JP2019153605A - Device, method, program for predicting variations in falling, and robot system - Google Patents

Abstract

To predict variations in falling of a workpiece including a packaging material and a content packed with the packaging material when adsorbing and conveying the workpiece.SOLUTION: A receiving unit 22 receives information indicating the type of a material of a packaging material O for a workpiece W that includes the packaging material O and a content C packed with the packaging material O, the workpiece W adsorbed and held by an adsorption pad P attached to a robot arm R and conveyed. An adsorption pressure variation derivation unit 24 refers to correlation information indicating the correlation between the type of the material of the packaging material O and variations in adsorption pressure between the packaging material O and adsorption pad P when the packaging material O is adsorbed by the adsorption pad P under a predetermined condition for every type of the material of the packaging material O, and derives variations in adsorption pressure corresponding to the information indicating the type of the material of the packaging material received by the receiving unit 22. A falling variation prediction unit 26 predicts variations in falling of the workpiece W when the robot arm R conveys the workpiece W on the basis of the derived variations in adsorption pressure.SELECTED DRAWING: Figure 4

Description

  The present invention relates to a fall variation prediction device, a fall variation prediction method, a fall variation prediction program, and a robot system.

  A pick-and-place device is one of devices for conveying workpieces such as parts and products in a factory production line. The pick-and-place device includes, for example, a holding body that holds a workpiece by sucking it, such as a suction pad, sucks and holds the workpiece at a predetermined location, conveys the workpiece in the held state, and Release the suction and place the workpiece.

  As an example of a pick-and-place apparatus that sucks and transports a transport object, for example, a substrate transport apparatus that transports a substrate such as a wafer by vacuum suction in a semiconductor manufacturing process has been proposed (for example, see Patent Document 1). ). In the substrate transfer device described in Patent Document 1, in consideration of the adhesion of foreign matters such as dust to the vacuum suction surface, the vacuum pressure of the substrate suction portion is detected, and the detected pressure data is processed, Next, a change in the vacuum pressure of the suction portion of the substrate to be processed is predicted.

JP 2007-281073 A

  For example, when a workpiece including a packaging material and contents packed in the packaging material is to be transported, wrinkles and the like are generated on the packaging material on the suction surface. If it does not, it will cause variations in the occurrence of falling. When drops vary, it is necessary to set operation command values such as adsorption pressure and robot arm acceleration in anticipation of the variations, so it is important for the user to know the variations in drops.

  However, in the technique described in Patent Document 1, the object to be transported is a substrate, and variations in dropping due to wrinkling of the object to be transported are not taken into consideration. In addition, in the case where the object to be transported is a work including a packaging material and contents packaged with the packaging material, wrinkles are randomly generated in the packaging material. Therefore, the actual detection is performed as in the technique described in Patent Document 1. It is difficult to predict the subsequent change in the adsorption pressure of the adsorption unit based on the adsorption pressure of the adsorption unit.

  The present invention has been made in view of the above points, and a drop variation that can predict a drop variation of a workpiece when sucking and conveying a workpiece including a packaging material and contents packaged with the packaging material. It is an object of the present invention to provide a prediction apparatus, a method, a program, and a robot system that operates according to the predicted variation in the falling of the workpiece.

  In order to achieve the above object, a fall variation predicting apparatus according to the present invention is a work including a packaging material and contents packaged with the packaging material, and is held by suction by a suction member attached to a robot arm. A receiving unit that receives information indicating the type of material of the packaging material of the work to be conveyed, the type of material of the packaging material, and the packaging material for each type of packaging material by the suction member under predetermined conditions Corresponding to information indicating the type of material of the packaging material received by the receiving unit with reference to correlation information indicating a correlation between variations in the adsorption pressure between the packaging material and the adsorption member when adsorbed A derivation unit for deriving a variation in the suction pressure to be performed, and a prediction of a variation in the drop of the workpiece when the robot arm transports the workpiece based on the variation in the adsorption pressure derived by the deriving unit. It is configured to include a part.

  According to the drop variation predicting device according to the present invention, the reception unit is a work including the packaging material and the contents packaged by the packaging material, and is conveyed while being sucked and held by the suction member attached to the robot arm. Information indicating the type of material of the work packaging material is received. Then, the derivation unit varies the adsorption pressure between the packaging material and the adsorption member when the packaging material is adsorbed by the adsorption member under a predetermined condition for each type of packaging material and the packaging material type. With reference to the correlation information indicating the correlation between the suction pressure and the pressure, the variation in the adsorption pressure corresponding to the information indicating the type of the packaging material received by the receiving unit is derived. Further, the predicting unit predicts the variation in the drop of the workpiece when the robot arm transports the workpiece based on the variation in the suction pressure derived by the deriving unit.

  In this way, referring to the correlation information indicating the correlation between the type of packaging material and the variation in adsorption pressure, deriving the variation in adsorption pressure corresponding to the information indicating the type of packaging material received. This makes it possible to derive variations in suction pressure that correlate with variations in workpiece drop, so that variations in workpiece drop when sucking and transporting workpieces including packaging materials and contents packed in packaging materials can be reduced. Can be predicted.

  Further, the receiving unit further receives at least one information of thickness information for each type of the packaging material, information on the contents, and information on the suction member as correction information, and the derivation unit includes the Based on the wrinkle generation state of the packaging material corresponding to the correction information received by the receiving unit, it is possible to correct the variation in the adsorption pressure obtained from the correlation information. Thereby, since the fluctuation | variation of adsorption pressure is derived | led-out reflecting the generation | occurrence | production condition of the wrinkle of a packaging material in detail, the dispersion | variation in the fall of a workpiece | work can be estimated more accurately.

  In addition, when the correction information received by the reception unit includes information on the thickness of the packaging material, the derivation unit is configured to reduce the variation in the adsorption pressure as the thickness of the packaging material increases. Can be corrected. This is because the wrinkle of the packaging material is less likely to occur as the thickness of the packaging material increases.

  When the correction information received by the receiving unit includes information indicating the mass of the content as the content information, the derivation unit increases the adsorption pressure as the mass of the content increases. It can correct | amend so that the dispersion | variation in may become small. This is because as the mass of the contents is larger, the tension of the packaging material becomes stronger and the wrinkle of the packaging material is less likely to occur.

