Patent Application
20250172926
The present invention relates to an assistance device, an assistance method and an assistance program for assisting a maintenance work for one or a plurality of substrate processing apparatuses.
A substrate processing apparatus is used to execute various processes on various substrates such as a semiconductor substrate. In the substrate processing apparatus 1, a series of processes is executed on a substrate in accordance with a predetermined processing procedure (processing recipe), for example. In order to prevent an occurrence of a processing defect in a substrate due to an abnormality present in a substrate processing apparatus, a data processing system for making determination in regard to an abnormality present in a substrate processing apparatus has been proposed (see Patent Document 1, for example).
In the data processing system, a plurality of physical quantities related to a substrate processing apparatus are measured during a process for a substrate, and these measurement results are arranged in a chronological order, so that a plurality of time-series data pieces are generated. The plurality of time-series data pieces include data of the physical quantities such as a flow rate of a processing liquid discharged from a nozzle and a pressure in a chamber, for example. Each time-series data piece is compared with predetermined reference data, so that an evaluation value is calculated. It is determined whether an abnormality is present in the time-series data based on the calculated evaluation value.
[Patent Document 1] JP 2020-47847 A
In the following description, a person who performs a maintenance work for a substrate processing apparatus is referred to as a maintenance worker. The maintenance worker for the substrate processing apparatus can recognize whether an abnormality has occurred in the substrate processing apparatus based on an abnormality determination result provided by the above-mentioned data processing system. However, even though being able to recognize an occurrence of an abnormality in the substrate processing apparatus, an unskilled maintenance worker might not be able to specify the cause of the abnormality. Alternatively, even though being able to specify the cause of an occurrence of an abnormality, an unskilled maintenance worker might not be able to identify the content of appropriate work for resolution of the occurring abnormality. In these cases, the maintenance worker requires a long period of time to perform the maintenance work on the substrate processing apparatus.
An object of the present invention is to provide an assistance device, an assistance method and an assistance program that enable a maintenance worker to perform an appropriate maintenance work on a substrate processing apparatus in a short period of time regardless of a degree of skill.
With the assistance device, assistance information based on deviation information is generated. Thus, a maintenance worker who performs the maintenance work on the substrate processing apparatus can perform an appropriate maintenance work on the substrate processing apparatus in a short period of time based on the generated assistance information regardless of a degree of skill.
In this case, the maintenance worker can recognize one or a plurality of maintenance subject components in a short period of time based on the generated assistance information.
In this case, the maintenance worker can recognize an appropriate maintenance work corresponding to the state of each of the one or plurality of maintenance subject components in a short period of time based on the generated assistance information.
With the assistance method, assistance information based on deviation information is generated. Thus, the maintenance worker who performs a maintenance work on the substrate processing apparatus can perform an appropriate maintenance work on the substrate processing apparatus in a short period of time based on the generated assistance information regardless of a degree of skill.
With the assistance program, assistance information based on deviation degree information is generated. Thus, the maintenance worker who performs a maintenance work on the substrate processing apparatus can perform an appropriate maintenance work on the substrate processing apparatus in a short period of time based on the generated assistance information regardless of a degree of skill.
With the present invention, a maintenance worker can perform an appropriate maintenance work on a substrate processing apparatus in a short period of time regardless of a degree of skill.
An assistance device, an assistance method and an assistance program according to one embodiment of the present invention will be described below with reference to the drawings. In the following description, a substrate refers to a semiconductor substrate, a substrate for an FPD (Flat Panel Display) such as a liquid crystal display device or an organic EL (Electro Luminescence) display device, a substrate for an optical disc, a substrate for a magnetic disc, a substrate for a magneto-optical disc, a substrate for a photomask, a ceramic substrate, a substrate for a solar battery, or the like. In the following description, a person who performs a maintenance work for a substrate processing apparatus is referred to as a maintenance worker.
First, the overall configuration of a substrate processing apparatus management system including an assistance device according to the present embodiment will be described.
