JPS63104132A - Extension system for summary of parts list - Google Patents

Abstract

PURPOSE:To omit the change of a record pointer and to attain operations under control of a multi-programming job by preparing a heap data table and a stack pointer table and carrying out the summary extension by means of the heap sorting principle. CONSTITUTION:An item X to under go the summary extension is accepted with an external input and the record on the item X is retrievel out of a data base. Then the record on a slave parts of the item X is retrieved out of a data base and the succession information is set the record on the retrieved slave parts. These records are stored in a heap table based on the heap principle. Then it is checked whether the master part undergone retrieval of the slave parts is equal or not to the first parts of the data table. If so, the first record is extracted out of the heap table and this table is rearranged. Then plural same records are collected and a record X is delivered. The operation is through as long as no data is contained in a data table. While the first data is extracted out of the heap table when the data table contains data. Then the slave parts is retrieved and processed in the same way as the previous time.

Description

DETAILED DESCRIPTION OF THE INVENTION (Field of Industrial Application) The present invention relates to a bill of materials summary development method in a structured bill of materials.

(Prior art) A summary parts list is a table that summarizes in the form of a list intermediate parts and raw materials that are required when manufacturing a certain item, without regard to the processing order of parts or the assembly order of products. These basic units are aggregated and shown at once, even if the materials are used multiple times and at various levels.

Figure 5 is a structural parts list for item X. υItem X is a child part A.
and C, part A is made up of child parts B and E, part C is made up of child parts E and H, and so on). The part record information also includes the required number of child parts, etc.), and each part has a hierarchical structure, with item X at level 1, part A at level 2, and parts B and C.
indicates that it is hierarchically classified as level 3, etc.

Here, part E is a common component of parts A and C (9), and parts E and subsequent parts are also developed from these two directions.

This means that parts after E must be expanded twice. Therefore, for part E, it is efficient to consolidate the expansions from these two directions and perform the subsequent expansions only once, and this is the summary expansion method.

A conventional bill of materials summary development method for creating a summary bill of materials from the structural bill of materials shown in FIG. 5 will be described with reference to FIG. 6.

First, a table 61 is prepared in which a pointer is provided for each hierarchy or level of the structural parts list, and initial settings are made. The initial setting value is the end (END) code for each level (FIG. 6(a)).

Read the next Ka upper record X (X is a part name, and the record related to it will be referred to as record Set the address for each record. i.e. level 1
Address of record X (hereinafter referred to as ADR(X)), ADR(A) at level 2, A at level 3.
Set DR(C). Then, the END (initial value of the table) that has been in the pointer table 61 is set to the pointer in each record 62 (FIG. 6(b)). Since END is detected in the pointer in record X, which is the record of X retrieved from the database, level l ends.

Next, look at pointer table 610 level 2 and record A.
, search for child records connected to it, find records B and record E, set these addresses to each level of the corresponding pointer table 61, and pointers in records B and E to the ADR ( C) and setting E N D (6th
Figure (C)).

Such processing is repeated in order of levels such as hl, U, l), E, F, G, H, etc. However, since the child record EVi when reading C is already chained in the pointer table, it is not set as an executive (FIG. 6(d)).

As described above, in the conventional summary expansion method, when processing is carried out in level order while inheriting some information from the higher level, it is considered that even records below records with a high degree of sharing such as E only need to be processed once. There is.

(Problems to be Solved by the Invention) As explained above, in the conventional summary expansion method, it is necessary to have an address for tuning in records at the same level, and it is essential to change this record.

Therefore, it cannot operate under multiprogramming,
Another problem is that the physical I10 required for changing records increases.

(Means for solving the problem) The method of the present invention prepares a table for storing data so as to form a heave with respect to a sort key, initializes the table, receives an item for summary expansion, and searches the data of the item. The first process supplies the item as a summary output target item to the second process, and the third process checks whether there are any child items constituting the supplied summary output target item and if there are no child items, the third process
A second step that supplies the item data for summary output to the third step, searches for the data of the child item when there is the child item, stores it in the table, and supplies the item data for summary output to the third step. Compare the process, the supplied summary output target item, and the first data stored in the table, and if they are the same, extract the first data and aggregate it with the data of the summary output target item. a third step that outputs the summary result and moves on to a fourth step; and if data is stored in the table, it is extracted and supplied to the second step as a summary target item, and the data is stored in the table. and a fourth step that ends when the data is not stored.

(Example) Next, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a flowchart showing one embodiment of the present invention.

