and the supply rate indicating the supply rate of the supply base It has a processing unit that calculates the required amount,
The order quantity calculation means has a processing unit for calculating the order quantity based on the calculation result and inventory information of the order quantity calculation means and the order lot.

The order quantity calculation system of the present invention is
The demand prediction parameters include parts replenishment, demand forecasting technique for forecasting demand for replenishment, parts performance acquisition period, unit period, index,
The necessary amount calculation parameters include a supply rate of the supply center, a procurement rate of the supply base, a contract rate with a customer,
The demand prediction unit includes an automatic update unit that automatically updates a demand prediction method of the demand prediction parameter.

  According to the present invention, it is possible to provide a parts order quantity calculation system that can optimize inventory and does not need to have excessive inventory.

It is a conceptual diagram explaining parts distribution in a parts integrated management support system. It is a block diagram which shows the structure of the order quantity calculation system of this invention applied to a components integrated management support system. It is a flowchart which shows the processing flow of order quantity calculation. It is a flowchart which shows a specific example of the processing flow of the demand forecast and required quantity calculation in order quantity calculation.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a conceptual diagram illustrating a flow of replenishment of parts to a replenishment center, a replenishment base, and replenishment to a base in the part integrated management support system.

  In the figure, reference numeral 1 is a factory (business division) that provides parts, and 2 is a parts integrated management support system that receives a necessary amount of parts when parts are replenished from the factory 1 and parts are consumed. Hereinafter, this is referred to as a logistics system. The logistics system 2 has a replenishment center 21 for replenishing parts from the factory 1, one or more replenishment bases 22 for replenishing parts from the replenishment center 21, and one or more bases 23 for receiving parts from the replenishment bases.

  The replenishment rate from the replenishment center 21 to the plurality of replenishment bases 22 and the procurement rate that can be immediately accommodated in the territory of the replenishment base 22 can be designated by parameters. In the replenishment base 22, the contract rate can also be specified by a parameter. Then, customers who do not have a contract are ordered from the replenishment center 21.

  In this way, the replenishment base does not need to have excessive inventory by adjusting the probability (procurement rate) that the parts can be replenished immediately from the replenishment center 21 when parts are consumed at each base 23.

  FIG. 2 is a block diagram showing the configuration of the order quantity calculation system of the present invention applied to the parts integrated management support system.

  In the figure, the order quantity calculation system includes a server 3, and the server includes an input / output device 31, a calculation device 32, and a storage device 33.

  The input / output device 31 includes a demand prediction parameter specifying unit 311 and a parts ordering unit 312. The demand prediction parameter designating unit 311 designates the parts supply rate and the procurement rate with parameters in order to predict the demand at the supply center 21 and the supply base 22.

  The parts ordering unit 312 receives a request from an ordering examination requesting unit 325 described later, and orders the necessary parts to the procurement system 4 based on the examination result.

  The storage device 33 includes a demand prediction parameter DB 331, a consumption result DB 332, a prediction result DB 333, an inventory information DB 334, and an order lot DB 335.

  The demand prediction parameter DB 331 includes parameters specified by the demand prediction parameter specifying unit, that is, a demand prediction method parameter, a result acquisition period parameter, a unit period parameter, an index parameter, a supply rate parameter, a procurement rate parameter, and a contract rate parameter. Store.

  The computing device 32 includes a designated demand prediction parameter receiving unit 321, a consumption result / prediction result automatic updating unit 326, an order review requesting unit 325, a demand prediction unit 322, a necessary amount calculation unit 323, and an order amount calculation unit 324.

  The designated demand prediction parameter reception unit 321 receives the parameter from the demand prediction parameter designation unit 311 and stores the parameter in the demand prediction parameter DB 331 of the storage device 33.

  The automatic update unit 326 compares the demand predicted value of the consumption result DB 332 with the result of the prediction result DB 333 for each product type, and applies (automatically updates) an optimal demand prediction method.

  The order review request unit 325 receives an order quantity calculation unit 324 (to be described later) and makes an order review request to the ordering department via the input / output device 31.

  The demand prediction unit 322 predicts the consumption of the replenishment center 21 (national consumption prediction) and the consumption of the replenishment base 22 (replenishment base consumption prediction × (1−GC-specific bar call rate)).

