WO2024062731A1 - Debinding recipe setting method - Google Patents

Debinding recipe setting method Download PDF

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Publication number
WO2024062731A1
WO2024062731A1 PCT/JP2023/025007 JP2023025007W WO2024062731A1 WO 2024062731 A1 WO2024062731 A1 WO 2024062731A1 JP 2023025007 W JP2023025007 W JP 2023025007W WO 2024062731 A1 WO2024062731 A1 WO 2024062731A1
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Prior art keywords
degreasing
data
analysis
existing
processed material
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PCT/JP2023/025007
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French (fr)
Japanese (ja)
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優 田中
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株式会社島津製作所
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Publication of WO2024062731A1 publication Critical patent/WO2024062731A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B28—WORKING CEMENT, CLAY, OR STONE
    • B28B—SHAPING CLAY OR OTHER CERAMIC COMPOSITIONS; SHAPING SLAG; SHAPING MIXTURES CONTAINING CEMENTITIOUS MATERIAL, e.g. PLASTER
    • B28B11/00—Apparatus or processes for treating or working the shaped or preshaped articles
    • C—CHEMISTRY; METALLURGY
    • C04—CEMENTS; CONCRETE; ARTIFICIAL STONE; CERAMICS; REFRACTORIES
    • C04B—LIME, MAGNESIA; SLAG; CEMENTS; COMPOSITIONS THEREOF, e.g. MORTARS, CONCRETE OR LIKE BUILDING MATERIALS; ARTIFICIAL STONE; CERAMICS; REFRACTORIES; TREATMENT OF NATURAL STONE
    • C04B35/00—Shaped ceramic products characterised by their composition; Ceramics compositions; Processing powders of inorganic compounds preparatory to the manufacturing of ceramic products
    • C04B35/622—Forming processes; Processing powders of inorganic compounds preparatory to the manufacturing of ceramic products
    • C04B35/626—Preparing or treating the powders individually or as batches ; preparing or treating macroscopic reinforcing agents for ceramic products, e.g. fibres; mechanical aspects section B
    • C04B35/63—Preparing or treating the powders individually or as batches ; preparing or treating macroscopic reinforcing agents for ceramic products, e.g. fibres; mechanical aspects section B using additives specially adapted for forming the products, e.g.. binder binders
    • C04B35/638—Removal thereof
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N25/00—Investigating or analyzing materials by the use of thermal means
    • G01N25/20—Investigating or analyzing materials by the use of thermal means by investigating the development of heat, i.e. calorimetry, e.g. by measuring specific heat, by measuring thermal conductivity

