Control system, control method, and program

Abstract

A control system (100) comprises one or more processors (here, a processor (12)) and a memory (here, a memory (13)). The processor (12) acquires past operation data of an operation carried out by a clothing treatment device (here, a dryer (20)) that carries out treatment related to clothing. The processor (12) calculates, on the basis of the acquired past operation data, an assumed required time assumed to be required for the treatment related to the clothing, and a float time. The processor (12) then outputs the calculated assumed required time and float time.

Description

Control System, Control Method, and Program

[0001] The present disclosure relates to a control system or the like that controls a clothing treatment device that executes processing related to clothing.

[0002] For example, Patent Document 1 discloses a washing machine. This washing machine reads the previous washing time from the storage means after reserving the end time, calculates the washing start time by the calculation means, and automatically starts the washing operation by the washing start means when the calculated washing start time is reached, and ends the washing operation when the washing process is completed.

[0003] Japanese Patent Laid-Open No. 5-76688

[0004] The present disclosure provides a control system or the like that makes it easy to approach the time when the processing related to clothing actually ends to the preset end time of the processing.

[0005] A control system according to an aspect of the present disclosure includes one or more processors and a memory. The one or more processors acquire past operation data executed by a clothing treatment device that executes processing related to clothing. The one or more processors calculate an assumed required time and a margin time that are assumed to be required for the processing related to the clothing based on the acquired past operation data. The one or more processors output the calculated assumed required time and the margin time.

[0006] A control method according to an aspect of the present disclosure is a control method executed by one or more processors. In the control method, past operation data executed by a clothing treatment device that executes processing related to clothing is acquired. In the control method, an assumed required time and a margin time that are assumed to be required for the processing related to the clothing are calculated based on the acquired past operation data. In the control method, the calculated assumed required time and the margin time are output.

[0007] A program according to an aspect of the present disclosure causes one or more processors to execute the control method.

[0008] According to the control system or the like in the present disclosure, there is an advantage that it is easy to approach the time when the processing related to clothing actually ends to the preset end time of the processing.

[0009] FIG. 1 is an explanatory diagram of a specific example of a problem. FIG. 2 is a schematic diagram showing an example of an overall configuration including a control system according to an embodiment. FIG. 3 is a block diagram showing an example of an overall configuration including a control system according to an embodiment. FIG. 4 is an explanatory diagram of an estimated required time and a margin time. FIG. 5 is a diagram showing an example of setting a margin coefficient. FIG. 6 is a diagram showing an example of data stored in an operation data storage unit. FIG. 7 is a diagram showing an example of data stored in a parameter storage unit. FIG. 8 is a flowchart showing a first example of calculation of an average value and a standard deviation in a control system according to an embodiment. FIG. 9 is a flowchart showing a second example of calculation of an average value and a standard deviation in a control system according to an embodiment. FIG. 10 is a flowchart showing a third example of calculation of an average value and a standard deviation in a control system according to an embodiment. FIG. 11 is a schematic diagram showing updating of an average value and a standard deviation in the third calculation example. FIG. 12 is a flowchart showing a first example of operation of a control system according to an embodiment. FIG. 13 is a flowchart showing a second example of operation of a control system according to an embodiment. FIG. 14 is a flowchart showing a third example of operation of a control system according to an embodiment. FIG. 15 is a diagram showing a first example of display in a dryer according to an embodiment. FIG. 16 is a diagram showing a second example of display in a dryer according to an embodiment. Fig. 17 is a diagram showing a third display example of the dryer according to the embodiment. Fig. 18 is a flowchart showing a part of the operation of the third display example of the dryer according to the embodiment. Fig. 19 is a diagram showing a fourth display example of the dryer according to the embodiment. Fig. 20 is a diagram showing a fifth display example of the dryer according to the embodiment. Fig. 21 is an explanatory diagram of advantages of the control system according to the embodiment. Fig. 22 is an explanatory diagram of other advantages of the control system according to the embodiment.

[0010] [1. Findings that Form the Basis of the Present Disclosure] First, the inventor's point of view will be explained below.

[0011] For example, Patent Document 1 discloses a washing machine that, after a user sets the end time of a washing operation, calculates the start time of the washing operation based on the time required for the previous washing operation, and automatically starts the washing operation at the calculated start time. As such, conventionally, a technology is known that sets the scheduled start time of a process related to clothes (in Patent Document 1, the washing operation) so that the process will be completed by the end time set by the user.

[0012] Although the washing machine described above sets the scheduled start time so that the washing operation will finish by the end time set by the user, the operation may take longer than expected, and the washing operation may finish later than the end time set by the user. If the washing operation has not finished by the set end time, the user is likely to become dissatisfied, fearing that it will affect other household chores.

[0013] Patent Literature 1 discloses a technology that adds a margin to the expected operation time and subtracts the resulting time from the end time to set the scheduled start time in order to prevent the washing operation from ending later than the end time set by the user. As a result, even if the actual operation time is longer than the expected operation time, the scheduled start time is set taking the margin into account, making it easier to avoid the washing operation ending later than the end time set by the user.

[0014] However, in the technology disclosed in Patent Document 1, the margin time added to the estimated operation time is a time that is experimentally set in advance, for example, during the design stage of the machine depending on the laundry load or operating conditions. Therefore, with the technology disclosed in Patent Document 1, if the actual operation time is almost the same as the estimated operation time, the washing operation will end earlier than the end time set by the user by the margin time. As a result, the washed clothes will be left in the washing machine for a long time between the end of the washing operation and the end time set by the user, which will make the clothes more likely to wrinkle or develop odors.

[0015] A specific example of the above problem will be described below with reference to FIG. 1. FIG. 1 is an explanatory diagram of the specific example of the problem. FIG. 1 illustrates an example in which a user uses a dryer instead of a washing machine to dry clothes. First, (1) the user schedules a drying operation. In the example shown in FIG. 1, the user schedules a drying operation for 10:00 PM, with the desired end time set to 6:00 AM the following day. Next, (2) the dryer calculates the estimated time required for the drying operation. The estimated time is the time estimated to be required from the start to the end of the drying operation by the dryer. Here, the dryer calculates the estimated time based on the time required for the previous drying operation, similar to the technology disclosed in Patent Document 1. In the example shown in FIG. 1, the dryer calculates the estimated time to be 2 hours and 40 minutes.

[0016] Next, (3) the dryer subtracts the calculated estimated required time from the desired end time, and then (4) subtracts a predetermined margin to calculate the scheduled start time. In the example shown in Figure 1, the dryer subtracts the estimated required time of 2 hours and 40 minutes from the desired end time of 6:00 the next day, and then subtracts the predetermined margin of 1 hour and 20 minutes to calculate the scheduled start time as 2:00 the next day. As already mentioned, the predetermined margin is a time that is experimentally set in advance in accordance with, for example, the laundry load or operating conditions during the design stage of the dryer.

[0017] Then, (5) the dryer waits until the scheduled start time arrives, and (6) starts the drying operation at the scheduled start time. Then, (7) the dryer ends the drying operation when almost the same amount of time as the estimated required time has passed from the scheduled start time. In the example shown in Figure 1, the dryer ends the drying operation at 4:30 the next day, 2 hours and 30 minutes after the scheduled start time of 2:00, which is almost the same amount of time as the estimated required time.

[0018] Furthermore, (8) since users generally do not go to the location where the dryer is installed until the desired end time, the time from the end time of the drying operation to the desired end time is the time that the clothes are left in the dryer. In the example shown in Figure 1, the time that the clothes are left in the dryer is 1 hour and 30 minutes, and since the clothes are left in the dryer for a long time, they are more likely to develop wrinkles or odors.

[0019] In view of the above, the inventors have come up with the present disclosure.

[0020] Hereinafter, the embodiments will be described in detail with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component placement and connection forms, steps, step order, etc. shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components not recited in independent claims will be described as optional components.

[0021] It should be noted that the drawings are schematic diagrams and are not necessarily strict illustrations. In addition, in the drawings, substantially the same components are denoted by the same reference numerals, and overlapping descriptions may be omitted or simplified.

[0022] (Embodiment) [2. Configuration] First, the overall configuration including the control system 100 according to the embodiment will be described with reference to Fig. 2 and Fig. 3. Fig. 2 is a schematic diagram showing an example of the overall configuration including the control system 100 according to the embodiment. Fig. 3 is a block diagram showing an example of the overall configuration including the control system 100 according to the embodiment.

[0023] As shown in Fig. 2, the control system 100 according to the embodiment is realized by a server 10 and a dryer 20. The server 10 is communicably connected to a plurality of dryers 20A, 20B, 20C, ... and a plurality of terminals 30A, 30B, 30C, ... via a network N1. The network N1 is, for example, a wide area network such as the Internet, but is not limited thereto. For example, the network N1 may be a mobile phone carrier network, an access network of an Internet provider, a public access network, or the like.

