Manufacturing data processing system having a plurality of manufacturing apparatuses

A manufacturing data processing system includes a plurality of manufacturing apparatuses, a plurality of data processing devices for processing manufacturing data associated with the plurality of manufacturing apparatuses, a plurality of communication channels for communicating the manufacturing data between the plurality of manufacturing apparatuses and the plurality of data processing devices, and a management device. The management device determines a combination of the data processing device that processes the manufacturing data associated with each of the plurality of manufacturing apparatuses and the communication channel that communicates the associated manufacturing data between each of the plurality of manufacturing apparatuses and the data processing device, based on the communication speed of the communication channel and the data processing capability of each of the plurality of data processing devices.

This application is a new U.S. patent application that claims benefit of JP 2015-256921 filed on Dec. 28, 2015, the content of 2015-256921 is incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a manufacturing data processing system having a plurality of manufacturing apparatuses, and more specifically relates to a manufacturing data processing system that processes manufacturing data associated with a plurality of manufacturing apparatuses.

2. Description of Related Art

Machining apparatuses such as machine tools and manufacturing apparatuses such as robots have been used alone. Contrarily, production systems in which a plurality of manufacturing apparatuses are connected through communication channels to a host computer that makes a production plan are proposed. The host computer directs the type, number, and the like of products that each manufacturing apparatus is to manufacture. The manufacturing apparatuses each produce the directed number of directed products, thus allowing the production of desired products in desired delivery times with the efficient use of production resources. Such production systems include not only machining apparatuses such as machine tools or robots, but also manufacturing machines, control devices, sensors, and the like, such as PLCs, carrier machines, measuring instruments, testing machines, pressing machines, press fitting machines, printing machines, die-casting machines, injection molding machines, food machines, packaging machines, welding machines, washing machines, coating machines, assembling machines, mounting machines, wood working machines, sealing machines, and cutting machines. The apparatuses and devices included in the production systems are referred to as FA devices. In the following description, machine tools, robots, and sensors are used as the FA devices, but the present invention is not limited thereto.

The above production systems are required to collect, process, and memorize a large amount of manufacturing data associated with a plurality of FA devices, and to feedback processing results to the corresponding FA devices. Thus, the production systems have a data processing device for processing the manufacturing data, a memory device for storing the manufacturing data, and communication channels for communicating the manufacturing data between each FA device and the data processing device. Since the manufacturing data is stored in form of a database, the memory device may be hereinafter referred to as a database.

In recent years, machine learning using various types of real-time data generated by machine tools, robots, and various sensors is considered. For example, the machine learning may be used to determine the movement of an axis of the machine tool or the robot, or to make a failure diagnosis using a current value. This allows for the reduction of a load on operators and programmers, and also allows for easily achieving high quality, high efficiency, and the like, which have been achieved only by skilled operators and programmers.

Machine learning requires a database for storing data and a learning unit for analyzing the data. It is conventionally conceived that hardware resources such as a CPU, a memory, and an external storage device that constitute the database and the learning unit are provided in each of FA devices such as machine tools, robots, and various sensors, to perform learning in each FA device. However, providing the hardware resources in each FA device causes an increase in hardware costs. Therefore, a learning server having the database and the learning unit is provided and connected to the FA devices through a network. When performing learning, learning data is transmitted from the FA devices to the learning server through the network. In the learning server, the learning data is accumulated in the large database, and the learning unit performs learning. Learning results are transmitted from the learning server to the FA devices through the network. Such a system having the learning server has a similar configuration to the above production system in which, for example, the learning unit corresponds to the data processing device.

Furthermore, in the above production system, manufacturing data associated with many FA devices is so-called big data. The production system has a similar configuration to a cloud system in which big data is accumulated in a large database and processed by a server connected through a network.

Japanese Unexamined Patent Publication (Kokai) No. 2014-068110 describes communication devices connected to transmission channels and a switching control method. The plurality of transmission channels are provided between the communication devices. In the event that one of the transmission channels has a failure, the output of data is redirected to another of the transmission channels having no failure, to maintain data communication.

