JP2006343838A - Production status improvement system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To acquire a production status improvement system capable of automatically diagnosing productivity in a manufacturing line on the basis of conditions of production facilities and conditions of workpieces as products to be produced and automatically solving a problem, if any, in a FA factory. <P>SOLUTION: The production status improvement system comprises a function 103 for detecting degradation in productivity from production data 101 comprising operation data of the production facilities and progress data of workpieces, a function 105 for diagnosing productivity to solve the problem on the basis of information 104 resulting from detecting the degraded productivity, and a productivity improvement executing function 107 for generating a command execution statement 106 to a manufacture execution system. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a production status improvement system used in a factory that has been made into an FA (factory automation) that uses an automatic transfer machine or a robot.

  In an FA factory that manufactures products using automatic conveyors and robots, the production line includes workpieces that are products, processing equipment for processing the workpieces into finished products, power required for processing, gas, etc. It is composed of auxiliary materials, jigs and tools, and transport equipment and workers necessary to transport the workpiece from the processing equipment to the next processing equipment.

  The situation where the productivity of the production line deteriorates occurs because any of these elements constituting the production line cannot perform a desired function. For example, processing equipment failure, power stop due to power failure, repair of jigs / tools, lack of capability of transfer equipment, absence of workers, etc. are applicable. Since such a situation that deteriorates productivity occurs on a production line on a daily basis, high productivity cannot be maintained unless these conditions are constantly monitored and necessary measures are taken.

  Thus, various techniques for monitoring the deterioration of productivity and identifying the cause of problems have been proposed. For example, in Patent Document 1, regarding such a problem in production status, the operating status of the production facility is constantly monitored by dividing it into predetermined categories, and the transition of the operating status of the production facility, the ratio of the status of the operating status, etc. There is disclosed a technique of always displaying a graph in a predetermined unit. According to this, it is possible to grasp not only the status of operation and non-operation in the production facility but also the cause of non-operation.

Japanese Patent Laid-Open No. 11-224108

  By the way, the factor of the deterioration of productivity is not necessarily specified only by monitoring the operating state of the production facility. An example of the factor that deteriorates productivity will be described with reference to FIGS. 31 and 32. FIG. In addition, FIG. 31 is a figure explaining the case where productivity deteriorates because a workpiece | work does not exist. FIG. 32 is a diagram for explaining a case where productivity deteriorates because there is no conveying means.

  In FIG. 31, the production facility 3105 has finished the work of the work 3101, but there is no work to be worked next in the work place 3102. Therefore, the worker 3103 shows a case where the next work is moved from the work place 3102 to the transfer device 3104 and the next work cannot be started, and is in an empty state. This state is a state in which the productivity is deteriorated because there is no work to be performed next even though the production facility is in an operable state.

  In FIG. 32, the production facility 3105 finishes the work processing of the workpiece, and there is also a workpiece 3202 to be worked next in the workpiece storage area 3102, but the next workpiece 3202 is conveyed to be supplied to the production facility 3105. This shows a case where the worker 3103 or the transport device 3104 is not available because it does not exist. This state is a state in which the productivity is deteriorated because there is no means for transporting the workpiece even though the production facility is operable.

  From these two examples, productivity deterioration factors cannot be identified simply by monitoring the operational status of production facilities. To identify productivity degradation factors, information on the operational status of production facilities such as breakdowns and power outages In addition, it is understood that the determination must be made based on a plurality of pieces of information such as the presence / absence of the workpiece, information on the location of the workpiece, and information on the worker and the transfer device. However, in the past, it has been necessary to rely on specialists such as industrial engineering (IE) engineers to grasp advanced conditions such as collecting and analyzing information from a plurality of information sources.

  However, with the widespread use of FA systems, the number of factories that operate the entire production line without human intervention has increased in recent years. Thus, if production activities are performed without human intervention, There may be cases where the above-mentioned signs of productivity deterioration resulting from multiple factors are overlooked. In other words, an automated production line requires a technique for quickly detecting a deterioration in productivity without relying on human hands. This is the first issue.

  Next, even if we are able to grasp the advanced production status based on multiple information sources and detect signs of productivity deterioration that are often overlooked, the most effective prescription for improving productivity is There must be technology to choose from. This will be described with reference to FIG. FIG. 33 is a diagram for explaining the situation of deterioration of productivity and prescriptions.

  The deterioration of productivity cannot be identified by the operating state such as production equipment failure or setup stop, but can be classified gradually by analyzing a plurality of information sources. There are various countermeasures required for each cause. Therefore, FIG. 33 shows a “productivity deterioration situation”, a “production situation” at that time, and an “effective prescription” for the situation.

  In the “productivity deterioration status”, a product waiting status 3301 and a transport resource waiting status 3302 are shown. The “production status” in the thing waiting status 3301 is the status described with reference to FIG. 31, that is, the production facility is in an operable state, but there is no work to be performed next, so productivity is reduced. The situation is getting worse. The “effective prescription” for that is to search for workable work in progress in the upstream process, and to instruct the work to proceed with production promptly.