  In addition, when the correction information received by the receiving unit includes information indicating the filling rate of the content with respect to the packaging material as the content information, the derivation unit has a higher filling rate, It can correct | amend so that the dispersion | variation in the said adsorption pressure may become small. This is due to the fact that the higher the filling rate, the stronger the tension of the packaging material and the less the occurrence of wrinkling of the packaging material.

  When the correction information received by the receiving unit includes information indicating the number of the suction members used for sucking and holding one workpiece as the suction member information, the derivation unit includes It can correct | amend so that the dispersion | variation in the said adsorption pressure becomes small, so that there are many numbers. This is because the greater the number of adsorbing members, the stronger the tension of the packaging material and the less the occurrence of wrinkling of the packaging material.

  When the correction information received by the receiving unit includes information indicating whether or not the suction member has a function of improving the suction pressure as information on the suction member, the derivation unit includes: When the adsorption member has the function, correction can be made so that the variation in the adsorption pressure is reduced. When the adsorbing member has such a function, it is possible to suppress the generation of wrinkles in the packaging material or to suppress the generation of a gap between the packaging material and the adsorption member.

  In addition, the drop variation prediction apparatus according to the present invention indicates information indicating the variation in the drop of the workpiece predicted by the prediction unit, and indicates the number of trials related to the operation of the robot arm according to the variation in the drop of the workpiece. An output unit that outputs at least one piece of information for changing the setting of the operation command value for operating the robot arm according to the information and the variation in the falling of the workpiece can be configured. . Thereby, the user can check or use the predicted variation in the falling of the workpiece.

  The predetermined condition refers to a case where the thickness of the packaging material is a standard thickness and the content is in a standard state. For example, the thickness of the packaging material is a minimum thickness that can be practically used, and the content This can be the case when the object is empty.

  The fall variation prediction method according to the present invention is a work in which a computer includes a packaging material and contents packaged by the packaging material, and is conveyed while being held by suction by a suction member attached to a robot arm. Information indicating the type of the packaging material of the workpiece, and the type of the packaging material and the packaging material for each type of the packaging material when adsorbed by the adsorption member under predetermined conditions Referring to the correlation information indicating the correlation with the variation in the adsorption pressure between the packaging material and the adsorption member, the variation in the adsorption pressure corresponding to the information indicating the received material type of the packaging material is derived and derived. In this method, a process including predicting a variation in the falling of the workpiece when the robot arm transports the workpiece based on the variation in the suction pressure.

  The fall variation prediction program according to the present invention is a work including a packaging material and contents packaged by the packaging material, and is conveyed while being sucked and held by a suction member attached to a robot arm. A receiving unit that receives information indicating the type of material of the packaging material of the workpiece, the type of packaging material, and the packaging material for each type of packaging material adsorbed by the adsorption member under predetermined conditions The adsorption pressure corresponding to the information indicating the type of the material of the packaging material received by the reception unit with reference to the correlation information indicating the correlation between the variation of the adsorption pressure between the packaging material and the adsorption member Based on the derivation unit for deriving the variation of the workpiece and the variation in the suction pressure derived by the deriving unit, the variation in the drop of the workpiece when the robot arm transports the workpiece is predicted. Is a program for functioning as a predictor for.

  Further, the robot system according to the present invention is configured so that when the information for changing the setting of the operation command value for operating the robot arm is output from the output unit of the drop variation prediction apparatus, the operation is performed. A control unit is configured to control the robot arm to operate based on the operation command value changed based on the information for changing the command value setting.

  According to the drop variation predicting apparatus, method, and program according to the present invention, the received packaging material type is referred to by referring to the correlation information indicating the correlation between the packaging material type and the adsorption pressure variation. By deriving the variation in the suction pressure corresponding to the information to be shown, it is possible to predict the variation in the drop of the workpiece when the workpiece including the packaging material and the contents packed with the packaging material is sucked and conveyed. Further, according to the robot system of the present invention, the robot arm can be operated according to the predicted variation in the falling of the workpiece.

It is a figure for demonstrating adsorption | suction of the workpiece | work by a suction pad. It is a figure for demonstrating the wrinkles which generate | occur | produce in the packaging material of the workpiece | work containing a packaging material and the content packaged with the packaging material. It is a block diagram which shows the hardware constitutions of a fall dispersion | variation prediction apparatus. It is a block diagram which shows the example of a function structure of a fall dispersion | variation prediction apparatus. It is a figure which shows an example of the reception screen in 1st Embodiment. It is a figure which shows an example of the correlation information database in 1st Embodiment. It is a figure for demonstrating the prediction process of the dispersion | variation in fall. It is a figure which shows an example of a prediction result screen. It is a flowchart which shows the flow of operation | movement of the fall dispersion | variation prediction apparatus which concerns on 1st Embodiment. It is a figure which shows an example of the reception screen in 2nd Embodiment. It is a figure which shows an example of the correlation information database in 2nd Embodiment. It is a figure for demonstrating the derivation | leading-out process of the dispersion | variation in the adsorption pressure in 2nd Embodiment. It is a figure for demonstrating the generation | occurrence | production state of a wrinkle according to the mass of the contents. It is a figure for demonstrating the generation | occurrence | production condition of a wrinkle according to the filling rate of the content with respect to a packaging material. It is a figure for demonstrating the generation | occurrence | production condition of a wrinkle according to the number of the suction pads with respect to one workpiece | work. It is a graph which shows an example of the relationship between the mass of the contents at the time of deriving adsorption pressure variation, and variation in adsorption pressure. It is a graph which shows an example of the relationship between the filling rate of the content with respect to a packaging material, and the dispersion | variation in adsorption pressure at the time of deriving adsorption pressure dispersion | variation. It is a graph which shows an example of the relationship between the number of the suction pads with respect to one workpiece | work, and the dispersion | variation in adsorption pressure at the time of derivation | leading-out of adsorption pressure. It is a figure for demonstrating the generation | occurrence | production state of a wrinkle according to the thickness of a packaging material. It is a graph which shows an example of the relationship between the thickness of a packaging material, and the dispersion | variation in adsorption pressure at the time of deriving adsorption pressure dispersion | variation. It is a figure for demonstrating the generation | occurrence | production condition of a wrinkle according to the presence or absence of a wrinkle option. It is a figure for demonstrating an example of the derivation | leading-out process of the dispersion | variation in the adsorption pressure in 2nd Embodiment. It is a figure for demonstrating the safety factor according to the prediction result of fall dispersion | variation. It is a flowchart which shows the flow of operation | movement of the fall dispersion | variation prediction apparatus which concerns on 2nd Embodiment. It is a figure for demonstrating the other example of the output of the prediction result of fall dispersion | variation. It is a block diagram which shows schematic structure of a robot system.

