JP2013089122A - Work information guidance device, work information guidance method and computer program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To extract information that guides a user in understanding working relationships between each worker and other workers in a same work team, in such a manner as to indicate the number of workers by time and place.SOLUTION: Process data P(t) is generated from a workflow. When an RFID reader 210 placed in a work area receives ID information on RFID tags worn by workers 220, position measurement data S''(t) indicating the actions of the workers is generated. The position measurement data S''(t) and the process data P(t) for respective work categories W are compared, and cross-correlation Cindicating similarity of numbers of workers by elapsed time and place and total required time difference Tare calculated for the respective work categories W, and then information indicating the calculation result is displayed.

Description

  The present invention relates to a work information guidance device, a work information guidance method, and a computer program, and more particularly, to extract knowledge (implicit knowledge) information related to actions taken by an operator based on experience and intuition at a work site. It is suitable for use in.

Conventionally, in a work site, a workflow in which the behavior of each worker is described in time series is created, and each worker performs work based on this workflow. As a technique for creating or providing such a workflow, there are techniques described in Patent Documents 1, 2, and 3.
In the technique described in Patent Document 1, a desired process example is searched from past process examples, a desired process example obtained from the search result of the process example is used as a new process model, and a process model is described as necessary. Are added or modified using a user interface. In the technique described in Patent Document 2, when a user requests to start editing a process instance flow during the execution of a process, the process is stopped and the user is allowed to edit the process instance flow. In the technique described in Patent Document 3, work information is stored in association with time information, and position information of each staff is stored in association with time information. The accumulated data is extracted and provided.

JP 2007-188144 A JP 2007-4776 A JP 2002-236744 A

By the way, at work sites such as the steel industry, in order to improve production efficiency and reduce production costs, the number of operations is being reduced by automating operations. In addition, a situation has occurred in which the number of skilled workers (in the following description, “skilled worker” is referred to as “skilled worker” as necessary) is reduced.
Experts often take effective actions that are not described in the workflow, relying on their experience and intuition. In actual work sites, non-experts can “see, ask, imitate, and remember” the actions of skilled workers, and on-the-job training (OJT) can prevent such effective actions of skilled workers. It is handed down to experts. Therefore, based on such experience and intuition, how to clarify knowledge about the actions taken by the skilled person (in the following explanation, this “knowledge” will be referred to as “implicit knowledge” as necessary) Whether it is useful is an important issue.

  However, in the conventional technique described above, the user only edits the workflow or presents the behavior of the staff, and does not disclose a technique for extracting tacit knowledge possessed by a skilled person.

Therefore, the present inventors have proposed a technique described in Japanese Patent Application No. 2011-5113. In such a technique, first, an action corpus in which data indicating an operator's action and actions described in a workflow are associated with each other is prepared. And the technique corresponding to the data which shows the actual worker's action was extracted from the action corpus, and the technique which changes a workflow based on the extracted action was proposed. This technology makes it possible to extract tacit knowledge possessed by a skilled person.
By the way, in a work site, a plurality of workers may act as one work team. In such a case, it is desirable to extract how each worker (expert) behaves in relation to other workers in the same work team as tacit knowledge of the worker.
However, the technique described in Japanese Patent Application No. 2011-5113 basically extracts tacit knowledge of a single expert. For this reason, the information that serves as a guideline for grasping how each worker (expert) behaves in relation to other workers in the same work team is used. There was a problem that it was difficult to extract as.

  The present invention has been made in view of the above-described problems, and for understanding how each worker (expert) behaves in relation to other workers in the same work team. It is an object of the present invention to be able to extract information serving as a guideline in the form of the number of workers for each time and place.

  The work information guidance device of the present invention is a workflow in which work performed by a plurality of workers as one work team is described in a time series, a work classification to which the work belongs, a place where the work is performed, Process data setting means for setting process data indicating the contents of the workflow including the necessary number of workers required for the work and the time required for the work as attributes, and a predetermined place in the work place When the behavior information indicating the behavior of the worker is received from the device, the worker performs the location, the worker, the time that the worker is in the location, and the worker at the location based on the behavior information. Position measurement data setting means for setting position measurement data for specifying the work classification to which the work belongs and the work team to which the worker belongs, and the position measurement data setting means From the position measurement data set by, the actual number of workers, who is the number of workers per time and place when a plurality of workers of the same work team performed the work included in the workflow, was extracted. The comparison calculation means for calculating the degree of similarity between the actual number of workers for each time and place and the required number of persons for each time and place in the process data is calculated by the comparison calculation means and the comparison calculation means. And a comparison calculation result display means for displaying information indicating the degree of similarity for each work category.

  The work information guidance method of the present invention is a workflow in which work performed by a plurality of workers as one work team is described in time series, and the work classification to which the work belongs, the place where the work is performed, A process data setting step for setting process data indicating the contents of a workflow including the necessary number of workers required for performing the work and the time required for the work as attributes, and a predetermined place in the work place When the behavior information indicating the behavior of the worker is received from the device, the worker performs the location, the worker, the time that the worker is in the location, and the worker at the location based on the behavior information. A position measurement data setting step for setting position measurement data for specifying the work classification to which the work belongs and the work team to which the worker belongs, and the position measurement data setting process From the position measurement data set by, the actual number of workers, who is the number of workers per time and place when a plurality of workers of the same work team performed the work included in the workflow, was extracted. A comparison calculation step for calculating the degree of similarity between the actual number of workers for each hour and place and the required number of people for each hour and place in the process data is calculated by the comparison calculation step and the comparison calculation step. And a comparison calculation result display step for displaying information indicating the degree of similarity for each work category.

  A computer program according to the present invention causes a computer to execute each step of the work information guidance method.

  According to the present invention, based on the behavior information indicating the behavior of the worker, the worker, the place where the worker is located, the time when the worker is in the place, and the worker at the place Set position measurement data to identify the work category to which the work belongs and the work team to which the worker belongs, and compare the set position measurement data with the process data indicating the contents of the workflow to determine the time. The degree of similarity of the number of workers for each place is calculated for each work category, and information indicating the degree of similarity is displayed. Therefore, information that serves as a guideline for grasping how each worker behaves in relation to other workers in the same work team, in the form of the number of workers per hour and place. Can be extracted and displayed.

It is a figure which shows an example of a functional structure of a work information guidance apparatus. It is a figure which shows an example of a work site. It is a figure which shows an example of a workflow. It is a figure which shows an example of the attribute information of a workflow. It is a figure which shows notionally an example of the content of process data P (t). It is a figure which shows notionally an example of the content of the position measurement data produced by the position measurement data creation part. It is a figure which shows notionally an example of the content of the position measurement data to which the work classification was provided. It is a figure which shows notionally an example of the content of the position measurement data converted into the data of the same format as process data. It is a figure which shows notionally an example of all the contents of the position measurement data converted into the data of the same format as process data. It is a figure which shows the part of the partial matrix of the injection | pouring completion | finish process of process data, and the part of the partial matrix of the injection | pouring completion | finish process of position measurement data. It is a figure which shows the partial matrix which normalized the partial matrix of the injection | pouring completion | finish process of process data, and the partial matrix which normalized the partial matrix of the injection | pouring completion | finish process of position measurement data. It is a figure which shows an example of "the difference (total time difference) and cross correlation of total required time" of each work division of the work team whose team name is "2." It is a figure which shows the specific example of a display of the result of the comparison for every work division of the actual work of a work team, and a workflow. It is a flowchart explaining an example of operation | movement of a work information guidance apparatus.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings.
FIG. 1 is a diagram illustrating an example of a functional configuration of the work information guidance device 100. In this embodiment, a workflow is prepared in which work (actions) performed by a plurality of workers as one work team is described in time series. The work information guidance apparatus 100 compares “data indicating actual behavior of each worker” with “data indicating behavior required for each worker” obtained from the workflow in the work team. And the work information guidance apparatus 100 alert | reports (guidance) the information which shows those differences as the tacit knowledge information of each worker of the said work team.
Hereinafter, details of the functions of the work information guidance apparatus 100 will be described. The hardware of the work information guidance device 100 can be realized by using, for example, an information processing device including a CPU, ROM, RAM, HDD, and various interfaces.