SUMMARY OF THE INVENTION

FA devices such as machine tools, robots, and various sensors generate an enormous amount of real-time data and continue generating the data as long as the machine tools, robots, and various sensors continue operating. Since processing the real-time data of several hundreds, thousands, or tens of thousands of the machine tools, the robots, and the various sensors requires an ultrafast network, an extremely large database, and an ultrahigh performance processor, such a system is very expensive.

Furthermore, the FA devices such as the machine tools, the robots, and the various sensors are not necessarily operated every day. A part of the machine tools and the robots may be required to be stopped for maintenance. Also, since the amount of data generated by each individual machine tool, robot, or sensor may fluctuate, it is necessary for the network, the database, and the processor to be able to process a maximum amount of communication data, thus causing very poor cost efficiency.

An object of the present invention is to provide a manufacturing data processing system that collects and processes manufacturing data associated with FA devices such as machine tools, robots, and various sensors.

More specifically, an object of the present invention is to provide a manufacturing data processing system that performs machine learning using real-time data generated by FA devices such as machine tools, robots, and various sensors as manufacturing data.

A manufacturing data processing system according to the present invention includes a plurality of manufacturing apparatuses, a plurality of data processing devices for processing manufacturing data associated with the plurality of manufacturing apparatuses, a plurality of communication channels for communicating the manufacturing data between the plurality of manufacturing apparatuses and the plurality of data processing devices, and a management device. The management device determines a combination of the data processing device that processes the manufacturing data associated with each of the plurality of manufacturing apparatuses and the communication channel that communicates the associated manufacturing data between each of the plurality of manufacturing apparatuses and the data processing device, based on the communication speed of the communication channel and the data processing capability of each of the plurality of data processing devices.

At least a part of the plurality of data processing devices may have a learning unit.

The manufacturing data processing system may further include a network management device for switching a connection between the plurality of communication channels.

DETAILED DESCRIPTION OF THE INVENTION

Before describing embodiments, an FA device, FA devices having a learning unit, and a conventional cloud type manufacturing data processing system having a learning unit will be described.

FIG. 1shows an example of the configuration of an FA device.

An FA device10includes an object to be controlled (or object to be detected)11and a controller12. The controller12includes a control unit13and a communication unit15, which is connected to communication channels. The control unit13is realized by software or firmware on a computer. The communication unit15is realized by a communication device or communication software. The control unit13communicates with a host computer and controllers of other FA devices through the communication channels, while controlling the object to be controlled11.

As described above, the FA device is a machining apparatus such as a machine tool, or a manufacturing machine, a control device, a sensor, or the like such as a robot, a PLC, a carrier machine, a measuring instrument, a testing machine, a pressing machine, a press fitting machine, a printing machine, a die-casting machine, an injection molding machine, a food machine, a packaging machine, a welding machine, a washing machine, a coating machine, an assembling machine, a mounting machine, a wood working machine, a sealing machine, or a cutting machine. The object to be controlled (or object to be detected)11corresponds to a main body portion of the FA device.

FIG. 2Ashows the configuration of an FA device having a learning function in which a learning unit is provided in the control unit.FIG. 2Bshows the configuration of another FA device having a learning function to which a computer is added as a learning unit.

In the configuration ofFIG. 2A, the controller12has a memory14to form a learning database, and the control unit13has a learning unit16therein, in addition to the configuration ofFIG. 1. The learning unit16is realized by software of the computer that forms the control unit13. The configuration ofFIG. 2Ais adoptable when the computer that forms the control unit13has an adequate processing capability for learning. However, the processing capability of the computer that forms the control unit13is generally inadequate for realizing the learning unit16. Thus, the configuration ofFIG. 2Amay not be able to realize a learning unit having an adequate learning function.

Therefore, as shown inFIG. 2B, a computer is mounted in the controller12to realize a learning unit17. However, this requires significant hardware resources by which the memory capacity of the database14and the computer processing capability of the learning unit17are obtained to achieve an adequate learning function, thus causing an increase in hardware costs.

FIG. 3shows an example of the configuration of a conventional manufacturing data processing system having a learning server that is shared among a plurality of FA devices.

