KR20230113126A - Management analysis apparatus of industrial furance - Google Patents

Abstract

Work related to verifying the operation of an industrial furnace should be automated as much as possible to be performed simply. A management analysis device for an industrial furnace (200) comprises: a measurement logging data creation part sequentially receiving sensor data as data from a sensor measuring the conditions of an industrial furnace (100) to create measurement logging data arranged with the value of the sensor data in time-series; an extracted data creation part creating extracted data as data obtained by extracting a part subjected to prescribed treatment in the industrial furnace (100) from the measurement logging data; and a difference data calculation part comparing the two extracted data in which treatment conditions are mutually matched to calculate differential data showing the degree of difference.

Description

Industrial furnace management analysis device {MANAGEMENT ANALYSIS APPARATUS OF INDUSTRIAL FURANCE}

The present invention relates to an industrial furnace management and analysis device or the like that performs various treatments such as degreasing and sintering on an object to be treated stored in a furnace.

Conventionally, as shown in Patent Document 1, processes such as sintering, semi-sintering, firing, degreasing, soldering, metallization, quenching, solution treatment, tempering, and annealing have been performed in industrial furnaces.

During the processing, the operating state of the industrial furnace is measured by various sensors such as a control thermocouple, heater power, vacuum gauge, and the like, and the values are logged. One of the purposes of this logging is to pursue the cause when an abnormality is confirmed in a process object in a certain process.

By the way, when checking recorded logging data (hereinafter, also referred to as measurement logging data), in order to compare and verify the past normal processing record, it is necessary to carry out the following, for example.

(1) Manually edit the measurement logging data that is being recorded continuously, and cut it out by the date and time when each process was performed.

(2) Comparison is performed using table calculation software or the like for the cut out data, and an abnormal point is identified.

Japanese Unexamined Patent Publication No. 2000-17305

However, manually editing the measurement logging data is a cumbersome task and a burden on the operator as the number of comparison objects increases. In addition, it is difficult to understand visually because of numerical processing.

The main object of the present invention is to provide an industrial furnace management and analysis device or the like that can reduce the burden on workers by automating these operations and enabling simple comparison and verification.

That is, the industrial furnace management and analysis device according to the present invention sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace, and generates measurement logging data in which the values of the sensor data are arranged in time series. A logging data generator and a cutout data generator that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in an industrial furnace, from measurement logging data, and two cutout data whose processing conditions match each other. Compare , and a difference data calculation unit that calculates difference data representing the degree of the difference.

In such a case, conventional manual work or checking and comparison of measurement and logging data using separate table calculation software or the like becomes unnecessary, and work time can be significantly reduced and efficiency can be promoted. Cut-out of logging data can be performed just by selecting batch data, reducing work time.

1 is an overall schematic diagram of an industrial processing system in one embodiment of the present invention.
2 is a data explanatory diagram showing an example of a processing recipe in the same embodiment.
3 is a graph showing changes in temperature and pressure in a series of processing examples in the same embodiment.
Fig. 4 is a functional block diagram of the management analysis device in the embodiment.
Fig. 5 is a flowchart showing the operation of the management analysis device in the embodiment.
6 is a data explanatory diagram showing an example of measurement logging data in the embodiment.
Fig. 7 is a flowchart showing the operation of the management analysis device in the embodiment.
8 is a data explanatory diagram showing an example of arrangement data in the embodiment.
Fig. 9 is a flowchart showing the operation of the management analysis device in the embodiment.
Fig. 10 is a screen display diagram showing an example of an output display by a two-data comparison function in the embodiment.
Fig. 11 is a flowchart showing the operation of the management analysis device in the embodiment.
Fig. 12 is a screen display diagram showing an output display example by a multi-data characteristic value comparison function in the same embodiment.

EMBODIMENT OF THE INVENTION Hereinafter, one embodiment of this invention is described with reference to drawings.

As shown in FIG. 1 , the management analysis device 200 according to the present embodiment monitors the operating state of the industrial furnace 100 and constitutes the industrial processing system A together with the industrial furnace 100 .