[Workflow setting unit 101]
The workflow setting unit 101 sets (stores) workflow information based on an operation of a user interface (operation device) by an operator.
<Specific examples of work sites>
FIG. 2 is a diagram illustrating an example of a work site.
In the present embodiment, a case where three workers work as one work team in a continuous casting facility will be described as an example.
In FIG. 2, the work site 200 includes a crane 201, a TDC (tundish car) 202, an MD (mold) 203, a pulpit 204, and a plaza 205. The crane 201 carries the ladle in which the molten steel produced | generated by the converter was poured. Molten steel is poured from the ladle set on the rotary turret by the crane 201 into the MD 203 as a mold through a tundish placed on the TDC 202. In the process of passing through the MD 203, a slab is formed from the molten steel. Palpit 204 is a so-called operation room.
One RFID (Radio Frequency Identification) reader 210a to 210d is installed in each of the work area of the crane 201, the work area of the TDC 202, the work area of the MD 203, and the work area of the Palpit 204.

<Specific examples of workflow>
FIG. 3 is a diagram illustrating an example of a workflow, and FIG. 4 is a diagram illustrating an example of attribute information of the workflow illustrated in FIG.
As shown in FIG. 3, in this embodiment, the workflow is performed in the continuous casting facility until the molten ladle is injected from the ladle to the tundish until the processing for the empty ladle is performed. A case where the workflow is for the above work will be described as an example. As described above, in the workflows shown in FIGS. 3 and 4, each work belongs to one of the three work categories of the injection end process, the adjustment process, and the empty processing process.

4, “work name” indicates the name of each work, and corresponds to the work name shown in FIG. “Place” indicates a place (work area) where the work of “work name” is performed. The “necessary number” is the number of workers necessary to perform the work of “work name”. “Man-hour” indicates the total time required for the work of “work name”. Here, every time the man-hour value increases by 1, the total required time increases by 30 seconds. For example, when the value of the man-hour is “2”, the total required time is 60 seconds (= 2 × 30 seconds).
The “work order” indicates the order in which the work of “work name” is performed. Here, since it is conceivable that a plurality of people perform different work in parallel, there may be work having the same “work order”. For example, one worker performs a turret half turn (SN connector removal) when “work order” is “2”, while another worker performs monitoring work when “work order” is “2”.

Here, an overview of the workflow shown in FIGS. 3 and 4 will be described.
First, when pouring of the molten steel from the ladle into the tundish is completed, a long nozzle (LN) communicated with the hot water outlet formed in the center of the bottom of the ladle and the insertion port formed in the center of the tundish canopy. ) Is removed (“LN removal”). This “LN removal” is performed by two workers in the work area of the TDC 202 over 60 seconds (see FIG. 4).
Next, the turret is made to make a half turn (1/4 rotation) (“turret half turn”). At this time, the sliding nozzle (SN) is removed (“SN connector removal”). This “turret half turn” is performed by two workers in the work area of the TDC 202 over 60 seconds (see FIG. 4). reference).

Next, the turret is further turned half a turn (1/4 turn) (“turret half turn”). At this time, a long nozzle is attached to the hot water outlet formed in the center of the bottom of the ladle where the molten steel is injected next and the insertion opening formed in the center of the tundish canopy ("LN installation"). This “turret half turn” is also performed by two workers in the work area of the TDC 202 over 60 seconds (see FIG. 4).
Then, the sliding nozzle of the attached long nozzle is opened (“SN open”). This “SN opening” is also performed by two workers in the work area of the TDC 202 over 60 seconds (see FIG. 4).
Thereafter, the TDC is adjusted (“TDC adjustment”). “TDC adjustment” is performed by one worker in the work area of the TDC 202 over 60 seconds (see FIG. 4).
Another operator performs “operation monitoring” from the start of the turning of the turret until the sliding nozzle is opened and the subsequent TDC adjustment (“TDC adjustment”) is started. This “operation monitoring” is performed by one worker in the work area of the Palpit 204 over 300 seconds (see FIG. 4).
Thus, the injection end process is completed.

Next, various adjustment operations are started (“adjustment start”). This “adjustment start” is given to the workflow for the purpose of indicating the start of the work division.
In the adjustment process, one of the workers moves to another place (“move”). The total time required for “movement” is 240 seconds (see FIG. 4). Also, TDC adjustment is performed (“TDC adjustment”). “TDC adjustment” is performed by a single worker in the work area of the TDC 202 over 180 seconds (see FIG. 4). Further, “operation monitoring” is performed while the “movement” and “TDC adjustment” are performed. “Operation monitoring” is performed by one worker over 240 seconds in the work area of the Palpit 204 (see FIG. 4).
Thus, the adjustment process ends.

Next, the empty pan processing operation is started (“empty pot processing start”). This “empty pan processing start” is given to the workflow for the purpose of indicating the start of the work division.
In the empty pot processing step, “empty pot processing” and “operation monitoring” are performed in parallel. “Empty pan processing” is performed by one worker in the work area of the crane 201 for 1200 seconds, and “operation monitoring” is performed by one worker in the work area of the Palpit 204 over 1200 seconds. Is what you do.
Thus, the empty pan processing step is completed.

As shown in FIG. 4, in the present embodiment, the workflow attribute information includes a work name, a work category, a place, a required number of people, a man-hour, and a work order.
As shown in FIGS. 3 and 4, in the present embodiment, the workflow is divided into three work sections, that is, an injection end process, an adjustment process, and an empty pan process. This work classification represents a unit to be compared with data indicating the behavior of the worker as will be described later. Therefore, as long as the workflow is divided at a certain part of the workflow, the work division may be determined in any way. For example, you may determine each which divided | segmented the workflow into every predetermined time (for example, 10 minutes) as a work division.

  The workflow setting unit 101 is realized, for example, when the CPU stores, in an HDD or the like, workflow information (information shown in FIGS. 3 and 4) input based on a user interface operation. The workflow information may be transmitted from an external device or read from a portable storage medium.

[Process data creation unit 102]
The process data creation unit 102 creates process data P (t) that can be compared with data indicating the behavior of the worker from the workflow information set by the workflow setting unit 101 as described later. To store (set).
The format of the process data P (t) is, for example, the following formula (1).
P (t) = (t, process (t), n _p1 (t), n _p2 (t),... N _pm (t)) (1)

In the formula (1), t represents elapsed time. However, here, the elapsed time t is expressed in units of the above-described man-hours. That is, with the elapsed time t value being “0” (workflow start time (in this case, the injection end process start time)) as a reference, the elapsed time t value is incremented by “1” every 30 seconds. Will be added.
process (t) represents a work category to which the work being performed at the elapsed time t belongs.
n _pm (t) represents the number of workers (necessary number) who need to work at the location pm at the elapsed time t.
FIG. 5 is a diagram conceptually showing an example of the contents of the process data P (t). As shown in FIG. 5, in this embodiment, work is performed in five locations: a work area of the crane 201, a work area of the TDC 202, a work area of the MD 203, a work area of the Palpit 204, and other areas. A place. Therefore, in the expression (1), the value of m is “5”.