The manufacturing data processing system ofFIG. 3includes a plurality of FA devices (10A to10N), a learning server20having a database21and a learning unit22, and a communication network30provided among the plurality of FA devices (10A to10N) and the learning server20. The communication network30is, for example, a ring network such as a token ring network.

During learning, the plurality of FA devices (10A to10N) transmit data to the learning server20through the network30. In the learning server20, the learning data is accumulated in the large database21, and the learning unit22performs learning. Learning results are transmitted from the learning server20to the corresponding FA devices through the network30.

Note that, the configuration ofFIG. 3is also applicable in the case of providing a management server that collects, analyzes, and manages the manufacturing data of the plurality of FA devices, as well as the learning server. In such a case, the management server is substituted for the learning server20.

The FA devices such as machine tools, robots, and various sensors generate an enormous amount of real-time data and continue generating the data as long as the machine tools, the robots, and the various sensors continue operating. When the number of the machine tools, the robots, and the various sensors is several hundreds, thousands, or tens of thousands, processing an enormous amount of real-time generated data requires an ultrafast network, an extremely large database, and an ultrahigh performance processor, thus requiring a very expensive system. A lack of the channel capacity of the network, the capacity of the database, or the processing capability of the processor causes a failure of desired processing (learning) with desired timing.

Also, in the configuration ofFIG. 3, the amount of data generated by each individual machine tool, robot, or sensor may fluctuate. The network, the database, and the processor are required to be able to process a maximum amount of communication data, thus causing very poor cost efficiency. The following embodiments provide manufacturing data processing systems that process (learn) real-time data generated by FA devices such as machine tools, robots, and various sensors as manufacturing data at low costs.

FIG. 4shows the configuration of a manufacturing data processing system according to a first embodiment of the present invention.

The manufacturing data processing system according to the first embodiment includes an FA device group40, first communication channels71, a plurality of network management devices73A to73C, second communication channels72, and a server group100.

In the drawing, the FA device group40has a robot41A, a machine tool41B, a robot41C, a machine tool41D, and a sensor41E. The robot41A, the machine tool41B, the robot41C, the machine tool41D, and the sensor41E each have the configuration as shown inFIG. 1. The object to be controlled11corresponds to a main body portion. The control unit13controls the main body portion. For example, in the robot41A, the object to be controlled11is a main body portion of the robot, and the control unit13is a robot controller that controls the main body portion of the robot. The FA device group40may include any of the above-described manufacturing apparatuses, control devices, sensors, and the like, in addition to or instead of the machine tools, the robots, and the sensor.

The server group100includes learning servers50A,50B, and50C and a management server53. The learning servers50A,50B, and50C include a database51A,51B, and51C and a learning unit52A,52B, and52C, respectively. The databases51A to51C have a configuration corresponding to the memory (database)14, and the learning units52A to52C have a configuration corresponding to the learning unit (computer)17as shown inFIG. 2B. The management server53performs general management.

The learning servers50A,50B, and50C perform learning for the control units of the robot41A, the machine tool41B, the robot41C, the machine tool41D, and the sensor41E included in the FA device group40. However, the learning servers50A,50B, and50C may perform learning for the entire manufacturing data processing system such as assignments of tasks to the individual FA devices.

Although not illustrated, when the learning servers50A,50B, and50C perform learning for the FA devices, the robot41A, the machine tool41B, the robot41C, the machine tool41D, and the sensor41E included in the FA device group40may have a learning result execution unit such as a neural communication channel to execute a learning result.

In the first embodiment, the plurality of learning servers are provided anyway. Therefore, it is possible to reduce the storage capacity of a memory device forming the database51A,51B, or51C and the processing capability of a processor forming the learning unit52A,52B, or52C in each learning server relatively when compared with the system having a single learning server as shown inFIG. 3.