[0024] In the following, except when explicitly distinguishing between the individual units, the dryers 20A, 20B, 20C, etc. will be simply referred to as "dryer 20," and the terminals 30A, 30B, 30C, etc. will be simply referred to as "terminal 30." Furthermore, in the following, the dryers 20A, 20B, 20C, etc. will be described as being the same model, but the dryers 20A, 20B, 20C, etc. do not necessarily have to be the same model. Similarly, in the following, the terminals 30A, 30B, 30C, etc. will be described as being the same model, but the terminals 30A, 30B, 30C, etc. do not necessarily have to be the same model.

[0025] In the embodiment, dryers 20A, 20B, 20C, ... are associated with terminals 30A, 30B, 30C, ..., respectively. For example, dryer 20A can communicate with terminal 30A, but cannot communicate with other terminals 30. Such association between each dryer 20 and each terminal 30 is performed by server 10. Note that the association between dryers 20 and terminals 30 may be many-to-many. For example, multiple terminals 30 owned by multiple members of a family may be associated with one dryer 20. Furthermore, multiple dryers 20 may be associated with a terminal 30 owned by one person. Alternatively, multiple terminals 30 may be associated with multiple dryers 20.

[0026] <Dryer> The dryer 20 is a device that performs processing related to clothes (hereinafter also referred to as a "clothing processing device") and performs a drying operation to dry washed clothes. In the embodiment, the dryer 20 is a device that also has a function of performing a washing operation to wash clothes and is a washing machine with a drying function, but is not limited to this. For example, the dryer 20 may only have a function of performing a drying operation.

[0027] As shown in FIG. 3, the dryer 20 includes a communication interface (hereinafter referred to as "communication I / F") 21, an input interface (hereinafter referred to as "input I / F") 22, a processor 23, a memory 24, a tank 25, a heat pump 26, a display 27, and one or more sensors 28.

[0028] The communication I / F 21 is connected to the network N1 and communicates with external devices via the network N1. Specifically, the communication I / F 21 communicates with the server 10 via the network N1. The communication I / F 21 also communicates with a corresponding terminal 30 via the network N1. For example, the communication I / F 21 of the dryer 20A communicates with a corresponding terminal 30A via the network N1.

[0029] The input I / F 22 accepts input from a user who uses the dryer 20. In the embodiment, the input I / F 22 is configured with a touch panel or one or more buttons. The input I / F 22 accepts input of operating conditions related to the operation of the dryer 20, for example. The operating conditions may include, for example, the amount of laundry to be loaded into the dryer 20, the operating mode of the dryer 20, the operating course of the dryer 20, and the end time of the operation (reserved time). In the embodiment, since the dryer 20 is a washing machine with a drying function, the operating course may include a course for performing a washing operation, a course for performing a drying operation, or a course for performing both a washing operation and a drying operation. In the embodiment, the operating mode may include, for example, a mode for operating at a standard intensity, a mode for operating at an intensity weaker than the standard intensity, or a mode for operating at an intensity stronger than the standard intensity.

[0030] Regarding the amount of laundry to be loaded into the dryer 20, the input I / F 22 may accept the amount of laundry detected by a sensor included in one or more sensors 28 (described later) instead of accepting an input by the user. For example, the processor 23 may detect the amount of laundry loaded into the tub 25 based on the load or current value of the motor 29 (described later) when the motor 29 rotates the tub 25. In this case, the one or more sensors 28 may include a sensor for detecting the load and a sensor for detecting the current value. The input I / F 22 may accept the amount of laundry detected by a weight sensor included in the one or more sensors 28.

[0031] The processor 23 executes a process for controlling processing related to laundry by executing a computer program stored in the memory 24. In the embodiment, the processor 23 executes a process for controlling a washing operation and a process for controlling a drying operation.

[0032] Specifically, processor 23 controls the rotation of tub 25, into which the clothes to be treated are placed, thereby performing a washing operation to wash the clothes placed in tub 25. More specifically, dryer 20 includes motor 29 in addition to tub 25, and processor 23 controls the operation (rotation) of motor 29 to rotate tub 25 and perform a washing operation. Note that motor 29 is a specific example of an actuator that rotates tub 25, and may be replaced with a component other than motor 29 as long as it has the function of rotating tub 25. Processor 23 also controls tub 25 and heat pump 26, which takes in air from tub 25, generates hot air, and sends it into tub 25, thereby performing a drying operation to dry the washed clothes in tub 25. Processor 23 also performs a washing operation or a drying operation in accordance with operating conditions received via input I / F 22 (or input I / F 32 of terminal 30).

[0033] The processor 23 also executes the washing or drying operation based on information detected by each of one or more sensors 28 included in the dryer 20. The one or more sensors 28 include, for example, a weight sensor that detects the weight of the clothes (cloth amount) in the tub 25, a temperature sensor that detects the temperature of the air taken in from the tub 25 to the heat pump 26 (suction temperature), a temperature sensor that detects the temperature of the air sent from the heat pump 26 to the tub 25 (discharge temperature), and a humidity sensor that detects the humidity in the tub 25. The processor 23 executes the drying operation, for example, from the start of the drying operation until a time based on the weight detected by the weight sensor has elapsed. During the drying operation, the processor 23 also sequentially adjusts the time for executing the drying operation based on the suction temperature and discharge temperature detected by each temperature sensor or the humidity detected by the humidity sensor.

[0034] The memory 24 is a storage device that stores computer programs executed by the processor 23 and information necessary for implementing various functions. The memory 24 is realized by a semiconductor memory such as a non-volatile memory such as a read-only memory (ROM) or a volatile memory such as a random access memory (RAM). The memory 24 may be realized as an internal memory of the processor 23, rather than as an external memory of the processor 23.

[0035] The display 27 is, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and displays and presents various information to the user. In this embodiment, the display 27 also serves as a touch panel display that constitutes the input I / F 22.

[0036] <Terminal> The terminal 30 is, for example, a smartphone carried by a user who uses the dryer 20. Note that the terminal 30 is not limited to a smartphone, and may be an information processing terminal such as a tablet terminal or a laptop or desktop personal computer.

[0037] As shown in FIG. 3, the terminal 30 includes a communication I / F 31, an input I / F 32, a processor 33, a memory 34, and a display 35.

[0038] The communication I / F 31 is connected to the network N1 and communicates with external devices via the network N1. Specifically, the communication I / F 31 communicates with the server 10 via the network N1. The communication I / F 31 also communicates with the corresponding dryer 20 via the network N1. For example, the communication I / F 31 of the terminal 30A communicates with the corresponding dryer 20A via the network N1.

[0039] The input I / F 32 accepts input from a user. In this embodiment, the input I / F 32 is configured with a touch panel or one or more buttons. Like the input I / F 22 of the dryer 20, the input I / F 32 accepts input of operating conditions, for example, when starting operation of the dryer 20. In other words, the input I / F 32 accepts input when the user remotely operates the dryer 20. The processor 33 generates control information based on the input information accepted by the input I / F 32 and transmits the control information to the corresponding dryer 20 via the communication I / F 31 and the network N1.

[0040] The processor 33 executes computer programs stored in the memory 34 to perform processes for realizing various functions of the terminal 30 .

[0041] The memory 34 is a storage device that stores computer programs executed by the processor 33 and information necessary for implementing various functions. The memory 34 is realized by a semiconductor memory such as a non-volatile memory such as a ROM or a volatile memory such as a RAM. The memory 34 may be realized as an internal memory of the processor 33 instead of an external memory of the processor 33.

[0042] The display 35 is, for example, a liquid crystal display or an organic EL display, and displays and presents various information to the user. In this embodiment, the display 35 also serves as a touch panel display that constitutes the input I / F 32.

[0043] <Server> As shown in FIG. 3 , the server 10 includes a communication I / F 11 , a processor 12 , and a memory 13 .

[0044] The communication I / F 11 is connected to the network N1 and communicates with external devices via the network N1. Specifically, the communication I / F 11 communicates individually with each dryer 20 via the network N1. The communication I / F 11 also communicates individually with each terminal 30 via the network N1.

[0045] The processor 12 executes computer programs stored in the memory 13 to perform processes for realizing various functions of the server 10. In the embodiment, the processor 12 executes processes for realizing an acquisition unit 121, a parameter calculation unit 122, and a time calculation unit 123.

[0046] The acquisition unit 121 acquires operation data transmitted from each dryer 20 via the network N1. The operation data is data related to the operation performed by the dryer 20, and includes information detected by each of one or more sensors 28 of the dryer 20 (such as laundry amount, suction temperature, discharge temperature, or humidity), information indicating the operation mode, information indicating the operation course, the actual operation time, and the difference between the actual operation time and an estimated operation time (described later). The acquisition unit 121 acquires operation data from the dryer 20 each time the dryer 20 performs an operation. Note that the acquisition unit 121 may acquire the operation data from the dryer 20 periodically, for example, in a lump.

[0047] The operating data acquired by the acquisition unit 121 is processed into a data format that can be stored in the memory 13, and then stored in an operating data storage unit 131 (described later) of the memory 13 in a form linked to the ID (identifier) ​​of the dryer 20 that sent the data and the date and time of transmission. Note that if the acquired operating data indicates an abnormal value or is missing data, the acquisition unit 121 may perform exception processing, such as not storing the data in the memory 13.