The process data creation unit 102 is realized, for example, when the CPU reads out workflow information from the HDD or the like, creates process data P (t) shown in Formula (1), and stores the process data P (t) in the HDD or the like.
In the present embodiment, the process data P (t) is created by inputting a workflow, but it is not always necessary to do so. For example, the process data P (t) may be directly acquired and stored (set) based on the operation of the user interface (operation device) by the operator without inputting workflow information.

[Tag ID acquisition unit 103]
The tag ID acquisition unit 103 acquires RFID tag ID information from the RFID readers 210a to 210d.
In FIG. 2, workers 220a to 220c work while wearing RFID tags. When the RFID tag enters the communication area of the RFID reader 210, the RFID reader 210 receives information on the ID of the RFID tag. Then, the RFID reader 210 transmits the received RFID tag ID information and the RFID reader 210 ID information to the work information guidance apparatus 100.

In the present embodiment, the tag ID acquisition unit 103 acquires (accumulates) ID information transmitted from the RFID reader 210 every time a predetermined time (for example, 30 seconds) elapses with reference to the workflow start time. And
In the tag ID acquisition unit 103, for example, the communication interface receives information on IDs (the ID of the RFID tag and the ID of the RFID reader 210) transmitted from the RFID reader 210, and the CPU receives the information on the two IDs received. This is realized by associating the reception time information of the ID with each other and storing them in a RAM or the like.

[Position measurement data creation unit 104]
In the work information guidance device 100 (position measurement data creation unit 104), team / worker identification information is set which indicates which worker of which team corresponds to the ID of the RFID tag. In addition, RFID reader identification information indicating which RFID reader 210 is installed in which work area is set. These settings can be made, for example, based on an operation of a user interface (operation device) by an operator.

The position measurement data creation unit 104 identifies the ID value acquired by the tag ID acquisition unit 103, the RFID reader 210 that is the transmission source of the ID, and the timing at which the ID is acquired. Then, the position measurement data creation unit 104 determines which worker of which team is in which location at which timing based on the identified result, team / worker identification information, and RFID reader identification information. .
Here, when the position measurement data creation unit 104 cannot determine where the worker is, such as when the ID cannot be acquired from the RFID reader 210, the worker uses the RFID reader 210. It is determined that the operator is at a remote location or is moving between work areas, and the operator is determined to be in another location.

Then, the position measurement data creation unit 104 creates the position measurement data S (t) based on the result of the above determination.
The format of the position measurement data S (t) is, for example, the following formula (2).
S (t) = (t, team (t), p _w1 (t), p _w2 (t),... P _wn (t)) (2)
In the formula (2), t represents time. However, here, unlike Equation (1), t represents the actual time.
team (t) represents the name of the team that is working at time t.
p _wn (t) represents a place where the worker w is present at time t.
FIG. 6 is a diagram conceptually illustrating an example of the content of the position measurement data S (t) created by the position measurement data creation unit 104. FIG. 6 shows only position measurement data S (t) corresponding to a part of the workflow. As described above, in this embodiment, since three workers work as one work team, the number of workers included in the position measurement data S (t) as shown in FIG. Is three (see workers A, B and C). That is, in the formula (2), the value of n is “3”.
In the position measurement data creation unit 104, for example, the CPU reads information of ID (ID of the RFID tag and ID of the RFID reader 210) from the RAM or the like, and the position measurement data S (t) shown in the equation (2) Is realized and stored in a RAM or the like.

[Work classification giving unit 105]
In this embodiment, an alarm based on voice announcement (VA) is issued at the start and end of each work section. The VA alarm information indicating the contents of the VA is stored in a process computer (not shown) together with the VA generation time information indicating the time when the alarm is generated by the VA.
The work classification assigning unit 105 receives the VA alarm information and the VA occurrence time information from the process computer. Based on the VA alarm information and the VA occurrence time information, the work classification assigning unit 105 performs the work performed at the time t indicated by the position measurement data S (t) created by the position measurement data creation unit 104. The work classification process (t) to which the

Then, the work category assigning unit 105 assigns the work category process (t) to the position measurement data S (t), and creates position measurement data S ′ (t) in the format shown in the following equation (3).
S ′ (t) = (t, process (t), team (t), p _w1 (t), p _w2 (t),... P _wn (t)) (3)
FIG. 7 is a diagram conceptually illustrating an example of the content of the position measurement data S ′ (t) to which the work division process (t) is assigned. FIG. 7 shows position measurement data S ′ (t) obtained by assigning a work division process (t) to the position measurement data S (t) shown in FIG.
The work classification assigning unit 105 receives, for example, VA alarm information and VA occurrence time information from a process computer that is connected so that the communication interface can communicate with each other via a communication line. Based on the position measurement data S (t) read from the RAM or the like, the position measurement data S ′ (t) shown in the equation (3) is created and stored in the RAM or the like.

[Position measurement data conversion unit 106]
The position measurement data conversion unit 106 converts the position measurement data S ′ (t) into data S ″ (t) in the same format as the process data P (t).
The format of the position measurement data S ″ (t) is, for example, the following equation (4).
S ″ (t) = (t, process (t), n ′ _p1 (t), n ′ _p2 (t),... N ′ _pm (t)) (4)

In the formula (4), t represents elapsed time. Similarly to the equation (1), the elapsed time t is set to the value of the elapsed time t every 30 seconds with reference to the time when the value of the elapsed time t is “0” (workflow start time (here, start time of the injection end process)). It is assumed that the value is incremented by “1”.
process (t) represents a work category to which the work being performed at the elapsed time t belongs.
n ′ _pm (t) represents the number of workers (actual number) working at the location pm at the elapsed time t.

FIG. 8 is a diagram conceptually illustrating an example of the content of the position measurement data S ″ (t) converted into data having the same format as the process data P (t). FIG. 8 shows position measurement data S ″ (t) obtained by converting the position measurement data S ′ (t) shown in FIG. 7 into data having the same format as the process data P (t) shown in FIG. Yes.
As shown in FIG. 5, in the present embodiment, the process data P (t) employs an elapsed time t in which a value is incremented by “1” every 30 seconds, not the actual time t. ing. Further, in the process data P (t), the number of workers (necessary number) that need to work in each work area (place; Palpit, TDC, MD, etc., crane) is set for each elapsed time t. Has been.

Therefore, the position measurement data conversion unit 106 determines the number of workers working in each work area (place; Palpit, TDC, MD, etc., crane) from the position measurement data S ′ (t). The position measurement data S ′ (t) is aggregated every time to be position measurement data S ″ (t) in the same format as the process data P (t).
In the position measurement data conversion unit 106, for example, the CPU reads the position measurement data S ′ (t) from the RAM or the like, creates the position measurement data S ″ (t) shown in the equation (4), and the RAM It is realized by memorizing in etc.

[Comparison calculation unit 107]
The comparison calculation unit 107 compares the process data P (t) and the position measurement data S ″ (t) for each work category. In the present embodiment, the comparison calculation unit 107 calculates “difference in total required time and similarity of the number of workers for each elapsed time and place” between the workflow and the actual work for each work category.
FIG. 9 is a diagram conceptually illustrating an example of all contents of the position measurement data S ″ (t) converted into data having the same format as the process data P (t). Here, the position measurement data S ″ (t) shown in FIG. 9 is the position measurement data S ″ (t) corresponding to the process data P (t) shown in FIG.