  In addition, the “production status” in the transfer resource waiting status 3302 is the same as the status described with reference to FIG. 32, that is, the productivity is low because there is no means for transferring the workpiece even though the production facility is operable. It is a situation that is exacerbating. The “effective prescription” in response to this is to instruct a worker or a transfer device, which is a transfer resource of the workpiece, to transfer the workable work to the production facility promptly.

  In other words, a factory that has been FA-enabled needs technology that can automatically diagnose the deterioration of productivity without relying on human hands, and automatically select the most effective prescription from a number of countermeasures. This is the second problem.

  Furthermore, even if an effective measure for improving productivity can be selected, there must be a technique for implementing the measure. For example, in the example shown in FIG. 31, the target for the countermeasure is the production facility and the work arrival procedure for the previous process, and in the example shown in FIG. 32, the target for the countermeasure is the transport device or the transport worker. It is. Such diversified targets must be effectively addressed with diversified measures.

  If the target of the countermeasure is an operator, it can usually be dealt with by means such as displaying instruction contents on a terminal on the line side. On the other hand, the start order of production equipment and workpieces in a factory that has been converted to FA is highly controlled by an FA control system called a manufacturing execution system (MES). If you don't coordinate with it, you can't cope well.

  However, various measures for improving productivity usually vary depending on the circumstances specific to each production line. Therefore, if these measures are taken into consideration from the design stage of the FA control system, it is necessary to equip them with functions. The entire system will be enlarged and the efficiency will be worsened. That is, a technique for implementing measures for improving productivity without enlarging the existing FA system is required. This is the third issue.

  However, although the conventional technology can grasp the cause of non-operation of production facilities, it has a function to identify signs of productivity deterioration and causes of deterioration by combining information from multiple information sources other than production facilities. It does not have, and the first problem cannot be solved. In addition, specific measures for improving productivity are predicated on human judgment and must be handled manually, and the second and third problems cannot be solved.

  The present invention has been made in view of the above, and in a factory that has been made into a factory automation, it automatically diagnoses the productivity of the production line based on the status of the production equipment and the status of the workpiece, which is a product, The purpose is to obtain a production status improvement system that can automatically solve the problem if there is.

  In order to achieve the above-described object, a production status improvement system according to the present invention includes at least an operation of the production facility in a factory in which a production line includes a production facility and a production execution system that performs automatic operation control of the production facility. Production data acquisition means for acquiring production data including data and progress data of a workpiece that is a product, and a factor that deteriorates productivity in the manufacturing line based on the production data is divided into the production equipment and the workpiece Search the storage means storing the productivity deterioration detection function detected in association with the productivity deterioration factor and the measures for improving the productivity based on the productivity deterioration factor detected by the productivity deterioration detection function. There is no confusion in the production line between the productivity diagnosis function for selecting an appropriate countermeasure and the productivity improvement measure selected by the productivity diagnosis function. In which characterized in that a productivity improvement measures execution function of instructing the manufacturing execution system.

  According to the present invention, it is possible to automatically diagnose the productivity of the production line based on the state of the production facility and the state of the workpiece that is the product, and if there is a problem portion, the problem can be automatically solved.

  According to the present invention, there is an effect that the production line can always be stably operated without intervention of manpower, and productivity can be maintained high.

  Exemplary embodiments of a production status improvement system according to the present invention will be described below in detail with reference to the drawings.

  FIG. 1 is a block diagram showing a functional configuration of a production status improvement system according to an embodiment of the present invention. As shown in FIG. 1, the production status improvement system according to this embodiment includes a process 102 for inputting production data 101 in which data relating to operation of production facilities and data relating to work progress are described, and the production data 101. A function 103 that detects productivity deterioration, a productivity diagnosis function 105 that performs productivity diagnosis for problem solving based on the result information 104 of productivity deterioration detection, and an execution command statement 106 for the manufacturing execution system based on the diagnosis result Has a productivity improvement execution function 107 for generating. These functions can be realized by the apparatus configuration shown in FIG. 2 or FIG. 3, for example.

  FIG. 2 is a system diagram showing an apparatus configuration (part 1) for realizing the functional configuration of the production status improvement system shown in FIG. The production line 203 having the automatic production equipment group 201 and the production execution system 202 for controlling the FA system shown in FIG. 2 includes production data storage device 204, arithmetic device 205, line controller 207, and output device 208. Is arranged. These apparatuses and the manufacturing execution system 202 are connected to a cable 206 of a local area network (LAN), for example.

  2, the line controller 207 can collect the production data 101 shown in FIG. 1 including data relating to the operation of the production equipment and information relating to the progress of the work that is the product. This corresponds to “input process 102”. The production data 101 is stored in the production data storage device 204 by the line controller 207 via the cable 206.