[0048] The parameter calculation unit 122 calculates, for each dryer 20 , parameters used to calculate the estimated required time and the leeway time, based on the operation data acquired by the acquisition unit 121 .

[0049] Here, the estimated required time is the estimated time required for a clothing processing device such as the dryer 20 to complete a clothing processing operation from the start to the end.

[0050] The margin time is a time set so that the processing of the clothes will finish before the end time set by the user even if the actual time required for the processing of the clothes exceeds the estimated required time. Here, the margin time is a time set so that the drying operation will finish before the end time set by the user even if the actual time required for the drying operation of the dryer 20 exceeds the estimated required time.

[0051] In the embodiment, the parameter calculation unit 122 performs statistical processing based on all past operation data or operation data for a predetermined period of time in the past, to calculate the above parameters for each dryer 20. Specifically, the parameter calculation unit 122 calculates, for each dryer 20, the average value μ and standard deviation σ of the time required for actual operation.

[0052] The parameter calculation unit 122 may also execute a process of updating the margin coefficient a based on the operation data, as will be described later. The parameter calculation unit 122 may calculate the average value μ and the standard deviation σ for each operation condition of the dryer 20, not just for each dryer 20, and may update the margin coefficient a for each operation condition of the dryer 20.

[0053] The mean value μ and standard deviation σ calculated by the parameter calculation unit 122 are stored in a parameter storage unit 132 (described later) of the memory 13. The margin coefficient a is also stored in the parameter storage unit 132 of the memory 13.

[0054] The time calculation unit 123 calculates the estimated required time and the margin time using the mean value μ and standard deviation σ calculated by the parameter calculation unit 122 and the margin coefficient a. Specifically, as shown in FIG. 4 , the time calculation unit 123 calculates the mean value μ as the estimated required time and calculates the margin time by multiplying the standard deviation σ by the margin coefficient a. Here, the margin coefficient a is assumed to be "3." FIG. 4 is an explanatory diagram of the estimated required time and the margin time. In FIG. 4 , it is assumed that the required time for the drying operation follows a normal distribution. Under the above assumption, calculating the margin time by multiplying the standard deviation σ by the margin coefficient a = 3 means that the margin coefficient a is set so that approximately 99.7% of the drying operation will be completed by the end time set by the user, i.e., so that the delay rate is kept below 0.3%.

[0055] In the embodiment, the margin coefficient a is initially set to "3." However, it may be updated based on past operation data, specifically, based on the difference between the actual end time and the set end time of the clothing processing. For example, a predetermined value (e.g., 0.1) may be added to the margin coefficient a each time a delay occurs between the set end time and the actual end time of the clothing processing. Also, for example, a predetermined value (e.g., 0.1) may be subtracted from the margin coefficient a each time an early end occurs, in which the actual end time of the clothing processing is one hour or more earlier than the set end time. The margin coefficient a may be updated at the same time as the mean value μ and the standard deviation σ are updated.

[0056] The margin coefficient a may also be manually adjusted by, for example, a user using the dryer 20. FIG. 5 is a diagram illustrating an example of how the margin coefficient a is set. FIG. 5 illustrates a setting screen displayed on the display 35 of the terminal 30. The setting screen displays a knob A1 that the user can slide. For example, if the margin coefficient a is set to its initial value when the knob A1 is positioned at the center, and the user slides the knob A1 in the "avoid early termination" direction (to the left in FIG. 5), the margin coefficient a is set to a value smaller than the initial value depending on the amount of sliding. In this case, the user can set the margin time in the drying operation to be shorter. In addition, for example, if the user slides the knob A1 in the "avoid delay" direction (to the right in FIG. 5), the margin coefficient a is set to a value larger than the initial value depending on the amount of sliding. In this case, the user can set the margin time in the drying operation to be longer.

[0057] The memory 13 is a storage device that stores computer programs executed by the processor 12 and information necessary for implementing various functions. The memory 13 is realized, for example, by a semiconductor memory. Note that the memory 13 may be realized as an internal memory of the processor 12, rather than as an external memory of the processor 12.

[0058] In this embodiment, the memory 13 has two storage areas: an operating data storage unit 131 and a parameter storage unit 132. Note that the memory 13 may have two independent memories: a memory that stores the operating data storage unit 131 and a memory that stores the parameter storage unit 132.

[0059] The operation data storage unit 131 stores past operation data for each laundry processing device (here, for each dryer 20). FIG. 6 is a diagram showing an example of data stored in the operation data storage unit. In the example shown in FIG. 6, the operation data includes an "appliance ID," an "operation start time" when the operation actually started, an "operation end time" when the operation actually ended, an "operation program," an "operation mode (here, drying mode)," a "laundry load," an "actual operation time (here, actual drying time)" that is the time actually required for the operation, a "reservation status" that indicates whether the user has set an end time and reserved the operation, and a "reservation delay time" that indicates the difference between the end time set by the user and the time the operation actually ended. The operation data may also include information detected by one or more sensors 28.

[0060] The parameter storage unit 132 stores the mean value μ, standard deviation σ, and margin coefficient a calculated by the parameter calculation unit 122 as parameters. FIG. 7 is a diagram showing an example of data stored in the parameter storage unit 132. FIG. 7A shows an example of a case where parameters are stored for each laundry processing device (here, for each dryer 20). In the example shown in FIG. 7A, the data stored in the parameter storage unit 132 includes an "appliance ID," an "mean value μ," a "standard deviation σ," a "margin coefficient a," and a "last update date and time" indicating the date and time when the parameters were last updated. FIG. 7B shows an example of a case where parameters are stored for each operating condition (here, the operating program and laundry load) of a laundry processing device (here, the dryer 20). In the example shown in FIG. 7B, the data stored in the parameter storage unit 132 includes an "appliance ID," an "operating program," a "laundry load," an "mean value μ," a "standard deviation σ," a "margin coefficient a," and a "last update date and time."

[0061] 3. Calculation of Average Value and Standard Deviation Below, an example of calculation of the average value μ and standard deviation σ in the control system 100 according to the embodiment will be described. The following description focuses on processing for one of the clothing processing devices (here, the dryer 20). The calculation process of the average value μ and standard deviation σ described below is executed periodically (for example, once a day) as a batch process for all the clothing processing devices.

[0062] <First Calculation Example> The first calculation example is an example in which the mean value μ and the standard deviation σ are calculated regardless of the operating conditions of the dryer 20. Fig. 8 is a flowchart showing the first calculation example of the mean value μ and the standard deviation σ in the control system 100 according to the embodiment.

[0063] First, the parameter calculation unit 122 acquires all past operation data of the target dryer 20 by reading them from the operation data storage unit 131, or operation data for a predetermined period of time in the past (step S101). Next, the parameter calculation unit 122 calculates the mean value μ and the standard deviation σ by performing statistical processing based on all of the acquired past operation data or operation data for a predetermined period of time in the past (step S102). Then, the parameter calculation unit 122 associates the calculated mean value μ and standard deviation σ with the device ID of the target dryer 20 and writes them into the memory 13 (here, the parameter storage unit 132) (step S103).

[0064] <Second Calculation Example> The second calculation example is an example in which the mean value μ and the standard deviation σ are calculated for each operating condition of the dryer 20. Fig. 9 is a flowchart showing the second calculation example of the mean value μ and the standard deviation σ in the control system 100 according to the embodiment.

[0065] First, the parameter calculation unit 122 acquires all past operating data or operating data for a predetermined period of time of the target dryer 20 by reading it from the operating data storage unit 131 (step S201). Next, the parameter calculation unit 122 divides the acquired all past operating data or operating data for a predetermined period of time by operating condition (step S202). Next, the parameter calculation unit 122 selects one of the operating conditions and performs statistical processing based on the operating data for the selected operating condition to calculate the mean value μ and the standard deviation σ (step S203).

[0066] If there are any unselected operating conditions remaining (step S204: No), the parameter calculation unit 122 repeats steps S203 and S204. On the other hand, if there are no unselected operating conditions remaining, that is, if all operating conditions have been selected (step S204: Yes), the parameter calculation unit 122 associates the calculated average values ​​μ and standard deviations σ of all operating conditions with the device ID of the dryer 20 to be processed and writes them into the memory 13 (here, the parameter storage unit 132) (step S205).

[0067] <Third Calculation Example> The third calculation example is an example of calculating the mean value μ and the standard deviation σ when there is insufficient past operation data for the dryer 20 to be processed. Like the first calculation example, the third calculation example is an example of calculating the mean value μ and the standard deviation σ regardless of the operation conditions of the dryer 20. However, like the second calculation example, the mean value μ and the standard deviation σ may be calculated for each operation condition of the dryer 20. Figure 10 is a flowchart showing the third calculation example of the mean value μ and the standard deviation σ in the control system 100 according to the embodiment.