Therefore, prior to the description of this management analysis device 200, first, the industrial furnace 100 will be briefly described.

This industrial furnace 100 performs, for example, industrial processing such as degreasing treatment and sintering treatment on the object to be processed W, and the pressure vessel 1 and the inside of the pressure vessel 1 A heat insulating material (2) constituting the arranged casing shape, a tight box (3) disposed inside the heat insulating material (2), a heater (4) for heating the inside of the heat insulating material (2), and a gas in the pressure vessel (1) a gas stirring mechanism 5 for agitating the gas, a gas supply mechanism 6 for supplying gas into the pressure container 1 and the tight box 3, and discharging gas from the pressure container 1 and the tight box 3 and a gas discharge mechanism 7 for controlling, a sensor (not shown) for sensing the state of each of the above-mentioned parts, and a control device 8 for controlling the operation of each of the above-mentioned parts for processing such as degreasing and sintering.

Each part is described in detail below.

The pressure vessel 1 can be hermetically sealed, including, for example, a cylindrical vessel body 11 and vessel lids 12 provided at both ends of the vessel body 11 . In this embodiment, a container cooling mechanism 9 for cooling the wall of the pressure container 1 is provided.

This container cooling mechanism 9 has a refrigerant passage 91 formed inside the wall, and a refrigerant circuit 92 through which a refrigerant for cooling (here, liquid such as water) flows through the refrigerant passage 91. ) is composed of The refrigerant passage 91 is formed on the inner and outer wall surfaces of the wall to have a double structure consisting of an inner wall and an outer wall. The refrigerant circuit 92 includes a refrigerant supply pipe 921 having one end connected to a refrigerant inlet formed in a refrigerant flow passage 91 and a refrigerant pump having a discharge port connected to the other end of the refrigerant supply pipe 921 to pump refrigerant ( 922) and a refrigerant outlet pipe 923 having one end connected to a refrigerant outlet formed in the refrigerant flow path 91. In this embodiment, the other end of the refrigerant outflow pipe 923 is connected to the inlet of the refrigerant pump 922 so that the refrigerant circulates. In addition, in order to cool the refrigerant in the circulation process, a radiator 924 having a fin or the like is provided on the refrigerant outlet pipe 923 (or the refrigerant supply pipe 921), and on the refrigerant supply pipe 921, A valve 925 for controlling the circulation of the refrigerant is provided. In addition, this refrigerant circuit may be of a discharge type that constantly sends fresh refrigerant to the refrigerant flow path, rather than a circulation type.

The heat insulating material 2 is, for example, in the shape of a casing including a cylindrical heat insulating material main body 21 and heat insulating material lids 22 provided at both ends thereof, and is made of a heat-resistant material such as graphite felt or graphite foil. It consists of This heat insulating lid 22 is configured to be able to be opened and closed from the outside of the pressure container 1 by an opening and closing mechanism not shown.

The tight box 3 can be hermetically accommodating the object W to be processed, and is disposed inside the heat insulating material 2 . More specifically, this tight box 3 is composed of graphite or the like, and is provided with a tight box main body 31 forming a cylinder and tight box lids 32 formed on both ends thereof. This tight box lid 32 is structured so that it can be opened and closed from the outside of the pressure vessel 1 by an opening and closing mechanism not shown.

The heater 4 is, for example, rod-shaped, made of graphite, which generates heat by passing an electric current, and a plurality of heaters 4 are intermittently arranged inside the heat insulating material 2 so as to surround the periphery of the tight box 3 .

The gas agitation mechanism 5 includes a fan 51 disposed in the pressure container 1 and a fan motor 52 that drives the fan 51, and rotation of the fan 51 generates pressure. It stirs the gas in the container 1 and is used for forced cooling or equal heating.

