Classifications

• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B23/00—Testing or monitoring of control systems or parts thereof
  • G05B23/02—Electric testing or monitoring
  • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
  • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B19/00—Programme-control systems
  • G05B19/02—Programme-control systems electric
  • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
  • G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by quality surveillance of production
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/31—From computer integrated manufacturing till monitoring
  • G05B2219/31439—Alarms can be warning, alert or fault
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/32—Operator till task planning
  • G05B2219/32179—Quality control, monitor production tool with multiple sensors
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/32—Operator till task planning
  • G05B2219/32222—Fault, defect detection of origin of fault, defect of product
• • G—PHYSICS
  • G05—CONTROLLING; REGULATING
  • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
  • G05B2219/00—Program-control systems
  • G05B2219/30—Nc systems
  • G05B2219/45—Nc applications
  • G05B2219/45127—Portable, hand drill
• • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
  • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
  • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
  • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
  • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

• the present disclosure relates to a method, monitoring node and computer program associated with a tool communications network, of monitoring a manufacturing process.
• a manufacturing process may include combining more or less complex components where the components are fixed together in an assembly line.
• the components may be delivered momentary with the need for them in the manufacturing process. It is often high requirements on tolerances on the components in combination with demands on cost control.
• power tools and systems with power tools including portable power tools such as power wrenches operated by an operator
• the power tools in assembly lines may have a controller connected to them and the controller controls the work performed by the power tool so that the power tool works automatically. I.e. the controller controls that the power tool is operated correctly, e.g. performing a wrench operation with the correct torque etc.
• the controllers are connectable to a communications network.
• a supervisor or production technician of the manufacturing process may be challenged with the need to look for information at many different places.
• Information such as error codes, on controllers and displays, feedback from operators and similar, to get an overview of the manufacturing process. It may be troublesome to conclude if there are any problems at any given moment, or easy to misunderstand random error codes
• a method is provided performed by a monitoring node associated with a tool communications network, of monitoring a manufacturing process.
• the method comprises receiving a first manufacturing parameter value related to an individual workpiece associated with a first manufacturing step.
• the method comprises detecting when the first manufacturing parameter value is out of a first predetermined range.
• the method comprises receiving a second manufacturing parameter value related to the individual workpiece associated with a second manufacturing step.
• the method comprises detecting when the second manufacturing parameter value is out of a second predetermined range.
• the method comprises determining that the individual workpiece is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and that the second manufacturing parameter value is out of the second predetermined range.
• a monitoring node is provided.
• the monitoring node is associated with a tool communications network, of monitoring a manufacturing process and the monitoring node comprising a processor and a memory.
• the memory comprises instructions which when executed by the processor causes the monitoring node to receive a first manufacturing parameter value related to an individual workpiece associated with a first manufacturing step.
• the memory comprises instructions which when executed by the processor causes the monitoring node to detect when the first manufacturing parameter value is out of a first predetermined range.
• the memory comprises instructions which when executed by the processor causes the monitoring node to receive a second manufacturing parameter value related to the individual workpiece associated with a second manufacturing step.
• the memory comprises instructions which when executed by the processor causes the monitoring node to detect when the second manufacturing parameter value is out of a second predetermined range.
• the memory comprises instructions which when executed by the processor causes the monitoring node to determine that the individual workpiece is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and that the second manufacturing parameter value is out of the second predetermined range.
• a computer program comprising computer readable code means which when run in a monitoring node associated with a tool communications network, of monitoring a manufacturing process causes the monitoring node to receive a first manufacturing parameter value related to an individual workpiece associated with a first manufacturing step.
• the computer program causes the monitoring node to detect when the first manufacturing parameter value is out of a first predetermined range.
• the computer program causes the monitoring node to receive a second manufacturing parameter value related to the individual workpiece associated with a second manufacturing step.
• the computer program causes the monitoring node to detect when the second manufacturing parameter value is out of a second predetermined range.
• the computer program causes the monitoring node to determine that the individual workpiece is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and that the second manufacturing parameter value is out of the second predetermined range.
• the use of a power tool influences the first and/or second manufacturing parameters.
• the first manufacturing step is performed by a first manufacturing station and the second manufacturing step is performed by the first manufacturing station or a second manufacturing station.
