Industrial furnace control and analysis equipment

Abstract

To provide a control analyzer of an industrial furnace automatizing an operation related to the operation verification of an industrial furnace as much as possible to easily execute comparative verification.SOLUTION: A control analyzer comprises: a measurement logging data creation part sequentially receiving sensor data as data from a sensor measuring the conditions of an industrial furnace 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 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 the difference.SELECTED DRAWING: Figure 4

Description

Technical Field

[0003]

[0001] The present invention relates to a management analysis device for an industrial furnace that performs various processes such as degreasing and sintering on a workpiece accommodated in the furnace.

Background Art

[0002] Conventionally, as shown in Patent Document 1, in an industrial furnace, processes such as sintering, semi-sintering, firing, degreasing, brazing, metallizing, quenching, vitrification treatment, annealing, and tempering are performed.

[0003] During that process, the operating state of the industrial furnace is measured by various sensors, such as a control thermocouple, heater power, and vacuum gauge, and the values are logged. One of the purposes of this logging is to pursue the cause when an abnormality is confirmed in the workpiece during a certain process.

[0004] By the way, when checking the recorded logging data (hereinafter also referred to as measurement logging data), for example, the following needs to be done in order to compare and verify it with past normal process records. (1) Manually edit the continuously recorded measurement logging data and cut it out by the date and time when each process was performed. (2) Compare the cut-out data using spreadsheet software or the like to identify abnormal locations.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, manually editing measurement logging data is a more complicated task as the number of comparison targets increases, which burdens the operator. Also, it is difficult to visually understand due to numerical processing.

[0007] The primary objective of this invention is to provide an industrial furnace management and analysis device that can reduce the burden on workers by automating these tasks and facilitating comparative verification. [Means for solving the problem]

[0008] In other words, the industrial furnace management and analysis device according to the present invention is characterized by comprising: a measurement logging data generation unit that sequentially receives sensor data, which is data from a sensor that measures the state of an industrial furnace, and generates measurement logging data in which the values ​​of this sensor data are arranged in a time series; an extraction data generation unit that generates extraction data, which is data extracted from the measurement logging data in which a predetermined process has been performed in the industrial furnace; and a difference data calculation unit that compares two sets of extraction data whose processing conditions match and calculates difference data that indicates the degree of the difference. [Effects of the Invention]

[0009] With this system, the need for manual checking and comparison of measurement logging data, or using separate spreadsheet software, is eliminated, significantly reducing work time and promoting efficiency. Logging data can be extracted simply by selecting batch data, further reducing work time. [Brief explanation of the drawing]

[0010] [Figure 1] This is a schematic diagram of an industrial processing system in one embodiment of the present invention. [Figure 2] This is a data diagram illustrating an example of a processing recipe in the same embodiment. [Figure 3] This graph shows the changes in temperature and pressure in a series of processing examples in the same embodiment. [Figure 4] This is a functional block diagram of the control and analysis device in the same embodiment. [Figure 5]This is a flowchart showing the operation of the control and analysis device in the same embodiment. [Figure 6] This is a data diagram illustrating an example of measurement logging data in the same embodiment. [Figure 7] This is a flowchart showing the operation of the control and analysis device in the same embodiment. [Figure 8] This is a data diagram illustrating an example of batch data in the same embodiment. [Figure 9] This is a flowchart showing the operation of the control and analysis device in the same embodiment. [Figure 10] This is a screen display diagram showing an example of output display using the two-data comparison function in the same embodiment. [Figure 11] This is a flowchart showing the operation of the control and analysis device in the same embodiment. [Figure 12] This is a screen display diagram showing an example of output display using the multi-data feature value comparison function in the same embodiment. [Modes for carrying out the invention]

[0011] Hereinafter, one embodiment of the present invention will be described with reference to the drawings.

[0012] As shown in Figure 1, the control and analysis device 200 according to this embodiment monitors the operating status of the industrial furnace 100 and, together with the industrial furnace 100, constitutes the industrial processing system A. Therefore, before explaining the control and analysis device 200, let me first give a brief explanation of the industrial furnace 100.