The assistance device 4 according to the present embodiment is used to assist the maintenance work for each substrate processing apparatus 1 performed by the maintenance worker. The assistance device 4 is connected to each of the one or plurality of substrate processing apparatus 1 and the information analysis device 3 by a wired or wireless communication line or a wired or wireless communication network. For example, the assistance device 4 is connected to each of the one or plurality of substrate processing apparatuses 1 and the information analysis device 3 by a communication network such as the Internet. In the present embodiment, the assistance device 4 is connected to each of the one or plurality of substrate processing apparatuses 1 and the information analysis device 3 by a wired or wireless LAN.
As shown in
The substrate holder 112 is configured to be capable of holding a plurality of substrates W. The processing tank 111 is configured to be capable of accommodating the plurality of substrates W held by the substrate holder 112. A cleaning liquid for cleaning the substrate W is stored in the processing tank 111.
The lifting-lowering device 112a supports the substrate holder 112 to be movable in an upward-and-downward direction and moves the substrate holder 112 in the upward-and-downward direction with the control of the control device 100. Thus, the lifting-lowering device 112a can immerse the plurality of substrates W held by the substrate holder 112 in the cleaning liquid stored in the processing tank 111, and can pull up the plurality of substrates W immersed in the cleaning liquid from the processing tank 111. The plurality of substrates W are cleaned by being immersed in the cleaning liquid. Further, in the lifting-lowering device 112a, a motor (not shown) as a power source for moving the substrate holder 112 in the upward-and-downward direction is provided.
A chemical liquid pipe 113 and a pure water pipe 114 are connected to the processing tank 111. A chemical liquid valve 113a and a flowmeter 124 are provided in the chemical liquid pipe 113. The chemical liquid valve 113a is a control valve the opening of which is adjustable by the control of the control device 100.
The chemical liquid pipe 113 guides a chemical liquid supplied from a chemical liquid supply system (not shown) to the processing tank 111 when the chemical liquid valve 113a is opened. The flow rate (a supply amount per unit time) of the chemical liquid supplied to the processing tank 111 through the chemical liquid pipe 113 changes in accordance with an opening (a degree of opening) of the chemical liquid valve 113a. As the chemical liquid, BHF (Buffered Hydrofluoric Acid), DHF (Dilute Hydrofluoric Acid), hydrofluoric acid, hydrochloric acid, sulfuric acid, nitric acid, phosphoric acid, acetic acid, oxalic acid, ammonia, or the like is used. The flowmeter 124 detects a flow rate of the chemical liquid in the portion farther downstream than the chemical liquid valve 113a in the chemical liquid pipe 113, and provides a detection result to the control device 100.
A pure water valve 114a and a flowmeter 125 are provided in the pure water pipe 114. The pure water valve 114a is a control valve the opening of which is adjustable by the control of the control device 100.
The pure water pipe 114 guides a pure water supplied from a pure water supply system (not shown) to the processing tank 111 when the pure water valve 114a is opened. The flow rate (supply amount per unit time) of the pure water supplied to the processing tank 111 through the pure water pipe 114 changes in accordance with an opening (a degree of opening) of the pure water valve 114a. The flowmeter 125 detects a flow rate of the pure water in the portion farther downstream than the pure water valve 114a in the pure water pipe 114, and provides a detection result to the control device 100.
The bubbler pipe 115 is fixed to a portion inside of the processing tank 111 and in the vicinity of the lower end portion of the processing tank 101 by a bubbler fixture (not shown). A gas pipe 116 is connected to the bubbler pipe 115. In the gas pipe 116, a gas valve 116a, a flowmeter 126 and a manometer 127 are provided. The gas valve 116a is a control valve the opening of which is adjustable by the control of the control device 100.
The gas pipe 116 guides a nitrogen gas supplied from a gas supply system (not shown) to the bubbler pipe 115 in the processing tank 111 when the gas valve 116a is opened. The flow rate (supply amount per unit time) of the nitrogen gas supplied to the bubbler pipe 115 through the gas pipe 116 changes in accordance with an opening (a degree of opening) of the gas valve 116a.