In this embodiment, a heave table shown in FIG. 4(a) is prepared prior to processing. There are two types of heave tables, one of which is a data table TABLE, which is a memory that stores data. The other one is the stack pointer table PTBL, which stores pointer values. In FIG. 4(a), PP is a pointer to the stack pointer table PTBL.

Some symbols will be defined below for convenience of explanation.

PP indicates a pointer without indicating the position where the pointer is set. That is, PP=n indicates that the pointer points to the PTBLOnth position in the stack pointer table. Next, PTBL(n) indicates the value stored at the nth position in the stack pointer table PTBL. Further, T A B L E (n) indicates the data stored in the nth position of the data table TABLE.

Further, V A L U E (n) indicates the sort key value of the nth data stored in the data table TABLE. The sort key value shall be indicated by the level number of the item and the physical address of the record.

The physical address of the record shall in this case be an alphabetical term. That is, the physical address of record A is smaller than the physical address of record B.

Next, the heave principle is adopted as a rule for storing data in the data table TABLE.

That is, VALUE(n) (VALUE(2n) and VALUE(n)(VALUE(2n+1)
The data is stored in the data table TABLE as follows.

Also, the pointer PP of the stack pointer table PTBL
is incremented by -1 each time data in the data table TABLE is deleted, and incremented by +1 each time data is added. In addition, whenever an empty space becomes available in the data table TABLE, the empty address (in this case, the number indicating which position became empty) is saved in the stack pointer table, and the next data can be inserted. By having the address as information below the pointer PP, the pointer PP indicates the number of valid data in the data table TABLE.
Cheetah table at that point by efficiently utilizing the empty space inside.
The size of I'ABLE can be kept optimal.

The initial value of the stack pointer table PTBL is set to a sequential number starting from 1, which is the maximum size of the data table TABLE, and the initial value of the data table TABLE is set to the maximum value of the sort key value (hereinafter referred to as HIGH-VALUE).

Next, this embodiment will be explained with reference to FIG. 1 and using the structural parts list shown in FIG. 5 as an example.

This embodiment is based on 1. shown in FIG. II, III and ■4
It consists of two processes.

In the first step shown in (2), first, item X to be expanded as a summary is received as input from the outside (step 101), and then the heave table is initialized. That is, store HIGH-VALUE in each column of the data table TABLE, store sequential numbers starting from 1 in each column of the stack pointer table P'I'BL, and set the pointer PP to the 1 position of the stack pointer table device. (step 102).

Next, a record regarding item X is searched from the database (step 103).

Next, proceed to the second step indicated by ■. That is, a record of child parts of item X is searched from the database (step 10).
4). If there are no child parts, the process moves to the eighth step (N branch of step 105), but if there is, inheritance information is set in the searched child part records (parts A and C in this case) (step 106) of the heave. Store these records in the heave table according to the principle (
Step 107). The heave table storage process will be described later. FIG. 4(b) shows a state in which record person and record C are stored in the heave table.

Next, proceed to the third step indicated by ■. Here, first, it is checked whether the parent part (in this case, Then, the heave table is organized (step 110), and since there are multiple identical records, they are aggregated (step 111), and the aggregation results are output (step 112). The heave table extraction process will be described later. Since record X is not the same as the first record (record A) in the data table (step 112) to output record X (N branch of step 109), the process moves to the fourth step.

In the fourth step, if there is no data in the data table TABLE, the process ends (N branch of step 113), and if there is, the first data is extracted from the heave table (step 114).L moves on to the second step of searching for its child parts. . In this case, record A is extracted, and after the extraction, the heave table is organized. The result is Figure 4 (C)K
This is an indication.

In this way, in this embodiment, using the heave table, the sort key order is KX→A→B→C→D→E-, F→G-
, H and one summary output can be obtained.

Next, the heave table storage process in step 107 and the extraction process from the heave table in steps 110 and 114 will be described.

FIGS. 4(a), (C), and (e) show the storage state of the heave table before the heave table storage process,
In contrast, Figures 4(b), (d), and (
f) shows the state after the storage process. Also, Fig. 4(b),
4(d) shows the storage state of the heave table before the extraction process from the heave table, whereas FIGS. 4(C) and 4(e) show the storage state after the heave table extraction process, respectively.

First, step 107 will be explained with reference to FIG. 2, which is a flowchart of the heave table storage process.

Regarding the storage of the child part A of X, in step 201, PP=1PP TBL(t)=1 in FIG. Since m = Q in step 202, step 206 passes through the ON branch of step 203.
In this case, A is set as TABLE (1), that is, it is set first, and P
p=2.

Storage of child part C of X is PP = 2, PTBL (2)
=2=n, m=1, VALUE(1)=A sort key.