  Hereinafter, an example of an embodiment of the present invention will be described with reference to the drawings. In each drawing, the same reference numerals are given to the same or equivalent components and parts. In addition, the dimensional ratios in the drawings are exaggerated for convenience of explanation, and may be different from the actual ratios.

  (First embodiment)

The drop variation prediction apparatus according to the present embodiment predicts variation in drop of a workpiece when the workpiece is transported by a robot having a robot arm. As shown in FIG. 1, the robot picks up a workpiece W by an elastic suction pad P attached to the tip of a robot arm R having a vacuum pipe, conveys the workpiece W, and places the workpiece W at a destination. Pick and place device. The workpiece W is picked up by sucking at the suction pressure p _A set in the robot and setting the inside of the suction pad P to a negative pressure, and placing the workpiece W by releasing the suction.

As shown in FIG. 1, when the surface of the workpiece W is not wrinkled, the suction pressure p _A set for the robot and the suction pressure p _{B on} the suction surface between the suction pad P and the workpiece W are approximately p. It is in a relationship of _a = _{p B.} Therefore, in this case, if the suction pressure p _A is set appropriately such that the workpiece W does not fall, the workpiece W does not fall during conveyance.

In this embodiment, as shown in FIG. 2, the workpiece W includes a packaging material O and a content C packaged with the packaging material O. When the workpiece W is sucked, wrinkles that connect the inside and the outside of the suction pad P are generated in the region including the suction portion of the packaging material O by the suction pad P due to the suction of the suction pad P. This situation is shown in the dashed line portion in FIG. The right diagram in FIG. 2 is a diagram schematically showing a case where a portion within a one-dot broken line in the left diagram in FIG. 2 is viewed from above. Due to the generation of the wrinkles, a gap is generated between the suction pad P and the packaging material O, and the suction pressure p _A set for the robot and the suction pressure p of the suction surface between the suction pad P and the workpiece W are set. _B has a relationship of p _A > p _B. When the adsorption pressure p _B of the suction surface becomes too small, so that the workpiece W from falling. Wrinkles occurring packaging material O, for each adsorption, wrinkle depth, number, position in a random state such as, for every change wrinkling states, in variations every time the value of the adsorption pressure p _B of the suction surface Become.

For this reason, even when the operation command values such as the adsorption pressure p _A and the acceleration of the robot arm R are the same, the workpiece W drops in variation. As described above, the drop variation prediction apparatus according to the present embodiment predicts the variation in fall of the workpiece W when the workpiece W including the packaging material O and the contents C packaged with the packaging material O is sucked and conveyed. To do.

  FIG. 3 is a block diagram illustrating a hardware configuration of the drop variation prediction apparatus 10 according to the present embodiment. As shown in FIG. 3, the fall variation prediction device 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a monitor 16, and an optical disk drive. A device 17 and a communication interface 18 are included. Each component is connected to be communicable with each other via a bus 19.

  In the present embodiment, the ROM 12 or the storage 14 stores a drop variation prediction program that executes a drop variation prediction process. The CPU 11 is a central processing unit, and executes various programs and controls each component. That is, the CPU 11 reads a program from the ROM 12 or the storage 14 and executes the program using the RAM 13 as a work area. The CPU 11 controls the above components and performs various arithmetic processes according to a program recorded in the ROM 12 or the storage 14.

  The ROM 12 stores various programs and various data. The RAM 13 temporarily stores a program or data as a work area. The storage 14 is configured by an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and stores various programs including an operating system and various data.

  The input unit 15 includes a keyboard 151 and a pointing device such as a mouse 152, and is used for performing various inputs. The monitor 16 is a liquid crystal display, for example, and displays various information such as prediction results. The monitor 16 may function as the input unit 15 by adopting a touch panel method. The optical disc drive device 17 reads data stored in various recording media (CD-ROM, Blu-ray disc, etc.), writes data to the recording media, and the like.

  The communication interface 18 is an interface for communicating with other devices. For example, standards such as Ethernet (registered trademark), FDDI, or Wi-Fi (registered trademark) are used.

  Next, a functional configuration of the drop variation prediction device 10 according to the first embodiment will be described.

  FIG. 4 is a block diagram illustrating an example of a functional configuration of the drop variation prediction apparatus 10. As shown in FIG. 4, the drop variation prediction device 10 includes a receiving unit 22, an adsorption pressure variation deriving unit 24, a drop variation prediction unit 26, and an output unit 28 as functional configurations. Each functional configuration is realized by the CPU 11 reading out the fall variation prediction program stored in the ROM 12 or the storage 14, developing it in the RAM 13, and executing it. The adsorption pressure variation deriving unit 24 is an example of the deriving unit of the present invention, and the drop variation predicting unit 26 is an example of the predicting unit of the present invention.

  The receiving unit 22 receives information indicating the material type of the packaging material O of the workpiece W including the packaging material O and the contents C packaged with the packaging material O. The reception unit 22 displays a reception screen 40 as shown in FIG. In the example of FIG. 5, the reception screen 40 has a pull-down menu 41 for selecting and inputting the material type of the packaging material O from preset options, and an OK button selected when the input information is confirmed. 42, and a cancel button 43 selected when canceling the input information. Instead of the pull-down menu 41, an input box for directly inputting text data indicating the material of the packaging material O may be used. When the user inputs information indicating the material of the packaging material O from the pull-down menu 41 of the reception screen 40 displayed on the monitor 16 and selects the OK button 42, the reception unit 22 displays the package input on the reception screen 40. Information indicating the type of material of material O is received.

  The adsorption pressure variation deriving unit 24 refers to the correlation information database (DB) 30 and derives a variation in adsorption pressure corresponding to information indicating the type of material of the packaging material O received by the receiving unit 22. The correlation information DB 30 indicates the type of the packaging material O and the space between the packaging material O and the suction pad P when the packaging material O is adsorbed by the suction pad P under a predetermined condition for each type of packaging material O. It is the database in which the correlation information which shows the correlation with the dispersion | variation in adsorption pressure of was memorize | stored.