  The calculation device 205 is programmed in advance with a procedure for detecting productivity deterioration, and corresponds to the “productivity deterioration detection function 103” shown in FIG. In addition, the arithmetic unit 205 is programmed in advance with procedures for generating an execution command for a production status diagnosis and a manufacturing execution system, and the “productivity diagnosis function 105” and “productivity improvement execution function 107” shown in FIG. Equivalent to.

  The output device 208 takes in an execution command that is a calculation result sent from the arithmetic device 205 onto the cable 206, and transmits it to the manufacturing execution system 202 via the cable 206. As a result, an execution instruction 106 is issued to the manufacturing execution system 202.

  The apparatus configuration shown in FIG. 2 can realize stable operation of the production line at all times without the need for an operator worker. In FIG. 2, the manufacturing execution system 202, the production data storage device 204, the arithmetic device 205, the line controller 207, and the output device 208 are connected to the LAN cable 206. Internet is also acceptable.

  Next, FIG. 3 is a system diagram showing an apparatus configuration (part 2) for realizing the functional configuration of the production status improvement system shown in FIG. The production line 303 having the automatic production equipment group 201 shown in FIG. 3 and the production execution system 202 for controlling the FA system is replaced with the production data storage device 204, the arithmetic unit 205, and the line controller 207 shown in FIG. The output device 309 instead of the input device 307 and the output device 208 is arranged. These devices are connected to a LAN cable 206. An input device 312 is connected to the manufacturing execution system 202.

  In FIG. 3, the input device 307 allows the operator 308 to input the production data 101 shown in FIG. 1 including data relating to the operation of the production facility and information relating to the progress of the workpiece that is the product. This corresponds to “process 102 for inputting data”. The production data 101 is stored in the production data storage device 204 via the cable 206 by the operator 308 operating the input device 307.

  As described with reference to FIG. 2, the arithmetic unit 205 corresponds to the “productivity deterioration detection function 103”, “productivity diagnosis function 105”, and “productivity improvement execution function 107” shown in FIG.

  The output device 309 takes in an execution command which is a calculation result sent from the arithmetic device 205 onto the cable 206 and displays it on the operator 310. The operator 310 outputs the display contents from the output device 309, brings it to the input device 312 and becomes the operator 311. The operator 311 inputs the output result of the output device 309 from the input device 312 to the manufacturing execution system 202. As a result, an execution instruction 106 is issued to the manufacturing execution system 202.

  In this way, the process 102 for inputting the production data 101 shown in FIG. 1 and the execution instruction 106 to the manufacturing execution system can also be performed by the operator. Now, how the above three problems are solved in the production status improvement system configured as described above will be described in the order of the first problem, the second problem, and the third problem. .

(A) Configuration and operation of the function 103 for detecting productivity deterioration shown in FIG. 1: This makes the measure for solving the first problem clear. FIG. 4 is a block diagram illustrating a configuration example of the productivity deterioration detection function illustrated in FIG. For example, as shown in FIG. 4, the productivity deterioration detection function 103 shown in FIG. 1 starts with the production resource state information 403 from the production data 101 in which the data relating to the marriage of the production equipment and the data relating to the progress of the work are described. Production resource state information generating means 402 for generating In addition, it has a production status categorizing means 404 that searches the safety work amount knowledge base 409 from a plurality of production resource status information 403 to classify the production status of the production line. Then, the productivity deterioration type knowledge base 408 is searched based on the production state information 405 obtained by the production state classification unit 404 to determine whether or not the productivity is deteriorated, and the productivity deterioration determination result 407 is output. Productivity deterioration judging means 406 is provided.

  Next, with reference to FIGS. 5 to 24, the configuration and operation of these three means will be described in order. 5 to 15 are diagrams for explaining the production resource status information generating unit 402, FIGS. 16 to 20 are diagrams for explaining the production status categorizing unit 404, and FIGS. 21 to 24 are productivity diagrams. It is a figure explaining the deterioration judgment means 406. FIG.

  (1) First, the configuration and operation of the production resource state information generation unit 402 shown in FIG. 4 will be described with reference to FIGS. FIG. 5 is a diagram showing an example of the production data shown in FIG. The production data 101 is transmission / reception history data of an execution command communicated between the production facility and the production execution system, and information including date / time, production facility ID, and work ID is described as character string data. .

  In the example shown in FIG. 5, reference numerals 501 to 503 denote date and time information, reference numerals 504 to 506 denote production equipment IDs, reference numerals 507 to 509 denote execution instructions, and reference numerals 510 to 516 denote work IDs. In many cases, the storage format of the character string data differs depending on the production equipment and execution command (hereinafter referred to as “command”), and the writing position and writing of data in which date and time information, production equipment ID, and work ID are described, respectively. The data lengths are different. This is because such log data is only for keeping a communication history of the FA system and is not designed for the purpose of improving productivity.