[0068] First, the parameter calculation unit 122 acquires all past operation data of the target dryer 20 or operation data for a predetermined period of time by reading it from the operation data storage unit 131 (step S301). If there is no past operation data of the target dryer 20 (step S302: Yes), the parameter calculation unit 122 sets the mean value μ, standard deviation σ, and degree of constraint n to default values ​​(here, the mean value μ0, standard deviation σ0, and degree of constraint n0) (step S303).

[0069] Here, the degree of constraint n represents the degree to which the updated mean value μ and standard deviation σ are constrained to the mean value μ and standard deviation σ before updating when the mean value μ and standard deviation σ are updated in step S307, which will be described later. That is, the smaller the degree of constraint n, the greater the amount of variation in the updated mean value μ and standard deviation σ from the mean value μ and standard deviation σ before updating, and the greater the degree of constraint n, the smaller the amount of variation in the updated mean value μ and standard deviation σ from the mean value μ and standard deviation σ after updating. The default value n0 of the degree of constraint n is set to a relatively small value.

[0070] The default value μ0 of the mean value μ is set to the average value of the mean values ​​μ calculated for all dryers 20, including the dryer 20 to be treated. Similarly, the default value σ0 of the standard deviation σ is set to the average value of the standard deviation σ calculated for all dryers 20, including the dryer 20 to be treated.

[0071] For example, if there is past data on the dryer 20 that the user used before using the dryer 20 to be processed, the mean value μ and standard deviation σ contained in the past data on the dryer 20 that the user used in the past may be set to the default value μ0 for the mean value μ and the default value σ0 for the standard deviation σ.

[0072] Then, the parameter calculation unit 122 writes the set average value μ (here, the default value μ0), standard deviation σ (here, the default value σ0), and degree of constraint n (here, the default value n0) into the memory 13 (here, the parameter storage unit 132) by linking them to the equipment ID of the dryer 20 to be processed (step S304).

[0073] If past operating data for the target dryer 20 is available, i.e., if the target dryer 20 has actually started to be used (step S302: No), and if the operating data is new (step S305: Yes), the parameter calculation unit 122 reads the previous mean value μ, standard deviation σ, and degree of constraint n from the parameter storage unit 132 (step S306). Note that the "new operating data" here refers to operating data obtained by operating the dryer 20 and that has not yet been used to calculate the mean value μ and standard deviation σ. The parameter calculation unit 122 then updates the mean value μ and standard deviation σ based on the new operating data using an algorithm capable of sequential updates, such as the Welford algorithm or the Bayesian estimation algorithm (step S307). In step S307, the degree of constraint n is updated to a larger value each time the mean value μ and standard deviation σ are updated. Then, the parameter calculation unit 122 associates the updated mean value μ, standard deviation σ, and degree of constraint n with the device ID of the dryer 20 to be processed and writes them in the parameter storage unit 132 (step S304). Note that if there is no new operating data for the dryer 20 to be processed (step S305: No), the parameter calculation unit 122 does not update the mean value μ, standard deviation σ, and degree of constraint n.

[0074] FIG. 11 is a schematic diagram showing the updating of the mean value μ and the standard deviation σ in the third calculation example. In FIG. 11, the rightmost normal distribution represents the case where the number of times the dryer 20 to be treated has been operated is 0, and the leftmost normal distribution represents the latest mean value μ and standard deviation σ. As shown in FIG. 11, the mean value μ and standard deviation σ are updated as the number of times the dryer 20 to be treated has been operated increases, and are optimized for the dryer 20 to be treated. Note that after the number of times the dryer 20 to be treated has been operated reaches a predetermined value, the mean value μ and standard deviation σ may be calculated using the first or second calculation example.

[0075] [4. Operation] The operation of the control system 100 according to the embodiment will be described below. The following operation is started when the user turns on the power of the dryer 20 by operating the dryer 20 or the terminal 30. The following describes a case where the user reserves a drying operation as a process related to clothes. The control system 100 may execute any of the first to third operation examples shown below.

[0076] <First Operation Example> The first operation example is an example in which a drying operation of the dryer 20 is performed by setting a scheduled start time regardless of whether the user has set an operation course, that is, regardless of the operating conditions. Fig. 12 is a flowchart showing the first operation example of the control system 100 according to the embodiment. Fig. 12(a) shows the operation of the dryer 20, and Fig. 12(b) shows the operation of the server 10.

[0077] First, the dryer 20 acquires the estimated required time and the margin time of the drying operation (step S401 in FIG. 12A). Specifically, the dryer 20 transmits a request signal to the server 10 requesting the estimated required time and the margin time (step S401A in FIG. 12A). The request signal includes at least the device ID information of the dryer 20 that sent the request signal.

[0078] When the time calculation unit 123 of the server 10 receives the request signal, it acquires the mean value μ and standard deviation σ associated with the device ID of the dryer 20 that transmitted the request signal by reading them from the memory 13 (here, the parameter storage unit 132) (step S501 in FIG. 12B). At this time, the time calculation unit 123 also acquires the leeway coefficient a associated with the device ID of the dryer 20 that transmitted the request signal by reading them from the parameter storage unit 132. Next, the time calculation unit 123 calculates the estimated required time and the leeway time based on the acquired mean value μ and standard deviation σ (step S502 in FIG. 12B). Specifically, the time calculation unit 123 calculates the acquired mean value μ as the estimated required time, and calculates the leeway time by multiplying the acquired standard deviation σ by the leeway coefficient a. Then, the time calculation unit 123 outputs the estimated required time and the margin time by transmitting a signal including the calculated estimated required time and margin time to the dryer 20 that sent the signal (step S503 in FIG. 12B). This allows the dryer 20 to receive and acquire the estimated required time and margin time for the drying operation (step S401 in FIG. 12A).

[0079] Next, the dryer 20 displays the settable time on the display 27 of the dryer 20 (step S402 in (a) of FIG. 12). Here, the settable time refers to the range of end times that the user can set, taking into account the total time of the acquired estimated required time and the margin time. The minimum settable time is the time obtained by adding the total time to the current time. For example, if the current time is 17:40 and the total time is 4 hours, the minimum settable time is 21:40. Furthermore, the maximum settable time is the time obtained by adding a predetermined time (e.g., 1 day) to the current time. For example, if the current time is 17:40 and the predetermined time is 1 day, the maximum settable time is 17:40 the next day.

[0080] Next, the dryer 20 acquires the end time (step S403 in FIG. 12A). Specifically, the input I / F 22 of the dryer 20 accepts the end time setting input by the user within the settable time range, thereby acquiring the end time.

[0081] Next, the dryer 20 measures the amount of laundry (step S404 in FIG. 12A). Specifically, the dryer 20 measures the amount of laundry of the clothes placed in the tub 25 based on the load or current value of the motor 29 when the motor 29 rotates the tub 25. The dryer 20 may also measure the amount of laundry of the clothes in the tub 25 based on the weight of the clothes in the tub 25 detected by a weight sensor.

[0082] Next, the dryer 20 sets a scheduled start time, which is a scheduled time to start the drying operation (step S405 in FIG. 12A). Specifically, the dryer 20 calculates and sets the scheduled start time by subtracting the total time of the estimated required time and the leeway time from the end time set by the user.

[0083] The dryer 20 then waits until the scheduled start time is reached (step S406 in FIG. 12(a)). If the user resets the end time or changes the end time before the scheduled start time is reached (step S409 in FIG. 12(a): No), the dryer 20 subtracts the total of the estimated required time and the leeway time from the changed end time to calculate and reset the scheduled start time (step S408 in FIG. 12(a)). If the end time remains unchanged before the scheduled start time is reached (step S407 in FIG. 12(a): No), the dryer 20 waits until the scheduled start time is reached.

[0084] Thereafter, when the scheduled start time arrives (step S409 in FIG. 12A: Yes), the dryer 20 executes the reserved drying operation (step S410 in FIG. 12A). As a result, the drying operation ends approximately at the end time set by the user.

[0085] <Second Operation Example> The second operation example is an example in which the user sets an operation course, that is, sets a scheduled start time for each operation condition and performs drying operation of the dryer 20. Fig. 13 is a flowchart showing the second operation example of the control system 100 according to the embodiment. (a) of Fig. 13 shows the operation of the dryer 20, and (b) of Fig. 13 shows the operation of the server 10.

[0086] First, the dryer 20 acquires an operating course for the drying operation (step S601 in FIG. 13A). Specifically, the input I / F 22 of the dryer 20 accepts an operating course setting input by a user, whereby the dryer 20 acquires the operating course.

[0087] Next, the dryer 20 acquires the estimated required times and margin times for all laundry amount conditions of the acquired operating course (step S602 in FIG. 13A). Specifically, the dryer 20 transmits a request signal to the server 10 requesting the estimated required times and margin times for all laundry amount conditions of the acquired operating course (step S602A in FIG. 13A). Here, the laundry amount conditions include three conditions according to laundry amounts: a first condition in which the laundry amount is a standard amount, a second condition in which the laundry amount is less than the standard amount, and a third condition in which the laundry amount is more than the standard amount. Of course, the laundry amount conditions may include four or more conditions according to laundry amounts.