[0013] This industrial furnace 100 performs industrial processes such as degreasing and sintering on the workpiece W, and includes a pressure vessel 1, a housing-shaped heat insulator 2 disposed inside the pressure vessel 1, a tight box 3 disposed inside the heat insulator 2, a heater 4 for raising the temperature inside the heat insulator 2, a gas stirring mechanism 5 for stirring the gas inside the pressure vessel 1, a gas supply mechanism 6 for supplying gas into the pressure vessel 1 and the tight box 3, a gas discharge mechanism 7 for discharging gas from the pressure vessel 1 and the tight box 3, a sensor (not shown) for sensing the states of the respective parts, and a control device 8 for controlling the operations of the respective parts for degreasing, sintering and other processes. Each part will be described in detail below.

[0014] The pressure vessel 1 is a sealable one 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 vessel cooling mechanism 9 for cooling the wall of the pressure vessel 1 is provided.

[0015] This vessel cooling mechanism 9 is composed of a refrigerant flow passage 91 formed inside the wall and a refrigerant circuit 92 for circulating a cooling refrigerant (here, a liquid such as water) in the refrigerant flow passage 91. The refrigerant flow passage 91 has a double structure consisting of an inner wall and an outer wall of the wall, and is formed between the inner and outer walls. The refrigerant circuit 92 includes a refrigerant supply pipe 921 having one end connected to a refrigerant inlet provided in the refrigerant flow passage 91, a refrigerant pump 922 having a discharge port connected to the other end of the refrigerant supply pipe 921 for pumping the refrigerant, and a refrigerant outflow pipe 923 having one end connected to a refrigerant outlet provided in the refrigerant flow passage 91. In this embodiment, the other end of the refrigerant outflow pipe 923 is connected to the suction port of the refrigerant pump 922 so that the refrigerant circulates. Also, in order to cool the refrigerant during the circulation process, a radiator 924 having fins or the like is provided on the refrigerant outflow pipe 923 (or the refrigerant supply pipe 921), and a valve 925 for controlling the flow of the refrigerant is provided on the refrigerant supply pipe 921. Note that this refrigerant circuit may be a non-circulating type that always feeds new refrigerant into the refrigerant flow passage instead of a circulating type.

[0016] The heat insulating material 2 is in the form of a housing having, for example, 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. The heat insulating material lid 22 is configured to be opened and closed from the outside of the pressure vessel 1 by an opening and closing mechanism not shown.

[0017] The tight box 3 is capable of being sealed to accommodate the workpiece W, and is disposed inside the heat insulating material 2. More specifically, the tight box 3 is made of graphite or the like, and has a cylindrical tight box main body 31 and tight box lids 32 provided at both ends thereof. The tight box lid 32 is configured to be opened and closed from the outside of the pressure vessel 1 by an opening and closing mechanism not shown.

[0018] The heater 4 generates heat by passing an electric current therethrough, and is, for example, a rod-shaped one made of graphite. A plurality of heaters 4 are intermittently arranged inside the heat insulating material 2 so as to surround the tight box 3.

[0019] The gas stirring mechanism 5 includes a fan 51 disposed inside the pressure vessel 1 and a fan motor 52 for driving the fan 5. By the rotation of the fan 51, the gas inside the pressure vessel 1 is stirred and used for forced cooling or uniform heating.

[0020] The gas supply mechanism 6 includes a gas source 61 for storing, generating or both storing and generating nitrogen, argon, hydrogen, carbon monoxide, helium, methane, etc., a first gas supply pipe 62 connecting the gas source 61 to the pressure vessel 1, a second gas supply pipe 63 connecting the gas source 61 to the tight box 3, and opening and closing valves 64, 65 provided in the respective gas supply pipes 62, 63. By opening and closing these opening and closing valves 64, 65, gas supply to and gas supply stop from the pressure vessel 1 and the tight box 3 can be independently performed. Since the heat insulating material 2 is not completely airtight, gas is introduced into the heat insulating material 2 by introducing gas into the pressure vessel 1.