The flowmeter 126 detects a flow rate of the nitrogen gas in the portion farther downstream than the gas valve 116a in the gas pipe 116, and provides a detection result to the control device 100. In this case, the control device 100 adjusts the opening of the gas valve 116a based on the flow rate provided by the flowmeter 126 such that the nitrogen gas is supplied to the bubbler pipe 115 at a predetermined flow rate. The manometer 127 detects an inner pressure in the portion farther downstream than the gas valve 116a in the gas pipe 116, and provides a detection result to the control device 100.
The openings of the chemical liquid valve 113a and the pure water valve 114a are adjusted, so that the chemical liquid and the pure water are supplied into the processing tank 111 at a predetermined ratio. In this state, the gas valve 116a is further opened. Thus, the nitrogen gas is supplied to the bubbler pipe 115, and a large amount of bubbles are generated in the bubbler pipe 115. The generated bubbles are lifted in the processing tank 111. Therefore, the chemical liquid and the pure water supplied into the processing tank 111 are mixed, and the cleaning liquid is generated. Instead of the nitrogen gas, another inert gas such as an argon gas may be supplied to the bubbler pipe 115.
The heater 117 is further provided in a portion inside of the processing tank 111 and in the vicinity of the lower end portion of the processing tank 111. The heater driver 118 drives the heater 117 by supplying electric power to the heater 117. An amount of power supplied from the heater driver 118 to the heater 117 is controlled by the control device 100.
Further, a drain pipe is connected to a bottom portion of the processing tank 111. A valve (not shown) is provided in the drain pipe. The valve provided in the drain pipe is opened, so that the cleaning liquid in the processing tank 111 is discharged to the outside of the substrate processing apparatus 1A.
In the processing tank 111, a liquid level meter 121, a concentration meter 122 and a thermometer 123, as a plurality of detectors for detecting the states of the cleaning liquid stored in the processing tank 111, are provided.
The liquid level meter 121 detects a height of liquid surface (liquid level) of the cleaning liquid stored in the processing tank 111 and provides a detection result to the control device 100. The concentration meter 122 detects a concentration of the cleaning liquid (chemical concentration) stored in the processing tank 111 and provides a detection result to the control device 100. The thermometer 123 detects a temperature of the cleaning liquid stored in the processing tank 111 and provides a detection result to the control device 100.
The control device 100 includes a CPU (Central Processing Unit) and a memory, for example, and controls an operation of the lifting-lowering device 112a, an operation of the heater driver 118, openings of the chemical liquid valve 113a, the pure water valve 114a and the gas valve 116a, and the like. The memory of the control device 100 stores a substrate processing program for execution of a cleaning process for the substrate W executed by the substrate processing apparatus 1A.
Further, based on the detection results of the flowmeters 124, 125, 126, the detection result of the liquid level meter 121 and the detection result of the concentration meter 122, the control device 100 adjusts the openings of the chemical liquid valve 113a, the pure water valve 114a, the gas valve 116a and the drain pipe (not shown). Thus, in a state in which the cleaning liquid having a predetermined chemical concentration is stored in the processing tank 111, the liquid level of the cleaning liquid is maintained at a predetermined height. Further, based on the temperature provided by the thermometer 123, the control device 100 controls the heater driver 118 such that the cleaning liquid stored in the processing tank 111 is maintained at a predetermined temperature.
Further, the control device 100 has an emergency shutdown function for stopping an operation of the substrate processing apparatus 1A in a case in which a person enters a predetermined space inside of the substrate processing apparatus 1A or a predetermined detector (the concentration meter 122, for example) provided in the substrate processing apparatus 1A is not functioning.
In each substrate processing apparatus 1, as information for detection of an abnormality present in the substrate processing apparatus 1, a plurality of processing information pieces representing the operations or states related to a process for the substrate W are defined. As indicated by the thick solid arrows in
As shown in the balloon of
The information analysis device 3 of
Here, it is assumed that an inappropriate substrate process is executed because a substrate process is executed with an abnormality present in the substrate processing apparatus 1. In this case, at least the relationship between two processing information pieces forming one combination out of the plurality of combinations deviates from the invariant relationship.