The comparison calculation unit 107 handles the process data P (t) and the position measurement data S ″ (t) as a matrix.
The process data P (t) is represented by the following equation (5), and the position measurement data S ″ (t) is represented by the following equation (6).
P (t) = {P _O1 , P _O2 ,..., P _OW } ^T (5)
S ″ (t) = {S _O1 , S _O2 ,..., S _OW } ^T (6)
In the example illustrated in FIG. 5, the process data P is a 56 × 5 matrix, and in the example illustrated in FIG. 9, the position measurement data S ″ is a 49 × 5 matrix.

In equation (5), P _OW is a “partial matrix indicating the part of the work section W” of the matrix representing the process data P, and in equation (6), S _OW is a matrix representing the position measurement data S ″. Is a “submatrix indicating the part of the work section W”. In the present embodiment, the work division is composed of three work divisions, ie, an injection end process, an adjustment process, and an empty pan process, so the value of W is “3”.
In the example shown in FIG. 5, the partial matrix P _O1 of the process data P (t) injection end process is a matrix of 10 rows and 5 columns, and the sub matrix P _O2 of the adjustment process is a matrix of 6 rows and 5 columns. The sub-matrix P _O3 of the empty pot processing step is a matrix of 40 rows and 5 columns.
In the example shown in FIG. 9, the submatrix S _O1 of the position measurement data S ″ (t) injection end process is a matrix of 20 rows and 5 columns, and the submatrix S _O2 of the adjustment process is 10 rows and 5 columns. The empty pan processing submatrix S _O3 is a matrix of 19 rows and 5 columns.

The comparison calculation unit 107 extracts partial matrices P _O1 , P _O2 , P _O3 , S _O1 , S _O2 , S _O3 of each work section W from the process data P (t) and the position measurement data S ″ (t). To do.
And the comparison calculation part 107 calculates the difference _TdW of the total required time of each operation _| work division W by the following (7) Formula.
T _dW = t _PW −t _SW (7)

Here, t _PW is the total required time of the work section W of the process data P, and is specified by the number of rows of the submatrix _POW of the work section W of the process data P. t _SW is the total time required for the work section W of the position measurement data S ″, and is specified by the number of rows of the submatrix S _OW of the work section W of the position measurement data S ″.
For example, in FIG. 5, the number of rows partial matrix P _O1 of the injection termination step of the process data P (t) is "10", the total required time t _P1 end of infusion step of the process data P are expressed in steps And “10”. As described above, since one man-hour is 30 seconds, the total required time t _P1 of the process of completing the injection of the process data P is 300 (= 10 × 30) seconds in real time.

In FIG. 9, since the number of rows in the submatrix S _{O1 in} the injection end process of the position measurement data S ″ (t) is “20”, the total required time t in the injection end process of the position measurement data S ″. _S1 is “20” in terms of man-hours. Therefore, the total required time t _S1 of the injection end process of the position measurement data S ″ (t) is 600 (= 20 × 30) seconds in real time.
As described above, the difference T _{d1 in} the total required time of the injection end process is “−10 (= 10−20)” in terms of man-hours. The comparison calculation unit 107 performs such calculation for the adjustment process and the empty pan processing process.

Next, the comparison calculation unit 107 calculates the similarity of the number of workers for each elapsed time and each place. In the following description, “similarity of the number of workers for each elapsed time and place” is referred to as “cross-correlation” as necessary.
In the present embodiment, the comparison calculation unit 107 calculates the cross-correlation for each work section W as follows. Here, a method for calculating the cross-correlation of the injection end process will be described as an example. FIG. 10 shows a part of the partial matrix P _O1 of the process data P (t) injection end process (FIG. 10A) and a part of the submatrix S _O1 of the position measurement data S ″ (t) injection end process. It is a figure which shows (FIG.10 (b)).

As shown in FIG. 10, the number of rows in the submatrix _PO1 of the process data P (t) in the injection end process is different from the number of rows in the submatrix _{SO1 in} the injection end process of the position measurement data S ''. Basically, the same work is performed in the same work section W. Therefore, the difference between the number of rows of the submatrix P _O1 at the injection end process of the process data P (t) and the number of rows of the submatrix S _O1 at the injection end process of the position measurement data S ″ (t) This may be caused by the fact that the time actually required becomes earlier or later. Further, in the same work section W, it is considered that the number of workers in each place (work area) does not change extremely with time.

Therefore, in the present embodiment, the comparison calculation unit 107 includes the number of rows of the submatrix P _O1 of the injection end process of the process data P (t) and the submatrix S of the injection end process of the position measurement data S ″ (t). Calculate the least common multiple of _{O1 with} the number of rows. Then, the comparison calculation unit 107 determines that the number of rows of the submatrix P _O1 of the process data P implantation end process and the number of rows of the submatrix S _O1 of the implantation end process of the position measurement data S ″ (t) are respectively Each submatrix P _O1 and S _O1 is stretched so that the number of rows of the calculated least common multiple is obtained. Specifically, comparing calculating unit 107 increments the number of the calculated least common multiple submatrices P _O1, divided by the number of lines S _O1, the value of each row of partial matrix P _O1, S _O1, partial matrix P _O1 , S _O1 are repeatedly arranged without changing the positional relationship of each row. In the following description, it is referred to as “normalization” as necessary to align the number of rows of each of the partial matrices P _O1 and S _O1 in this way. If the number of rows in each of the sub-matrices P _O1 and S _O1 is the same, normalization is not necessary.

FIG. 11 shows a partial matrix P _rO1 (FIG. 11 (a)) _obtained by normalizing the partial matrix P _O1 of the process data P (t) injection end process and the position measurement data S ″ (t) injection end process. submatrix S _O1 normalized submatrix S _Ro1 illustrates (FIG. 11 (b)) a.
In the example illustrated in FIG. 10, the number of rows in the submatrix P _O1 of the injection end process of the process data P (t) is “10”, and the submatrix S _O1 of the injection end process of the position measurement data S ″ (t). The number of rows is “20”. These least common multiples are “20”.

Therefore, the comparison calculation unit 107 changes the submatrix P _O1 of the process data P (t) injection end process from a 10 × 5 matrix to a 20 × 5 matrix. Specifically, first, the comparison calculation unit 107 divides the least common multiple (= 20) calculated as described above by the number of rows (= 10) of the submatrix P _O1 of the process data P injection end process. . This value is “2 (= 20 ÷ 10)”. Then, the comparison calculation unit 107 arranges the value of each row of the submatrix P _O1 of the process data P implantation end process “2” times without changing the positional relationship of each row.

For example, in the example shown in FIG. 11A, the value (1 2 0 0 0) of the first row of the partial matrix P _O1 shown in FIG. 10A is shown in the first and second rows of the partial matrix P _rO1 . _Are repeatedly arranged, and the value (1 2 0 0 0) of the second row of the partial matrix P _O1 shown in FIG. _10A is repeatedly arranged in the third and fourth rows of the partial matrix P _rO1 . In the same manner, the values of each row of the partial matrix P _O1 shown in FIG. 10A are repeatedly arranged without changing the positional relationship of each row of the partial matrix P _O1 . As a result, the partial matrix P _rO1 shown in FIG. In this way, the partial matrix P _O1 shown in FIG. 10A is normalized.

On the other hand, the number of rows of the submatrix S _{O1 in} the injection end process of the position measurement data S ″ (t) is “20”, which is the same as the least common multiple (= 20) calculated as described above. Therefore, the partial matrix S _rO1 shown in FIG. _11B is the same as the partial matrix S _O1 shown in FIG. That is, the comparison calculation unit 107 does not normalize the partial matrix S _O1 shown in FIG.
The comparison calculation unit 107 performs the normalization of the partial matrices P _OW and S _OW as described above for the adjustment process and the empty pan processing process. In the adjustment step, the number of rows of the submatrix P _O2 is “6”, and the number of rows of the submatrix S _O1 is “10”, so that the normalized submatrices P _rO2 and S _rO2 have 30 rows each. It becomes a 5-column matrix. In the empty pot processing step, the number of rows of the submatrix P _O3 is “40”, and the number of rows of the submatrix S _O1 is “19”. Therefore, the normalized submatrices P _rO3 and S _rO3 are respectively It becomes a matrix of 760 rows and 5 columns.