  FIG. 6 shows an example of the correlation information DB 30. In the example of FIG. 6, the correlation information DB 30 is assigned identification information “ID” for each type of packaging material O, and stores “packaging material” and “adsorption pressure variation” in association with each other. Has been.

  The “packaging material” is information indicating the type of material of the packaging material O. In the example of FIG. 6, information indicating the type of material of the packaging material O configured by stacking a plurality of types of materials is shown. In FIG. 6, “OPP / PE” represents a two-layer structure of OPP (biaxially stretched polypropylene) and PE (polyethylene), and “PET / CPP” represents PET (polyester) and CPP ( “PET / Al / CPP” represents a three-layer structure of PET, Al (aluminum) and CPP, and “OPP / EVOH / PE”. "Represents a three-layer structure of OPP, EVOH (ethylene vinyl alcohol copolymer) and PE.

  “Adsorption pressure variation” means that the actual machine is repeatedly moved under predetermined conditions, the adsorption pressure between the packaging material O and the adsorption pad P is measured, the variance of the measured values is calculated, and the correlation information is correlated. It is stored in the information DB 30. The predetermined condition can be, for example, the following condition as a condition in which wrinkles are most likely to occur.

・ The contents C packed in the packaging material O is emptied, and the tension of the packaging material O is minimum. ・ The thickness of the packaging material O is minimum (generally about 30 μm).

  In general, the wrapping material O, which is a hard material, is less likely to wrinkle, and the variation in adsorption pressure is small. Although FIG. 6 shows an example in which the variation in the adsorption pressure is represented by the variance, an index representing another variation such as a standard deviation may be used.

  Specifically, the adsorption pressure variation deriving unit 24 searches the “information of the packaging material” in the correlation information DB 30 for information indicating the type of the material of the packaging material O received by the receiving unit 22, and the retrieved “ By obtaining the “adsorption pressure variation” corresponding to the “packaging material”, the adsorption pressure variation corresponding to the information indicating the type of the material of the packaging material O received by the receiving unit 22 is derived.

  The drop variation prediction unit 26 predicts the variation in the drop of the workpiece W when the robot arm R transports the workpiece W based on the variation in the adsorption pressure derived by the adsorption pressure variation deriving unit 24. The variation in the drop of the workpiece W correlates with the variation in the suction pressure between the packaging material O and the suction pad P. The greater the variation in the suction pressure, the greater the variation in the drop of the workpiece W. Therefore, for example, as shown in FIG. 7, the drop variation predicting unit 26 sets a plurality of drop variations such as “large”, “medium”, and “small” in accordance with the magnitude of the variation in adsorption pressure. Predict in stages.

  The output unit 28 outputs screen information indicating the prediction result by the drop variation prediction unit 26 to the monitor 16. Thereby, the prediction result screen 50 as shown in FIG. 8 is displayed on the monitor 16, for example. In the example of FIG. 8, the prediction result screen 50 includes a message 51 indicating the prediction result and a confirmation button 52 that is selected when the prediction result is confirmed.

  Next, the operation of the drop variation prediction apparatus 10 according to the first embodiment will be described.

  FIG. 9 is a flowchart showing a flow of operations executed by the CPU 11 of the drop variation prediction apparatus 10. The CPU 11 reads the drop variation prediction program from the ROM 12 or the storage 14, develops it in the RAM 13, and executes it, thereby performing a drop variation prediction process.

  For example, the CPU 11 displays a reception screen 40 as shown in FIG. 5 on the monitor 16 as the reception unit 22, and the packaging material O of the workpiece W including the packaging material O and the contents C packaged with the packaging material O. Information indicating the type of material is accepted (step S12).

  The CPU 11 searches the “packaging material” in the correlation information DB 30 for information indicating the type of the material of the packaging material O received by the reception unit 22 as the adsorption pressure variation deriving unit 24, and searches for the “packaging material” By acquiring “adsorption pressure variation” corresponding to “material”, variation in adsorption pressure corresponding to information indicating the type of material of the packaging material O received by the receiving unit 22 is derived (step S14).

  For example, as shown in FIG. 7, the CPU 11 sets the degree of variation in the drop to “large” according to the magnitude of the variation in the adsorption pressure derived by the adsorption pressure variation deriving unit 24. Prediction is made in multiple stages such as “medium” and “small” (step S16).

  CPU11 outputs the screen information which shows the prediction result by the fall dispersion | variation prediction part 26 to the monitor 16 as the output part 28 (step S18). Thereby, the prediction result screen 50 as shown in FIG. 8 is displayed on the monitor 16, for example. Then, the CPU 11 ends the fall variation prediction process.

  As described above, according to the drop variation predicting device 10 of the first embodiment, the packaging material O is used by the suction pad P under predetermined conditions for each type of packaging material O and each type of packaging material O material. Information indicating the type of the material of the received packaging material O with reference to the correlation information DB 30 in which correlation information indicating the correlation between the variation of the suction pressure between the packaging material O and the suction pad P when adsorbed is stored. The variation of the adsorption pressure corresponding to is derived. Since there is a correlation that the variation in the suction pressure increases as the variation in the suction pressure increases, the workpiece W drops when the robot arm R transports the workpiece W according to the variation in the suction pressure. Can be predicted. Thereby, the user can know whether or not the falling of the workpiece W varies without actually confirming the workpiece W by repeatedly conveying the workpiece W, and taking into account the predicted variation in the falling of the workpiece W. Thus, it is possible to determine whether or not the robot operation command value needs to be adjusted.

  (Second Embodiment)

  In the second embodiment, the variation in the adsorption pressure derived based on the material type of the packaging material O is used as correction information using information that affects the wrinkle generation status other than the material type of the packaging material O, A case where the corrected variation in the adsorption pressure is derived will be described.

  Note that the hardware configuration of the drop variation prediction apparatus according to the second embodiment is the same as that of the drop variation prediction apparatus 10 according to the first embodiment, and thus the description thereof is omitted.