Each of the network management devices73A to73C is communicatably connected to the robot41A, the machine tool41B, the robot41C, the machine tool41D, and the sensor41E included in the FA device group40through the first communication channels71. Each of the network management devices73A to73C is communicatably connected to the learning servers50A,50B, and50C and the management server53included in the server group100through the second communication channels72, to control connections between the first communication channels71and the second communication channels72. Each of the plurality of network management devices is connected to every FA device and every learning server. However, each of the plurality of network management devices may not be connected to every FA device and every learning server. Also, each of the plurality of FA devices and the plurality of learning servers is connected to every network management device. However, each of the plurality of FA devices and the plurality of learning servers may not be connected to every network management device. Furthermore, the network management devices73A to73C may be integrated into one network management device.

The first communication channels71and the second communication channels72, which can be enabled or disabled in a free manner, form a relatively low-speed network.

FIG. 5Ashows the configuration of a communicator provided in the FA devices41A to41E, the learning servers50A to50C, or the management server53.FIG. 5Bshows the configuration of a communicator provided in each of the network management devices73A to73C.

As shown inFIG. 5A, the communicator provided in the FA devices41A to41E, the learning servers50A to50C, or the management server53has communication ports83A,83B, . . . , and83M, the number of which is equal to the number of the connected first communication channels71or second communication channels72, and a communication control unit81. The communication control unit81has a buffer memory82that temporarily stores communication data. The communication control unit81transmits transmission data from the control unit to one of the communication ports83A,83B, . . . , and83M, and transmits reception data from the communication port83A,83B, . . . , or83M to the control unit.

As shown inFIG. 5B, each of the network management devices73A to73C has communication ports86A,86B, . . . , and86L, the number of which is equal to the number of the connected first communication channels71, communication ports87A,87B, . . . , and87P, the number of which is equal to the number of the connected second communication channels72, and a communication channel switching unit85. The communication channel switching unit85switches the connection between the communication port86A,86B, . . . , or86L and the communication port87A,87B, . . . , or87P. The communication channel switching unit85may switch the connection between one of the communication ports86A,86B, . . . , and86L and another one of the communication ports86A,86B, . . . , and86L, and the connection between one of the communication ports87A,87B, . . . , and87P and another one of the communication ports87A,87B, . . . , and87P. This allows communication between the FA devices, between the learning servers, or between the learning server and the management server.

In the manufacturing data processing system according to the first embodiment, each of the FA devices41A to41E notifies the management server53of the generation speed (data size per second) of learning data, in response to a query from the management server53. Each of the learning servers50A to50C notifies the management server53of the generation speed (data size per second) of learning data, in response to a query from the management server53. Each of the network management devices73A to73C notifies the management server53of the generation speed (data size per second) of learning data, in response to a query from the management server53. Based on these notifications, the management server53notifies each FA device to which learning server the FA device should transmit the learning data. The management server53notifies the network management devices73A to73C regarding which communication channels to enable and which communication channels to disable, and which FA device is connected to which learning server through the enabled communication channels. The management server53notifies the learning server, when the learning data transmitted from the FA device exceeds the processing capability of the learning server, to which learning server the learning server should transfer the learning data. As described above, the management server53determines combinations of the FA device, the communication channels (network management device), and the single or plurality of learning servers. When the generation speed of the learning data of each FA device, the communication speed of each communication channel, or the processing speed of the learning data of each learning server varies dynamically, the management server53may be arbitrarily notified of the dynamic variation and dynamically change the combination of the FA device, the communication channels (network management device), and the single or plurality of learning servers.

FIG. 6shows an example of connections between the FA device group and the learning server group in the manufacturing data processing system according to the first embodiment.

In the example ofFIG. 6, an FA device44A is connected to a learning server54A having a database55A and a learning unit56A through a first communication channel71A, a network management device74A, and a second communication channel72A. An FA device44D is connected to a learning server54C having a database55C and a learning unit56C through a first communication channel71D, a network management device74C, and a second communication channel72D.

On the contrary, FA devices44B and44C are connected to a network management device74B through first communication channels71B and71C, respectively, and the network management device74B is connected to a learning server54B having a database55B and a learning unit56B through a second communication channel72B.

The example ofFIG. 6is suitable for processing learning data generated by the FA devices44A and44D in the learning servers54A and54C, respectively, and is realized when the learning server54B has a sufficient processing capability to process learning data generated by the FA devices44B and44C. It is also required, as a matter of course, that each communication channel is able to transmit necessary data. For example, the second communication channel72B has a high communication speed so as to be able to transmit the learning data generated in the FA devices44B and44C.