When normalization of the submatrices P _OW and S _OW is completed as described above, the comparison calculation unit 107 calculates the cross-correlation C _W for each work section _W by the following equation (8).

In equation (8), | P _rOW | is the positive square root of the square sum of each element of the submatrix P _rOW , and | S _rOW | is the positive square root of the square sum of each element of the submatrix S _rOW. is there.
In the equation (8), P _rOW · S _rOW is the sum of inner products for the same row of these two sub-matrices (P _rOW , S _rOW ).
The comparison calculation unit 107 performs the calculation of Expression (8) for each of all the work sections W (in the present embodiment, the injection end process, the adjustment process, and the empty pot processing process).

The comparison calculation unit 107 calculates the “total time difference T _dW and cross-correlation C _W ” of each work section W calculated as described above, and the position measurement data S ″ ( The team name team (t) included in the position measurement data S ′ (t) that is the source of t) is associated with each other and stored in the comparison calculation result storage unit 108 in order from the newest.
The comparison calculation unit 107 also compares the “total difference in required time” for each work category W of the same team name team (t) with the “total required time difference T _dW and cross-correlation C _W ” for each work category W stored this time. _Read “T _dW and cross-correlation C _W ”. Then, the comparison calculation unit 107 calculates and compares “the arithmetic average value of the difference T _{dW in} the total required time of each work section W and the arithmetic average value of the cross-correlation C _W of each work section W” in the same work team. The result is stored in the calculation result storage unit 108. Note that, for example, a moving average value may be calculated instead of the arithmetic average value.

FIG. 12 is a diagram illustrating an example of “total required time difference T _dW (time difference) and cross-correlation C _W ” for each work section W of the work team whose team name is “2”. In FIG. 12, data No. indicates the acquisition order (calculation order) of the information shown in FIG. 12, and the larger the data No. number, the more newly acquired (calculated) it is.
In the present embodiment, the comparison calculation unit 107 has a table as shown in FIG. 12 for each work team. The comparison calculation unit 107 changes (or adds) the value in each column of each table, thereby “time-series value and average value” of “the difference T _{dW in} total required time for each work section W”; and "time-series values and average value" of "cross-correlation C _W of each working segment W" for each work team, can be stored in the comparison calculation result storage unit 108.

  For example, the comparison calculation unit 107 reads out the process data P (t) from the HDD or the like, and also reads out the position measurement data S ″ (t) from the RAM or the like, and performs calculations of equations (5) to (8). These results are realized by storing the results in an HDD or the like. The comparison calculation result storage unit 108 is realized by using, for example, an HDD.

[Comparison calculation result display section 109]
The comparison calculation result display unit 109 displays a comparison result for each work category W between the actual work and the work flow of the work team that has been calculated by the comparison calculation unit 107. In the present embodiment, as a result of the comparison, “the difference in total required time T _dW and cross-correlation C _W ” for each work section W is displayed.
FIG. 13 is a diagram illustrating a specific display example of the result of comparison for each work category W between the actual work and the work flow of the work team.
In the example illustrated in FIG. 13, when the comparison calculation unit 107 calculates the “total time difference T _dW and cross-correlation C _W ” for each work section W by the comparison calculation unit 107, the comparison calculation result display unit 109 The following information (A) and (B) is displayed for the working team.
(A) Total time difference T _dW (time series value and average value) for each work category W
(B) Cross-correlation C _W (time series value and average value) for each work category W
These information (A) and (B) are displayed in the display area 1301 of FIG. 13 (refer to the “time difference” column of the display area 1301 for information on (A), and information on (B). , See “Cross-correlation” column in display area 1301).

Further, in the example illustrated in FIG. 13, the comparison calculation result display unit 109 displays the following information (C) and (D) for other work teams other than the work team that is the object of calculation.
(C) Difference in total required time for each work category W T _dW (average value)
(D) Cross-correlation C _W (average value) for each work category W
The information of (C) and (D) is displayed in the display area 1302 of FIG. 13 (refer to the “time difference” column of the display area 1302 for the information of (C), and for the information of (D). , See “Cross-correlation” column in display area 1302). For example, the latest value may be displayed in addition to or instead of the average value of (C) and (D).
From the information shown in FIG. 13, for example, the operator can grasp the following.

First, according to the result of the work of the team whose team name is “2”, the work time longer than the man-hour set in the workflow is required in the injection end process and the adjustment process, and in the empty pan processing process, it is set in the workflow. It can be seen that the working time is shorter than the number of man-hours (see the time difference column in the display area 1301).
Specifically, according to the average work of the team whose team name is “2”, in the injection end process, it takes about 7.5 man-hours (3.25 minutes) than the man-hours set in the workflow. In the adjustment process, about 3 man-hours (1.5 minutes) are required than the time set in the workflow, and in the empty pan processing process, about 18 man-hours (9 minutes) than the time set in the workflow. It can be seen that the working time can be shortened (see the average column in the display area 1301).
Further, according to the result of the work of the team whose team name is “2”, it can be seen that the number of workers for each elapsed time and place is significantly different from the workflow in the adjustment process (see the cross-correlation column in the display area 1301). ).
Specifically, according to the average work of the team whose team name is “2”, the cross-correlation is 0.70 in the injection end process, and the cross-correlation is 0.80 in the empty pan treatment process. In the adjustment step, it can be seen that the cross-correlation value is 0.49 (see the average column in the display area 1301).

In addition, according to the work of the team with the team name “2”, the team with the team name “2” requires more time for the pouring process and the adjustment process than the other teams. It can be seen that the work does not require time (see the average column in the display area 1301 and the display area 1302).
Also, according to the work of the team with the team name “2”, the team with the team name “2” has a larger cross-correlation value between the injection end process and the adjustment process than the other teams. It can be seen that the value of the cross-correlation is small (see the average column in the display area 1301 and the display area 1302).
The comparison calculation result display unit 109 is created by, for example, the CPU reading out the information shown in (A) to (D) from the HDD or the like, and creating display data for displaying the display screen shown in FIG. This is realized by displaying an image based on the display data on the display.

(Operation flowchart)
Next, an example of the operation of the work information guidance device 100 will be described with reference to the flowchart of FIG.
First, in step S1401, the workflow setting unit 101 sets (stores) workflow information. In the present embodiment, the workflow setting unit 101 sets workflow attribute information shown in FIG.
Next, in step S1402, the process data creation unit 102 creates process data P (t) from the workflow information set in step S1401 (see formula (1)).

Next, in step S1403, the tag ID acquisition unit 103 acquires the ID information of the RFID tag from the RFID readers 210a to 210d.
Next, in step S1404, the position measurement data creation unit 104 obtains the ID value of the RFID tag acquired in step S1403, the RFID reader 210 that is the transmission source of the ID, and the timing at which the ID is acquired. Based on the result, position measurement data S (t) is created (see equation (2)).

Next, in step S1405, the work category assignment unit 105 determines the work category process (t) to which the work performed at time t belongs based on the VA alarm information and the VA occurrence time information, and the work category The process (t) is assigned to the position measurement data S (t) to create the position measurement data S ′ (t) (see the expression (3)).
Next, in step S1406, the position measurement data conversion unit 106 converts the position measurement data S ′ (t) into data having the same format as the process data P (t), and creates the position measurement data S ″ (t). (Refer to equation (4)).