  As shown in FIG. 4, the drop variation prediction apparatus 210 according to the second embodiment includes a reception unit 222, an adsorption pressure variation deriving unit 224, a drop variation prediction unit 26, and an output unit 228 as functional configurations. . Each functional configuration is realized by the CPU 11 reading out the fall variation prediction program stored in the ROM 12 or the storage 14, developing it in the RAM 13, and executing it. The adsorption pressure variation deriving unit 224 is an example of the deriving unit of the present invention, and the drop variation predicting unit 26 is an example of the predicting unit of the present invention.

  In response to the type of material of the packaging material O, the reception unit 222 displays information on the thickness of the packaging material O, information on the contents C, and information on the suction pad P in accordance with the type of material of the packaging material O. It is received as correction information for correcting variations in the suction pressure. The information on the contents C is, for example, information indicating the mass of the contents C and information indicating the filling rate of the contents C with respect to the packaging material O. The information about the suction pad P includes, for example, information indicating the number of suction pads P used for sucking and holding one workpiece W, and the function of the suction pad P to improve the suction pressure of the suction surface with the packaging material O. It is information indicating whether or not it has.

  For example, the reception unit 222 displays a reception screen 240 as illustrated in FIG. 10 on the monitor 16. In the example of FIG. 10, the reception screen 240 includes a pull-down menu for selecting and inputting the material type of the packaging material O, an input area 44 including an input box for inputting the thickness of the packaging material O, and contents An input area 45 including an input box for inputting each of the mass and filling rate of the contents C as information of C, an input box for inputting the number of suction pads P as information of the suction pads P, and An input area 46 including a check box for selecting a function of the suction pad P, an OK button 42, and a cancel button 43 are included. Note that an input box may be used instead of the pull-down menu included in the input area 44. In addition, a pull-down menu may be used instead of each text box included in the input areas 44, 45, and 46. Further, a pull-down menu may be used instead of the check box included in the input area 46.

  When the user inputs information indicating the type of the material of the packaging material O and correction information in the input areas 44, 45, 46 of the reception screen 240 displayed on the monitor 16 and selects the OK button 42, the reception unit 222. Accepts information indicating the type of the material of the packaging material O input on the acceptance screen 240 and correction information.

  The suction pressure variation deriving unit 224 generates the wrinkle of the packaging material O corresponding to the correction information received by the receiving unit 222, based on the variation in the suction pressure acquired from the correlation information DB 230 according to the type of the material of the packaging material O. Correct based on the situation.

  FIG. 11 shows an example of the correlation information DB 230. In the example of FIG. 11, the correlation information DB 230 is assigned identification information “ID” for each type of material of the packaging material O, “packaging material”, “maximum adsorption pressure variation”, and “packaging”. “Maximum mass of contents without breaking material” is stored in association with each other. The “maximum adsorption pressure variation” is the same as the “adsorption pressure variation” of the correlation information DB 30 in the first embodiment, and is a variation in adsorption pressure according to the type of material of the packaging material O under a predetermined condition. “Maximum mass of the contents that the packaging material does not break” means that when the thickness of the packaging material O is minimum (generally 30 μm), the packaging material O It represents the limit value of the mass of the content C that is not torn or stretched beyond the tolerance of a product. The “maximum mass of the contents that the packaging material does not break” is determined experimentally.

  Specifically, as shown in FIG. 12, the adsorption pressure variation deriving unit 224 sets the adsorption pressure variation acquired from the correlation information DB 230 according to the type of the material of the packaging material O as the maximum adsorption pressure variation p_max. The maximum adsorption pressure variation p_max is corrected by the correction information, and the final adsorption pressure variation p is derived. As corrections based on the correction information, factors affecting the wrinkle generation state of the packaging material O include (a) the tension of the packaging material O, (b) the thickness of the packaging material O, and (c) the suction of the suction pad P. The presence or absence of a function to improve pressure (hereinafter also referred to as “wrinkle option”) is applied. (A) Wrinkles are less likely to occur as the packaging material O is stretched, (b) Wrinkles are less likely to occur as the packaging material is thicker, and (c) If the suction pad P has an option for wrinkles, Hard to occur. The fact that wrinkles are less likely to occur means that the adsorption pressures are less likely to vary. Therefore, the adsorption pressure variation deriving unit 224 determines whether or not wrinkles are likely to occur due to the above factors (a) to (c). Accordingly, the maximum adsorption pressure variation p_max is corrected. Specifically, when wrinkles are difficult to occur, the maximum adsorption pressure variation p_max is corrected to be smaller than when wrinkles are likely to occur.

  Hereinafter, a wrinkle occurrence state corresponding to each of the correction information and a correction example corresponding to the above factors (a) to (c) will be described.

  First, the mass of the contents C is one piece of correction information that affects the tension of the packaging material O in (a). As shown in FIG. 13, the smaller the mass of the contents C, the weaker the tension of the packaging material O, and the packaging material O is easily sucked into the suction holes of the suction pad P at the time of suction, and wrinkles are likely to occur. On the other hand, the larger the mass of the contents C, the stronger the tension of the packaging material O, and it becomes difficult for the packaging material O to be sucked into the suction holes of the suction pad P during suction, so that wrinkles are less likely to occur. In addition, in FIG. 13, the number of wrinkles (the wavy line portion in the suction pad P) and the height of the wrinkles are shown by the number of wrinkles and the height of the wrinkles. This means that wrinkles are unlikely to occur. The same applies to the following drawings.

  As other correction information that affects the tension of the packaging material O in (a), there is a filling rate of the contents C to the packaging material O. As shown in FIG. 14, the lower the filling rate of the contents C, the weaker the tension of the packaging material O, and wrinkles are likely to occur. On the other hand, the higher the filling rate of the contents C, the stronger the tension of the packaging material O and the less the wrinkle is generated.

  As other correction information that affects the tension of the packaging material O in (a) above, there is the number of suction pads P used for sucking and holding one workpiece W. FIG. 15 schematically shows an example of the arrangement of the suction pads P with respect to one workpiece W in each case where the number of the suction pads P is 1 to 4. As the number of the suction pads P increases, the packaging material O is pulled between the suction pads P, and the area of the weak tension area (the hatched portion in the packaging material O in FIG. 15) is reduced, and the tension condition is stronger. The area of the white portion in the packaging material O in FIG. 15 increases, and wrinkles are less likely to occur.