  That is, the production data 101 does not clearly indicate the production resource state information 402 necessary for improving productivity. Therefore, first, information processing for extracting the production resource state information 403 necessary for improving the productivity from the production data 101 must be performed. This includes a case where the production resource state information 403 is extracted regarding the state of the production facility (FIGS. 6 to 12) and a case where the production resource state information 403 is extracted regarding the state of the work (FIGS. 13 to 15).

  (1a) A case where the production resource state information 403 regarding the state of the production facility is extracted will be described. FIG. 6 is a diagram for explaining a process of extracting production resource state information about the state of production equipment necessary for improving productivity from production data. FIG. 7 is a diagram for explaining the stored contents of the information extraction knowledge base shown in FIG. FIG. 8 is a diagram showing an example of the computerized data shown in FIG. FIG. 9 is a diagram illustrating an example of the equipment state transition knowledge base illustrated in FIG. 6. FIG. 10 is a diagram illustrating an example of production resource state information of the production facility illustrated in FIG. 11 and 12 are diagrams showing an example of the equipment state transition knowledge base used for explaining an operation example of the process for generating the production resource state information shown in FIG.

  In the information extraction knowledge base 607 shown in FIG. 6, as shown in FIG. 7, the “production equipment ID”, the “command” corresponding thereto, and the “work ID” indicating the type of the target work are indicated. The number of bytes is configured. In “work ID”, “work ID (1)” to “work ID (4)” are exemplified.

  In the information extraction process 602 shown in FIG. 6, referring to the information extraction knowledge base 607 showing the data start position and its meaning for each production equipment type and command shown in FIG. A part in which the ID, date, and command are described is extracted, and for example, information data 603 as shown in FIG. 8 is created.

  The computerized data 603 is input to a process 605 that receives a rearrangement process in the process 604 of rearrangement in ascending order by date of production facility ID and generates production resource state information. The equipment state transition knowledge base 608 shown in FIG. 6 includes, for example, a state transition of “command 1” and “command 2” and a state transition of “status from command 1 to command 2” as shown in FIG. And are recorded.

  In the process 605 for generating the production resource state information, the equipment state transition knowledge base 608 is obtained by a command combination of two consecutive records on the information data 603 subjected to the rearrangement process in the process 604 of rearrangement by date of production equipment ID. , The production resource state information 606 of the production facility is generated. For example, as shown in FIG. 10, the production resource status information 606 of the production facility includes a production facility ID, a work ID, a start date / time, an end date / time, a status time, a status, and the like.

  The generation operation of the process 605 for generating the production resource status information will be specifically described with reference to FIGS. In the equipment state transition knowledge base 608 shown in FIG. 11 and FIG. 12, the state transition in two states, “command of previous record” and “command of subsequent record”, and state transition of “status from previous record to subsequent record” It is recorded.

  Then, in the equipment state transition knowledge base 608 shown in FIG. 11, (1) start of processing device, (2) start of transfer device, and (3). As the history of the “command of the subsequent record”, (1) the end of the processing apparatus, (2) the end of the transfer device, (3)... Start, and “status from the previous record to the subsequent record” are recorded. As the history of (1), (1) during processing, (2) during conveyance, and (3) stagnation are recorded.

  On the other hand, in the equipment state transition knowledge base 608 shown in FIG. 12, the history of the “previous record command” includes (1) processing device end, (2) processing device end, (3) transport device end, (4 ) End of transport device, and (5) End of transport device are recorded. As the history of “command of subsequent record”, (1) start of processing device, (2) start of transfer device, (3) start of processing device, (4) start of transfer device (different from transfer device of previous record) (5) The start of the transport device (same as the transport device of the previous record) is recorded. Also, the history of “status from previous record to subsequent record” includes (1) stagnation due to waiting for person / next processing, (2) waiting for transport, (3) stagnation due to waiting for person / next processing, (4) waiting for transport, (5) Stagnation at the same location is recorded.

  In FIG. 11 and FIG. 12, in the two records before and after the data sorted in ascending order by date and time by work ID, the date and time when the command of the subsequent record was started from the date and time when the command of the previous record was started, that is, the previous The period until the command of the record is released is the time period in which the command of the previous record was maintained. For example, when the command of the previous record is “processing end” and the command of the subsequent record is “processing start”, the work state is set to “stagnation”.

  In addition, when the command of the previous record is “processing start”, the command of the subsequent record is “processing end”, and the production facility is a processing facility, the work state is set to “processing”. When the command of the previous record is “processing start”, the command of this record is “processing end”, and the production facility is a transfer device, the work state is set to “transporting”.

  In addition, regarding the factor classified as “Stagnant” in the production status status, “Stillness due to waiting for human / next processing” is used when the production facility is a processing device, and “ “Waiting for transport” is performed, and in particular, when the transport equipment is the same, the status is subdivided into “stagnation at the same place”.