Next, in step S1407, the comparison calculation unit 107 calculates the partial matrices P _O1 , P _O2 , P _O3 , S _O1 , and the like of each work section W from the process data P (t) and the position measurement data S ″ (t). S _O2 and S _O3 are extracted (see FIGS. 5 and 9).
Next, in step S1408, the comparison calculation unit 107 selects one unselected work category W. In the present embodiment, it is assumed that the work division W is selected in the order of the pouring end process, the adjustment process, and the empty pan processing process.

Next, in step S1409, the comparison calculation unit 107 calculates the total required time difference T _dW of the work category W selected in step S1408 (see equation (7)).
Next, in step S1410, the comparison calculation unit 107 compares “the number of rows of the partial matrix P _OW of the process data P (t) and the position measurement data S ″ (t) in the work section W selected in step S1408. matrix S the least common multiple of the _OW number of lines "to calculate the partial matrix S _OW of the partial matrix P _OW and position measurement data S" process data P (t) in the operation block W selected in step S1408 '' (t) ”Is normalized (see FIGS. 10 and 11, the normalized partial matrices P _OW and S _OW are the partial matrices P _rOW and S _rOW ).

Next, in step S1411, comparing calculating unit 107 calculates a cross-correlation C _W of operation block W selected in step S1408 ((see 8)).
Next, in step S1412, the comparison calculation unit 107 determines whether all work categories W have been selected. If all the work sections W are not selected as a result of this determination, the process returns to step S1408, and the processes in steps S1408 to S1412 are repeated until the processes for all work sections W are completed.
When the processing for all the work sections W is completed, the process proceeds to step S1413. In step S1413, the comparison calculation unit 107 compares the “total time difference T _dW and cross-correlation C _W ” of each work section W and the position measurement data S ″ (t) used when calculating them. And the team name team (t) included in the position measurement data S ′ (t), which is the source of the data, are stored in the comparison calculation result storage unit 108 in order from the newest one.

Next, in step S1414, the comparison calculation unit 107 compares each work section W with the same team name team (t) as the “total time difference T _dW and cross-correlation C _W ” of each work section W stored in step S1413. The past “total time difference T _dW and cross-correlation C _W ” is read out, and “the arithmetic average value of the total time difference T _dW of each work section W and the cross-correlation of each work section W in the same work team” The arithmetic average value of C _W is calculated and stored in the comparison calculation result storage unit 108.
Next, in step S1415, the comparison calculation result display unit 109 displays the “total time required for each work section W” of the work team having the team name team (t) different from the team name team (t) specified in step S1413. Difference T _dW (average value) and cross-correlation C _W (average value) for each work category W
"Is read out.

Next, in step S1416, the comparison calculation result display unit 109 displays the “total time difference T _dW (time series value for each work category W) of the work team of the team name team (t) specified in step S1413. And an average value) and a cross-correlation C _W (time-series value and average value) for each work section W ”are displayed in the display area 1301, and“ difference in total required time for each work section W ”of other work teams is displayed. “T _dW (average value) and cross-correlation C _W (average value) for each work section W” are displayed in the display area 1302.
And the process by the flowchart of FIG. 14 is complete | finished.

(Summary)
As described above, in this embodiment, the process data P (t) is created from the workflow. When the RFID reader 210 provided in the work area receives information on the ID of the RFID tag worn by the worker 220, position measurement data S ″ (t) indicating the behavior of the worker is created. The position measurement data S ″ (t) and the process data P (t) are compared for each work section W, and the cross-correlation C _W that is the degree of similarity of the number of workers for each elapsed time and place and the total required time The difference _TdW is calculated for each work section W, and information indicating the calculated result is displayed. Therefore, each worker (skilled person) in the team provides information that serves as a guideline for grasping how to act in relation to other workers in the same team. Can be extracted as tacit knowledge information of the worker.

  In the present embodiment, when the RFID reader 210 provided in the work area receives the ID information of the RFID tag worn by the worker 220, the value of the ID and the RFID that is the transmission source of the ID The leader 210 and the timing at which the ID is acquired are identified, and based on the result, which worker of which team is in which location at which timing is determined, and the position measurement data S (t) is obtained. create. Then, the position measurement data S ′ (t) is created by assigning the work division process (t) specified based on the VA alarm information and the VA occurrence time information to the position measurement data S (t), and the position measurement data S '(T) is converted into data of the same format as the process data P (t) to generate position measurement data S ″ (t). Therefore, from the behavior of the worker 220, the process data P (t), the position measurement data S ″ (t), and the position measurement data S ″ (t), even if it is not directly known to which work category the work of the worker 220 belongs. Can be compared for each work section W.

In the present embodiment, the number of rows of the submatrix P _OW of each work section W of the process data P (t) and the number of rows of the submatrix S _OW of each work section W of the position measurement data S ″ (t). Calculate the least common multiple of Then, the calculated least common multiple submatrices P _OW, by the number of divided by the number of lines S _OW, partial matrix P _OW, the value of each row of S _OW, partial matrix P _OW, positional relationship between each row of S _OW The sub-matrices P _OW and S _OW are normalized by repeatedly arranging them without changing, and the normalized sub-matrices P _rOW and S _rOW are compared. Therefore, even when the number of data of “process data P (t) and position measurement data S ″ (t)” in the same work section W does not match, the process data P (t) and the position measurement data S ″ ( t) can be compared for each work section W.

(Modification)
In the present embodiment, in order to know which worker 220 of which team is in which location at which timing, the worker 220 wears an RFID tag, and the RFID reader 210 determines the ID of this RFID tag. Received. However, this is not always necessary.
For example, when a button operated by the worker 220 is installed in each work area and the button is operated when the worker 220 arrives at each work area, based on the installation position and operation timing of the operated button. It may be possible to grasp which worker 220 is in which place at which timing. In this case, for example, a plurality of different buttons are set for each team, and the work information guidance device 100 is set in advance to indicate which button is the button of which team. The apparatus 100 can identify the team to which the worker 220 who operates the button belongs. In addition, by previously setting in the work information guidance apparatus 100 information that correlates the number of button operations and the team, the work information guidance apparatus 100 allows the worker 220 who operates the buttons based on the number of button operations. You can also identify the team to which the belongs.
In addition, the field of view camera ID, the worker 220, and the team name are associated with each other in advance and set in the work information guidance apparatus 100, and the work area grasped from the field of view image obtained by the field of view camera, Based on the time when the field-of-view image was acquired and the ID of the field-of-view camera, it is also possible to know which worker 220 of which team is at which location.

In this embodiment, each of the matrices representing the process data P (t) and the position measurement data S ″ (t) is set to the number of workers in each elapsed time, and the work in each place. A matrix with the number of persons in each column as values. However, each of the matrices representing the process data P (t) and the position measurement data S ″ (t) has the number of workers at each location as the value of each row, and the number of workers at each elapsed time is represented by each It is good also as a matrix made into a column value.
Further, in the present embodiment, when each of the process data P (t) and the position measurement data S ″ (t) is represented by a matrix, the work at each elapsed time is performed in order from the number of workers whose elapsed time is relatively early. The number of participants is arranged from the first line. However, the number of workers at each elapsed time may be arranged from the top row in order from the number of workers with a relatively late elapsed time. Even when the matrix is represented as described above, it is a matter of course that the number of workers at the same place are arranged in the same row or the same column.

Furthermore, as long as the degree of similarity of the number of workers for each elapsed time and place is indicated for each work category W, it is not always necessary to calculate the cross-correlation C _{W according} to the equation (8). For example, an absolute value of a value obtained by subtracting “the number of workers of the position measurement data S ″ (t)” from “the number of workers of the process data P (t)” in the same work category, the same elapsed time, and the same work area, You may use the value added about the thing of the same work classification as the similarity of the number of work persons for every elapsed time and every place.