  Based on the above points, the adsorption pressure variation deriving unit 224 corrects the adsorption pressure variation p to be smaller as the mass of the contents C is larger. Further, the adsorption pressure variation deriving unit 224 corrects the adsorption pressure variation p to be smaller as the filling rate of the contents C to the packaging material O is higher. Further, the suction pressure variation deriving unit 224 corrects the suction pressure variation p to be smaller as the number of suction pads P used for sucking and holding one workpiece W is larger. Hereinafter, an example of the derivation of the adsorption pressure variation p will be described more specifically.

Adsorption pressure variation deriving unit 224, for example, as shown in the following equation (1), using a function F_tension, variations _{p IN} adsorption pressure input, based on the tension of (a) packaging material O, Adsorption pressure variation p _OUT is corrected.

p _OUT = f_tension (p _IN , m, fill, pad_num)
= Max (f_tension_m (p _IN , m, th),
f_tension_fill (p _IN , fill),
f_tension_pad_num (p _IN , pad_num)
... (1)

  m is the mass of the contents C of the workpiece W, fill is the filling rate, pad_num is the number of suction pads P, and th is the thickness of the packaging material O. The above equation (1) indicates that the tension is maximized from the tension of the packaging material O caused by either the mass of the contents C, the filling rate, or the number of the suction pads P, that is, the packaging material O. This represents calculating the variation in adsorption pressure when the occurrence of wrinkles is assumed to be minimal.

  In the equation (1), f_tension_m is a function for obtaining the adsorption pressure variation from the tension due to the mass of the contents C. f_tension_m can be expressed by the following equation (2), for example.

  m_max is a constant representing the maximum mass of the contents C that does not break the packaging material, and is information acquired from the correlation information DB 230. Further, th_min is a constant representing the minimum value of the thickness of the packaging material O and is, for example, 30 μm. For example, as shown in FIG. 16, the larger the mass m of the content C, the greater the tension of the packaging material O, and the more difficult the wrinkle is and the variation in the adsorption pressure becomes smaller. This is a formula representing In the present embodiment, the term “th / th_min” in the expression (2) is the value of the maximum mass of the contents that the packaging material is not broken in the correlation information DB 230 (m_max) is the thickness of the packaging material O. Since this is a measured value in the case of minimum (th_min), the actual thickness of the packaging material O is reflected in this term.

  In the equation (1), f_tension_fill is a function for obtaining the adsorption pressure variation from the tension depending on the filling rate of the contents C. f_tension_fill can be expressed by the following equation (3), for example.

f_tension_fill (p _IN , fill)
= -P _IN * fill + p _IN (3)

  For example, as shown in FIG. 17, the higher the filling rate of the contents C, the greater the tension of the packaging material O, and the less the wrinkle is generated and the variation in the adsorption pressure is reduced. This is a formula representing

  In the equation (1), f_tension_pad_num is a function for obtaining the suction pressure variation from the tension depending on the number of suction pads P. f_tension_pad_num can be expressed by the following equation (4), for example.

f_tension_pad_num (p _IN , pad_num)
= P _IN / pad_num (4)

  For example, as shown in FIG. 18, the equation (4) indicates that as the number of suction pads P increases, the tension of the wrapping material O increases, so that wrinkles are less likely to occur and variations in suction pressure are also reduced. This is the expression.

  Next, the case where the thickness of the packaging material O is used as the correction information will be described. As shown in FIG. 19, the thinner the packaging material O, the easier it is for the packaging material O to be deformed at the time of adsorption, and wrinkles are more likely to occur. On the other hand, the thicker the packaging material O, the harder the deformation of the packaging material O at the time of adsorption and the less the occurrence of wrinkles. Therefore, the adsorption pressure variation deriving unit 224 performs correction so that the adsorption pressure variation p decreases as the thickness of the packaging material O increases.

Adsorption pressure variation deriving unit 224, for example, as shown in the following equation (5), using a function F_thickness, variations _{p IN} adsorption pressure input, based on the thickness of the (b) packaging material O, Adsorption pressure variation p _OUT is corrected.

p _OUT = f_thickness (p _IN , th)
= P _IN / (th / th_min) (5)

  For example, as shown in FIG. 20, the expression (5) is an expression that indicates that as the thickness of the packaging material O increases, wrinkling of the packaging material O becomes difficult and variation in the adsorption pressure decreases.

  Next, a description will be given of the case where (c) the presence or absence of the wrinkle option of the suction pad P is used as the correction information. Examples of the wrinkle option include a guard for preventing the packaging material O from being drawn into the suction hole of the suction pad P as shown in the upper right diagram of FIG. For example, the skirt portion of the suction pad P is softened and the outer shape of the skirt is made to follow the wrinkles of the packaging material O, thereby preventing a gap between the suction pad P and the packaging material O from being generated. As shown in FIG. 21, when there is a wrinkle option, the wrinkle of the packaging material O or the gap between the suction pad P and the packaging material O is less likely to occur than when there is no wrinkle option. Variation in adsorption pressure can be suppressed. Therefore, the adsorption pressure variation deriving unit 224 corrects the variation in the adsorption pressure to be small when the adsorption pad P has a wrinkle option.

The suction pressure variation deriving unit 224 uses, for example, the function f_pad_option to change the input suction pressure variation p _IN to (c) the presence or absence of the wrinkle pad option, as shown in the following equation (6). Based on this, the adsorption pressure variation p _OUT is corrected.

  Equation (6) is an equation representing that the more the suction pad P has a wrinkle option, the more difficult it is to wrinkle the packaging material O, and the smaller the variation in suction pressure. In equation (6), k_i is a constant assigned for each wrinkle option op_i (i = 1, 2,...) For correcting the adsorption pressure variation p to be small. When wrinkle option op_i = True (when suction pad P has wrinkle option op_i), when 0 <k_i <1, and op_i = False (suction pad P does not have wrinkle option op_i) Case), k_i = 1. Num_of_options is a constant representing the total number of wrinkle options.

