Methods and computer systems for reducing runtimes in material requirements planning

Methods and computer systems are provided for reducing the runtime of a material requirements planning run. In one embodiment, a computer system loads a plurality of bills of materials into a data structure. The computer system may analyze parent-child relationships between components of the plurality of bills of materials in the data structure and set for each component in the data structure a counter value that indicates the number of parent components for each component. The counter value of a specific child component may be decremented when the planning of a parent component of the specific child component is completed. The computer system may then proceed with the planning of the specific child component if the associated counter value indicates that the planning of all parent components of the specific child component is completed.

FIELD

Embodiments of the present invention generally relate to electronic data processing and, more particularly, to methods, computer program products and systems for material requirements planning (MRP).

BACKGROUND

Some computer systems, such as for example Enterprise Resource Planning (ERP) systems or Supply Chain Management (SCM) systems, support functions to plan material requirements for production. Complex products that include many components typically have large bills of materials (BOM). A bill of materials includes all components of a product in a hierarchical structure. The hierarchy indicates for each component which parent component is needed. A parent component can have multiple child components. When running material requirements planning for multiple products, multiple BOMs are processed simultaneously because some of the products may use the same components. Therefore, to plan these components that are used by multiple products, the requirements by each of the products are to be considered.

Some systems use parallelization to cope with a huge amount of data in case of simultaneous planning of many products. To ensure that all requirements are considered for a specific component, some systems create a data structure that includes the BOMs of all products being subject to material requirements planning and introduce planning levels in this data structure. Within a planning level, all components are planned before the system moves on to the next planning level. This guarantees that all requirements of the previous planning level are considered.

However, when using parallelization, it can occur that all but one component of a planning level are already planned and the system cannot move on to the next planning level because of the one still unplanned component. As a consequence, only one process is active while the last component of a planning level gets planned, whereas other parallel processes remain idle.

The idle processes have to wait until the last process finishes before parallel processing at the next planning level can continue. The waiting period can be long. In the case of configurable products, individual customer requirements exist at more than just the final product level which may cause waiting times at multiple planning levels. For example, if the final product is a kitchen, an inlay shelf may be included which is also included as a component in almost any other kitchen of the kitchen manufacturer. Thus, having orders for various kitchens creating requirements in the MRP for the same shelf, this shelf can become a long-runner in the MRP that occupies a process for hours and leaves the other processes waiting before moving to the next planning level.

Usually, such long-runners can be found at various planning levels and can form multiple barriers to parallel planning.

SUMMARY

Consistent with embodiments of the present invention, methods, computer systems and computer program products are provided for reducing MRP runtimes. This may be achieved by embodiments of the invention, as disclosed and claimed herein.

In accordance with one embodiment, a method is provided that comprises: loading a plurality of bills of materials into a data structure; analyzing parent-child relationships between components of the plurality of bills of materials in the data structure; setting for each component in the data structure a counter value that indicates the number of parent components for each component; decrementing the counter value of a specific child component when the planning of a parent component of the specific child component is completed; and proceeding with the planning of the specific child component if the associated counter value indicates that the planning of all parent components of the specific child component is completed.

Consistent with one embodiment, by introducing counters associated with components, the computer system may be able to decide about proceeding with the planning of components on a component-by-component basis. The need for planning levels to ensure the completeness of the planning of superordinate components may be eliminated. Further, parallelization of MRP runs can be used more efficiently because waiting times of idle processes can be avoided.

Aspects consistent with the present invention may be realized and attained by means of the elements and combinations particularly pointed out in this disclosure and the appended claims. The described combination of the features consistent with the invention is not be understood as a limitation, and all the features can be combined in other constellations without departing from the spirit and scope of the invention. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the invention as described.

DETAILED DESCRIPTION

FIG. 1is a block diagram of an exemplary computer system900for materials requirement planning, consistent with an embodiment of the invention. As illustrated, computer system900includes a first storage component200storing a plurality of bills of materials. Each bill of material may be associated with a product that can be subject to material requirements planning (MRP). The first storage component will also be referred to herein as a plurality (200) of BOMs.