[0021] Alternatively, multiple gas sources 61 may be provided to allow multiple types of gas to be introduced into the pressure vessel 1 and the tight box 3, or a gas supply pipe may be connected to the insulation material 2 so that gas is introduced from the insulation material 2 into the pressure vessel 1.

[0022] The gas discharge mechanism 7 comprises an exhaust pump 71, a first gas discharge pipe 72 connecting the pressure vessel 1 to the inlet of the exhaust pump 71 to discharge gas from the pressure vessel 1, a second gas discharge pipe 73 connecting the tight box 3 to the inlet of the exhaust pump 71 to discharge gas from the tight box 3, and on / off valves 74 and 75 provided on each gas discharge pipe 72 and 73, respectively. By opening and closing these on / off valves, the discharge of gas from the pressure vessel 1 and the tight box 3 and the stopping of gas discharge can be performed independently. Since the insulation material 2 is not completely airtight, gas is discharged from within the insulation material 2 when gas is discharged from the pressure vessel 1. In Figure 1, reference numerals 76 and 77 indicate a wax reservoir tank and a wax trap provided on the second discharge pipe 73.

[0023] Sensors (not shown) such as pressure sensors, temperature sensors, current sensors (voltage sensors), and flow sensors are provided to detect the operating status of various parts of the industrial furnace 100. Pressure sensors are installed in the required locations to detect pressure, such as inside the pressure vessel 1, inside the tight box 3, and near the intake port of the exhaust pump 71. Temperature sensors are installed at the necessary locations to detect the temperature of the pressure vessel 1, the insulation material 2, the refrigerant, etc.

[0024] Current sensors (voltage sensors) are installed at the required locations to detect the operating current (and voltage) and power of the heater 4, each pump 71, 922, each valve 64, 65, 74, 75, 925, fan motor 52, etc.

[0025] The control device 8 is, for example, a PLC, and is a type of computer equipped with a CPU, memory, transmission and reception ports, etc. The receiving port receives sensor data from each of the sensors, and the transmitting port transmits drive signals to the heater 4, pumps 71, 922, valves 64, 65, 74, 75, 925, fan motor 52, etc., controlling each part so that degreasing, sintering, and other processes are carried out according to a predetermined recipe.

[0026] A recipe is data that specifies processing conditions such as the time-dependent changes in pressure and temperature, and the timing of gas introduction and discharge. In this context, it is basically applied to one batch from heating to cooling. An example of a recipe is shown in Figure 2.

[0027] In this embodiment, a predetermined number of recipes are stored in a specific area of ​​memory, and the user can select the desired recipe by entering the recipe number assigned to each recipe.

[0028] Next, we will briefly explain the operation of each part according to the recipe, paying particular attention to pressure and temperature. Figure 3 is a graph showing the changes in pressure and temperature according to this recipe.

[0029] First, the workpiece W is placed inside the tight box 3. Here, the workpiece W is, for example, a so-called green body, which is made by mixing metal powder with a binder and then injection molding it.

[0030] After closing each lid, when the user selects a recipe and issues a start command, the control device 8 operates the exhaust pump 71 and opens valves 74 and 75 according to the recipe, performing an initial vacuum evacuation of the inside of the tight box 3 and the pressure vessel 1 (including the insulation material 2). At the same time, the control device 8 energizes the heater 4, raising the internal temperature of the pressure vessel 1.

[0031] The control device 8 receives output data (sensor data) from each of the sensors, and when the detected temperature inside the pressure vessel 1 (or the detected temperature of the insulation material 2) reaches a predetermined temperature as shown in the recipe, it starts the degreasing process. This degreasing process consists of, for example, three steps.

[0032] In the first step, the control device 8 controls the power supplied to the heater 4 so that the detected temperature inside the pressure vessel is maintained at the set temperature indicated in the recipe for the duration specified in the recipe. Simultaneously, during this specified period, the control device 8 controls the opening of the gas introduction valves 64, 65 and the exhaust valves 73, 74 so that the detected pressure inside the tight box 3 and the pressure vessel 1 becomes the set pressure indicated in the recipe, thereby introducing degreasing gas while exhausting the decomposition gas generated from the material to be processed W. In the second step, the control device 8 controls the power supplied to the heater 4 in order to raise the detected temperature inside the pressure vessel to the next set temperature indicated in the recipe.