  The correction based on the above factors (a) to (c) applied to the maximum adsorption pressure variation p_max may be applied in any order. Below, as shown in FIG. 22, the case where it applies in order of (a), (b), (c) is demonstrated. In this case, the finally derived adsorption pressure variation p can be expressed by the following equation (7).

p = f_pad_option (p2, op_i)
p2 = f_thickness (p1, th)
p1 = f_tension (p_max, m, fill, pad_num, th)
... (7)

  The output unit 228 outputs a safety factor as information for changing the setting of the operation command value of the robot according to the degree of variation in the drop of the workpiece W predicted by the drop variation prediction unit 26. In the present embodiment, for example, the safety factor is a value of 0 to 1 that is multiplied by a set value such as the maximum speed and maximum acceleration of the robot arm R or an operation command value such as an adsorption pressure value set in the robot. For example, as shown in FIG. 23, the output unit 228 has a safety factor that is closer to 0 as the degree of variation in the drop of the workpiece W predicted by the drop variation prediction unit 26 increases, and decreases as the degree of variation in drop decreases. A value close to. The output safety factor is multiplied by the operation command value set in the robot. Accordingly, the robot operates based on the operation command value multiplied by the output safety factor in consideration of the drop variation.

  Next, the operation of the drop variation prediction apparatus 210 according to the second embodiment will be described.

  FIG. 24 is a flowchart showing a flow of operations executed by the CPU 11 of the drop variation predicting apparatus 210. The CPU 11 reads the drop variation prediction program from the ROM 12 or the storage 14, develops it in the RAM 13, and executes it, thereby performing a drop variation prediction process.

  The CPU 11 displays, for example, a reception screen 240 as shown in FIG. 10 on the monitor 16 as the reception unit 222 and sucks the workpiece W including the packaging material O and the contents C packaged with the packaging material O. A condition is accepted (step S22). The conditions include information indicating the material type of the packaging material O, information on the thickness of the packaging material O as correction information for correcting variations in adsorption pressure according to the material type of the packaging material O, and contents C information and suction pad P information are included.

  The CPU 11 refers to the correlation information DB 230 as the adsorption pressure variation deriving unit 224, and acquires the maximum adsorption pressure variation p_max corresponding to the material type information of the packaging material O received by the reception unit 222 (step S24). .

  The CPU 11 serves as the suction pressure variation deriving unit 224 according to the mass m of the contents C received by the receiving unit 222, the filling rate fill, and the number pad_num of the suction pads P, for example, Equations (1) to (4). According to the equations (7) and (7), the maximum adsorption pressure variation p_max is corrected to the adsorption pressure variation p1 (step S26).

  The CPU 11 serves as the adsorption pressure variation deriving unit 224 according to the thickness th of the packaging material O received by the receiving unit 222, for example, according to the equations (5) and (7). The variation p2 is corrected (step S28).

  The CPU 11 serves as the suction pressure variation deriving unit 224, for example, according to information on whether or not the suction pad P received by the receiving unit 222 has the wrinkle option op_i, according to formulas (6) and (7). Then, the adsorption pressure variation p2 is corrected to the adsorption pressure variation p (step S30). Thereby, the final adsorption pressure variation p is derived.

  As shown in FIG. 23, for example, as shown in FIG. , “Medium”, “Small”, etc., are predicted in a plurality of stages (step S32).

  As the output unit 228, for example, as illustrated in FIG. 23, the CPU 11 outputs a safety factor corresponding to the degree of variation in the drop of the workpiece W predicted by the drop variation prediction unit 26. The output safety factor is multiplied by the operation command value set in the robot. Therefore, the robot operates based on the operation command value multiplied by the output safety factor in consideration of the drop variation. Then, the CPU 11 ends the fall variation prediction process.

  As described above, according to the drop variation predicting apparatus 210 of the second embodiment, in addition to the type of the packaging material O, the thickness of the packaging material O that is a factor affecting the generation of wrinkles in the packaging material O is determined. The information shown, the information on the contents C, and the information on the suction pad P are received as correction information. Then, the drop variation prediction device 210 corrects the maximum adsorption pressure variation according to the type of the material of the packaging material O based on the correction information, and derives the final adsorption pressure variation. In this way, since the variation in the suction pressure is derived in more detail reflecting the wrinkle generation state of the packaging material O, the variation in the drop of the workpiece W can be predicted with higher accuracy.

  Further, by multiplying the motion command value set for the robot by the safety factor corresponding to the predicted drop variation variation, the motion command value can be changed according to the workpiece W drop variation.

  Note that the drop variation prediction device is not limited to the above-described embodiments, and various modifications can be made.

  For example, in the first embodiment, when information indicating the degree of variation in the predicted drop of the workpiece W is presented, in the second embodiment, the operation command value according to the degree of variation in the predicted drop of the workpiece W. However, the present invention is not limited to this. For example, information indicating an instruction of the number of trials related to the operation of the robot may be presented according to the predicted degree of variation in the drop of the workpiece W. Specifically, as shown in FIG. 25, when the degree of variation in fall is large, a message instructing to increase the number of test operations for adjusting the operation command value before the actual operation of the robot. May be displayed on the monitor 16.

  Further, in each of the above-described embodiments, the case has been described in which the drop variation prediction is predicted in three stages of “large”, “medium”, and “small”, but the present invention is not limited to this. For example, prediction may be performed in two stages, or prediction may be performed in four or more stages. Further, the variation in the adsorption pressure derived by the adsorption pressure variation deriving unit may be output as it is as a predicted drop variation. This is because there is a correlation between the variation in the suction pressure and the variation in the drop of the workpiece W, and thus the variation in the suction pressure itself becomes an index indicating the variation in the drop of the workpiece W.

  Moreover, although 2nd Embodiment demonstrated the case where all the information which shows the thickness of the packaging material O, the information of the content C, and the information of the suction pad P was used as correction | amendment information, it is not limited to this. At least one of these pieces of information may be used as correction information.

  Further, as shown in FIG. 26, the drop variation prediction device according to each of the above embodiments can be applied to a robot system 60. A robot system 60 illustrated in FIG. 26 includes a drop variation prediction device 10 (210), a presentation unit 61, a control unit 62, and a robot unit 63. The robot unit 63 includes a robot arm R having a suction pad P attached to the tip, and a drive mechanism for operating the robot arm R. The drive mechanism operates the robot arm R based on a control signal from the control unit 62.

  The presentation unit 61 can be configured by a display device such as a display, a speaker that outputs sound, and the like. The presentation unit 61 outputs the information indicating the variation in the fall of the workpiece W and the information indicating the number of trials related to the operation of the robot arm R according to the variation in the fall of the workpiece W, which is output from the fall variation prediction apparatus 10 (210). And a message or the like based on information for changing the setting of the operation command value for operating the robot arm according to the variation in the falling of the workpiece.