The information analysis device 3 calculates a plurality of deviation degrees in regard to a plurality of processing information pieces. A deviation degree indicates a degree of deviation from the predetermined invariant relationship between two processing information pieces to the relationship between two actually collected processing information pieces in regard to the two processing information pieces. Further, based on the plurality of calculated deviation degrees, the information analysis device 3 calculates an abnormality degree of the substrate processing apparatus 1 as an abnormality score. The specific example of a method of calculating an abnormality score will be described below.
As indicated by the thick one-dot and dash arrows in
Further, in regard to each substrate processing apparatus 1, the information analysis device 3 determines whether an abnormality score exceeds a predetermined abnormality determination threshold value. As indicated by the wavy dotted arrow in
In the present embodiment, an abnormality that does not require maintenance by the maintenance worker has a lower abnormality score (degree of abnormality), and an abnormality that requires maintenance by the maintenance worker has a higher abnormality score (degree of abnormality).
In case of a low abnormality score, it includes a case in which, it is predicted, based on the invariant relationships respectively corresponding to the plurality of above-mentioned combinations, that all of a plurality of processing conditions are in a normal range.
On the other hand, in case of a high abnormality score, it includes a case in which the actual temporal change of “d. CHEMICAL CONCENTRATION” is significantly larger than the temporal change of “d. CHEMICAL CONCENTRATION” that is predicted based on the temporal change of “f. FLOW RATE OF CHEMICAL LIQUID,” for example. When this state continues, it causes a processing defect in the substrate W, generation of a harmful gas, and damage to a component of the substrate processing apparatus 1, for example, due to the inability to adjust the chemical concentration of a cleaning liquid.
Further, in case of a high abnormality score, it includes a case in which the actual value of “a. LIQUID LEVEL” is significantly different from the value of “a. LIQUID LEVEL” that is predicted based on the temporal change of “g. FLOW RATE OF NITROGEN GAS,” for example. When this state continues, it causes a processing defect in the substrate W, generation of a harmful gas, and damage to a component of the substrate processing apparatus 1, for example, due to the inability to ensure the immersion of the substrate W in a cleaning liquid.
As described above, in the information analysis device 3, the plurality of combinations each of which includes two different processing information pieces are defined. In order to calculate an abnormality score, a deviation degree is calculated in regard to each combination.
In order to calculate a deviation degree, the information representing the invariant relationship between “b. OPENING OF CHEMICAL LIQUID VALVE” and “f. FLOW RATE OF CHEMICAL LIQUID” is required. In the following description, the information representing the invariant relationship between two processing information pieces is referred to as invariant information. The invariant information is preferably created by machine learning, for example.
It is assumed that machine learning is performed to obtain the invariant information between “b. OPENING OF CHEMICAL LIQUID VALVE” and “f. FLOW RATE OF CHEMICAL LIQUID.” In this case, before a process is actually executed on the substrate W in each substrate processing apparatus 1, a data piece “b” and a data piece “f” obtained when the substrate processing apparatus 1 is ideally operating (normally operating) in accordance with a recipe are provided to the information analysis device 3.
In the upper portion of
According to the two graphs in the upper portion of
The invariant information is not limited to the above-mentioned example, and may be generated by simulation or the like in which it is assumed that the substrate processing apparatus 1 is normally operating, or may be determined by an administrator or the like who manages each substrate processing apparatus 1, for example.