[0088] When the time calculation unit 123 of the server 10 receives the request signal, it reads the mean value μ and standard deviation σ for all laundry weight conditions associated with the device ID of the sending dryer 20 from the memory 13 (here, the parameter storage unit 132) to obtain them (step S701 in FIG. 13B). At this time, the time calculation unit 123 also reads the margin coefficient a for all laundry weight conditions associated with the device ID of the sending dryer 20 from the parameter storage unit 132 to obtain them. Next, the time calculation unit 123 calculates the estimated required time and margin time for each laundry weight condition based on the mean value μ and standard deviation σ for each laundry weight condition (step S702 in FIG. 13B). Specifically, the time calculation unit 123 calculates the estimated required time using the obtained mean value μ and calculates the margin time by multiplying the obtained standard deviation σ by the margin coefficient a for each laundry weight condition. The time calculation unit 123 then outputs the estimated required time and margin time for each laundry load condition by transmitting a signal including the calculated estimated required time and margin time for each laundry load condition to the dryer 20 (step S703 in FIG. 13B). This allows the dryer 20 to receive and acquire the estimated required time and margin time for all laundry load conditions of the acquired operating course (step S602 in FIG. 13A).

[0089] Next, the dryer 20 selects the longest total of the estimated required time and the allowance time from the totals of the estimated required time and the allowance time for each of the acquired laundry amount conditions (step S603 in FIG. 13A).

[0090] Furthermore, if there are external conditions that affect the execution time of the laundry processing (here, the drying operation), the dryer 20 calculates a correction time based on the external conditions (step S604 in FIG. 13A). Here, the external conditions include, for example, the air temperature in the tub 25 detected by a temperature sensor, or whether or not a filter used in the drying operation is clogged. For example, if there is an external condition that the air temperature in the tub 25 is lower than a threshold, the dryer 20 calculates the correction time to be 10 minutes. Also, if there is an external condition that the filter is clogged, the dryer 20 calculates the correction time to be 20 minutes. Note that if there are no external conditions, the dryer 20 calculates the correction time to be 0 minutes in step S604.

[0091] Next, the dryer 20 displays the settable time on the display 27 of the dryer 20 (step S605 in FIG. 13A). Here, the minimum settable time is the time obtained by adding the total time of the selected estimated required time, the margin time, and the calculated correction time to the current time. The maximum settable time is the time obtained by adding a predetermined time (e.g., one day) to the current time.

[0092] Next, the dryer 20 acquires the end time (step S606 in FIG. 13A). Specifically, the input I / F 22 of the dryer 20 accepts the end time setting input by the user within the settable time range, thereby acquiring the end time.

[0093] Next, the dryer 20 measures the amount of laundry (step S607 in FIG. 13A). Specifically, the dryer 20 measures the amount of laundry of the clothes placed in the tub 25 based on the load or current value of the motor 29 when the motor 29 rotates the tub 25. The dryer 20 may also measure the amount of laundry of the clothes in the tub 25 based on the weight of the clothes in the tub 25 detected by a weight sensor.

[0094] Next, the dryer 20 sets the scheduled start time, which is the scheduled time to start the drying operation (step S608 in FIG. 13A). Specifically, the dryer 20 selects the estimated required time and the margin time corresponding to the laundry amount condition according to the measured laundry amount from all laundry amount conditions. The dryer 20 then calculates the total time by adding the correction time to the selected estimated required time and margin time, and calculates and sets the scheduled start time by subtracting the calculated total time from the end time set by the user.

[0095] The dryer 20 then waits until the scheduled start time arrives (step S609 in FIG. 13A). Note that the processing performed by the dryer 20 while it is waiting is the same as steps S407 to S409 in the first calculation example, and therefore will not be described here. After that, when the scheduled start time arrives, the dryer 20 executes the reserved drying operation (step S610 in FIG. 13A). As a result, the drying operation ends approximately at the end time set by the user.

[0096] <Third Operation Example> Similar to the second operation example, the third operation example is an example in which the user sets an operation course, that is, sets a scheduled start time for each operation condition, and performs drying operation of the dryer 20. However, unlike the second operation example, the third operation example measures the laundry amount before obtaining the end time. Fig. 14 is a flowchart showing the third operation example of the control system 100 according to the embodiment. Fig. 14(a) shows the operation of the dryer 20, and Fig. 14(b) shows the operation of the server 10.

[0097] First, the dryer 20 acquires an operating course for the drying operation (step S801 in FIG. 14A). Specifically, the input I / F 22 of the dryer 20 accepts an operating course setting input by a user, thereby acquiring the operating course.

[0098] Next, the dryer 20 measures the amount of laundry (step S802 in FIG. 14A). Specifically, the dryer 20 measures the amount of laundry of the clothes placed in the tub 25 based on the load or current value of the motor 29 when the motor 29 rotates the tub 25. The dryer 20 may also measure the amount of laundry of the clothes in the tub 25 based on the weight of the clothes in the tub 25 detected by a weight sensor.

[0099] Next, the dryer 20 acquires the estimated required time and the margin time under predetermined conditions (step S803 in FIG. 14A). Here, the predetermined conditions include the acquired operating course and the measured laundry amount. Specifically, the dryer 20 transmits a request signal to the server 10 requesting the estimated required time and the margin time under the predetermined conditions (step S803A in FIG. 14A).

[0100] When the time calculation unit 123 of the server 10 receives the request signal, it acquires the mean value μ and standard deviation σ for the predetermined conditions associated with the device ID of the dryer 20 that transmitted the request signal by reading them from the memory 13 (here, the parameter storage unit 132) (step S901 in FIG. 14B). At this time, the time calculation unit 123 also acquires the margin coefficient a for the predetermined conditions associated with the device ID of the dryer 20 that transmitted the request signal by reading them from the parameter storage unit 132. Next, the time calculation unit 123 calculates the estimated required time and margin time under the predetermined conditions based on the acquired mean value μ and standard deviation σ for the predetermined conditions (step S902 in FIG. 14B). Specifically, the time calculation unit 123 calculates the acquired mean value μ as the estimated required time, and calculates the margin time by multiplying the acquired standard deviation σ by the margin coefficient a. Then, the time calculation unit 123 outputs the estimated required time and the margin time under the predetermined conditions by transmitting a signal including the calculated estimated required time and margin time under the predetermined conditions to the dryer 20 that sent the signal (step S903 in FIG. 14B). This allows the dryer 20 to receive and acquire the estimated required time and margin time under the predetermined conditions (step S803 in FIG. 14A).

[0101] Next, if an external condition exists, the dryer 20 calculates the correction time based on the external condition (step S804 in FIG. 14A). If an external condition does not exist, the dryer 20 calculates the correction time to be 0 minutes in step S804.

[0102] Next, the dryer 20 displays the settable time on the display 27 of the dryer 20 (step S805 in FIG. 14A). Here, the minimum settable time is the time obtained by adding the total time of the acquired estimated required time, the margin time, and the calculated correction time to the current time. The maximum settable time is the time obtained by adding a predetermined time (e.g., one day) to the current time.

[0103] Next, the dryer 20 acquires the end time (step S806 in FIG. 14A). Specifically, the input I / F 22 of the dryer 20 accepts the end time setting input by the user within the settable time range, thereby acquiring the end time.

[0104] Next, the dryer 20 sets a scheduled start time, which is a scheduled time to start the drying operation (step S807 in FIG. 14A). Specifically, the dryer 20 calculates a total time by adding a correction time to the estimated required time and the surplus time, and calculates and sets the scheduled start time by subtracting the calculated total time from the end time set by the user.

[0105] The dryer 20 then waits until the scheduled start time arrives (step S808 in FIG. 14A). Note that the processing performed by the dryer 20 while it is waiting is the same as steps S407 to S409 in the first calculation example, and therefore will not be described here. After that, when the scheduled start time arrives, the dryer 20 executes the reserved drying operation (step S809 in FIG. 14A). As a result, the drying operation ends approximately at the end time set by the user.

[0106] In the above-described first to third operation examples, some of the operations of dryer 20 may be executed by terminal 30. For example, the process of displaying the settable time on display 27 of dryer 20 may be replaced by the process of displaying the settable time on display 35 of terminal 30. Furthermore, for example, the process of input I / F 22 of dryer 20 accepting setting input of an operating course or an end time may be replaced by the process of input I / F 32 of terminal 30 accepting setting input of an operating course or an end time.

[0107] [5. Display Examples] The following describes operation screens for operating a laundry processing device (here, the dryer 20). Note that, although first to fifth display examples of the operation screens displayed on the display 27 of the dryer 20 are described below, the operation screens described below may also be displayed on the display 35 of the terminal 30.

[0108] <First Display Example> Fig. 15 is a diagram showing a first display example of the dryer 20 according to the embodiment. Fig. 15(a) shows an operation screen displayed on the display 27 when the power of the dryer 20 is turned on. The operation screen displays an area A2 for inputting an operation course of the dryer 20, an area A3 for inputting an operation mode of the dryer 20, and an area A4 for reserving the operation of the dryer 20 (setting an end time). The operation screen also displays an area A5 for instructing the dryer 20 to perform a drying operation without reserving it. When reserving a drying operation, the user selects area A2 to input an operation course, selects area A3 to input an operation mode, and selects area A4 to input an end time. When starting the drying operation of the dryer 20 without reserving it, the user selects area A5.