  (1b) A case where the production resource status information regarding the workpiece status is extracted will be described. FIG. 13 is a diagram for explaining a process of extracting production resource state information about a work state necessary for improving productivity from production data. FIG. 14 is a diagram illustrating an example of the work state transition knowledge base illustrated in FIG. 13. FIG. 15 is a diagram showing an example of the production resource status information of the workpiece shown in FIG.

  13, when the information extraction process 602 creates the information data 603 as shown in FIG. 8 in which the production facility ID, the work ID, the date and time, and the command are described in the procedure described with reference to FIG. The converted data 603 is input to a process 1305 that receives the rearrangement process in the process 1304 for rearranging the work IDs in ascending order by date and time and generates production resource state information.

  In the process 1305 for generating the production resource state information, the work state transition knowledge base 1307 is generated by a command combination of two consecutive records on the information data 603 subjected to the rearrangement process in the process 1304 for rearranging in order of date and time by work ID. The production resource status information 1306 of the workpiece is generated by referring to the information. In the work state transition knowledge base 1307, for example, as shown in FIG. 14, in “Previous Record” and “After Record”, transitions are recorded by associating production equipment with corresponding commands. In the “work state from the previous record to the subsequent record”, a transition is recorded for each “command corresponding to the production facility” in the “previous record” and “following record”.

  The work resource status information 1306 can be generated as follows, for example. In FIG. 13 and FIG. 14, in the two consecutive records on the information data 603 sorted in ascending order of the date by work ID, the command of the subsequent record was started from the date and time when the command of the previous record was started. The date and time, that is, the period until the command of the previous record is released is the time zone in which the command of the previous record has continued. For example, when the command of the previous record is “processing completed” and the command of the subsequent record is “processing started”, the work state is set to “stagnation”.

  Further, when the command of the previous record is “processing start”, the command of the subsequent record is “processing end”, and the production facility is a processing facility, the work state is set to “processing”. When the command of the previous record is “processing start”, the command of this record is “processing end”, and the production facility is a transfer machine, the work state is set to “transporting”.

  In addition, regarding the factor classified as “Stagnant” in the production status, “Stillness due to waiting for next person / next process” when the production facility is a processing device, and “When the production facility at the next destination is a carrier” “Waiting for transport” is performed, and in particular, when the transport equipment is the same, the status is subdivided into “stagnation at the same place”.

  As a result, for example, as shown in FIG. 15, work production resource state information 1306 describing the work ID, production facility ID, start date and time, end date and time, status time, status, and the like is obtained.

  (2) Next, referring to FIGS. 16 to 24, production status categorizing means 404 for categorizing the production status of the production line from the plurality of production resource status information 403 extracted from the production data 101 as described above. The configuration and operation will be described.

  FIG. 16 is a diagram illustrating an example of generation of production status information necessary for typifying the production status of the production line. As described above, the operation state of the production facility can be grasped only by the production resource state information of the production facility, but the cause cannot be grasped when the production facility is not in operation. For example, there is no work that is not in operation because there is no work to be processed, or there is a work that is in processing, but it cannot be understood whether the worker has not been in operation because the work is not set in the production facility. However, as shown in FIG. 16, the production status information can be generated by arranging the production resource status information of the production facility and the production resource status information of the workpiece in the same time series. That is, by combining the information on the production equipment and the workpiece status, the production status can be analyzed from both the viewpoint from the production equipment and the perspective from the workpiece.

  FIG. 17 is a diagram for explaining a method of analyzing the production status from such a combination of a plurality of production resource statuses. FIG. 17 shows the relationship between the in-process amount waiting for the processing of the production facility xx and the production amount in the most recent week. In terms of specific numerical values, it shows that there are 200 in-process quantities currently waiting for processing in this production facility xx for 100 production units in the last week of production facility xx. ing. This situation indicates a production situation with a large amount of work in progress that holds work in progress for two weeks.

  The in-process amount in the production facility can be calculated by the procedure shown in FIG. FIG. 18 is a flowchart for explaining the procedure for calculating the amount of work in progress in the production facility. FIG. 19 is a diagram illustrating an example of data used when the in-process amount is calculated according to the procedure illustrated in FIG. The data 1901 for calculating the amount of work in progress shown in FIG. 19 includes the processing end date and time 1902 of the work processed by the production facility from the production resource status information 606 of the production facility, and the work previous information from the production resource status information of the workpiece. The date and time 1902 at which the process of the process is completed is extracted, and sorted in association with the command 1903 in the order of time.

  In FIG. 18, in step (hereinafter abbreviated as “ST”) 1801, data 1901 relating to the number of work in process as shown in FIG. 19 is created, and the work amount is initialized to 0 (ST 1802). First data (date and time 1902) of data 1901 for calculation is read (ST1803), next data (command 1903) is read (ST1804), and if the command 1903 is “start” (ST1805: Yes), the in-process amount is determined. 1 is added (ST1806), and if it is “end” (ST1805: No, ST1807: Yes), the in-process amount is decremented by 1 (ST1808).