In a state where the invariant information is stored in the information analysis device 3, a process is executed on the substrate W in each substrate processing apparatus 1, and an actual data piece “b” and an actual data piece “f” are collected by the information analysis device 3. In the center portion of
When the actual data piece “b” is collected, the data piece “f” is predicted based on the pre-stored invariant information. Further, when the actual data piece “f” is collected, the data piece “b” is predicted based on the pre-stored invariant information. In the lower portion of
In a case in which the substrate processing apparatus 1 is normally operating, the actual data piece “b” and the predicted data piece “b” coincide or substantially coincide with each other. Further, the actual data piece “f” and the predicted data piece “f” coincide or substantially coincide with each other. However, in a case in which an abnormality is present in the substrate processing apparatus 1, the actual data piece “b” and the predicted data piece “b” are likely to deviate from each other. Further, the actual data piece “f” and the predicted data piece “f” are likely to deviate from each other. It is considered that, the larger a degree of abnormality that occurs in the substrate processing apparatus 1, the larger a degree of deviation, and the smaller a degree of abnormality that occurs in the substrate processing apparatus 1, the smaller a degree of deviation.
As such, in the present embodiment, the difference value between the data representing the actually collected processing information piece and the data representing the predicted processing information piece is calculated as a deviation degree. In the example of
In the following description, the processing information pieces for “a. LIQUID LEVEL,” “b. OPENING OF CHEMICAL LIQUID VALVE,” “c. OPEN-CLOSE SIGNAL OF CHEMICAL VALVE,” “d. CHEMICAL CONCENTRATION,” “e. TEMPERATURE OF CLEANING LIQUID,” “f. FLOW RATE OF CHEMICAL LIQUID,” “g. FLOW RATE OF NITROGEN GAS,” and “h. PRESSURE OF NITROGEN GAS” are referred to as processing information pieces “a,” “b,” “c,” “d,” “e,” “f,” “g” and “h,” respectively.
For example, the value “52” at the intersection of the row for the processing information piece “a” in the left column and the column for the processing information piece “g” in the upper row represents the deviation degree between the processing information piece “a” that is predicted based on the processing information piece “g” and the actually acquired processing information piece “a.” Further, the value “50” at the intersection of the row for the processing information piece “g” in the left column and the column for the processing information piece “a” in the upper row represents the deviation degree between the processing information piece “g” that is predicted based on the processing information piece “a” and the actually acquired processing information piece “g.”
The assistance device 4 of
However, even though being able to recognize the degree of an abnormality present in the substrate processing apparatus 1, the maintenance worker might not be able to specify the cause of the abnormality in the substrate processing apparatus 1. Alternatively, even though being able to specify the cause of an occurrence of an abnormality, an unskilled maintenance worker might not be able to identify the content of appropriate work for resolution of the occurring abnormality. In these cases, each maintenance worker requires a long period of time to perform the maintenance work for the substrate processing apparatus.
As such, as indicated by the thick dotted arrow in
The memory of the assistance device 4 stores the data-related component information and the temporal component information in advance in order to generate the above-mentioned assistance information. The data-related component information is the information representing each of a plurality of processing information pieces collected by the information analysis device 3 and one or a plurality of components related to the processing information piece. The data-related component information is defined in advance by the maintenance worker for one substrate processing apparatus 1, an administrator who manages one substrate processing apparatus 1, or the like, before the substrate process is executed in the one substrate processing apparatus 1, for example. Specifically, the data-related component information is generated and updated when the maintenance worker, the administrator or the like operates the operation unit of the substrate processing apparatus 1 or the operation unit 4b of the assistance device 4.
Further, as the components related to the processing information piece “d,” the chemical liquid pipe 113 and the concentration meter 122 are shown. As the components related to the processing information piece “e,” the chemical liquid pipe 113, the heater 117 and the thermometer 123 are shown. As the component related to the processing information piece “f,” the chemical liquid pipe 113 is shown.
Further, as the components related to the processing information piece “g,” the bubbler pipe 115, the bubbler fixture, the flowmeter 126 for gas and the gas pipe 116 are shown. As the components related to the processing information piece “h,” the bubbler pipe 115, the bubbler fixture and the gas pipe 116 are shown.
The temporal component information is the information related to a deterioration state that changes over time in regard to each of the plurality of components related to at least part of the plurality of processing information pieces in the data-related component information. In the assistance device 4, the temporal component information is updated to the latest state in a predetermined period.