The gas supply mechanism 6 includes a gas source 61 for storing, generating, or both of nitrogen, argon, hydrogen, carbon monoxide, helium, methane, and the like, and the gas source 61 in a pressure vessel 1 A first gas supply pipe 62 to connect, a second gas supply pipe 63 to connect the gas source 61 to the tight box 3, and an on-off valve 64 formed on each of the gas supply pipes 62 and 63, respectively , 65). And it is comprised so that gas supply and gas supply stoppage to the pressure container 1 and the tight box 3 can be performed independently by opening and closing these on-off valves 64 and 65. Since this heat insulating material 2 is not completely airtight, gas is introduce|transduced also into the heat insulating material 2 by introducing gas into the pressure vessel 1.

In addition, a plurality of gas sources 61 may be provided so that a plurality of types of gases can be introduced into the pressure container 1 and the tight box 3, or a gas supply pipe is connected to the heat insulating material 2, and the heat insulating material 2 ) into the pressure vessel 1.

The gas discharge mechanism 7 includes an exhaust pump 71 and a first gas discharge pipe 72 connecting the pressure vessel 1 to the suction port of the exhaust pump 71 to discharge the gas in the pressure vessel 1. and a second gas discharge pipe 74 connecting the tight box 3 to the inlet of the exhaust pump 71 to discharge the gas inside the tight box 3, and a gas discharge pipe 72, 73, respectively. It is provided with on-off valves 74 and 75. And it is comprised so that gas discharge|emission from the pressure container 1 and the tight box 3 and gas discharge stop can be performed independently by opening and closing these on-off valves 74 and 75. Since the heat insulating material 2 is not completely airtight, gas is discharged also from the inside of the heat insulating material 2 by discharging gas from the pressure vessel 1. In Fig. 1, reference numerals 76 and 77 denote a wax tank and a wax trap provided on the second discharge pipe 74.

As the sensors (not shown), a pressure sensor, a temperature sensor, a current sensor (voltage sensor), a flow rate sensor, and the like are provided, and the operating state of each part of the industrial furnace 100 can be detected.

The pressure sensor is installed at a required point so as to be able to detect the pressure in the pressure container 1, in the tight box 3, in the vicinity of the intake port of the exhaust pump 71, and the like.

Temperature sensors are installed at required points so as to be able to detect respective temperatures of the inside of the pressure container 1, the heat insulating material 2, the refrigerant, and the like.

The current sensor (voltage sensor) measures the operating current (and voltage) or power of the heater 4, each pump 71, 922, each valve 64, 65, 74, 75, 925, and the fan motor 52. It is installed at the required point so that each can be detected.

The said control device 8 uses PLC, for example, and is one type of computer provided with CPU, memory, a transmission/reception port, etc. Then, the receiving port receives the sensor data from the respective sensors, and the heater 4, the pumps 71 and 922, the valves 64, 65, 74, 75, and 925, and the fan motor ( 52), etc., to control each part so that processing such as degreasing and sintering according to a predetermined recipe is performed.

A recipe is data representing processing conditions such as pressure and temperature change over time, gas introduction and discharge timing, etc. Here, it is basically applied to one batch from temperature rise to cooling. An example of the recipe is shown in FIG. 2 .

In this embodiment, a plurality of predetermined recipes are stored in a predetermined area of the memory, and the user can select a desired recipe by inputting a recipe number attached to each recipe.

Next, the operation of each part based on the recipe will be briefly described with particular attention to pressure and temperature. 3 is a graph showing changes in pressure and temperature according to this recipe.

First, the object W to be processed is placed in the tight box 3 . The object W to be processed here is, for example, a so-called green body obtained by kneading metal powder with a binder and injection molding.

Then, after closing each lid, when the user selects a recipe and gives a start instruction, the controller 8 operates the exhaust pump 71 according to the recipe and opens the valves 74 and 75, The inside of the box 3 and the inside of the pressure vessel 1 (including the heat insulating material 2) are initially evacuated.

At the same time, the control device 8 energizes the heater 4 and raises the internal temperature of the pressure vessel 1 .

The control device 8 receives the output data (sensor data) from each of the sensors, and the detected temperature in the pressure vessel 1 (or the detected temperature of the heat insulating material 2) among them is determined by the recipe. When the temperature is reached, the degreasing treatment is started.