• the first manufacturing parameter value or the second manufacturing parameter value comprises sensor data, wherein the sensor data comprises at least one of: relative time, absolute time, torque, rotation speed, number of rotations, final torque, location of operation, time, temperature, electrical power and acceleration.
• One possible embodiment comprises transmitting an alarm message based on the step of determining that the individual workpiece is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and the second manufacturing parameter value is out of the second predetermined range.
• the alarm signal comprises at least one of: an identity of the individual workpiece, an identity of the first manufacturing step, an identity of the second manufacturing step, identity of individual power tools, the first manufacturing parameter value and the second manufacturing parameter value.
• One possible embodiment may comprise clustering of alarm messages related to at least one of: the first manufacturing station, the second manufacturing station, an individual power tool, and an individual workpiece.
• One possible embodiment comprises storing a plurality of the first manufacturing parameter values and the second manufacturing parameter values in a database, determining a deviation in distribution patterns of the first manufacturing parameter values and/or the second manufacturing parameter values by analysis of the stored first manufacturing parameter values and/or the second manufacturing parameter values, wherein the deviation of the
• manufacturing parameter values is associated with at least one of: the first manufacturing station, the second manufacturing station, an individual power tool, and the individual workpiece.
• One possible embodiment may comprise that the stored first manufacturing parameter values or the stored second manufacturing parameter values are analyzed to determine that a manufacturing parameter value is within the predetermined range, but deviating from a normal distribution pattern of manufacturing parameter values.
• One possible embodiment may comprise building a virtual representation of the production process, wherein the virtual representation illustrates deviation in distribution patterns of the first manufacturing parameter values and the second manufacturing parameter values.
• FIG. 1 is a block diagram illustrating a tool communication network.
• Fig 2 is a flow chart illustrating a procedure in a monitoring node.
• Fig. 3 is a flow chart illustrating a procedure in the monitoring node, according to further possible embodiments.
• FIG. 4 is a block diagram illustrating further possible embodiments.
• FIG. 5 is a block diagram illustrating the tool communication network in more detail, according to further possible embodiments.
• Fig. 6 is illustrating embodiments of the solution in a cloud computing solution.
• FIG. 7 is illustrating embodiments of the monitoring node in more detail.
• a solution is provided for monitoring of a manufacturing process.
• One example of a manufacturing process is where individual workpieces are joined together through different methods.
• the manufacturing process can range from joining a couple of workpieces together in a few steps through complex manufacturing lines for manufacturing of vehicles or aircrafts.
• the solution according to exemplary embodiments of the present disclosure collects manufacturing parameter values, detects and determine manufacturing parameter values out of predetermined ranges. This enables determination and identification of individual work piece faults, systematic faults, or deviations, and avoidance of for example expensive unplanned stops in a manufacturing process or an assembly line, and later costly product faults. Now the solution will be described in more detail.
• Fig. 1 illustrates a block diagram of a tool communications network 50.
• the tool communication network 50 comprises a monitoring node 100, a first manufacturing station 120, and a second manufacturing station 130.
• the figure further illustrates a workpiece 1 10.
• a tool communications network such as the tool communications network 50 illustrated in Fig. 1 , may be a communications network for enabling of communication between power tools and various units and devices controlling, supervising or collecting result data from the power tools. Result data may comprise manufacturing parameter values.
• the tool communications network 50 may be based on LAN-technologies (Local Area Network) such as Ethernet (e.g. according to IEEE 802.3), TCP/UDP/IP (Transfer Control Protocol/User Datagram Protocol/Internet Protocol), wireless protocols such as Wireless LAN (e.g.
• the tool communications network 50 may be operational in a factory or a manufacturing plant, for examples for manufacturing of consumer or industrial goods, including house hold appliances, cars, toys, machines, etc.
• the tool communications network 50 may be covering or connecting a number of assembly lines in facilities within a closed area such a campus with a number of buildings.
• the tool communications network 50 may be covering or connecting a number of factories or manufacturing plants remotely located from each other. Buildings, facilities, factories, manufacturing plants, not limiting to similar entities, are not shown in the figure.
• a monitoring node such as the monitoring node 100 in Fig. 1 , may be a monitoring node for monitoring of a manufacturing process or an assembly line.