The “RELATED PROCESSING INFORMATION” represents processing information related to each component, and the relationship between the component and the processing information related to the component is equal to the relationship between each processing information and the component represented by the data-related component information of
The specific example of generation of assistance information will be described. Here, in the assistance device 4 according to the present embodiment, one or a plurality of deviation-degree threshold values which are commonly or individually determined are stored in regard to a plurality of deviation degrees provided by the information analysis device 3. Each deviation-degree threshold value is defined such that it is possible to determine whether an abnormality of a predetermined degree has occurred in a component related to two processing information pieces used for calculation of a corresponding deviation degree.
In regard to each of the plurality of deviation degrees provided by the information analysis device 3, the assistance device 4 determines whether the deviation degree exceeds the deviation-degree threshold value. As such, in a case in which there is a deviation degree exceeding the deviation-degree threshold value, in regard to the combination of two processing information pieces used for calculation of the deviation degree and data-related component information, the assistance device 4 determines the component commonly related to the two processing information pieces as a maintenance subject component.
For example, it is assumed that “40” is defined as the common deviation-degree threshold value in regard to the plurality of deviation degrees of
Next, in regard to each of one or a plurality of determined maintenance subject components, the assistance device 4 calculates a degree of necessity for the maintenance work as a maintenance necessity value. A maintenance necessity value is calculated based on the temporal component information of a maintenance subject component using the following formula (1), for example.
A maintenance necessity value=((an elapsed period of time/estimated years)+(the number of failures/the number of operating components))×weight . . . (1)
The “weight” in the above-mentioned formula (1) is defined, for each maintenance subject component, in accordance with the type of abnormality that is estimated to occur due to damage or missing of the maintenance subject component. The types of abnormality include “leakage of a chemical liquid,” “damage to a substrate,” “extension of a processing period of time” and the like. In this case, the “leakage of a chemical liquid” is highly likely to affect health of the maintenance worker for the substrate processing apparatus 1, or the like. Therefore, a high weight (“3,” for example) is assigned to a maintenance subject component that may cause “leakage of a chemical liquid” due to damage or missing of the component. On the other hand, the “damage to a substrate” is less likely to affect the health of the maintenance worker for the substrate processing apparatus 1, or the like. Therefore, a medium weight (“2,” for example) is assigned to a maintenance subject component that may cause “damage to a substrate” due to damage or missing of the component. On the other hand, the “extension of a processing period of time” does not affect the health of the maintenance worker for the substrate processing apparatus 1, or the like, and is less likely to cause damage to the substrate processing apparatus 1 or a substrate. Therefore, a low weight (“1,” for example) is assigned to a maintenance subject component that may cause “extension of a processing period of time” due to damage or missing of the component.
Thereafter, in regard to each of the one or plurality of maintenance subject components, the assistance device 4 generates information including a maintenance work instruction corresponding to the maintenance subject component as assistance information based on a calculated maintenance necessity value and transmits the assistance information to the substrate processing apparatus 1.
Specifically, the assistance device 4 determines, in regard to each of the one or plurality of maintenance subject components, which one of the plurality of predetermined levels (three levels of high, medium and low, for example) the calculated maintenance necessity value belongs to. Such level assignment can be carried out by setting of a plurality of different reference values, for example, in regard to a maintenance necessity value.
When the maintenance subject component is the “liquid level meter 121,” and the level of the maintenance necessity value is “high,” the assistance device 4 generates assistance information including “a maintenance work instruction for replacement of the liquid level meter 121,” for example. Further, in this case, the assistance device 4 may generate assistance information including “work information to be presented to a maintenance worker in regard to the procedure for replacement of the liquid level meter 121,” “report information for creation of a report in regard to replacement of the liquid level meter 121,” and the like.
Further, when the maintenance subject component is the “liquid level meter 121,” and the level of the maintenance necessity value is “medium,” the assistance device 4 generates assistance information including “a maintenance work instruction for checking an operation of the liquid level meter 121 in detail,” for example. Further, in this case, the assistance device 4 may generate assistance information including “work information to be presented to a maintenance worker in regard to the procedure for checking of an operation of the liquid level meter 121 in detail,” “report information for creation of a report in regard to checking of an operation of the liquid level meter 121,” and the like.