  Similarly, the process of ST1804 to ST1808 is repeated while data 1901 relating to the number of devices in process remains (ST1809: No). As a result of the repetition, when there is no data 1901 related to the number of in-process (ST1809: Yes), in-process amount information as shown in FIG. 20 is obtained. This hourly in-process information can be calculated for each production facility.

  Next, with reference to FIG. 21 to FIG. 24, a creation procedure for classifying the production status will be described. To classify production celebrations, a typical model pattern of deterioration in productivity is registered in advance, and it is determined whether or not the combination status of a plurality of production resource status information matches this model pattern. If so, the process is to classify the model pattern.

  FIG. 21 is a diagram showing a model pattern of productivity deterioration used when categorizing the production status. As shown in FIG. 21, the model pattern of productivity deterioration is expressed by a character string. In FIG. 21, the model pattern of the production facility 001 is “0” for the first byte (first character), “1” for the second byte (second character), and “1” for the third byte (third character). It is shown that.

  FIG. 22 is a diagram illustrating an example of a model pattern creation rule. FIG. 22 shows a byte position (character position) and a rule for it. For example, the rule for the first byte (first character) compares the in-process amount with the safe in-process amount. If the in-process amount is larger than the safe in-process amount, the rule is “1”, and the in-process amount exceeds the safe in-process amount. If it is less, it is described as “0”.

  Here, the safe work-in-process amount refers to the maximum number of workpieces that can be stored in the production facility. The safe work-in-progress amount is referred to from the safe work-in-progress knowledge base 409 in which the safe work-in-progress amount is described. FIG. 23 is a diagram illustrating an example of the safety work amount knowledge base illustrated in FIG. 4. As shown in FIG. 23, the safety work amount knowledge base 409 includes a production facility 2301 and a safe work amount 2302.

  Returning to FIG. 22, the rule for the second byte (second character) is described as “1” if the operation rate is less than 70%, and “0” if it is 70% or more. The rule for the third byte (third character) is “0” if there is no work in progress, that is, if the number of works arriving in the work area is zero, and “1” if there is one or more. 1 "is described. Thereafter, the character string is given meaning by the position and value in the character string.

  FIG. 24 is a diagram illustrating an example in which the result of categorization of a production holiday is stored in one data table. As shown in FIG. 24, the result of the categorization of a production holiday is shown by a production facility and a model pattern composed of a character string representing the production holiday at the production facility.

  (3) Next, the productivity deterioration determining means 406 shown in FIG. 4 will be described with reference to FIG. FIG. 25 is a diagram showing an example of the productivity deterioration type knowledge base 408 shown in FIG. As shown in FIG. 25, the productivity deterioration type knowledge base 408 shown in FIG. 4 is a model pattern in which the productivity deterioration is a concern among the character strings representing the production state obtained as described above, and the production state deterioration with respect to the model pattern. The relationship with the factor is stored. For example, the production status deterioration factor for the model pattern “011...” Is “thing waiting status”, the production status deterioration factor for the model pattern “101...” Is “conveyance resource waiting status”, and the model pattern “111.・ It is recorded that the factor that deteriorates the production status for "" is a situation where there is a problem with the work management rules ".

  The productivity deterioration judging means 406 shown in FIG. 4 performs the pattern matching between the productivity deterioration type knowledge base 408 and the production situation type table shown in FIG. It is possible to detect whether or not it is in progress, and the productivity deterioration determination result 407 which is the detection information 104 of the productivity deterioration detection shown in FIG. 1 is obtained.

(B) Configuration and operation of the productivity diagnosis function 105 shown in FIG. 1: This makes the measure for solving the second problem clear. 26 is a block diagram illustrating a configuration example of the productivity diagnosis function illustrated in FIG. As shown in FIG. 26, the productivity diagnosis function 105 shown in FIG. 1 includes a process means 2601 for searching a productivity improvement measure knowledge base and a productivity improvement measure knowledge base 2603 in which the productivity improvement measures are recorded in advance. I have.

  FIG. 27 is a diagram illustrating an example of the productivity improvement countermeasure knowledge base. As shown in FIG. 27, the productivity improvement countermeasure knowledge base 2603 records a production condition deterioration factor 2701 and an execution command statement 2702 for taking countermeasures against it. For example, the execution command statement 2702 “conversion of work priority table in upstream process” is recorded for the production condition deterioration factor 2701 “thing waiting state”. An execution command statement 2702 “conversion of destination table of transfer device” is recorded for the production condition deterioration factor 2701 “waiting condition for transfer resource”. In addition, the execution command statement 2702 “display“ work management rule change necessary ”displayed on the terminal” is recorded for the production situation deterioration factor 2701 “the situation where there is a problem with the work operation rule”.