• a workpiece such as the workpiece 1 10 in Fig. 1
• a workpiece 1 10 may also be a pre-assembled component, such as a gearbox, an engine, a cabling package, electronic box, landing gear, a wing, or similar.
• Other non-limiting examples of workpiece 1 10 is: chassis, engine block, main bearing caps, conrod bearing caps, camshaft journal holder, oil pump, engine cylinder head.
• a manufacturing station such as the first manufacturing station 120 and the second manufacturing station 130, illustrated in Fig. 1 , may be an arrangement with a power tool, further described later in the document, material for production, arrangements for material handling, the power tool itself, different equipment for the power tool, interaction devices for power tool operation such as indicator lamps, displays, tool holders and so forth.
• Another term for manufacturing station may be work station.
• FIG. 2 illustrates a flowchart of a method performed by a monitoring node 100 associated with a tool communications network 50, of monitoring a
• the method comprises receiving S100 a first
• step S110 the method comprises detecting S110 when the first manufacturing parameter value is out of a first predetermined range.
• step S120 the method comprises receiving a second manufacturing parameter value related to the individual workpiece 1 10 associated with a second manufacturing step.
• step S130 the method comprises detecting when the second manufacturing parameter value is out of a second predetermined range.
• step S140 comprises determining that the individual workpiece 1 10 is faulty, based on the steps of detecting that the first manufacturing parameter value is out of a first
• the first manufacturing parameter value and the second manufacturing parameter value may be values such as number of rotations, final torque, angle, location of operation, time, tool temperature, workpiece 1 10 temperature, error codes, an indication of OK, or Not OK and similar manufacturing parameter value related to the manufacturing process.
• the first manufacturing step may be tightening of a screw of a nut, or a group of screws or nuts, application of glue, rivet, or similar operation in a manufacturing process or assembly line, for example performed at a first manufacturing station 120.
• the second manufacturing step may be a secondary operation performed at the first manufacturing station 1 10.
• manufacturing step may be tightening of a screw of a nut, or a group of screws or nuts, application of glue, rivet or similar operation in a manufacturing process or assembly line, for example performed at a second manufacturing station 130.
• Detection of when the first manufacturing parameter value is out of a first predetermined range may for example comprise that the final torque is outside a predetermined range, or that the torque is above a predetermined threshold during driving down phase of a nut, before the tightening phase. Another example may be that the number of expected rotations has been exceeded when the final torque is reached. Or that any other manufacturing parameter value is outside a
• Detection of when the second manufacturing parameter value is out of a second predetermined range may for example comprise tightening of an additional nut or screw of the workpiece 1 10 and that the second manufacturing parameter value is out of a second predetermined range, during or after the operation.
• the second manufacturing parameter value may relate to the same type of manufacturing parameter value such as final torque, but is related to another nut or screw.
• Detection of when the second manufacturing parameter value is out of a second predetermined range may for example comprise second manufacturing parameter value, such as torque during driving down phase of a nut, and that the second manufacturing parameter value is out of a second predetermined range, during or after the operation.
• the first manufacturing parameter value is determined to be out of range and the second manufacturing parameter value is determined to be out of range, it may be determined that the workpiece 1 10 is faulty. It may be difficult based on a single error signal, to determine the reason for the error. For example, handling of a workpiece 1 10 may cause a problem.
• the first manufacturing parameter value is out of a first predetermined range and followed by that the second manufacturing parameter value is out of a second
• Another example of the first manufacturing step is a scenario where a screw joint is needed to be screwed to a higher angle. In the first manufacturing step this might still be within the specification, however with a higher angle.
• another screw joint is added also with a higher angle.
• the higher angle may indicate that the faces of screw joint not is parallel to each other, which leads to that the screw joint is exposed for a higher tension than desired.
• the higher angle may also indicate that something is clamped in the screw joint.
• FIG. 10 Yet another example is where a pedal set is joined to a chassis in the first manufacturing step, where the screw joint results in a higher angle than desired.
• a steering column is added in the second manufacturing step.
• the screw joint holding the steering column is also holding the pedal set.
• the pedal set which sometimes is a frame of pressed metal sheet on an axis, might be skew and needs to be realigned by assistance of the screw joint. Another reason for fault might be if a cable has been clamped between the chassis and the pedal set.
• FIG. 3 illustrates embodiments of the method performed by the monitoring node 100.