[0109] FIG. 15B shows an operation screen that is displayed on the display 27 when the user selects area A4. The operation screen includes area A6, which displays the settable time, and area A7, which indicates that the end time setting is complete. In the example shown in FIG. 15B, area A6 displays a character string indicating that the settable time is "21:40 today to 14:30 tomorrow." The user inputs the end time in area A6 and then sets the end time by selecting area A7. In the example shown in FIG. 15B, the user specifies the end time as "21:40 today." The user may also specify the end time by directly entering numbers in area A6.

[0110] FIG. 15C shows an operation screen displayed on the display 27 when the user sets an end time. This operation screen differs from the operation screen shown in FIG. 15A in that, instead of area A4, area A8 is displayed, displaying the set end time of the dryer 20, and instead of area A5, area A9 is displayed, allowing the user to instruct the dryer 20 to schedule a drying operation. The user confirms that the end time has been set by looking at area A8 and then selects area A9. This causes the dryer 20 to set a scheduled start time and wait until the set scheduled start time. If the operating program and operating mode have already been transmitted to the server 10, the dryer 20 transmits the set end time to the server 10. On the other hand, if the operating program and operating mode have not yet been transmitted to the server 10, the dryer 20 transmits the set end time, operating program, and operating mode to the server 10. The timing for transmitting the set operating program and operating mode to the server 10 may be the same as or different from the timing for transmitting the set end time to the server 10. Then, when the scheduled start time arrives, the dryer 20 performs the drying operation.

[0111] <Second Display Example> Fig. 16 is a diagram showing a second display example of the dryer 20 according to the embodiment. Fig. 16(a) shows an operation screen that is displayed on the display 27 when a user reserves a drying operation of the dryer 20. The operation screen displays an area A10 indicating that the drying operation has been reserved and an area A11 indicating that the end time can be changed. The end time can be changed, for example, up until the drying operation starts. Area A11 may also display a deadline by which the end time can be changed. The operation screen also displays an area A12 for instructing the user to cancel the reservation of the drying operation and an area A13 for instructing the user to start the drying operation regardless of the reservation of the drying operation. If the user wants to change the end time, he or she selects area A11.

[0112] 16(b) shows an operation screen that is displayed on the display 27 when the user selects area A11. This operation screen displays area A14, which displays the available settable time, and area A15, which indicates that the end time setting has been completed. In the example shown in FIG. 16(b), area A14 displays a character string indicating that the available settable time is "17:50 today to 14:30 tomorrow." Here, area A14 may display the available settable time that is recalculated based on the reselected estimated required time and leeway time, for example, when the estimated required time and leeway time are reselected after measuring the laundry amount, as in the second operation example.

[0113] The user inputs the end time in area A14, and then selects area A15 to reset the end time. In the example shown in FIG. 16B, the user specifies the end time as "17:50 today." This causes the dryer 20 to reset the scheduled start time based on the reset end time and wait until the reset scheduled start time. The dryer 20 then performs the drying operation when the scheduled start time arrives.

[0114] <Third Display Example> Fig. 17 is a diagram showing a third display example of dryer 20 according to the embodiment. Fig. 17(a) shows an operation screen that is displayed on display 27 when the user sets the end time. Fig. 17(a) differs from Fig. 15(b) of the first display example in that area A16, which can be selected when the user wants to end the drying operation earlier, is also displayed. The user selects area A16 when they want to set the end time earlier than the settable time displayed in area A6.

[0115] 17(b) shows an operation screen displayed on the display 27 when the user selects area A16. The operation screen shows that the dryer 20 is measuring the laundry amount. FIG. 17(c) shows an operation screen displayed on the display 27 after the dryer 20 has measured the laundry amount.

[0116] Fig. 18 is a flowchart showing part of the operation of the dryer 20 according to the embodiment in the third display example. The flowchart shown in Fig. 18 shows the operation of the dryer 20 executed between step S605 and step S606 in the second operation example (see Fig. 13) described above. This operation is executed when the user selects area A16 as described above. Note that when this operation is executed, the dryer 20 does not execute step S607 because the laundry amount is measured in step S605A, which will be described later.

[0117] 18 , the dryer 20 measures the amount of laundry placed in the tub 25 based on, for example, the load or current value of the motor 29 when the motor 29 rotates the tub 25 (step S605A). Alternatively, the dryer 20 may measure the amount of laundry in the tub 25 based on the weight of the laundry in the tub 25 detected by a weight sensor. The dryer 20 then selects the total of the estimated required time and the leeway time corresponding to the measured amount of laundry (step S605B), recalculates the available time based on the selected total of the estimated required time and the leeway time, and redisplays the calculated available time on the display 27 (step S605C). The operation screen displays an area A17 in which the recalculated available time is displayed, and an area A18 for indicating that the end time setting has been completed.

[0118] In the example shown in FIG. 17C , area A17 displays text indicating that the available time is "17:30 today to 14:30 tomorrow" and that the measured laundry volume is "normal" (i.e., a standard amount). In other words, in the example shown in FIG. 17C , the total of the estimated required time and leeway time selected based on the measured actual laundry volume is shorter than the total of the estimated required time and leeway time selected assuming the maximum laundry volume. This allows the end time to be set earlier than the previous available time. The user inputs a specified end time in area A17 and then selects area A18 to set the end time again. In the example shown in FIG. 17C , the user specifies the end time as "17:30 today." The dryer 20 then sets the scheduled start time based on the set end time and waits until the scheduled start time. The dryer 20 then performs the drying operation when the scheduled start time is reached.

[0119] <Fourth Display Example> Fig. 19 is a diagram showing a fourth display example of dryer 20 according to an embodiment. Fig. 19(a) shows areas A6, A16, and A7, similar to Fig. 17(a) of the third display example. As in the third display example, the user selects area A16 when he or she wants to set the end time earlier than the settable time displayed in area A6.

[0120] 19(b) shows the operation screen displayed on the display 27 when the user selects area A16. The operation screen displays area A19, which the user selects when the amount of laundry placed in the tub 25 is less than the standard amount, area A20, which the user selects when the amount of laundry is the standard amount, and area A21, which the user selects when the amount of laundry is greater than the standard amount. The operation screen also displays a message indicating that if more laundry than the recommended amount is placed in the tub 25, the drying operation may not finish by the set time (end time). The user selects one of areas A19, A20, and A21 depending on the amount of laundry placed in the tub 25.

[0121] Figure 19(c) shows the operation screen displayed on display 27 when the user selects any one of areas A19, A20, and A21. The example shown in Figure 19(c) shows the operation screen when the user selects area A20, i.e., when the standard amount of laundry is loaded into tub 25. Dryer 20 calculates the estimated required time and margin time according to the laundry amount specified by the user, and recalculates the settable time based on the calculated estimated required time and margin time. Similar to the third display example shown in Figure 17(c), the operation screen displays area A17 in which the recalculated settable time is displayed, and area A18 for indicating that the end time setting has been completed.

[0122] In the example shown in FIG. 19(c), area A17 displays text indicating that the settable time is "17:30 today to 14:30 tomorrow" and that the user specified laundry volume is "normal" (i.e., a standard volume). The user inputs an end time in area A17 and then selects area A18 to set the end time again. In the example shown in FIG. 19(c), the user specifies the end time as "17:30 today." This causes the dryer 20 to set the scheduled start time based on the set end time and wait until the set scheduled start time. The dryer 20 then performs the drying operation when the scheduled start time is reached.

[0123] <Fifth Display Example> Fig. 20 is a diagram showing a fifth display example of the dryer 20 according to the embodiment. Similar to (a) of Fig. 16 showing the second display example, Fig. 20 shows an operation screen that is displayed on the display 27 when a user reserves a drying operation of the dryer 20. The operation screen further displays an area A22 for alerting the user that the drying operation may not be completed by the end time set by the user (desired end time). The operation screen is displayed on the display 27 when the dryer 20 determines that there is a large deviation in the estimated required time and the margin time. For example, the dryer 20 determines that there is a large deviation in the predictions of the estimated required time and the margin time when the margin time exceeds a first threshold value or when the number of delays that occurred in past operations exceeds a second threshold value.

[0124] By checking the warning, the user can be aware in advance that the drying operation may not finish by the desired end time. Note that the above warning to the user may be realized by, for example, a push notification.

[0125] [6. Effects, etc.] Advantages of control system 100 according to the embodiment will be described below using specific examples. Fig. 21 is an explanatory diagram of advantages of control system 100 according to the embodiment. Fig. 21(a) shows a specific example in which a user reserves a drying operation of dryer 20, and Fig. 21(b) shows a specific example in which a user reserves another process (here, a washing operation) in addition to the drying operation of dryer 20.