Further, when the maintenance subject component is the “liquid level meter 121,” and the level of the maintenance necessity value is “low,” the assistance device 4 generates assistance information including “a maintenance work instruction for simply checking an operation of the liquid level meter 121,” for example. Further, in this case, the assistance device 4 may generate assistance information including “work information to be presented to a maintenance worker in regard to the procedure for simply checking of an operation of the liquid level meter 121,” and the like.
The assistance information as described above is transmitted from the assistance device 4 to each substrate processing apparatus 1. In this case, in each substrate processing apparatus 1, the assistance information is presented to the maintenance worker by the display device or the speech output device. Thus, the maintenance worker for the substrate processing apparatus 1 can recognize, based on the received assistance information, what maintenance work is to be performed on which component in the substrate processing apparatus 1, easily and in a short period of time.
In the following description, it is assumed that the substrate processing apparatus management system 2 manages only one substrate processing apparatus 1. Therefore, a series of processes shown in
As described with reference to
Next, the control device 100 determines whether an abnormality score has been received from the information analysis device 3 (step S11). In a case in which an abnormality score has not been received, the control device 100 repeats the determination in the step S11. In a case in which an abnormality score has been received, the control device 100 stores the received abnormality score in association with the point in time at which the abnormality score is received (step S12).
Further, the control device 100 determines whether a warning has been received from the information analysis device 3 (step S13). In a case in which a warning has not been received, the control device 100 causes the process to proceed to the step S15, described below. In a case in which a warning has been received, the control device 100 outputs a warning in the form of video or sound using the display unit or the speech output device of the substrate processing apparatus 1 (step S14).
Further, the control device 100 determines whether assistance information has been received from the assistance device 4 (step S15). In a case in which assistance information has not been received, the control device 100 causes the process to return to the step S15. In a case in which assistance information has been received, the control device 100 presents, based on the received assistance information, a maintenance work instruction corresponding to a maintenance subject component using the display device or the speech output device (step S16). Thereafter, the control device 100 causes the process to return to the step S10.
As shown in
As shown in
Next, the score calculator 32 calculates an abnormality score of the substrate processing apparatus 1 based on the plurality of deviation degrees stored in the memory of the information analysis device 3 (step S23), and transmits the calculated abnormality score to the substrate processing apparatus 1 (step S24).
The memory of the information analysis device 3 stores the above-mentioned abnormality determination threshold value that is set in advance in accordance with the substrate processing apparatus 1. As such, the warning transmitter 34 determines whether the abnormality score calculated in the step S23 exceeds the abnormality determination threshold value (step S25). In a case in which the abnormality score does not exceed the abnormality determination threshold value, the warning transmitter 34 causes the process to return to the step S21. On the other hand, in a case in which the abnormality score exceeds the abnormality determination threshold value, the warning transmitter 34 transmits a warning to the substrate processing apparatus 1 (step S26), and causes the process to return to the step S20.
As shown in
Before the substrate process is started by the substrate processing apparatus 1 of
As described above, the data-related component information is defined by the maintenance worker, the administrator or the like. Further, the temporal component information changes over time. As such, as shown in
In a case in which the data-related component information has not been changed, the information updater 49 causes the process to proceed to the step S32, described below. On the other hand, when the data-related component information has been changed, the information updater 49 updates the data-related component information stored in the first storage 46 with newly changed data-related component information (step S31).
Next, the information updater 49 updates the temporal component information stored in the second storage 47 (step S32). This update process includes a process of updating an elapsed period of time, the number of failures and the number of operating components on the basis of a current point in time.
Next, the deviation degree acquirer 41 determines whether a plurality of deviation degrees have been received from the information analysis device 3 in regard to the substrate processing apparatus 1 of
Next, the subject determiner 42 determines a maintenance subject component based on the extracted deviation degree and the data-related component information stored in the first storage 46 (step S35). Specifically, the subject determiner 42 determines, in regard to each of the one or plurality of deviation degrees extracted in the step S34, the component commonly related to two processing information pieces used for calculation of the deviation degree as a maintenance subject component.