Further, if the “similarity of the number of workers for each elapsed time and place (cross-correlation C _W )” in the target team is displayed for each work category W, the information shown in FIG. There is no need to display. For example, other team information may not be displayed (that is, the display area 1302 need not be displayed). Further, the past information of the target team (the column after the data No. “2” in the display area 1301) and the average information (the average column in the display area 1302) may not be displayed. In addition, it is not necessary to display the difference T _dW (time difference) of the total required time for each work section W. However, it is preferable to display these pieces of information because information related to the tacit knowledge of the worker can be obtained from various aspects as described above.

In the present embodiment, the work information guidance device 100 identifies the work classification process (t) to which the work performed by the worker 220 belongs based on the VA alarm information and the VA occurrence time information. The position measurement data S ′ (t) is created by assigning the section process (t) to the position measurement data S (t). However, this is not always necessary. For example, a device (for example, a process computer) different from the work information guidance device 100 identifies the work classification process (t) to which the work performed by the worker 220 belongs and creates the position measurement data S ′ (t). The position measurement data S ′ (t) may be transmitted to the work information guidance device 100. Further, as described above, when using a visual field camera, the work division process (t) may be specified from the visual field image obtained by the visual field camera.
In addition, the contents of the workflow are not limited to those shown in FIGS. 3 and 4, and the work site is not limited to the continuous casting facility.

The embodiment of the present invention described above can be realized by a computer executing a program. Further, a means for supplying the program to the computer, for example, a computer-readable recording medium such as a CD-ROM recording such a program, or a transmission medium for transmitting such a program may be applied as an embodiment of the present invention. it can. A program product such as a computer-readable recording medium that records the program can also be applied as an embodiment of the present invention. The programs, computer-readable recording media, transmission media, and program products are included in the scope of the present invention.
In addition, the embodiments of the present invention described above are merely examples of implementation in carrying out the present invention, and the technical scope of the present invention should not be construed as being limited thereto. Is. That is, the present invention can be implemented in various forms without departing from the technical idea or the main features thereof.

(Correspondence with claims)
<Claims 1 and 10>
The process data setting means is realized by using, for example, the workflow setting unit 101 and the process data creation unit 102. The process data setting step is realized, for example, by executing the processes of steps S1401 and S1402 in FIG.
The position measurement data setting means is realized by using, for example, a tag ID acquisition unit 103, a position measurement data creation unit 104, a work category assignment unit 105, and a position measurement data conversion unit 106. The position measurement data setting step is realized, for example, by executing the processes of steps S1403 to S1406 in FIG. Here, the predetermined device in the place where the work is performed is realized by using, for example, the RFID reader 210, and the behavior information is realized by using, for example, information on the ID of the RFID tag.
The comparison calculation means is realized by using the comparison calculation unit 107, for example. The comparison calculation process is realized, for example, by executing the processes of steps S1407, S1410, and S1411 in FIG. Here, the degree of similarity for each work category is realized by using, for example, the cross-correlation C _W.
The comparison calculation result display means is realized by using, for example, the comparison calculation result display unit 109. The comparison calculation result display step is realized, for example, by executing the process of step S1416 in FIG. Here, the information indicating the degree of similarity for each work category is realized by, for example, the cross-correlation value in the column where the team name displayed in the display area 1301 in FIG. 13 is “2” and the data No. is “1”. The
<Claims 2 and 11>
The similarity storage unit is realized by using the comparison calculation result storage unit 108, for example. The similarity storing step is realized, for example, by executing the process of step S1413 in FIG. The information indicating the average for each work section is realized by, for example, the average value in the cross-correlation column of the display area 1301 in FIG.
<Claims 3 and 12>
The similarity storage unit is realized by using the comparison calculation result storage unit 108, for example. The similarity storing step is realized, for example, by executing the process of step S1413 in FIG. Here, the information indicating the similarity for each work category for a work team different from the work team for which the similarity for each work category is calculated is, for example, based on the cross-correlation value in the display area 1302 in FIG. Realized.
<Claims 4 and 13>
The difference in the total required time for each work section is realized by, for example, the difference in total required time T _dW, and the information indicating the difference in the total required time for each work section is, for example, the value of the time difference in the display area 1301 in FIG. It is realized by.
<Claims 5 and 14>
The required time storage means is realized by using, for example, the comparison calculation result storage unit 108. The required time storage process is realized, for example, by executing the process of step S1413 in FIG. Here, the information indicating the average of the differences in the total required time is realized by, for example, the average value in the time difference column of the display area 1301 in FIG.
<Claims 6 and 15>
The required time storage means is realized by using, for example, the comparison calculation result storage unit 108. The required time storage process is realized, for example, by executing the process of step S1413 in FIG. Here, the information indicating the difference in the total required time for each work category for a work team different from the work team for which the similarity for each work category is calculated is, for example, the time difference in the display area 1302 in FIG. Realized by value.
<Claims 7, 8, 16, 17>
For example, the process data P (t) shown in FIG. 5 is realized by using the process data as data indicating the number of workers in each place for each time and each work category.
The first data setting means is realized by using, for example, a tag ID acquisition unit 103, a position measurement data creation unit 104, and a work category assignment unit 105. The first data setting process is realized, for example, by executing the processes of steps S1404 and S1405 in FIG.
The second data setting unit is realized by using the position measurement data conversion unit 106, for example. The second data setting process is realized, for example, by executing the process of step S1406 in FIG.
Here, the work classification identification information is realized by, for example, VA alarm information, and the external device is realized by, for example, a process computer.
<Claim 9 and Claim 18>
The matrix representing the process data is realized by, for example, Expression (5), and the matrix representing the position measurement data is realized by, for example, Expression (6). The partial matrix of process data is realized by, for example, the partial matrix P _rO1 shown in FIG. 11, and the partial matrix of position measurement data is realized by, for example, the partial matrix S _rO1 shown in FIG.

DESCRIPTION OF SYMBOLS 100 Work information guidance apparatus 101 Workflow setting part 102 Process data creation part 103 Tag ID acquisition part 104 Position measurement data creation part 105 Work classification provision part 106 Position measurement data conversion part 107 Comparison calculation part 108 Comparison calculation result memory | storage part 109 Comparison calculation result Display unit 201 Crane 202 Tundish car (TDC)
203 Mold (MD)
204 Palpit 205 Square 210 RFID reader 220 Worker

Claims (19)