[0033] In the third step, gas introduction valves 64 and 65 are closed and exhaust valves 73 and 74 are opened to degas the system so that the detected pressure inside the tight box 3 and pressure vessel 1 becomes the low set pressure specified in the recipe for the duration specified in the recipe. During this time, the control device 8 maintains a constant temperature. Next, the control device 8 starts the sintering process. This sintering process consists of, for example, a first step and a second step. In the first step, the control device 8 controls the power supplied to the heater 4 in order to raise the detected temperature inside the pressure vessel to the set temperature indicated in the recipe. In the second step, the power supplied to the heater 4 is controlled so that the set temperature is maintained for the specified period indicated in the recipe. During each of these processes, the control device 8 controls the opening of the exhaust valves 73 and 74 so that the detected pressure becomes the set pressure indicated in the recipe. Once the sintering process is complete, the control device 8 starts the cooling process. In this cooling process, the control device 8 stops supplying power to the heater 4 while operating the fan 5, waiting for the workpiece W to cool down. However, as described above, the industrial processing system A of this embodiment further comprises a management and analysis device 200 connected to the control device 8 by wire or wireless.

[0034] This management and analysis device 200 is a so-called computer composed of a CPU, memory, communication interface, etc., and each part works in cooperation according to the program (software) stored in memory to perform functions such as a measurement logging data generation unit, batch data generation unit, extracted data generation unit, difference data calculation unit, feature value calculation unit, and output unit, as shown in Figure 4. Note that this management and analysis device 200 does not need to be a single physical unit, and in this case it is composed of a server and client terminals connected to each other wirelessly or by wire. The operation of this control and analysis device 200 will be described below, along with a description of the functions of each of the aforementioned parts.

[0035] First, as shown in Figure 5, the measurement logging data generation unit acquires sensor data, which is data from each sensor, from the control device 8 at predetermined sampling times (for example, every 30 seconds in this case) (steps S11, S12), arranges the values ​​of this sensor data in chronological order, and generates measurement logging data in which the time information of receipt is added to each sensor data (step S13). This measurement logging data is generated successively, for example, on a daily basis (step S14), and stored in the measurement logging data storage unit set in a predetermined area of ​​the memory (step S15). An example of measurement logging data is shown in Figure 6. Furthermore, the data from each sensor can be received directly via a network by making each sensor IoT-enabled, rather than going through a management device.

[0036] On the other hand, as shown in Figure 7, the batch data generation unit receives a recipe and time information of the time the recipe was performed from the control device 8 (step S21), and based on these, generates batch data which is data containing the processing conditions and time information for each process (step S22).

[0037] More specifically, this batch data generation unit extracts one process (for example, degreasing) from the recipe, identifies not only the start and end times of that process, but also the processing conditions and start and end times for each step (section in the claim) included in that process, and generates batch data (see Figure 8) showing these. The processing conditions here refer to the processing details shown in the recipe, such as the set temperature, set pressure, and type of gas. The batch data generation unit then stores the generated batch data in a batch data storage unit located in a predetermined area of ​​memory. The measurement logging data generation unit, measurement logging data storage unit, batch data generation unit, and batch data storage unit are all located on the server.

[0038] <2. Data Comparison Function> In this state, when a user requests a comparison of two data sets from the client terminal, the client terminal prompts the user to specify the process to be verified (step S31), as shown in Figure 9.

[0039] Therefore, when a user identifies and inputs, for example, the processing performed on the defective workpiece W, such as the processing time, processing type (degreasing, sintering, etc.), and recipe number, or specifies the batch data, the cutting data generation unit extracts the batch data corresponding to the specified processing from the batch data storage unit (step S32).

[0040] Then, the extracted data generation unit extracts measurement logging data from the measurement logging data storage unit, which includes data from the start time to the end time of the process recorded in the batch data (step S32), and generates extracted data by extracting the data from the measurement logging data for the period from the start time to the end time (step S33).