• the figure illustrates a flowchart of optional embodiments of the method performed by the solution.
• the use of a power tool 125 may influence the first and/or second manufacturing parameters.
• the power tool 125 is further illustrated in Fig. 4.
• the first and/or second manufacturing parameters are further illustrated in Fig. 4.
• a manufacturing step may be performed by the first manufacturing station 120 and the second manufacturing step may be performed by the first manufacturing station 120 or a second manufacturing station 130.
• a second example may be that the first manufacturing step comprises tightening of a nut performed in the first manufacturing station 120 and that the second
• manufacturing step comprises parallel tightening of a group of bolts performed by a second manufacturing station 130.
• the first manufacturing parameter value or the second manufacturing parameter value comprises sensor data.
• the sensor data may comprise at least one of: relative time, absolute time, torque, rotation speed, number of rotations, final torque, location of operation, time, temperature, electrical power and acceleration.
• the power tool 125 may for example register or detect manufacturing parameter values such as relative time, absolute time, torque, rotation speed, number of rotations, final torque, location of operation, time, temperature, electrical power consumption and acceleration. This does not limit the power tool 125 from registering other manufacturing parameter values as well.
• the solution is further not limited to the option of determining other manufacturing parameter values based on the described manufacturing parameter values, such as median value, average value, standard deviations, normal distribution, or other manufacturing parameter values which may be derived from the manufacturing parameter values registered or detected by the power tool 125.
• the method comprises a further step S150 of transmitting an alarm message based on the step of determining S140 that the individual workpiece 1 10 is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and the second manufacturing parameter value is out of the second predetermined range.
• the alarm signal may comprise at least one of: an identity of the individual workpiece 1 10, an identity of the first
• the alarm message may also be used for highlighting preventive control of other workpieces 1 10, to examine if they also may contain the same fault. Inclusion of any of: individual workpiece 1 10 identity, identity of the first manufacturing step, identity of the second manufacturing step, identity of the individual power tool 125, the first manufacturing parameter value and the second manufacturing parameter value, may enable an operator to faster identify where a fault has occurred and further enable better post analysis of faults.
• the method comprises yet another step S160 of clustering of alarm messages related to at least one of: the first manufacturing station 120, the second manufacturing station 130, an individual power tool 125, and an individual workpiece 1 10.
• the method comprises yet another step S170 of storing a plurality of the first manufacturing parameter values and the second manufacturing parameter values in a database 150.
• the first manufacturing parameter values and/or the second manufacturing parameter values stored in the database 150 may be used to determine a deviation in distribution patterns of the first manufacturing parameter values and/or the second manufacturing parameter values by analysis of the stored first manufacturing parameter values and the second manufacturing parameter values.
• the deviation of the manufacturing parameter values may be associated with at least one of: the first manufacturing station 120, the second manufacturing station 130, an individual power tool 125, and the individual workpiece 1 10.
• the stored first manufacturing parameter values or the stored second manufacturing parameter values may be analyzed to determine that a manufacturing parameter value is within the predetermined range, but deviating from a normal distribution pattern of
• An advantage with the stored manufacturing parameter values is that is may be possible to later analyze the data or look at historical data. It is for example possible for a car manufacturer to provide information about a specific vehicle that has been involved in an accident. It may for example be advantageous for the car manufacturer to be able to provide data about the manufacturing when the car left the manufacturing process.
• the method comprises a further step S180 of building a virtual representation of the production process.
• the virtual representation may illustrate deviation in distribution patterns of the first manufacturing parameter values and the second manufacturing parameter values.
• Fig. 4 shows a block diagram of the tool communications network 50, with the monitoring node 100.
• the monitoring node 100 may be comprised in a tool server, such as the tool server 140 illustrated in the figure.
• the tool server 140 facilitate where control data is prepared, how operations should be performed and are calculated, step-by-step work procedures are registered, suitable interactions between a tool controller 122 and a power tool 125, such as the power tool 125:A and the power tool 125:B.
• a database, such as the database 150 can be a specific database 150 for a monitoring node 100 or a general database serving both the tool server 140 as well as the monitoring node 100 and potentially other nodes in a tool communications network 50.
• the previously described first manufacturing station 120 and second manufacturing station 130 is further shown in the figure, accompanied by tool controllers 122.