[0126] First, a specific example of the case shown in FIG. 21(a) will be described. (1) A user schedules a drying operation. In the example shown in FIG. 21(a), the user schedules a drying operation for 22:00, with the desired end time set to 6:00 the following day. Next, (2) the control system 100 calculates the estimated required time and the margin time. In the example shown in FIG. 21(a), the control system 100 calculates the estimated required time to be 2 hours and 10 minutes, and the margin time to be 30 minutes.

[0127] Next, (3) the dryer 20 subtracts the calculated estimated required time from the desired end time, and then (4) subtracts the calculated leeway time to calculate the scheduled start time. In the example shown in Fig. 21(a) , the dryer 20 subtracts the estimated required time of 2 hours and 10 minutes from the desired end time of 6:00 the next day, and then subtracts the leeway time of 30 minutes to calculate the scheduled start time as 3:20 the next day.

[0128] Then, (5) the dryer 20 waits until the scheduled start time, and (6) starts the drying operation at the scheduled start time. Then, (7) the dryer 20 ends the drying operation when almost the same amount of time as the estimated required time has passed from the scheduled start time. In the example shown in (a) of Figure 21, the dryer 20 ends the drying operation at 5:30 the next day, 2 hours and 10 minutes after the scheduled start time of 3:20 the next day, which is almost the same amount of time as the estimated required time.

[0129] And (8) since the user generally does not go to the location where the dryer 20 is installed until the desired end time, the time from the end time of the drying operation to the desired end time is the time that the clothes are left in the dryer 20. In the example shown in Fig. 21(a), the time that the clothes are left in the dryer 20 is set to 30 minutes, and since the time that the clothes are left in the dryer 20 is shortened, the clothes are less likely to develop wrinkles or odors.

[0130] Next, a specific example of the case shown in FIG. 21(b) will be described. (1) The user schedules the washing operation and the drying operation. In the example shown in FIG. 21(b), the user schedules the washing operation and the drying operation for 22:00, and sets the desired end time to 6:00 the next day. Next, (2) the control system 100 calculates the estimated required time and the margin time. In the example shown in FIG. 21(b), the control system 100 calculates the estimated required time to be 1 hour and 40 minutes, and the margin time to be 30 minutes. The control system 100 also calculates the other process required time, which is the time required for the washing operation (other process). In the example shown in FIG. 21(b), the control system 100 calculates the other process required time to be 30 minutes.

[0131] Next, (3) the dryer 20 subtracts the calculated estimated required time from the desired end time, (4) subtracts the calculated required times for other processes, and (5) further subtracts the calculated leeway time to calculate the scheduled start time. In the example shown in Figure 21 (b), the dryer 20 subtracts the estimated required time of 1 hour and 40 minutes from the desired end time of 6:00 the next day, subtracts the required time for other processes of 30 minutes, and further subtracts the leeway time of 30 minutes to calculate the scheduled start time as 3:20 the next day.

[0132] Then, (6) the dryer 20 waits until the scheduled start time, and (7) starts the washing operation and the drying operation at the scheduled start time. Then, (8) the dryer 20 ends the drying operation when almost the same amount of time as the total of the required time for other processes and the estimated required time has elapsed from the scheduled start time. In the example shown in (b) of Figure 21, the dryer 20 ends the drying operation at 5:30 the next day, 2 hours and 10 minutes after the scheduled start time of 3:20 the next day, which is almost the same amount of time as the total of the required time for other processes and the estimated required time.

[0133] And (9) since the user generally does not go to the location where the dryer 20 is installed until the desired end time, the time from the end time of the washing operation and the drying operation to the desired end time is the time that the clothes are left in the dryer 20. In the example shown in Fig. 21(a), the time that the clothes are left in the dryer 20 is set to 30 minutes, and since the time that the clothes are left in the dryer 20 is shortened, the clothes are less likely to develop wrinkles or odors.

[0134] As described above, the control system 100 according to the embodiment calculates the estimated required time and the slack time based on the time required for past clothing-related processing. Therefore, compared to the technology disclosed in Patent Document 1, the control system 100 according to the embodiment has the advantage of making it easier to bring the actual end time of clothing-related processing closer to the preset end time of the processing. Therefore, the control system 100 according to the embodiment has the advantage that the user is less likely to feel dissatisfied with the clothing-related processing finishing later than the preset end time and with the clothing-related processing finishing earlier than the preset end time.

[0135] Furthermore, the control system 100 according to the embodiment has further advantages. Fig. 22 is a diagram illustrating other advantages of the control system 100 according to the embodiment. Fig. 22(a) shows a case where the technology disclosed in Patent Document 1 is used, and Fig. 22(b) shows a case where the control system 100 according to the embodiment is used.

[0136] As shown in (a) of Figure 22, for example, if a user schedules a drying operation at 0:30, the technology disclosed in Patent Document 1 makes it difficult to set an appropriate margin time for the state of the equipment because the margin time added to the expected operating time is preset during the equipment design stage, as mentioned above. Therefore, there is a possibility that the margin time will be set longer than necessary. In the example shown in (a) of Figure 22, the expected required time is 5 hours and 40 minutes, and the margin time is 1 hour and 20 minutes. Therefore, the user can only set the end time (end reservation setting) after 7:30, which is a total of 7 hours after the current time (here, 0:30).

[0137] In contrast, the control system 100 according to the embodiment can shorten the slack time as described above. Therefore, in the example shown in FIG. 22(b), the estimated required time is 5 hours and 40 minutes, and the slack time is 20 minutes. Therefore, the user can set the end time (scheduled end time) from 6:30, a total of 6 hours after the current time (here, 0:30). Thus, the control system 100 according to the embodiment has the advantage of easily setting the end time for clothing processing earlier.

[0138] [7. Other Embodiments] Although the embodiments have been described above, the present disclosure is not limited to the above-described embodiments.

[0139] In the above embodiment, the input I / F 22 of the dryer 20 and the input I / F 32 of the terminal 30 are both realized by touch panel displays, but this is not limited thereto. For example, the input I / F 22 of the dryer 20 and the input I / F 32 of the terminal 30 may each be configured with a plurality of buttons or the like. In this case, the display 27 of the dryer 20 and the display 35 of the terminal 30 may each be configured with a 7-segment display or the like.

[0140] In the above embodiment, after the operation of the laundry processing device (e.g., the dryer 20) has started, the remaining time or the end time may be displayed on the display 27 of the dryer 20 or the display 35 of the terminal 30. In this case, the remaining time may be based on the estimated required time, or may be based on both the estimated required time and the margin of time. The same applies to the end time.

[0141] In the above embodiment, the control system 100 calculates the slack time under the assumption that the drying operation time follows a normal distribution. However, this is not limited to this. For example, if a distribution shape that is more suitable for the actual situation is known for the distribution of the drying operation time, the control system 100 may calculate the slack time using a different method. For example, if it is known that the distribution of the drying operation time is always one minute or more and has a wide base in the positive direction, the control system 100 may assume that the drying operation time follows a log-normal distribution, calculate a group of parameters that identify the shape, and calculate the slack time using a formula that keeps the delay rate on this log-normal distribution below 0.3% or an arbitrary value.

[0142] In the above embodiment, the control system 100 may calculate the estimated required time and the margin time using a prediction model that has been trained in advance by machine learning, such as a neural network. In this case, the prediction model may be trained by, for example, supervised learning, so as to input past operating data and output the estimated required time and margin time. The prediction model may also be trained using operating conditions such as the operating course, operating mode, and laundry load as input.

[0143] In the above embodiment, the control system 100 implements the input I / F 22 using the display 27 of the dryer 20 and the input I / F 32 using the display 35 of the terminal 30, but this is not limited to this. For example, the control system 100 may implement the input I / F 22 of the dryer 20 and the input I / F 32 of the terminal 30 using an audio input I / F. Furthermore, the dryer 20 may present various information to the user using an audio output I / F instead of the display 27. Similarly, the terminal 30 may present various information to the user using an audio output I / F instead of the display 35.

[0144] In the above embodiment, the control system 100 calculates the estimated required time and margin time for the drying operation as a laundry-related process, but this is not limited to this. For example, the control system 100 may calculate the estimated required time and margin time for the washing operation as a laundry-related process. In this case, the control system 100 may calculate an average value and a standard deviation based on operation data related to past washing operations, calculate the estimated required time for the washing operation based on the calculated average value, and calculate the margin time for the washing operation based on the calculated standard deviation. Furthermore, for example, the control system 100 may calculate an overall estimated required time and margin time for the washing operation and the drying operation as a laundry-related process. In this case, the control system 100 may calculate an average value and a standard deviation based on operation data related to past washing operations and the drying operation, calculate the overall estimated required time for the washing operation and the drying operation based on the calculated average value, and calculate the overall margin time for the washing operation and the drying operation based on the calculated standard deviation.

[0145] Furthermore, the order of the processes described in the above embodiment is merely an example. The order of multiple processes may be changed, or multiple processes may be executed in parallel. Furthermore, a process executed by a specific processing unit may be executed by another processing unit. Specifically, part or all of the server's processes may be executed by a terminal or a dryer (clothes processing machine). Furthermore, part of the digital signal processing described in the above embodiment may be realized by analog signal processing.