The computer system900may also include a second storage component300that is used to store a data structure. The bills of materials associated with the products that are subject to MRP can be loaded through an interface503to the second storage component300. The second storage component will also be referred to herein as the data structure300.

In the data structure300, a child component can have multiple parent components that belong to multiple BOMs. In other words, the data structure300is used to establish parent-child relationships between parent components of various BOMs and a child component that is used by these parent components. As a consequence, the child component learns about requirements of multiple parent components originating from multiple products. Further, the child component is stored once in the data structure300instead of the redundant storage in plurality200of BOMs, where the child component is included in any product's BOM that makes use of the child component.

For example, the plurality200of BOMS can be implemented as a memory portion including tables with specific columns for storing parent and child attributes for each component of a BOM. The memory portion can be part of a database or can be part of the main memory of the computer system900.

The data structure300can also be implemented as a memory portion. Preferably, the data structure300is stored in the main memory because the access to the data structure300during the MRP run is faster than a database access would be.

The MRP run is controlled by an MRP engine100that has an interface502to the plurality200of BOMs and a further interface501to the data structure300.

By way of example, the MRP engine may control which BOMs are loaded from the plurality200of BOMs into the data structure300. The MRP engine may also analyze the parent-child relationships between components of the plurality200of BOMs in the data structure300to establish the above-explained parent-child relationships between parent components of various BOMs and a child component that is used by these parent components.

The MRP engine can be implemented as a computer program that is loaded into the memory of the computer system and executed by at least one processor of the system900. Other possible functions of the MRP engine are explained together with the following figures.

FIG. 2is an example of a portion of the data structure300at a first point in time after the data structure has been prepared by the MRP engine100to be used in a MRP run, consistent with an embodiment of the present invention.

Once the MRP engine100has analyzed parent-child relationships between the components of the plurality200of BOMs, the parent-child relationships310are established in the data structure300. The parent-child relationships310in the data structure300allow a child component A2to have multiple parent components F1, F2. By way of example, the components F1, F2may correspond to final products.

As further shown in the example ofFIG. 2, F1includes the child components A1, A2, which may correspond to sub-assemblies, for instance. A2further includes child components R1, R2, which may correspond to raw materials, for example. Additional sub-assemblies or raw materials that belong to F1may be provided and are not shown for convenience of illustration.

Once the parent-child relationships310are established in the data structure300, the MRP engine100scans the data structure300and sets a counter value (CV) for each component in the data structure300. Each counter value may indicate the number of parent components for the corresponding component. For example, the final products F1, F2have no parent components. Therefore, the corresponding counter values are set to CV=0. Further, the sub-assembly A1has the parent component F1. Therefore, its counter value is set to CV=1. Similarly, the sub-assembly A2has the parent components F1and F2. Therefore, its counter value is set to CV=2. And, the raw materials R1and R2have the parent component A2. Therefore, the corresponding counter values are set to CV=1.

At this point in time, no planning has been performed on any of the components which is illustrated inFIG. 2by unfilled circles.

FIG. 3shows an example of the portion of the data structure300at a second point in time after the MRP run has started. At the second point in time, the component F2has been planned successfully. This is illustrated by a bar pattern in the drawing.

The MRP engine100may decrement the counter values of the child components of F2after the completion of the planning of F2. In the example, the counter value of the specific child component A2is decremented from CV=2 to CV=1.

FIG. 4shows an example of the portion of the data structure300at a third point in time during the MRP run. At the third point in time, the planning of the component F1has been completed (illustrated by the bar pattern in the drawing).

As a consequence, the MRP engine100decrements the counter values of the child components of F1. In the example, the counter values of the specific child components A2and A1are decremented to CV=0. The counter value CV=0 associated with the specific child component A2indicates to the MRP engine that no further planning requirements are to be expected for the specific child component A2from any of its parent components F1, F2because the planning of the parent components F1, F2is completed. Therefore, the MRP engine can proceed with the planning of the specific child component A2.

FIG. 5is an example of an implementation of the data structure300, consistent with an embodiment of the invention. In this example, the data structure300is implemented as a non-relational table using pointers to reflect the parent-child relationships310between components.