• the tool controllers 122 have the primary task to control power tools 125, such as power tools 125:A and 125:B and accessory equipment.
• the tool controllers 122 may also need to manage configuration data and collect sensor data and store the sensor data as results of performed work operations.
• the monitoring node 100 associated with the tool communications network 50, of monitoring the manufacturing process is illustrated in Fig. 4 in conjunction with Fig. 7.
• the monitoring node 100 comprises a processor 350 and a memory 360.
• the memory 360 comprises instructions which when executed by the processor 350 causes the monitoring node 100 to receive the first manufacturing parameter value related to the individual workpiece 1 10 associated with the first manufacturing step.
• the memory 360 comprises instructions which when executed by the processor 350 further causes the monitoring node 100 to detect when the first manufacturing parameter value is out of the first predetermined range.
• the memory 360 comprises instructions which when executed by the processor 350 further causes the monitoring node 100 to receive the second manufacturing parameter value related to the individual workpiece 1 10 associated with the second manufacturing step.
• the memory 360 comprises instructions which when executed by the processor 350 further causes the monitoring node 100 to detect when the second
• the memory 360 comprises instructions which when executed by the processor 350 further causes the monitoring node 100 to determine that the individual workpiece 1 10 is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and that the second manufacturing parameter value is out of the second predetermined range.
• the use of a power tool 125 influences the first and/or second manufacturing parameters.
• the first manufacturing step may be performed by the first manufacturing station 120 and the second manufacturing step may be performed by the first manufacturing station 120 or the second manufacturing station 130.
• Fig. 5 illustrates non-limiting exemplifying embodiments of the solution, with the tool communications network 50 with the monitoring node 100.
• the figure further shows the first manufacturing station 120 and the workpiece 1 10.
• the figure further illustrates a second manufacturing station 130:A, where for example some operation is performed on the workpiece 1 10.
• further operations may be performed by a second manufacturing station 130:B, and yet further operations performed by a second manufacturing station 130:C on the workpiece 1 10.
• the first manufacturing parameter value or the second manufacturing parameter value comprises sensor data.
• the sensor data may comprise at least one of: relative time, absolute time, torque, rotation speed, number of rotations, final torque, location of operation, time, temperature, electrical power and acceleration.
• the monitoring node 100 may transmit an alarm message based on the step of determining that the individual workpiece 1 10 is faulty, based on the steps of detecting that the first
• manufacturing parameter value is out of the first predetermined range and the second manufacturing parameter value is out of the second predetermined range.
• the alarm signal comprises at least one of: an identity of the individual workpiece 1 10, an identity of the first manufacturing step, an identity of the second manufacturing step, identity of individual power tools 125, the first manufacturing parameter value and the second manufacturing parameter value.
• the monitoring node 100 clusters alarm messages related to at least one of: the first manufacturing station 120, the second manufacturing station 130, an individual power tool 125, and an individual workpiece 1 10.
• the monitoring node 100 stores a plurality of the first manufacturing parameter values and the second manufacturing parameter values in the database 150.
• the monitoring node 100 may further determine a deviation in distribution patterns of the first manufacturing parameter values or the second manufacturing parameter values by analysis of the stored first manufacturing parameter values and the second manufacturing parameter values.
• the deviation of the manufacturing parameter values may be associated with at least one of: the first manufacturing station 120, the second manufacturing station 130, an individual power tool 125, and the individual workpiece 1 10.
• the stored first manufacturing parameter values or the stored second manufacturing parameter values may be analyzed to determine that a manufacturing parameter value is within the predetermined range, but deviating from a normal distribution pattern of
• the monitoring node 100 builds a virtual representation of the manufacturing process.
• the virtual representation may illustrate deviation in distribution patterns of the first
• FIG. 6 illustrates further non-limiting exemplifying embodiments of the solution, with a tool communications network 50 and some alternative
• the monitoring node 100 detects, in one exemplifying embodiment, when the first manufacturing parameter value is out of a first predetermined range, when an operation is performed at the first manufacturing station 120 of the workpiece 1 10.
• the monitoring node 100 further detects when the second manufacturing parameter value is out of a second predetermined range.
• the monitoring node 100 may be comprised in a tool server 140, where the tool server 140 is located in, a factory or an assembly line.
• the monitoring node 100 is comprised in a cloud 160.