[0146] In the above embodiment, the control system 100 is realized by the server 10 and the dryer 20, but is not limited to this. For example, the control system 100 may be realized by the server 10 alone, the dryer 20 alone, or the terminal 30 alone.

[0147] In the above-described embodiments, each component may be realized by executing a software program suitable for that component, or by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0148] Furthermore, each component may be realized by hardware. For example, each component may be a circuit (or integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Furthermore, each of these circuits may be a general-purpose circuit or a dedicated circuit.

[0149] Furthermore, the general or specific aspects of the present disclosure may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM. They may also be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. For example, the present disclosure may be implemented as a control method executed by a computer, or may be realized as a program for causing a computer to execute such a control method. The present disclosure may also be realized as a computer-readable non-transitory recording medium on which such a program is recorded. The program here includes an application program for causing a general-purpose information terminal to function as the control system of the above-described embodiment.

[0150] In addition, this disclosure also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art would think of, or forms realized by arbitrarily combining the components and functions of each embodiment within the scope that does not deviate from the intent of this disclosure.

[0151] (Summary) As described above, the control system 100 according to the first aspect includes one or more processors (here, processor 12) and a memory (here, memory 13). The one or more processors acquire past operation data performed by a clothing processing device (here, dryer 20) that performs processing related to clothing. The one or more processors calculate an estimated required time and a margin time that are estimated to be required for processing related to clothing based on the acquired past operation data. The one or more processors output the calculated estimated required time and margin time.

[0152] This has the advantage that not only the estimated required time but also the surplus time is calculated based on the time required for past clothing processing, making it easier to shorten the surplus time and bring the actual time when clothing processing is completed closer to the pre-set end time of the processing.

[0153] In the control system 100 according to the second aspect, in the first aspect, one or more processors (here, processor 23) further acquire an end time of the processing related to the clothing. The one or more processors set an expected start time of the processing related to the clothing by subtracting the total time of the estimated required time and the leeway time from the acquired end time.

[0154] This has the advantage that the time when the processing relating to the clothes actually ends can be made closer to the preset end time of the processing.

[0155] In the control system 100 according to the third aspect, the processing related to the clothes in the first or second aspect is configured with a plurality of steps including a predetermined step (here, a drying operation). One or more processors (here, the processor 12) calculate the estimated required time and the leeway time for the predetermined step.

[0156] This has the advantage that it is easy to suppress fluctuations in the time required for a given process.

[0157] In addition, in the control system 100 relating to the fourth aspect, in any one of the first to third aspects, one or more processors (here, processor 12) calculate the average value μ of the time required by a clothing processing device (here, dryer 20) to process actual clothing in the past as the estimated required time, and calculate the spare time based on the standard deviation σ of the required time.

[0158] This has the advantage that the estimated required time and leeway time are calculated through statistical processing, making it easier to bring the time when processing related to clothing actually ends closer to the predetermined end time of the processing.

[0159] In addition, in the control system 100 relating to the fifth aspect, in any one of the first to fourth aspects, one or more processors (here, processor 12) calculate the estimated required time and the leeway time depending on the type of processing related to the clothes and the amount of fabric in the clothes.

[0160] This has the advantage that the estimated required time and leeway time appropriate for the type of processing and amount of laundry related to the clothes are calculated, making it easier to bring the time when the processing related to the clothes actually ends closer to the predetermined end time of the processing.

[0161] In addition, in the control system 100 relating to the sixth aspect, in any one of the first to fifth aspects, one or more processors (here, processor 12) calculate the estimated required time and the margin time further based on past operating data of one or more other clothing processing devices other than the clothing processing device (here, dryer 20).

[0162] This has the advantage that it is easy to calculate the estimated required time and leeway time appropriate for the clothing processing device to be processed, even if there is little or no past operating data for the clothing processing device to be processed.

[0163] In addition, in the control system 100 relating to the seventh aspect, in any one of the first to sixth aspects, if there are external conditions that affect the execution time of processing related to clothing, one or more processors (here, processor 23) calculate a correction time based on the external conditions, and add the calculated correction time to the estimated required time and the surplus time.

[0164] This has the advantage that it is possible to take into account external conditions that affect the execution time of the clothing processing, such as the air temperature in the tub 25, and therefore it is easier to bring the actual time at which the clothing processing ends closer to the predetermined end time of the processing.

[0165] In addition, in the control system 100 relating to the eighth aspect, in any one of the first to seventh aspects, one or more processors (here, processor 23) present a settable time, which is a range within which the end time of processing related to clothing can be set, based on the estimated required time and the remaining time.

[0166] This has the advantage that the user can set the end time within a range that allows the user to actually complete the processing related to the clothing with ample time to spare, which makes it easier to use.

[0167] In addition, in the control system 100 relating to the ninth aspect, in the second aspect, one or more processors (here, processor 23) determine whether there is a large variation in the estimated required time and the remaining time, and if it is determined that there is a large variation in the estimated required time and the remaining time, a warning is presented that the processing related to the clothing may not be completed by the end time.

[0168] This has the advantage that the user can know in advance that there is a possibility that the processing related to the clothes may not be completed by the end time, so the user is less likely to become dissatisfied.

[0169] A control method according to a tenth aspect is a control method executed by one or more processors (here, processor 12). The control method acquires past operation data of a clothing processing device (here, dryer 20) that performs processing related to clothing. The control method calculates an estimated required time and a margin of time expected to be required for processing related to clothing based on the acquired past operation data. The control method outputs the calculated estimated required time and margin of time.

[0170] This has the advantage that not only the estimated required time but also the surplus time is calculated based on the time required for past clothing processing, making it easier to shorten the surplus time and bring the actual time when clothing processing is completed closer to the pre-set end time of the processing.

[0171] A program according to an eleventh aspect causes one or more processors to execute the control method according to the tenth aspect.

[0172] This has the advantage that not only the estimated required time but also the surplus time is calculated based on the time required for past clothing processing, making it easier to shorten the surplus time and bring the actual time when clothing processing is completed closer to the pre-set end time of the processing.

[0173] The control system and the like of the present disclosure can be applied to a clothing processing device, such as a dryer, that performs processing related to clothing.

[0174] DESCRIPTION OF SYMBOLS 10 Server 11 Communication I / F 12 Processor 121 Acquisition unit 122 Parameter calculation unit 123 Time calculation unit 13 Memory 131 Operation data storage unit 132 Parameter storage unit 20, 20A, 20B, 20C Dryer 21 Communication I / F 22 Input I / F 23 Processor 24 Memory 25 Tub 26 Heat pump 27 Display 28 Sensor 30, 30A, 30B, 30C Terminal 31 Communication I / F 32 Input I / F 33 Processor 34 Memory 35 Display A1 to A22 Area

Claims

1. A control system comprising one or more processors and memory, wherein the one or more processors acquire past operation data performed by a clothing processing device that performs processing related to clothing, calculate an estimated required time and leeway time expected to be required for the processing related to clothing based on the acquired past operation data, and output the calculated estimated required time and leeway time.

2. The control system of claim 1, wherein the one or more processors further acquire an end time of the processing for the clothing, and set a scheduled start time of the processing for the clothing by subtracting the total time of the estimated required time and the leeway time from the acquired end time.

3. The control system according to claim 1 or 2, wherein the processing relating to the clothing is made up of a plurality of steps including a predetermined step, and the one or more processors calculate the estimated required time and the slack time for the predetermined step.

4. The control system described in claim 1 or 2, wherein the one or more processors calculate the estimated required time as the average of the time required by the clothing processing device to actually process the clothing in the past, and calculate the leeway time based on the standard deviation of the required time.

5. The control system according to claim 1 or 2, wherein the one or more processors calculate the estimated required time and the leeway time according to the type of processing related to the clothes and the amount of fabric in the clothes.

6. The control system according to claim 1 or 2, wherein the one or more processors calculate the estimated required time and the leeway time further based on past operating data of one or more other clothing processing devices other than the clothing processing device.

7. The control system of claim 1 or 2, wherein, when there are external conditions that affect the execution time of the processing related to the clothing, the one or more processors calculate a correction time based on the external conditions and add the calculated correction time to the estimated required time and the slack time.

8. The control system according to claim 1 or 2, wherein the one or more processors present a settable time within a range in which the end time of processing for the clothing can be set based on the estimated required time and the leeway time.

9. The control system of claim 2, wherein the one or more processors determine whether there is a large deviation between the estimated required time and the leeway time, and if it determines that there is a large deviation between the estimated required time and the leeway time, presents a warning that the processing related to the clothing may not be completed by the end time.

10. A control method executed by one or more processors, which comprises: acquiring past operational data performed by a clothing processing device that performs processing related to clothing; calculating an estimated required time and a surplus time estimated to be required for processing the clothing based on the acquired past operational data; and outputting the calculated estimated required time and surplus time.

11. A program causing one or more processors to execute the control method according to claim 10.

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