FIGS. 7A and 7Bshow other examples of connections between an FA device and a learning server or learning servers in the manufacturing data processing system according to the first embodiment.

InFIG. 7A, since an FA device46generates a large amount of learning data, the FA device46is connected to a learning server57A having a high processing capability so as to process the large amount of learning data. However, one first communication channel and one second communication channel have an inadequate communication speed. Thus, the FA device46is connected to the learning server57A through two first communication channels71E and71F, two network management devices76A and76B, and two second communication channels72E and72F.

InFIG. 7B, since an FA device48generates a large amount of learning data, the FA device48is connected to two learning servers60A and60B to process the large amount of learning data. A first communication channel71G has an adequate communication speed to transmit the learning data generated by the FA device48. A network management device78connects the first communication channel71G to second communication channels72G and72H, in order to transmit the learning data to the learning servers60A and60B.

As described above, in the manufacturing data processing system according to the first embodiment, the management server53determines the combinations of the FA device, the first and second communication channels, the network management device, and the learning server based on the generation speed of the learning data of the FA device, the communication speed of the communication channels, free space in the database of the learning server, and the data processing capability of the learning unit. Therefore, there can be various connection examples other than the examples shown inFIGS. 6 and 7.

In the first embodiment, the management server determines the combinations of the FA device, the communication channels, the network management device, and the learning server group based on the generation speed of the learning data of each FA device. However, the management server may determine the combinations of the FA device, the communication channels, the network management device, and the learning server group based on the size of learning data the FA device has and the size of unprocessed learning data the database of the learning server has.

The FA devices, the learning servers, and the network management devices may autonomously notify the management server53of data without a query from the management server53. Alternatively, the management server53may have information about data sizes in advance.

When the learning server performs machine learning not by a lamping analysis (butch processing) but by a stepwise analysis (real-time processing), it is possible to eliminate the need for providing the database in the learning server, and the learning unit may directly process learning data from the network through a buffer having a small capacity.

In this example, the first communication channels71and the second communication channels72form the relatively low-speed network that can be enabled or disabled in a free manner. However, a ring communication network such as a token ring network may be used instead. In this case, a plurality of ring communication networks is provided. The plurality of FA devices and the plurality of learning servers are each connected to the plurality of ring communication networks. A part of the ring communication networks are specific to communication between a certain one of the FA devices and a certain one of the learning servers. On the other hand, the remaining FA devices and learning servers are able to communicate through the remaining ring communication networks.

FIG. 8shows the configuration of a manufacturing data processing system according to a second embodiment of the present invention.

The difference between the manufacturing data processing system according to the second embodiment and the manufacturing data processing system according to the first embodiment is that a server group200has a management server66connected to learning servers63A to63C. The other configuration is the same as that of the first embodiment.

In the first embodiment, the management server is equal in level and position to the learning servers. On the contrary, in the second embodiment, the management server66is at a higher level than the learning servers63A to63C. The management server66communicates with each FA device included in the FA device group40through the learning server63A,63B, or63C, the second communication channel72, the network management device73A,73B, or73C, and the first communication channel71.

FIG. 9shows the configuration of a manufacturing data processing system according to a third embodiment of the present invention.

The difference between the manufacturing data processing system according to the third embodiment and the manufacturing data processing system according to the first embodiment is that a server group300has a management server67connected to the network management devices73A to73C through the second communication channels72, and learning servers68A to68C are connected to the second communication channels72and the like through the management server67. The other configuration is the same as that of the first embodiment.

In the third embodiment, the management server67is at a lower level than the learning servers68A to68C. The learning servers68A to68C communicate with each FA device included in the FA device group40through the management server67, the second communication channel72, the network management device73A,73B, or73C, and the first communication channel71.

In the above first to third embodiments, the server group has the learning servers. However, a manufacturing data analysis server may be provided instead of the learning server to analyze the manufacturing data of the FA devices included in the FA device group40.

The present invention provides a distributed processing type manufacturing data processing system at a low cost.