[0041] Furthermore, the extracted data generation unit searches for and extracts other batch data having the same processing conditions as the batch data recorded in the batch data, based on the processing type, recipe number, etc. (step S34), and extracts measurement logging data from the extracted other batch data in the same manner as above (step S35). Then, this measurement logging data is extracted using other batch data to generate extracted data that will serve as a comparison standard (step S36). Next, the difference data extraction unit compares these two extracted data sets and calculates difference data indicating the degree of the difference (step S37).

[0042] Here, "degree of difference" refers to, for example, the absolute value of the difference between the values ​​of a given sensor data (e.g., heater power) at each sampling time in two extracted data sets. Other statistical comparison methods can also be used, such as the absolute value of the difference in the averages of a series of sampling times, the difference in mean squares, or the difference in the area formed by each extracted data set when graphed.

[0043] Next, the output unit outputs the two extracted data sets in a comparable manner, and outputs the range corresponding to the difference data that exceeds a predetermined threshold, distinguishing it from the other ranges (step S38). The threshold can be set and changed by the user from the client terminal.

[0044] To explain in more detail, when the output unit receives a request from the user to compare a particular sensor data (for example, heater power), it displays the two extracted data points for this sensor data on the same coordinate system, superimposed on a graph, as shown in Figure 10, for example, and highlights the section corresponding to the process in which the value of the difference data exceeds a predetermined threshold. The above describes the two-data comparison function.

[0045] However, this functionality makes it possible to easily compare a poor-quality batch (process) in a sintering process, for example, with a past batch that was heat-treated using the same recipe, and to quickly identify and verify the differences.

[0046] Furthermore, the comparison of the two data sets may be performed at a smaller unit, such as a process unit, rather than a processing unit, or at a larger unit, such as a series of processes applied to a single object (e.g., degreasing, sintering, and cooling). Additionally, the values ​​of the differential data can be displayed on the same screen along with the graph. Instead of graphing the extracted data, it's also possible to divide it into two numerical tables and display them on the same screen for comparison. If data exceeding a threshold is found within a single process, it is acceptable to highlight the entire process.

[0047] Furthermore, you can, for example, select a highlighted area in the graph and then display the numerical values ​​of each extracted data point in a table format. Furthermore, the output can be presented in any format, such as graphs or tables, as long as it allows for the identification of processes that have exceeded the threshold. Furthermore, the comparison is not limited to processing in the same industrial furnace; it is also acceptable to compare processing in other industrial furnaces (for example, those with similar performance).

[0048] <Multi-data feature comparison function> On the other hand, when a request for multi-data feature value comparison is made from the client terminal, as shown in Figure 11, the client terminal prompts for input of the process to be compared, the steps in that process, and the processing conditions (step S41).

[0049] Therefore, when the user specifies and inputs the desired processing, steps, processing conditions, etc., including the recipe number, the extracted data generation unit extracts multiple batch data that match the specified conditions from the batch data storage unit (step S42), and displays the specified steps on the screen in a list for each batch data (step S43).

[0050] Next, when the user selects multiple desired processes from these processes, the extracted data generation unit generates extracted data for each batch of data, which consists of measurement logging data recorded for the period from the start time to the end time of the relevant process (step S44).

[0051] Next, the feature value calculation unit calculates the feature value of each extracted data (step S45). Examples of feature values ​​include "data value after a predetermined time has elapsed since the start of the process," "data value before a predetermined time has elapsed since the start of the process," "maximum or minimum data value in the process," and "average data value in the process," and the system is configured so that the user can select from among these.

[0052] Next, the output unit outputs the characteristic values ​​of each extracted data in a comparable manner, such as by displaying them as a time-series graph on the client terminal screen, as shown in Figure 12 (step S46). The above describes the multi-data feature value comparison function.

[0053] With this configuration, it is possible to extract only the data that matches specific conditions such as "same pattern, same process" and "maintained at 1800°C for 30 minutes or more" by traversing the processing steps.