InFIG. 5, each row of the table300refers to a component in the data structure. The relationship pointers310point from a parent component to its child components. Equally, the pointers can be implemented to point from child components to their parent components.

By way of example, table300can be based on a material master table of an application system. A material master table typically includes master data for each component (e.g., unit of measure, lot size, etc.) that is handled by the application system. By adding the relationship pointers310to the material master table, the BOM information and the material master data information is available in a single data structure. Therefore, during the MRP run, only one data structure (table300) needs to be accessed by the MRP engine. This reduces the total data access time.

In the example ofFIG. 5, the table300has a component column for storing a component ID (e.g., F1, F2, A1, etc.), a planning level column, a counter value column and a planning flag column.

The counter value column may store for each component the associated counter value CV that is calculated, as described inFIGS. 2 to 4.FIG. 5illustrates the state of the data structure at the first point in time (cf.FIG. 2).

The planning flag column may indicate for each component whether the component is subject to MRP or not. For example, some ERP systems set a planning flag for a specific component only if something has changed with respect to the requirements for this component. This can occur when the order size for a specific product using the specific component is changed or when further orders for products using the specific component are entered into the system or deleted from the system. Any of these cases has an impact on the requirements for the specific component and, therefore, will lead to setting a corresponding planning flag in the table300.

When performing the MRP run as described inFIGS. 2 to 4, the MRP engine may set the counter values only for those components having a planning flag. Further, in this implementation, the MRP engine can proceed with the planning of a child component only if the child component has a planning flag. One advantage of using the planning flag is that the MRP engine knows, in advance, any component in the table300that will not be affected by the MRP run. Thus, the MRP engine can ignore any component without a planning flag.

The values of the planning level column of this implementation may be obtained by using the parent-child relationships in the data structure to define a planning level for each component. How to define planning levels is known in the art and documented, for example, in the SAP training course “LO050: PP-Planning” or the SAP workshop “EWC10: Technical optimization of the Availability Check”.

In an embodiment of the invention, the MRP engine is able to proceed with the planning of the specific child component A2that belongs to a planning level1which is subordinate to the planning level0of at least one of the corresponding parent components F1, F1even if the planning of further components at the planning level0of the at least one corresponding parent component is incomplete. This allows the MRP engine to benefit from parallelization because the planning of the child component at the subordinate planning level can be performed by a first process while the planning of further components at superordinate planning levels can be performed by at least a second process in parallel. Without the concept of decrementing associated counters of child components (cf.FIGS. 2 to 4), the first process would need to wait until the further processes at the superordinate planning levels are completed.

Additionally, each component can have a further attribute for storing a time statistics where the planning duration of the previous MRP run is recorded for the component. In the table300, the further attribute may correspond to a further column. In this case, statements about the probable planning duration for each component can be derived by the MRP engine from a forecast based on the previous MRP run, since usually MRP runs in a company tend to be similar.

Components can be bundled into packages for optimized parallel processing. For example, components can be bundled so that long-runners are grouped with short-runners. The approximate MRP runtimes for the packages can be calculated in advance, to improve their grouping and approximate a simultaneous completion of all processes. MRP runtime is proportional to the number of planning items, such as, for example, planned orders, purchase requisitions, delivery schedule lines, etc., that are to be created during the planning run. The number of planning items per product depends on various planning mechanisms, such as the lot-sizing procedure and/or the number of requirements (e.g., sales orders, forecast demand) and does not change much over time. The number of planning items per product can be stored in a planning file for later use. The packages can then be built packages in such a way, that a predefined number of planning items is created in each package. For example, in an SAP APO-PP/DS application, good performance results can be achieved when each package creates approximately 1000 planning items. Complex planning items may require smaller packages.

Method steps consistent with embodiments of the present invention may be performed by one or more programmable processors executing a computer program to perform functions of the invention by operating on input data and generating output. Method steps can also be performed by, and apparatus consistent with the invention can be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

Processors suitable for the execution of a computer program may include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are at least one processor for executing instructions and one or more memory devices for storing instructions and data. In one embodiment, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks. Information carriers suitable for embodying computer program instructions and data may include all forms of non-volatile memory, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in special purpose logic circuitry.