  The required amount calculation unit 323 calculates the required amount (replenishment amount) of parts at the replenishment center 21 and the required amount (replenishment amount) of parts at the replenishment base.

The order quantity calculation unit 324 determines the part order quantity based on the result of the necessary quantity calculation unit 323.
These processing procedures will be described in detail below.

  FIG. 3 shows a processing flow of order quantity calculation, and is a processing flowchart of demand prediction, necessary quantity calculation and order quantity calculation of the replenishment center 21 and the replenishment base 22.

  In the figure, in step S3221, demand prediction of the replenishment center 21 and the replenishment base 22 is performed. These demand predictions are performed based on the past consumption results in the consumption result DB 332 and the demand prediction method of the demand prediction parameter DB 331, parameters such as the result acquisition period (month), unit period (month), index (0 to 1), and the like.

  As the demand prediction method, for example, a moving average method, exponential smoothing method, Holt method, and Holt Winters method are used, and automatic updating of the prediction method by the automatic updating unit 326 includes exponential smoothing method, moving average method, Holt winter method. Update in accordance with the priority of the law and Holt law. And the demand prediction parameter mentioned above utilizes what was registered into demand prediction parameter DB331 and the consumption performance DB332 for every kind. The demand prediction result is stored in the prediction result DB 333.

  Next, in step S3231 and step S3232, the required amount of the replenishment center 21 and the replenishment base 22 is calculated. The required amount (replenishment amount) of the replenishment center 21 is calculated using parameters that specify the replenishment rate in the demand prediction parameter DB 331 instead of using the optimum sufficiency rate as in the prior art.

  Similarly, the required amount (replenishment amount) of the replenishment base 22 is calculated using parameters that specify the procurement rate in the demand prediction parameter DB 331 instead of using the optimum satisfaction rate as in the prior art. In the case of a supply base, the contract rate parameter is taken into account.

  Thereafter, in step S3241, the calculation result (required amount of parts) is received by the required amount calculation unit 323, and the order quantity is determined from the inventory in the inventory information DB 334 of the storage device 33 and the number of lots in the order lot DB 335.

FIG. 4 is a flowchart showing a specific example of a necessary amount calculation flow.
In the figure, when the required amount calculation is started in step S32311, first, demand prediction, that is, consumption prediction is performed in step S32312 by the demand prediction unit S3221.

  This prediction is based on a desired demand prediction method stored in the demand prediction parameter DB 331, and predicts the number of consumptions that will occur in the future from past results, for example, results such as a result acquisition period, unit time, and index. For example, nationwide consumption prediction of the replenishment center 21 is performed with traffic during the lead time (consumption prediction). In addition, the wear prediction of the supply base 22 below the supply center 21 is also performed.

  Consumption prediction of the replenishment center 21 is performed by, for example, nationwide consumption prediction total, and consumption prediction of the replenishment base 22 is performed by replenishment base consumption prediction.

  Next, the required calculation units 3232 and 3233 calculate the required amounts of the supply center 21 and the supply base 22. Here, what is important is to use the parameters set by the demand prediction parameter specifying unit 311 without using the optimum satisfaction rate.

  Next, in step S32313, it is determined whether the supply center 21 or the supply base 22. As a result of the step, in the case of the replenishment base 22 (Yes), in step S32314, the contract rate parameter specified by the demand prediction parameter specifying unit 311 is received, and the necessary amount is calculated by taking the parameter into consideration. That is, the contract rate (0 <contract rate <1) is taken into account only in the case of the supply base 22.

  Next, in step S32315, initial values such as the out-of-stock rate US1 and resource C = 0 are set.

  Subsequently, in step S32316, the previous value (C-1) is saved (previous value (C-1) is saved), and in step S32317, resource C = C + 1 (resource (C + 1) loop) is configured. In step S32318, the out-of-stock rate US and the effective inventory utilization level are calculated.

  Next, in step S32319, it is determined whether the fullness rate parameter is P = 1, that is, 100%.

  For the fullness rate, parameters are specified as the fullness rate of the replenishment center = the replenishment rate, and the fullness rate of the replenishment base = the procurement rate.