[0054] Furthermore, by extracting data under the same processing conditions from the accumulated measurement logging data, and calculating and plotting the characteristic values ​​of each data point, long-term trends can be easily grasped. As a result, it is possible to identify items that have a high correlation with the wear and tear and component deterioration of the industrial furnace 100, and to verify whether there is any data that is extremely out of line.

[0055] Furthermore, the comparison of multiple data feature values ​​may be performed not only at the process level, but also at the processing level, or at a larger unit, such as a series of processes applied to a single object (e.g., degreasing, sintering, and cooling). Furthermore, each feature value can be displayed numerically in a graph, or it can be displayed in a table format on the same screen. Each feature value can be displayed not only as a time series, but also in comparison to processing in other industrial furnaces (for example, those with similar performance).

[0056] The features of the control and analysis device 200 described above can be summarized as follows. In this description of features, "processing" refers to various industrial processes applied to the object to be processed, and corresponds to any of the "processing," "steps," "series of processes," or other predetermined units of processing in the above embodiment.

[0057] (1) The management and analysis device 200 is characterized by comprising: a measurement logging data generation unit that sequentially receives sensor data, which is data from a sensor that measures the state of the industrial furnace 100, and generates measurement logging data in which the values ​​of this sensor data are arranged in a time series; an extraction data generation unit that generates extraction data, which is data extracted from the measurement logging data, which is data in which a predetermined process has been performed in the industrial furnace 100; and a difference data calculation unit that compares two sets of extraction data whose processing conditions match and calculates difference data that shows the degree of the difference.

[0058] With this type of system, the need for manual checking and comparison of measurement logging data, or using separate spreadsheet software, becomes unnecessary, significantly reducing working time and promoting efficiency.

[0059] (2) If the extracted data generation unit accepts the specification of one extracted data and extracts other extracted data that matches the processing conditions, the extracted data to be compared will be automatically extracted, thereby further improving work efficiency.

[0060] (3) Preferably, the system further includes a batch data generation unit that generates batch data for each process, which includes the processing conditions, start time, and end time, and the extracted data generation unit extracts measurement logging data between the start time and end time indicated in the batch data to generate extracted data. With this approach, processing conditions can be specified using batch data, improving usability.

[0061] (4) It is preferable that the batch generation unit specifies the processing conditions and start and end times for each predetermined section (corresponding to the steps described above) in a single process, generates batch data indicating these, and the difference data calculation unit calculates the difference data for each corresponding section in the two extracted data. With this approach, it becomes possible to compare the results in further divided intervals, enabling more precise verification.

[0062] (5) In order to make the comparison easier to understand, it is desirable to have an output unit that outputs two extracted data in a comparable manner, and further outputs the interval corresponding to the difference data that exceeds a predetermined threshold in a manner that can be distinguished from other intervals.

[0063] (6) It is even more preferable if the output unit displays the two extracted data sets superimposed on the same coordinate system as a graph, and highlights the interval corresponding to the difference data that exceeds a predetermined threshold.

[0064] (7) The industrial furnace 100 management and analysis device 200 includes: a measurement logging data generation unit that sequentially receives sensor data, which is data from a sensor that measures the state of the industrial furnace 100, and generates measurement logging data in which the values ​​of this sensor data are arranged in a time series; a cutout data generation unit that generates cutout data, which is data extracted from the measurement logging data in which a predetermined process has been performed in the industrial furnace 100; and a feature value calculation unit that performs a predetermined calculation on each of a plurality of cutout data whose processing conditions match each other, and calculates the feature value of each cutout data. With such a device, the feature values ​​of a large number of data under the same processing conditions are automatically calculated, so for example, by outputting these in a time series, it is possible to easily grasp long-term trends.

[0065] (8) Specifically, it is preferable that the device further includes an output unit that outputs the characteristic values ​​of each of the extracted data in a comparable manner.