This degreasing process consists of a 1st process - a 3rd process, for example.

In the first step, the control device 8 controls the power supplied to the heater 4 so that the detected temperature in the pressure container is maintained at the set temperature indicated by the recipe for only the set period indicated by the recipe. At the same time, for a certain period of time, the control device 8 controls the gas introduction valves 64 and 65 and the exhaust valve so that the detected pressures in the tight box 3 and in the pressure container 1 become the set pressure indicated by the recipe. The opening of 74 and 75 is controlled to exhaust decomposition gas generated from the object W while introducing degreasing gas.

In the second step, the control device 8 controls the supply power to the heater 4 in order to raise the detected temperature in the pressure container to the next set temperature indicated by the recipe.

In the third step, the gas introduction valves 64 and 65 are closed and exhausted so that the detected pressures in the tight box 3 and in the pressure container 1 become the low set pressure indicated by the recipe for only the set period indicated by the recipe. The valves 74 and 75 are opened to degas. During this time, the control device 8 keeps the temperature constant.

Next, the control device 8 starts the sintering process.

This sintering process consists of a 1st process and a 2nd process, for example.

In the first step, the control device 8 controls the supply power to the heater 4 in order to raise the detected temperature in the pressure container to the set temperature indicated by the recipe.

In the second process, the supply power to the heater 4 is controlled so that the set temperature is maintained for only the set period indicated by the recipe.

During each of these steps, the control device 8 controls the opening of the exhaust valves 74 and 75 so that the detected pressure becomes the set pressure indicated by the recipe.

When the sintering process ends in this way, the control device 8 starts the cooling process.

In this cooling step, the control device 8 stops supplying electric power to the heater 4, operates the fan 51, and waits for the object W to be cooled.

And, as described above, the industrial processing system A of this embodiment further includes a management analysis device 200 connected to the control device 8 by wire or wirelessly.

This management analysis device 200 is a so-called computer composed of a CPU, memory, communication interface, etc., and each unit cooperates according to a program (software) stored in the memory, as shown in FIG. 4, a measurement logging data generation unit, Functions as an arrangement data generating unit, a cutout data generating unit, a difference data calculating unit, a feature value calculating unit, an output unit, and the like are exhibited. In addition, this management and analysis device 200 does not have to be a physically integral body, and here it is composed of a server and a client terminal connected to each other wirelessly or by wire.

In the following, the operation of this management analysis device 200 will be described, concurrently with the explanation of the function of each unit described above.

First, as shown in FIG. 5 , the measurement logging data generation unit acquires sensor data, which is data from each of the sensors, from the control device 8 at predetermined sampling times (here, for example, every 30 seconds) (step S11, S12), the values of these sensor data are arranged in time series, and measurement logging data in which received time information is added to each sensor data is generated (step S13). This measurement logging data is sequentially generated on a daily basis, for example (step S14), and is stored in a measurement logging data storage unit set in a predetermined area of the memory (step S15). An example of measurement logging data is shown in FIG. 6 .

In addition, each sensor data may be directly received from these via a network by making each sensor into IoT, etc., without intervening a management apparatus.

On the other hand, as shown in FIG. 7 , the batch data generation unit receives a recipe and information on the time when the recipe was executed from the control device 8 (step S21), and based on these, the processing conditions for each process. Arrangement data, which is data including data and time information, is generated (step S22).

More specifically, this batch data generation unit extracts one process (for example, degreasing process) from a recipe, and not only the start time and end time of that process, but also each process included in the process (as defined in the claims). processing conditions and start and end times in each section) are specified, and batch data representing them (see FIG. 8) is generated. The processing conditions herein refer to the processing content indicated in the recipe, and refers to a set temperature, a set pressure, a gas type, and the like.

Then, the batch data generation unit stores the generated batch data in a batch data storage unit set in a predetermined area of the memory.

Further, these measurement logging data generating units, measurement logging data storage units, batch data generating units, and batch data storage units are provided in the server.