A workflow in which work performed by multiple workers as a single work team is described in time series, the work category to which the work belongs, the place where the work is performed, and the worker required to perform the work Process data setting means for setting process data indicating the contents of the workflow including the necessary number of persons and the time required for work as attributes,
When receiving behavior information indicating the behavior of the worker from a predetermined device at the place where the work is performed, based on the behavior information, the location, the worker, and the time the worker is at the location, Position measurement data setting means for setting position measurement data for specifying the work classification to which the work performed by the worker at the location belongs and the work team to which the worker belongs;
Based on the position measurement data set by the position measurement data setting means, the actual number of workers per hour and place when a plurality of workers of the same work team performed the work included in the workflow Comparison calculation means for calculating the degree of similarity between the extracted number of workers for each time / place and the required number of persons for each time / place in the process data for each work category,
And a comparison calculation result display means for displaying information indicating the degree of similarity for each of the work categories calculated by the comparison calculation means. Having a similarity storage means for storing information indicating the similarity for each work category calculated by the comparison calculation means;
The comparison calculation means further calculates an average of a plurality of work results of similarity for each work category,
2. The work information guidance device according to claim 1, wherein the comparison calculation result display means further displays information indicating the average of the similarities for each work category calculated by the comparison calculation means. . Information indicating the degree of similarity for each work category, calculated by the comparison calculation means, has similarity storage means for storing for each work team;
The comparison calculation result display means further displays information indicating the similarity for each work category for a work team different from the work team for which the similarity is calculated for each work category. The work information guidance device according to claim 1 or 2. The comparison calculation means is configured to calculate a total time required for work when workers of the same work team have performed work included in the workflow based on the position measurement data set by the position measurement data setting means. Calculated for each work category, the difference between the total required time of work for each work category determined for each category and the total required time of work for each work category in the process data,
The said comparison calculation result display means further displays the information which shows the difference in the total required time for every said work division calculated by the said comparison calculation means, The display of any one of Claims 1-3 characterized by the above-mentioned. Work information guidance device described in 1. A required time storage means for storing information indicating a difference in the total required time for each work section calculated by the comparison calculation means;
The comparison calculation means further calculates an average for a plurality of work results of differences in total required time for each work category,
5. The work according to claim 4, wherein the comparison calculation result display means further displays information indicating the average of the difference in total required time for each work category calculated by the comparison calculation means. Information guidance device. A time storage means for storing, for each work team, information indicating a difference in the total time required for each work section calculated by the comparison calculation means;
The comparison calculation result display means further includes information indicating a difference in total required time for each work category for a work team different from the work team for which the difference in total required time for each work category is calculated. 6. The work information guidance device according to claim 4, wherein the work information guidance device is displayed. The process data is data indicating the number of workers in each place for each hour and each work category,
When the position measurement data setting means receives behavior information indicating a worker's behavior from a predetermined device at a place where the work is performed, each position measurement data setting means for each time, each work category, and each work team based on the behavior information. First data setting means for setting data indicating a place where the worker is located;
The data set by the first data setting means is converted into data indicating the number of workers in each place for each time, each work section, and each work team, and the converted data is set as the position measurement data. The work information guidance device according to claim 1, further comprising: a second data setting unit. Work classification identification information acquisition means for acquiring work classification identification information generated at the start and end of work of each work classification from an external device,
When the first data setting means receives the behavior information indicating the behavior of the worker from a predetermined device at the place where the work is performed, the first data setting means, based on the behavior information, each worker for each time and each work team. Data indicating the place where the user is located, and based on the set data and the work category identification information acquired by the work category identification information acquisition means, each worker is present for each time, each work category, and each work team The work information guidance device according to claim 7, wherein data indicating a place is set. The comparison calculation means, the process data and the position measurement data, respectively, one of the number of workers at each time and the number of workers at each location, the value of each row, the other is the value of each column The number of workers in the same place is arranged in the same row or the same column, and the number of workers in a relatively early time or the number of workers in a relatively late time The number of workers in each time in order is represented by a matrix arranged from the first row or first column,
From the matrix representing the process data and the matrix representing the position measurement data, sub-matrices in the same work section are extracted, and the sum of the inner products for the same row of the extracted sub-matrices is extracted. The work information guidance device according to claim 1, wherein a value obtained by dividing a product of a positive square root of a sum of squares of each element is calculated as a similarity for each work section. . A workflow in which work performed by multiple workers as a single work team is described in time series, the work category to which the work belongs, the place where the work is performed, and the worker required to perform the work A process data setting step for setting process data indicating the content of the workflow including the necessary number of people and the time required for work as attributes,
When receiving behavior information indicating the behavior of the worker from a predetermined device at the place where the work is performed, based on the behavior information, the location, the worker, and the time the worker is at the location, A position measurement data setting step for setting position measurement data for specifying the work classification to which the work performed by the worker at the location belongs and the work team to which the worker belongs;
From the position measurement data set by the position measurement data setting step, the actual number of workers per hour and place when a plurality of workers of the same work team performed the work included in the workflow A comparison calculation step for calculating the degree of similarity between the extracted number of workers for each time / place and the required number of persons for each time / place in the process data for each work category,
And a comparison calculation result display step of displaying information indicating the degree of similarity for each of the operation categories calculated by the comparison calculation step. Having a similarity storage step of storing information indicating the similarity for each of the work categories calculated by the comparison calculation step;
The comparison calculation step further calculates an average for a plurality of work results of similarity for each work category,
11. The work information guidance method according to claim 10, wherein the comparison calculation result display step further displays information indicating the average of the similarities for each of the work categories calculated by the comparison calculation step. . A degree of similarity storage step of storing information indicating the degree of similarity for each work category calculated by the comparison calculation step for each work team;
The comparison calculation result display step further displays information indicating the similarity for each work category for a work team different from the work team for which the similarity is calculated for each work category. The work information guidance method according to claim 10 or 11. In the comparison calculation step, based on the position measurement data set in the position measurement data setting step, the total time required for the work when the workers of the same work team performed the work included in the workflow is the work Calculated for each work category, the difference between the total required time of work for each work category determined for each category and the total required time of work for each work category in the process data,
The said comparison calculation result display process further displays the information which shows the difference in the total required time for every said operation | work division calculated by the said comparison calculation process, The any one of Claims 10-12 characterized by the above-mentioned. The work information guidance method described in 1. A required time storage step for storing information indicating a difference in total required time for each of the work categories calculated by the comparison calculation step;
The comparison calculation step further calculates an average for a plurality of work results of differences in total required time for each work category,
14. The operation according to claim 13, wherein the comparison calculation result display step further displays information indicating the average of the difference in total required time for each of the operation categories calculated by the comparison calculation step. Information guidance method. A time storage step for storing, for each work team, information indicating a difference in total time required for each work category calculated by the comparison calculation step;
The comparison calculation result display step further includes information indicating a difference in total required time for each work category for a work team different from the work team subjected to calculation of a difference in total required time for each work category, The work information guidance method according to claim 13 or 14, wherein the work information guidance method is displayed. The process data is data indicating the number of workers in each place for each hour and each work category,
In the position measurement data setting step, when receiving behavior information indicating a worker's behavior from a predetermined device at a place where the work is performed, each time, each work division, and each work team based on the behavior information. A first data setting step for setting data indicating a place where the worker is located;
The data set in the first data setting step is converted into data indicating the number of workers in each place for each hour, each work category, and each work team, and the converted data is set as the position measurement data. The work information guidance method according to claim 10, further comprising a second data setting step. It has a work category identification information acquisition step for acquiring work category identification information generated at the start and end of each work category from an external device,
In the first data setting step, when the behavior information indicating the behavior of the worker is received from a predetermined device at the place where the work is performed, each worker for each time and each work team is based on the behavior information. Data indicating the place where the user is located, and based on the set data and the work category identification information acquired in the work category identification information acquisition process, there are workers for each time, each work category, and each work team. The work information guidance method according to claim 16, wherein data indicating a place is set. In the comparison calculation step, each of the process data and the position measurement data is set such that one of the number of workers at each time and the number of workers at each location is a value in each row, and the other is a value in each column. The number of workers in the same place is arranged in the same row or the same column, and the number of workers in a relatively early time or the number of workers in a relatively late time The number of workers in each time in order is represented by a matrix arranged from the first row or first column,
From the matrix representing the process data and the matrix representing the position measurement data, sub-matrices in the same work section are extracted, and the sum of the inner products for the same row of the extracted sub-matrices is extracted. The work information guidance method according to any one of claims 10 to 17, wherein a value obtained by dividing a square sum of squares of each element is calculated as a similarity for each work section.   A computer program for causing a computer to execute each step of the work information guidance method according to any one of claims 10 to 18.

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