Next, the necessity value calculator 43 calculates a maintenance necessity value of the maintenance subject component based on the determined maintenance subject component and the temporal component information stored in the second storage 47 (step S36). Specifically, in regard to each of the one or plurality of maintenance subject components determined in the step S35, the necessity value calculator 43 calculates a maintenance necessity value by using the temporal component information of the maintenance subject component and a predetermined arithmetic expression (the above-mentioned formula (1), for example).
Next, the instruction generator 45 generates assistance information corresponding to the maintenance subject component based on the maintenance necessity value calculated in the process of the step S36 (step S37). Specifically, in regard to each of the one or plurality of maintenance subject components, the level determiner 44 of
In the above-mentioned example, the series of processes shown in
Further, the series of processes shown in
In the information analysis device 3, in regard to each of one or plurality of substrate processing apparatuses 1, an abnormality degree of the substrate processing apparatus 1 is calculated as an abnormality score based on the invariant relationships in regard to a plurality of processing information pieces and a plurality of actually collected processing information pieces. In a case in which the abnormality score exceeds the abnormality determination threshold value, a warning is transmitted to the substrate processing apparatus 1. When the abnormality score is calculated, the degree of deviation between one processing information predicted based on invariant information and an actually collected processing information piece is calculated, in regard to each of a plurality of combinations including two predetermined different processing information pieces.
In the assistance device 4, based on a plurality of deviation degrees calculated by the information analysis device 3 and data-related component information, one or a plurality of maintenance subject components are appropriately determined from among a plurality of components included in the substrate processing apparatus 1.
Further, in regard to each of the one or plurality of determined maintenance subject components, a maintenance necessity value is calculated based on temporal component information, and assistance information corresponding to the level of the calculated maintenance necessity value is generated. Thus, the maintenance worker for the substrate processing apparatus 1 can easily recognize a maintenance subject component based on the generated assistance information regardless of a degree of skill. Further, the maintenance worker can perform an appropriate maintenance work for the substrate processing apparatus 1 in a short period of time.
A maintenance necessity value does not have to be calculated. In this case, the assistance information including a plurality of maintenance work instructions that are considered for a determined maintenance subject component may be generated.
Alternatively, a maintenance necessity value may be calculated based on another condition instead of the above-mentioned formula (1). For example, a maintenance necessity value may be an “elapsed period of time,” the “number of failures,” or a value obtained when an “elapsed period of time” is divided by “estimated years.”
However, the present invention is not limited to the above-mentioned example. Some or all of the data-related component information, the temporal component information and the content of the plurality of maintenance work instructions may be stored in another server provided outside of the assistance device 4. Alternatively, some or all of the data-related component information, the temporal component information and the content of the plurality of maintenance work instructions may be stored in the one or plurality of substrate processing apparatuses 1 or may be stored in the information analysis device 3. In this case, each of the subject determiner 42, the necessity value calculator 43 and the instruction generator 45 of the assistance device 4 acquire information necessary to achieve the function from outside of the assistance device 4.
In the following paragraphs, non-limiting examples of correspondences between various elements recited in the claims below and those described above with respect to various preferred embodiments of the present disclosure are explained. As each of various elements recited in the claims, various other elements having configurations or functions described in the claims can be also used.
In the above-mentioned embodiment, the substrate processing apparatuses 1, 1A to 1C are examples of a substrate processing apparatus, the assistance device 4 is an example of an assistance device, the deviation degree acquirer is an example of a deviation degree acquirer, the level determiner 44 and the instruction generator 45 are examples of an assistance information generator, the subject determiner 42 is an example of a subject determiner, the necessity value calculator 43 is an example of a necessity value calculator, and the CPU and the memory of the assistance device 4 are examples of a computer.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2022-006753 | Jan 2022 | JP | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2022/046740 | 12/19/2022 | WO |