<2 data comparison function>

In this state, when the user makes a request input for comparing the two data from the client terminal, as shown in Fig. 9, the client terminal prompts for a designation input of the process to be verified (step S31).

Therefore, the user specifies and inputs the processing performed on the problematic object W, for example, by the processing time, type of processing (degreasing processing, sintering processing, etc.), recipe number, or the like, or the batch processing described above. When data is designated, the cutout data generation unit extracts the batch data corresponding to the designated process from the batch data storage unit (step S32).

Then, the cutting data generation unit extracts measurement logging data including data from the start time to the end time of the processing recorded in the batch data from the measurement logging data storage unit (step S32), and the measurement logging Cutout data obtained by cutting out the data from the start time to the end time is generated from the data (step S33).

Further, the cutting data generation unit searches for and extracts other batch data having the same processing conditions as the processing conditions recorded in the batch data based on the type of processing, recipe number, etc. (step S34), and the extracted other batch data , measurement logging data is extracted in the same manner as above (step S35).

And this measurement logging data is cut out with other batch data, and cut-out data serving as a comparison standard are generated (step S36).

Next, the difference data extraction unit compares these two pieces of cut data and calculates difference data indicating the degree of the difference (step S37).

The "degree of difference" here is, for example, the absolute value of the difference between the values of predetermined sensor data (for example, heater power) at each sampling time in two cut-out data. In addition, differences by various statistical comparison techniques, such as absolute values of average differences of a series of a plurality of sampling times, differences in square averages, and differences in areas formed by each cutout data when graphed, can be used.

Next, the output unit outputs the two cutout data so that comparison is possible, and outputs the range corresponding to the difference data exceeding the predetermined threshold so that it can be distinguished from other ranges that are not otherwise (step S38). In addition, the threshold value can be set, changed, etc. by the user from the client terminal.

Specifically, when a user requests comparison of one sensor data (for example, heater power), the output unit converts the two cut-out data for the sensor data, for example, as shown in FIG. 10 . , It is graphed and displayed overlapping on the same coordinates, and a section corresponding to a process in which the difference data value exceeds a predetermined threshold value is highlighted.

The above is the two-data comparison function.

And with such a function, for example, when a batch (treatment) of poor quality occurs in the sintering process, it can be easily compared with past batches heat treated with the same recipe, and the differences are quickly extracted. so that it can be verified.

In addition, the two data comparison may be performed not in a processing unit but in a smaller unit, for example, a process unit, or a larger unit, for example, a series of treatments performed on one object to be treated (eg, degreasing/sintering). Cooling treatment) may be used as a unit.

It is also possible to display the value of the difference data together with the graph on the same screen.

It is also possible to divide the cut data into two as a numerical table without making a graph and display them on the same screen so that they can be compared.

When there is data exceeding the threshold value in one process, it is okay to highlight all of the process.

Further, for example, by performing a selection operation such as clicking on a highlighted portion in a graph, the values of each cutout data of that portion may be displayed in tabular form.

In addition, as long as it is an aspect in which a process exceeding a threshold value can be distinguished, it may be output in any format such as a graph or a table.

Moreover, it does not matter even if it compares not the process comparison in the same industrial furnace, but a comparison with the process in another (for example, the same performance) industrial furnace.

<Multi-data feature value comparison function>

On the other hand, when a request input for multi-data feature value comparison is made from the client terminal, as shown in Fig. 11, the client terminal prompts for designation input such as the process to be compared, the process in the process, and the process conditions. (step S41).

Therefore, when the user designates and inputs the desired processing, process, processing conditions, etc., including the recipe number, etc., the cut data generation unit extracts a plurality of batch data meeting the specified conditions from the batch data storage unit (step S42), The designated process is listed on the screen for each batch data (step S43).

Next, when the user selects a plurality of desired items from these processes, the cut data generation unit generates cut data obtained by cutting out the measurement logging data between the start time and the end time of the process recorded in each batch data ( Step S44).