  The process means 2601 searches the productivity improvement countermeasure knowledge base 2603 based on the productivity deterioration judgment result 407, and extracts the productivity improvement countermeasure 2602 which is a prescription for the corresponding productivity improvement. In this way, the most effective prescription can be automatically selected from a large number of measures.

(C) Configuration and operation of the productivity improvement execution function 107 shown in FIG. 1: This makes the measure for solving the third problem clear. FIG. 28 is a diagram showing an example of an execution target knowledge table used by the productivity improvement execution function 107 shown in FIG. As shown in FIG. 28, in the execution target knowledge table, an upstream process, a transport device, and a destination that are execution targets are recorded for each production facility. When the productivity improvement execution function 107 shown in FIG. 1 obtains the productivity improvement measure 2602 which is a prescription for productivity improvement from the productivity diagnosis function 105, the productivity improvement execution function 107 refers to the execution target knowledge table shown in FIG. It is determined to which production facility the execution instruction 106 for taking measures to improve the sex deterioration should actually be issued.

  As shown in FIGS. 2 and 3, the production status improvement system of the present invention is completely independent from the manufacturing execution system 202, but the production status improvement system of the present invention has the configuration shown in FIG. By displaying the determined execution instruction on the output device 309 shown in FIG. 3, the operator 310 becomes the operator 311 of the input device 312, and the manufacturing execution system 202 can execute improvement measures.

  However, when the production status improvement system of the present invention has the configuration shown in FIG. 2, there are two execution instructions for executing the countermeasure of the present invention and an execution instruction from the original manufacturing execution system. There are cases where the production line gets confused. Therefore, in order to achieve compatibility, the productivity improvement execution function 107 shown in FIG. 1 includes means for executing improvement measures without causing confusion in the production line, when the improvement target is a production facility (FIG. 29), It is provided separately when the improvement target is a workpiece (FIG. 30).

  In FIG. 29, there is a relationship between the “conveyance device XX conveyance destination table 2901” managed by the manufacturing execution system 202 and the “conveyance device xx conveyance destination table 2902” changed by the production status improvement system of the present invention. It is shown. In the example shown in FIG. 29, there are destinations “A to E” in the transfer destination table 2901 of the transfer device xx, even if the destination “B” is selected in the transfer destination table 2901 of the transfer device xx. In the changed transfer device XX transfer destination table 2902, only the destination “A” is selected with restrictions.

  According to this, an execution command “Transport equipment xx goes to destination B” issued by the manufacturing execution system 202 is executed, and an execution command “Transport equipment xx is issued to the destination A” issued by the production status improvement system of the present invention. Can be converted to "go to".

  Also, in FIG. 30, the “process xxx work priority table 3001” managed by the manufacturing execution system 202 and the “process xxx work priority table 3002” changed by the production status improvement system of the present invention. The relationship is shown. In the example shown in FIG. 30, in the work priority order table 3001, the priorities “1 to 6” are assigned in this order from the work 01 to the work 06. On the other hand, in the changed work priority table 3002, in order to speed up the progress of the work 06, the work 06 has a priority “1”, the work 01 has a priority “2”, and the work 02 has a priority “3”. The work 03 is changed to the priority “5”, and the work 04 is changed to the priority “4”.

  According to this, the execution instruction “process XXX is the fifth processing order in the process XXX” issued by the manufacturing execution system 202 is executed as the execution instruction “process XXX” issued by the production status improvement system of the present invention. The processing order of the work 06 can be converted to “first”, and the progress of the work 06 can be accelerated.

  According to this embodiment, since the production status improvement system can be configured independently of the manufacturing execution system, enlargement of the manufacturing execution system can be avoided.

  As described above, the production status improving system according to the present invention is useful for stably operating a production line at all times and maintaining high productivity in an FA factory without human intervention.