  In step S32319, when the fullness rate parameter is P = 1, that is, when the optimal fullness rate is not designated (P = 100%) (No), the process proceeds to step S32320, and in this step, the fullness rate parameter is designated (for example, P = 80%), and it is determined whether the fullness rate (1-out-of-stock rate US) exceeds the specified fullness rate ((1-US)> P). If the specified fulfillment rate is not exceeded (No), the process returns to step S32316. If it is the optimum filling rate designation (P = 100%) (Yes), the process proceeds to step S32321.

  In step S32321, it is determined whether the effective inventory utilization level has become smaller than the value at (C-1), that is, whether the effective inventory utilization level has exceeded the maximum value.

  As a result, when the maximum value is not exceeded (No), the process returns to step S32316. If the maximum value is exceeded (Yes), the process proceeds to step S32322. Then, in this step, data such as the resource C = C-1 and the out-of-stock rate US = USO of the optimal fulfillment rate (maximum effective inventory utilization) are saved, and the process proceeds to the next step S32323.

In step S32323, the resource C at this time is determined as necessary amount = C. That is, data such as the out-of-stock rate = US, the fullness rate = 1-US, etc. are determined.
Finally, in step S32324, the required amount calculation is ended.

  By specifying the replenishment rate and the procurement rate as in the above-described embodiment, it is possible for the part purchasing and deploying the parts to optimize the total order quantity of the parts. In addition, the contract amount for each product type, demand forecasting method, results acquisition period, unit period, index designation, and automatic update of the demand forecasting method allow optimization of the order quantity according to the characteristics of the product type. The effects on profits due to the optimization of this, for example, can be expected as follows.

(1) Order quantity reduction ⇒ Inventory quantity reduction ⇒ Reduction of unused parts ⇒ Reduction of disposal loss ⇒ Reduction of provision for material loss ⇒ Profit contribution (2) Order quantity reduction ⇒ Inventory quantity reduction ⇒ Storage cost reduction ⇒ Profit contribution (3) Order quantity Reduction ⇒ Inventory reduction ⇒ Total inventory value reduction ⇒ Depreciation cost reduction ⇒ Profit contribution (4) Order quantity reduction ⇒ Decrease order cost ⇒ CF contribution

In addition, this invention is not limited to the Example mentioned above, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described.
Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor.
Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. Actually, it may be considered that almost all the components are connected to each other.

1 Factory 2 Organizations and parts bases (logistics systems) that manage ordering of maintenance parts, base supply, emergency delivery, etc.
DESCRIPTION OF SYMBOLS 21 Supply center 22 Supply base 23 Base 3 Server 31, Input / output device 311 Demand prediction parameter designation | designated part 312 Parts ordering part 32 Arithmetic unit 321 Designated demand prediction parameter reception part 322 Demand prediction part 323 Necessary quantity calculation part 324 Order quantity calculation part 325 Order quantity request unit 326 Automatic update unit 33 Storage device 331 Demand element immediate parameter DB
332 Consumption results DB
333 prediction result DB
334 Inventory Information DB
335 Order lot DB
4 Procurement system (parts management system)

Claims (2)

In an order quantity calculation system in a system for supplying parts to a supply center and supplying parts from the supply center to a supply base,
Demand forecasting means for forecasting demand at the replenishment center and the replenishment base;
A required amount calculating means for calculating the required amount of the replenishment center and the replenishment base;
Order quantity calculation means for calculating the order quantity based on the calculation result and inventory information of the order quantity calculation means, and the order lot;
Have
The demand prediction means includes a processing unit that predicts the number of consumptions that will occur in the future based on past consumption results and demand prediction parameters specified for each type.
The required amount calculation means is based on the number of consumptions by the demand prediction means and the required quantity calculation parameter specified for each product type, from the supply rate indicating the supply rate of the supply center and the supply rate indicating the supply rate of the supply base It has a processing unit that calculates the required amount,
The order quantity calculation unit includes a processing unit that calculates an order quantity based on a calculation result of the order quantity calculation means, inventory information, and an order lot. The order quantity calculation system according to claim 1,
The demand prediction parameters include parts replenishment, demand forecasting technique for forecasting demand for replenishment, parts performance acquisition period, unit period, index,
The necessary amount calculation parameters include a supply rate of the supply center, a procurement rate of the supply base, a contract rate with a customer,
The order quantity calculation system, wherein the demand forecasting unit includes an automatic update unit that automatically updates a demand forecast method of the demand forecast parameter.