• the monitoring node 100 may be virtualized and the communication may be going directly between the first manufacturing station 120, the second manufacturing station 130 and the monitoring node 100 comprised in the cloud 1 60.
• An advantage with localization of the monitoring node 100 in a cloud 1 60 is that processing and storage resources may be possible to scale depending on work load in the production or the assembly line. Further advantages are the possibilities to aggregate data from manufacturing processes such as multiple production sites or assembly lines, to perform further analysis based on the aggregated data. Another advantage is avoidance of the need of local installations of monitoring nodes 100 where manufacturing processes such as production sites or assembly lines are geographically distributed.
• An optional embodiment of the solution is a configuration of the
• monitoring node 100 comprised in the tool server 140.
• the monitoring node 100 comprised by the tool server 140 performs some tasks, and another monitoring node 100 located in the cloud 1 60 performs other tasks.
• the monitoring node 100 located in the cloud may for example manage long term storage of first
• Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable
• computing resources e.g., networks, servers, storage, applications, and services, that can be rapidly provisioned and released with minimal management effort or service provider interaction.
• Fig. 7 illustrates an embodiment of the solution with the monitoring node 100 associated with the tool communications network 50, of monitoring the manufacturing process.
• the monitoring node 100 comprising the processor 350 and the memory 360, with the memory 360 comprising instructions which when executed by the processor 350 causes the monitoring node 100 to receive the first manufacturing parameter value related to an individual workpiece 1 10 associated with the first manufacturing step.
• the memory 360 comprising instructions which when executed by the processor 350 causes the monitoring node 100 to detect when the first manufacturing parameter value is out of the first predetermined range.
• the memory 360 comprising instructions which when executed by the processor 350 causes the monitoring node 100 to receive the second
• the memory 360 comprising instructions which when executed by the processor 350 causes the monitoring node 100 to detect when the second manufacturing parameter value is out of the second
• the memory 360 comprising instructions which when executed by the processor 350 causes the monitoring node 100 to determine that the individual workpiece 1 10 is faulty, based on the steps of detecting that the first manufacturing parameter value is out of the first predetermined range and that the second manufacturing parameter value is out of the second predetermined range.
• the monitoring node 100 may further comprise a communication interface 370, which may be considered to comprise conventional means for communicating from and/or to the other devices in the network, such as the database 150 and the first manufacturing station 120 or other devices or nodes in the tool communication network 50.
• the conventional communication means may include at least one transmitter and at least one receiver.
• the monitoring node 100 may further comprise one or more repository 375 and further functionality 380 useful for the monitoring node 100 to serve its purpose as monitoring node of monitoring a manufacturing process, such as power supply, internal
• the instructions executable by said processor may be arranged as a computer program 365 stored in said memory 360.
• the processor 350 and the memory 360 may be arranged in an arrangement 355.
• the arrangement 355 may alternatively be a microprocessor and adequate software and storage therefore, a Programmable Logic Device, PLD, or other electronic component(s)/processing circuit(s) configured to perform the actions, or methods, mentioned above.
• the computer program 365 may comprise computer readable code means, which when run in the monitoring node 100 causes the monitoring node 100 to perform the steps described in any of the method steps described in relation to Fig. 2 or 3.
• the computer program may be carried by a computer readable storage medium connectable to the at least one processor.
• the computer readable storage medium may be the at least one memory 360.
• the at least one memory 360 may be realized as for example a RAM (Random-access memory), ROM (Read-Only Memory) or an EEPROM (Electrical Erasable
• the computer program may be carried by a separate computer-readable medium, such as a CD, DVD or flash memory, from which the program could be downloaded into the at least one memory 360.
• the instructions described in the embodiments disclosed above are implemented as a computer program 365 to be executed by the processor 350 at least one of the instructions may in alternative embodiments be implemented at least partly as hardware circuits.
• the computer program may be stored on a server or any other entity connected to the communications network to which the monitoring node 100 has access via its communications interface 370.
• the computer program may than be downloaded from the server into the at least one memory 360, carried by an electronic signal, optical signal, or radio signal.

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Citations (7)

• 2017
  • 2017-12-15 WO PCT/EP2017/082969 patent/WO2018114643A1/en unknown
  • 2017-12-15 EP EP17825180.7A patent/EP3559768A1/de not_active Withdrawn

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