A's sort key, C's sort key, step 203, N.
After passing through the branch, C is set to TABLg(2), that is, second, and PP=3. This is shown in FIG. 4(b).

The storage of child parts B and E of A will be explained. The state before storage is shown in FIG. 4(C). First, the child part B is stored, PP=2, PTBL(2)=2=n, m=1, V
ALUE (1)=CO/-to #-, Con-1 key>B
Because of the sort key, the Y branch of step 203 is passed through step 2
04, TABLE(1)=C is T A B L
E Move to (2) and set n to 1 in step 20
2. TABLE (1) is B and P through the 203ON branch
Let P=3.

Next is the storage of E, PTBL (3) = 3 = n, m =
1, VALUE (1) = B's /-t *-, B (7) sort key ｜ E's sort key, so E is r A B L E
(3) and PP=4. This is Figure 4 (mountain). Figure 4 (f) shows the storage of the child parts of B, Figure 4 (2) shows the storage diagram of the child parts of C, and Figure 4 (2) shows the storage diagram of the child parts of E. 4
It is shown in figure (h). In this manner, data of child parts is stored in the heave data tables TABI and EK based on the heave principle.

Next, steps 110 and 114 will be explained with reference to FIG. 3, which is a flowchart of the extraction process from the heave table.

Consider the case where all A are extracted from FIG. 4(b) in step 114. In step 301, TABLE(1), that is, A
, and set k=l (Step 302), VALUE
Since the (2)=CO/-)*- value is not HIGH-VALUE, the process passes through the ON branch of step 303.

VALUE(2)≦VALUE(3)=HIGH-MA
TABLE (2) through the Y branch of LUE step 304
In other words, move C to TABLE (1) in step 305.
) k = 2, step 306), VALUE (4) and VALUE (5) are both KHIGH-VALUE, so in step 309 TABLE (2) KHIGH-VALUE
Set PP=2 and P 'I' B L(2)=
Set it to 2. This is the state shown in FIG. 4(C).

Next, when extracting B from FIG. 4(d), C becomes TABLE (1) in the same manner as described above, but in step 306
2 = 2 and the Y branch of step 303 and 2 T A
B L E (2) KHI GHV AL U E t
)L, PP=3 and P TBL (3)=2, and the empty storage position of the data table TABLE is saved to the stack pointer table PTBL.

In this way, after data is extracted, the heave table is organized according to the heave principle. Figure 4(g) is similar to Figure 4(f).
) is a diagram in which C is extracted from C and its child parts are stored, and the fourth
FIG. 4(h) is a diagram in which E is extracted from FIG. 4(g) and child parts of E are stored. When extracting this E, aggregation processing in steps 109, 110, 111, and 112 is performed.

In this embodiment, the heave is arranged in order of decreasing sort key value, but the present invention is not limited to this.

(Effects of the Invention) In the present invention, a heave data table and a stack pointer table are prepared and summary expansion is performed using the principle of heave sort.Therefore, there is no need to change the record pointer, and operation under multiprogramming is improved. 9, and the physical I10 does not increase.

[Brief explanation of the drawing]

FIG. 1 is a flow chart showing one embodiment of the present invention, and FIG.
The flowchart of the heave table storage process shown in the figure, Figure 3 is the first
Figure 4 is a flowchart of the extraction process from the heave table, Figure 4 is a data storage diagram showing the heave cheetah table and stack pointer table and their data storage process in parts list summary expansion, and Figure 5 is a structured parts list. FIG. 6 is a data storage diagram of a pointer table showing conventional parts table summary development. 61 -------Pointer table, 62...
Records, 101-114, 201-207, 301-
311...Step of flowchart, PP...
・Pointer, PTBL...Stack pointer table, TABLE Figure 1 (gradient (b) (C)
(d) (+!ri
(f) (g) (λ) Figure 4 Figure 5 (required) (d) Figure 6

Claims (1)

[Scope of Claims] A table is prepared to store data so as to constitute a heave with respect to a sort key, the table is initialized, an item for summary expansion is received, the data of the item is searched, and a second step is performed to select the item for summary output. The first step is to supply the summary output target item data to a third step, which checks whether there are any child items constituting the supplied summary output target item, and if there are no child items, the summary output target item data is supplied to a third process, and if the child item is In some cases, a second step searches for data on the child item, stores it in the table, and supplies the summary output target item data to a third step; A third step in which the first data is compared with the first data, and if they are the same, the first data is extracted and aggregated with the data of the summary output target item, a summary result is output, and the process moves on to the fourth step. and a fourth step which extracts data when data is stored in the table and supplies it to the second step as a summary target item, and ends when data is not stored in the table. Features a parts list summary expansion method.