[0066] (9) The following configuration can produce similar effects. A program for a management and analysis device characterized by performing the following functions: a measurement logging data generation unit that sequentially receives sensor data, which is data from a sensor that measures the state of an industrial furnace 100, and generates measurement logging data in which the values ​​of this sensor data are arranged in a time series; an extraction data generation unit that generates extraction data, which is data extracted from the measurement logging data, which is data in which a predetermined process has been performed in the industrial furnace 100; and a difference data calculation unit that compares two sets of extraction data whose processing conditions match and calculates difference data that shows the degree of difference between them.

[0067] (10) The following configuration can produce similar effects. A program for a management and analysis device characterized by performing the following functions: a measurement logging data generation unit that sequentially receives sensor data, which is data from a sensor that measures the state of an industrial furnace 100, and generates measurement logging data in which the values ​​of this sensor data are arranged in a time series; a cutout data generation unit that generates cutout data, which is data extracted from the measurement logging data, which is data in which a predetermined process has been performed in the industrial furnace 100; and a feature value calculation unit that performs a predetermined calculation on each of a plurality of cutout data whose processing conditions match each other, and calculates the feature value of each cutout data. [Explanation of Symbols]

[0068] 200...Management analysis equipment 100... Industrial furnaces

Claims

1. A measurement logging data generation unit sequentially receives sensor data, which is data from a sensor that measures the state of an industrial furnace, and generates measurement logging data by arranging the values ​​of this sensor data in a time series. A data extraction generation unit generates extracted data, which is data extracted from measurement logging data, specifically the portion where a predetermined process has been performed in an industrial furnace. A difference data calculation unit compares two extracted data sets whose processing conditions match and calculates difference data that shows the degree of the difference between them, An industrial furnace management and analysis device characterized by comprising an output unit that outputs two extracted data sets in a comparable manner, and outputs the interval corresponding to the difference data exceeding a predetermined threshold in a manner that can be distinguished from other intervals.

2. The industrial furnace management and analysis apparatus according to claim 1, wherein the extraction data generation unit receives the specification of one extraction data and extracts other extraction data that matches the processing conditions of that data.

3. The system further includes a batch data generation unit that generates batch data for each process, which includes the processing conditions, start time, and end time. The industrial furnace management and analysis apparatus according to claim 1 or 2, wherein the extracted data generation unit extracts measurement logging data between the start time and end time indicated by the batch data to generate extracted data.

4. The batch data generation unit identifies the processing conditions, start and end times for each predetermined section in a single process, and generates batch data indicating these conditions. The industrial furnace management and analysis apparatus according to claim 3, wherein the difference data calculation unit calculates difference data for each corresponding interval in two extracted data sets.

5. The industrial furnace management and analysis apparatus according to any one of claims 1 to 3, wherein the output unit displays the two extracted data sets superimposed on the same coordinate system as a graph, and highlights the interval corresponding to the difference data that exceeds a predetermined threshold.

6. The industrial furnace management and analysis apparatus according to any one of claims 1 to 3, comprising: a feature value calculation unit that performs a predetermined calculation on each of a plurality of extracted data sets whose processing conditions match each other, and calculates a feature value for each extracted data set.

7. The industrial furnace management and analysis apparatus according to claim 6, further comprising an output unit that outputs characteristic values ​​of each of the aforementioned extracted data in a comparable manner.

8. A measurement logging data generation unit sequentially receives sensor data, which is data from a sensor that measures the state of an industrial furnace, and generates measurement logging data by arranging the values ​​of this sensor data in a time series. A data extraction generation unit generates extracted data, which is data extracted from measurement logging data, specifically the portion where a predetermined process has been performed in an industrial furnace. A difference data calculation unit compares two extracted data sets whose processing conditions match and calculates difference data that shows the degree of the difference between them, A program for an industrial furnace management and analysis device, characterized by its function as an output unit that outputs two extracted data sets in a comparable manner, and outputs the section corresponding to the difference data that exceeds a predetermined threshold in a manner that can be distinguished from other sections.

9. The program for an industrial furnace management and analysis device according to claim 8, further characterized by having a feature value calculation unit that performs a predetermined calculation on each of a plurality of extracted data sets whose processing conditions match each other, and calculates a feature value for each extracted data set.

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