  When the information for changing the setting of the operation command value is output from the drop variation prediction device 10 (210), the control unit 62 is controlled based on the information for changing the setting of the operation command value. The operation command value set in advance at 62 is changed, and a control signal is sent to the drive mechanism so that the robot arm R operates based on the changed operation command value.

  In addition, various processors other than the CPU may execute the drop variation prediction process performed by the CPU reading and executing the software (program) in each of the above embodiments. As a processor in this case, PLD (Programmable Logic Device) whose circuit configuration can be changed after manufacture such as FPGA (Field-Programmable Gate Array) or the like, and ASIC (Application Specific Integrated Circuit) for executing specific processing such as Application Specific Circuit A dedicated electric circuit, which is a processor having a circuit configuration designed exclusively, is exemplified. Further, the fall variation prediction process may be executed by one of these various processors, or a combination of two or more processors of the same type or different types (for example, a plurality of FPGAs and a combination of a CPU and an FPGA). You may perform by combination etc.). Further, the hardware structure of these various processors is more specifically an electric circuit in which circuit elements such as semiconductor elements are combined.

  Moreover, although each said embodiment demonstrated the aspect by which the fall dispersion | variation prediction program was previously memorize | stored (installed) in the storage 14 or ROM12, it is not limited to this. The program may be provided in a recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), and a USB (Universal Serial Bus) memory. Further, the program may be downloaded from an external device via a network.

10, 210 Drop variation predicting device 22, 222 Accepting unit 24, 224 Adsorption pressure variation deriving unit 26 Fall variation predicting unit 28, 228 Output unit 30, 230 Correlation information database 60 Robot system 61 Presenting unit 62 Control unit W Work O Packaging C Contents P Suction pad R Robot arm

Claims (12)

Information indicating the type of material of the packaging material of the workpiece, which is a workpiece including the packaging material and the contents packaged by the packaging material and is sucked and held by the suction member attached to the robot arm. A reception department;
The type of packaging material and the variation in adsorption pressure between the packaging material and the adsorption member when the packaging material is adsorbed by the adsorption member under a predetermined condition for each type of packaging material With reference to correlation information indicating correlation, a derivation unit that derives variation in adsorption pressure corresponding to information indicating the type of material of the packaging material received by the reception unit;
A predicting unit that predicts variation in dropping of the workpiece when the robot arm transports the workpiece based on variation in the adsorption pressure derived by the deriving unit;
Fall variation prediction device including The accepting unit further accepts at least one of information on the thickness of the packaging material, information on the contents, and information on the suction member as correction information,
The drop according to claim 1, wherein the derivation unit corrects the variation in the adsorption pressure obtained from the correlation information based on a wrinkle generation state of the packaging material corresponding to the correction information received by the reception unit. Variation prediction device.   When the information on the thickness of the packaging material is included in the correction information received by the reception unit, the derivation unit corrects the variation in the adsorption pressure so that the thickness of the packaging material increases. The fall variation prediction apparatus according to claim 2.   When the correction information received by the receiving unit includes information indicating the mass of the content as the content information, the derivation unit may vary the adsorption pressure as the mass of the content increases. The fall variation prediction apparatus according to claim 2 or 3, wherein correction is performed so as to be small.   When the correction information received by the receiving unit includes information indicating the filling rate of the content with respect to the packaging material as the content information, the derivation unit increases the suction rate as the filling rate increases. The fall variation prediction apparatus according to any one of claims 2 to 4, wherein the drop variation is corrected so as to reduce the pressure variation.   When the correction information received by the receiving unit includes information indicating the number of the suction members used for sucking and holding one workpiece as the suction member information, the derivation unit has the number of The fall variation prediction apparatus according to any one of claims 2 to 5, wherein the amount of variation in the adsorption pressure is reduced as the amount increases.   When the correction information received by the receiving unit includes information indicating whether or not the suction member has a function of improving the suction pressure as information on the suction member, the derivation unit is The fall variation prediction device according to any one of claims 2 to 6, wherein when the member has the function, correction is performed so that the variation in the adsorption pressure is reduced.   According to the information indicating the variation in the drop of the workpiece predicted by the prediction unit, the information indicating the number of trials regarding the operation of the robot arm according to the variation in the drop of the workpiece, and the variation in the drop of the workpiece The fall variation prediction apparatus according to claim 1, further comprising an output unit that outputs at least one piece of information for changing a setting of an operation command value for operating the robot arm. .   The fall variation prediction device according to any one of claims 1 to 8, wherein the predetermined condition is that the thickness of the packaging material is a reference thickness and the content is in a reference state. Computer
Receives information indicating the type of material of the packaging material of the workpiece, which is a workpiece including the packaging material and the contents packed with the packaging material, and is sucked and held by the suction member attached to the robot arm. ,
The type of packaging material and the variation in adsorption pressure between the packaging material and the adsorption member when the packaging material is adsorbed by the adsorption member under a predetermined condition for each type of packaging material With reference to the correlation information indicating the correlation, the variation in the adsorption pressure corresponding to the information indicating the type of the received material of the packaging material is derived,
A drop variation prediction method for executing processing including predicting variation in fall of the workpiece when the robot arm transports the workpiece based on the derived variation in the suction pressure. Computer
Information indicating the type of material of the packaging material of the workpiece, which is a workpiece including the packaging material and the contents packaged by the packaging material and is sucked and held by the suction member attached to the robot arm. Reception desk,
The type of packaging material and the variation in adsorption pressure between the packaging material and the adsorption member when the packaging material is adsorbed by the adsorption member under a predetermined condition for each type of packaging material With reference to correlation information indicating correlation, a derivation unit for deriving variation in adsorption pressure corresponding to information indicating the type of material of the packaging material received by the reception unit, and
A drop variation prediction program for causing the robot arm to function as a predicting unit that predicts variation in dropping of the workpiece when the robot arm transports the workpiece based on variation in the suction pressure derived by the deriving unit.   The setting of the operation command value is changed when information for changing the setting of the operation command value for operating the robot arm is output from the output unit of the drop variation prediction device according to claim 8. A robot system including a control unit configured to control the robot arm to operate based on an operation command value changed based on information for performing the operation.