Next, the feature value calculation unit calculates feature values of each cut-out data (step S45). As the characteristic value, "data value after a predetermined time from the start of the process", "data value before a predetermined time from the start of the process", "maximum or minimum value of data in the process", "data value in the process Average value” and the like, and it is configured so that the user can select among them.

Next, as shown in Fig. 12, the output unit outputs the characteristic value of each cutout data so that comparison is possible, such as displaying a graph in time series on the screen of the client terminal (step S46).

The above is the multi-data feature value comparison function.

According to such a configuration, only data meeting specific conditions such as "same pattern, same process" and "keep at 1800°C for 30 minutes or longer" can be extracted by terminating the processing.

In addition, since data under the same processing conditions can be extracted from the accumulated measurement logging data, and feature values of each data can be calculated and plotted, long-term trends can be easily grasped. As a result, it is possible to confirm items highly correlated with wear and tear of the industrial furnace 100 or deterioration of parts, or to verify that there is no extremely deviated data.

In addition, the multi-data feature value comparison may be performed not in a process unit but in a processing unit, for example, and a series of treatments performed on a larger unit, for example, one object to be treated (eg, degreasing/sintering/cooling). treatment) may be performed in units.

In addition, it does not matter if each feature value is displayed numerically on a graph, and each feature value can be displayed on the same screen in the form of a table.

Each characteristic value may be displayed not only in time series, but also in comparison with processing in other industrial furnaces (for example, of the same performance).

The characteristics of the management analysis device 200 described above are summarized as follows. In addition, the "process" described in this feature refers to various industrial processes performed on the object to be treated, and any of the "processes", "processes", "series of processes", and other predetermined unit processes in the above embodiment is also considerable

(1) This management and analysis device 200 sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace 100, and generates measurement and logging data in which the values of this sensor data are arranged in time series. A measurement logging data generator, a cutout data generator that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in the industrial furnace 100, from the measurement logging data, and two cutouts whose processing conditions match each other It is characterized by comprising a difference data calculation unit that compares the data and calculates difference data representing the degree of the difference.

In such a case, conventional manual work or checking and comparison of measurement and logging data using separate table calculation software or the like becomes unnecessary, and work time can be significantly reduced and efficiency can be promoted.

(2) If the cutting data generation unit receives the designation of one cutting data and extracts other cutting data that meets the processing conditions, the cutting data to be compared is automatically extracted, so work efficiency can be further improved. there will be

(3) Further comprising a batch data generation unit for generating batch data, which is data including processing conditions and start and end times for each process, wherein the cutout data generator comprises a It is preferable to truncate metrology logging data to generate cutout data.

In such a case, processing conditions can be specified by batch data, and usability can be improved.

(4) The batch generation unit specifies processing conditions and start and end times in each predetermined section (corresponding to the above-mentioned process) in one process, respectively, generates batch data representing these, and difference data The calculation unit is more suitable if it calculates difference data for each corresponding section in the two cut-out data.

In such a case, comparison can be performed in units of sections in which the processing is further divided, and more precise verification is possible.

(5) In order to make the comparison easier to understand, an output unit for outputting the two cutout data in a comparable manner and outputting a section corresponding to the difference data exceeding a predetermined threshold in a distinguishable manner from other sections is additionally provided. It is desirable to have.

(6) It is more preferable that the output unit displays a graph of the two cutout data superimposed on the same coordinates and highlights a section corresponding to difference data exceeding a predetermined threshold.

(7) A measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace 100, and generates measurement logging data in which the values of the sensor data are arranged in time series, and measurement logging From the data, a cutout data generating unit that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in the industrial furnace 100, and a plurality of cutout data whose processing conditions coincide with each other. Predetermined calculation is performed Therefore, if the management analysis device 200 of the industrial furnace 100 is provided with a feature value calculation unit for calculating feature values of each cutout data, feature values of a plurality of data are automatically calculated under the same processing conditions. For example, long-term trends can be easily grasped by outputting them in time series.