It is a block diagram which shows the function structure of the production condition improvement system by one embodiment of this invention. It is a system diagram which shows the apparatus structure (the 1) which implement | achieves the function structure of the production condition improvement system shown in FIG. It is a system diagram which shows the apparatus structure (the 2) which implement | achieves the function structure of the production condition improvement system shown in FIG. It is a block diagram which shows the structural example of the productivity deterioration detection function shown in FIG. It is a figure which shows an example of the production data shown in FIG. It is a figure explaining the process which extracts the production resource state information about the state of the production equipment required for productivity improvement from the production data shown in FIG. It is a figure explaining the memory content of the information extraction knowledge base shown in FIG. It is a figure which shows an example of the information-ized data shown in FIG. It is a figure which shows an example of the equipment state transition knowledge base shown in FIG. It is a figure which shows an example of the production resource status information of the production facility shown in FIG. It is a figure which shows an example of the equipment state transition knowledge base used for demonstrating the operation example of the process which produces | generates the production resource state information shown in FIG. It is a figure which shows an example of the equipment state transition knowledge base used for demonstrating the operation example of the process which produces | generates the production resource state information shown in FIG. It is a figure explaining the process which extracts the production resource state information about the state of the workpiece | work required for productivity improvement from the production data shown in FIG. It is a figure which shows an example of the work state transition knowledge base shown in FIG. It is a figure which shows an example of the production resource status information of the workpiece | work shown in FIG. It is a figure which shows the production | generation example of production status information required in order to classify the production status of a production line. It is a figure explaining the method of analyzing a production condition from the combination of several production resource states. It is a flowchart explaining the calculation procedure of the in-process amount in the production facility shown in FIG. It is a figure which shows the example of data used when calculating the amount of work in process in the procedure shown in FIG. It is a figure which shows an example of the work amount information according to time calculated in the procedure shown in FIG. It is a figure which shows the model pattern of productivity deterioration used when classifying a production condition. It is a figure which shows an example of a model pattern creation rule. It is a figure which shows an example of the safety work amount knowledge base shown in FIG. It is a figure which shows the example which stored the result of categorization of a production letter celebration in one data table. It is a figure which shows an example of the productivity deterioration type knowledge base shown in FIG. It is a block diagram which shows the structural example of the productivity diagnostic function shown in FIG. It is a figure which shows an example of the productivity improvement countermeasure knowledge base shown in FIG. It is a figure which shows an example of the execution object knowledge table which the productivity improvement execution function shown in FIG. 1 uses. It is a figure explaining an example of the means (when improvement object is a production facility) which performs the improvement measure with which the productivity improvement execution function shown in FIG. 1 is provided. It is a figure explaining an example of the means (when improvement object is a workpiece | work) which performs the improvement measure with which the productivity improvement execution function shown in FIG. 1 is provided. It is a figure explaining the case where productivity deteriorates because a workpiece | work does not exist. It is a figure explaining the case where productivity deteriorates because there is no conveyance means. It is a figure for demonstrating the situation of productivity deterioration, and a prescription.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Production data 102 Process which inputs data 103 Function which detects productivity deterioration 104 Detection result information 105 Productivity diagnosis function 106 Execution command sentence 107 Productivity improvement execution function 201 Automatic production equipment group 202 Manufacturing execution system 203,303 Manufacturing line 204 Production Data Storage Device 205 Computing Device 206 Local Area Network (LAN) Cable 207 Line Controller 208, 309 Output Device 307 Input Device 308, 310, 311 Operator 312 Input Device of Manufacturing Execution System 402 Production Resource Status Information Generation means 403 Production resource status information 404 Production status classification means 405 Product status information 406 Productivity deterioration judgment means 407 Productivity deterioration judgment result 408 Productivity deterioration type knowledge base 409 Safety work amount knowledge base 602 Information extraction process 603 Informationized data 604 Data sorting process 605 Process for generating production resource state information 606 Production resource state information 607 Information extraction knowledge base 608 Equipment state transition knowledge base 1304 Process for sorting informationized data 1305 Production resource State information generation process 1306 Production resource state information 1307 Work state transition knowledge base

Claims (4)

In a factory that consists of a production line with production equipment and a production execution system that performs automatic operation control of this production equipment,
Production data acquisition means for acquiring production data including at least the operation data of the production equipment and the progress data of the workpiece which is a product;
A productivity deterioration detection function for detecting productivity deterioration factors in the production line based on the production data separately for the production equipment and the workpiece;
Productivity that searches for storage means that associates and stores productivity deterioration factors and measures for improving productivity based on the productivity deterioration factors detected by the productivity deterioration detection function and selects appropriate measures Diagnostic functions,
A productivity improvement measure execution function for instructing the manufacturing execution system to execute the productivity improvement measure selected by the productivity diagnosis function in a form that does not cause confusion in the manufacturing line;
Production status improvement system characterized by comprising The productivity deterioration detection function is
Means for creating production resource status information for each of the production facility and the workpiece from the production data;
Means for classifying the production status of the production line from the obtained plurality of production resource status information into a model pattern;
And a means for performing pattern matching between a pre-registered model pattern of a production situation in which productivity deterioration is a concern and a production situation converted into the model pattern to determine whether or not productivity has deteriorated. The production status improvement system according to claim 1.   When the execution instruction issued by the manufacturing execution system and the execution instruction for the productivity improvement countermeasure compete with each other, the productivity improvement countermeasure execution function executes the execution instruction issued by the manufacturing execution system for the productivity improvement countermeasure. 2. The production status improvement system according to claim 1, further comprising means for converting into an execution command.   The productivity improvement measure execution function includes an output unit that displays and outputs an execution command of the productivity improvement measure, and the manufacturing execution system includes an input unit that can input an execution command. The production status improvement system according to 1.

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