(8) Specifically, it is preferable to further include an output unit that outputs the feature value of each of the above cut-out data so that comparison is possible.

(9) The same effect can be exhibited even with the following configuration.

From the measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace 100, and generates measurement logging data in which the values of the sensor data are arranged in time series, and the measurement logging data, A cut-out data generating unit that generates cut-out data, which is data obtained by cutting out a portion where a predetermined process has been performed in the industrial furnace 100, and a difference between two cut-out data whose processing conditions match each other, and which indicates the degree of difference A program for a management analysis device characterized in that it exhibits a function as a difference data calculation unit that calculates data.

(10) The same effect can be exhibited even with the following configuration.

From the measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace 100, and generates measurement logging data in which the values of the sensor data are arranged in time series, and the measurement logging data, A cut-out data generating unit that generates cut-out data, which is data obtained by cutting out a portion where a predetermined process has been performed in the industrial furnace 100, and performs a predetermined operation on each of a plurality of cut-out data whose processing conditions coincide with each other, A program for a management analysis device characterized in that it exhibits a function as a feature value calculation unit that calculates feature values of cut-out data.

200: management analysis device
100: industrial furnace

Claims (10)

A measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of the industrial furnace, and generates measurement logging data in which the values of the sensor data are arranged in time series.
A cut-out data generation unit for generating cut-out data, which is data obtained by cutting out a portion where a predetermined process has been performed in an industrial furnace, from measurement logging data;
An industrial furnace management and analysis device characterized by comprising a difference data calculation unit that compares two pieces of cutout data whose processing conditions match each other and calculates difference data representing the degree of the difference. According to claim 1,
The cutting-out data generation unit receives designation of one cut-out data and extracts other cut-out data meeting the processing condition. According to claim 1,
Further comprising a batch data generation unit for generating batch data, which is data including process conditions, start time and end time for each process;
The cutting data generating unit cuts measurement logging data between a start time and an end time indicated by the batch data to generate cutout data. According to claim 3,
The batch data generation unit specifies processing conditions and start and end times in each predetermined section in one process, respectively, and generates batch data representing these;
The difference data calculation unit calculates difference data for each corresponding section in two cut-out data. According to any one of claims 1 to 4,
An industrial furnace management and analysis device further comprising an output unit for outputting two cutout data in a comparable manner and outputting a section corresponding to difference data exceeding a predetermined threshold in a distinguishable manner from other sections. According to claim 5,
The output unit displays a graph of the two cutout data superimposed on the same coordinates, and highlights a section corresponding to the difference data exceeding a predetermined threshold value. a measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of an industrial furnace, and generates measurement logging data in which values of the sensor data are arranged in time series;
a cutout data generation unit that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in an industrial furnace, from measurement logging data;
An industrial furnace management and analysis device characterized by comprising: a feature value calculation unit that performs a predetermined operation on each of a plurality of cut-out data whose processing conditions match each other and calculates a feature value of each cut-out data. According to claim 7,
An industrial furnace management and analysis device further comprising an output unit for outputting characteristic values of the respective cutting data in a comparable manner. a measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of an industrial furnace, and generates measurement logging data in which values of the sensor data are arranged in time series;
a cutout data generation unit that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in an industrial furnace, from measurement logging data;
A program stored in a medium characterized by causing an industrial furnace management and analysis device to exhibit a function as a difference data calculation unit that compares two cutout data whose processing conditions match each other and calculates difference data indicating the degree of the difference. a measurement logging data generation unit that sequentially receives sensor data, which is data from sensors that measure the state of an industrial furnace, and generates measurement logging data in which values of the sensor data are arranged in time series;
a cutout data generation unit that generates cutout data, which is data obtained by cutting out a portion where a predetermined process has been performed in an industrial furnace, from measurement logging data;
A medium characterized in that an industrial furnace management and analysis device exhibits a function as a feature value calculation unit that performs a predetermined operation on each of a plurality of cut-out data whose processing conditions match each other and calculates a feature value of each cut-out data. Programs stored in .

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