Definitions

  • the present invention relates to a device for setting a degreasing recipe for ceramic molded bodies, etc., and a method for setting a degreasing recipe.
  • Patent Document 1 a degreasing process is performed on a processed material such as a ceramic molded body according to a predetermined recipe.
  • a recipe is a degreasing procedure such as changes in pressure and temperature over time, type of degreasing gas, timing of degreasing gas introduction/extraction, etc.
  • Such recipes were created by setting the initial recipe based on subjective rules of thumb. After that, it will be determined by conducting verification using an actual degreasing furnace (actual furnace).
  • recipe verification must be performed at least once using an actual furnace, which increases power consumption.
  • recipe verification may not be completed in just one time, but may have to be performed multiple times, or recipes may need to be determined for different products to be processed.
  • you have multiple actual reactors you will have to carry out verification work in series, which will cause problems such as time and cost.
  • owning multiple actual reactors requires considerable capital investment, which is difficult in reality.
  • the present invention has been made with attention to such problems, and it is possible to set a degreasing recipe with low power consumption and in a short time, and to reduce wasted time and energy in the actual degreasing process performed according to the set recipe.
  • the main objective is to minimize losses as much as possible.
  • the skimming recipe setting method is as follows: Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data accumulation step of linking with degreasing result data indicating the results and accumulating them in memory; The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis step for analyzing based on physical analysis data and degreasing result data; A recipe setting step of setting a degreasing recipe for the newly processed material based on the analysis result in the analysis step is performed.
  • thermogravimetric measurement device by using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analysis device, it is possible to set a degreasing recipe based on statistical and theoretical data. Recipe verification work can be unnecessary or minimized. As a result, it is possible to save power and shorten the time involved in setting the degreasing recipe.
  • the differential thermal measuring device and the thermogravimetric measuring device may be provided in the form of a differential thermal/thermogravimetric measuring device.
  • thermogravimetry measurement devices are cheaper and smaller than actual furnaces, so by having multiple devices, it is possible to set degreasing recipes in parallel. Time reduction can be further promoted.
  • the degreasing recipe set in this way includes analysis data of past processed materials using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and analysis data of existing processed materials using an actual furnace. Since there is theoretical and statistical support established based on the degreasing result data, it is possible to reduce wasted time and energy loss in the actual degreasing process performed according to this degreasing recipe.
  • FIG. 1 is an overall schematic diagram showing a degreasing recipe setting device, a degreasing furnace, and a differential heat/thermogravimetric measuring device used in a degreasing recipe setting method in an embodiment of the present invention.
  • this degreasing recipe setting device 100 is a device that uses a differential thermal/thermogravimetric measuring device 300 to set a degreasing recipe for degreasing a processed material in a degreasing furnace 200.
  • the differential thermal/thermogravimetric measuring device 300 is an analysis device in which a differential thermal measuring device and a thermogravimetric measuring device are integrated, but this may be prepared as a separate analytical device.
  • the degreasing furnace 200 includes a heating furnace (hereinafter also referred to as an actual furnace) that accommodates a processed material such as a ceramic molded body, and a controller that controls the temperature, pressure, gas type, etc. in this heating furnace.
  • the object to be processed in the heating furnace is heated and degreased according to the degreasing recipe incorporated in this control device.
  • the differential thermal/thermogravimetric measuring device 300 includes a furnace that houses the object to be measured, a control device that controls the temperature, gas type, etc. in the furnace, and a thermogravimetric change amount of the object to be measured. It is equipped with a thermogravimetric change measurement mechanism for measuring and a differential thermal analysis mechanism for differential thermal analysis of the object to be measured, and it generates analysis data indicating the analysis results of the object to be measured, that is, thermogravimetric change data and differential thermal data. Output.
  • This differential heat/thermogravimetry measuring device 300 has a capacity and weight that can be placed on a desk, and is extremely small and inexpensive compared to the degreasing furnace 200.
  • a part of the processed material for example, a piece of the processed material or a powder obtained by crushing the processed material, is used as the object to be measured by the differential thermal/thermogravimetric measuring device 300.
  • This degreasing recipe setting device 100 is a so-called computer equipped with a CPU, a memory, a communication interface, an input/output interface, etc., and the CPU and its peripheral devices cooperate according to a predetermined program stored in the memory. 2, it functions as a data storage section, extraction section, analysis section, recipe setting section, etc.
  • this degreasing recipe setting device 100 is not limited to being physically formed by a single computer.
  • a plurality of computers such as a server/client system may be connected to enable wireless or wired communication, and some or all of the functions may be implemented by the control device of the degreasing furnace 200 or the differential thermal/thermogravimetric measuring device 300. It doesn't matter if it is made to double as a.
  • the data storage unit receives accumulated data, which is data related to processed items that have been degreased in the past in a degreasing furnace (hereinafter also referred to as existing processed items), for each processed item, and stores it in the memory. It is something that accumulates in a region.
  • the accumulated data includes degreasing result data showing the results of degreasing the existing treated material, and analysis data obtained by analyzing a part of the existing treated material before degreasing using a differential thermal/thermogravimetric measuring device ( (hereinafter also referred to as existing processing product analysis data) and the classification code of the existing processing product.
  • degreasing result data showing the results of degreasing the existing treated material
  • analysis data obtained by analyzing a part of the existing treated material before degreasing using a differential thermal/thermogravimetric measuring device (hereinafter also referred to as existing processing product analysis data) and the classification code of the existing processing product.
  • thermogravimetric change data and differential thermal analysis when a part of the existing processing material is heated at different heating rates. Contains data.
  • the degreasing result data includes items indicating whether the degreasing process has ended normally or abnormally, and a degreasing recipe.
  • Abnormalities include cracks, chips, and unacceptable deformation of the processed material.
  • the classification code indicates to which of the predetermined classifications the existing processed material belongs; for example, the weight falls within a plurality of predetermined ranges, or the shape falls within a predetermined range.
  • the shape is similar and the capacity is within a predetermined range. That is, the classification is determined by the weight, shape, and volume of the processed material, and each classification has a certain range.
  • the operator inputs the classification code here, it may be automatically input using a three-dimensional shape measuring machine, a weight scale, or the like.
  • Extraction unit This extraction unit extracts accumulated data of existing processing items, which will be used for analysis of new processing items to be described later, from a plurality of accumulated data accumulated in the data storage unit.
  • the extraction conditions are that the classification code matches, that is, it is the accumulated data of an existing processed product that is the same or similar in weight, shape, and volume to the newly processed product, and that the analysis data of the existing processed product is the same as the newly processed product analysis. Matching or approximating data.
  • statistical methods are used, such as checking that the root mean square of the difference of each corresponding point is less than a predetermined value. A method is used.
  • This analysis section analyzes data using the differential thermal/thermogravimetric measuring device 300 on a part of the newly processed material for which no degreasing recipe has been determined yet (hereinafter referred to as the newly processed material).
  • the newly processed product analysis data is received, and the new processed product analysis data is analyzed based on the existing processing product analysis data and degreasing result data extracted by the extraction section.
  • This newly processed material analysis data is linked to the classification code of the new processed material. Note that the manner in which these newly processed material analysis data and classification codes are accepted is the same as that for existing processed material analysis data and their classification codes.
  • this analysis section includes an existing processing material shift characteristic calculation section, a new processing material thermogravimetric change estimation section, and a threshold value setting section.
  • This existing processing material shift characteristic calculation unit calculates the temperature of the existing processing material based on the difference in heating rate of differential heat and thermogravimetric change of the existing processing material based on the existing processing material analysis data. Shift characteristics (hereinafter also referred to as existing processing material shift characteristics) are calculated.
  • the existing processing material analysis data includes differential heat and thermogravimetric changes at a plurality of different heating rates for the existing processing material.
  • this existing processing material shift characteristic calculating section calculates the differential heat and thermogravimetric change at each desired heating rate based on the difference in the differential heat and thermogravimetric change actually measured at these different heating rates.
  • the shift characteristic of the existing processed material which is the amount of shift from the actual measured value of thermogravimetric change, is calculated.
  • thermogravimetric change estimating unit Since the existing processed product extracted by the extraction unit is similar in terms of the form (weight, shape, capacity) and analysis data of the new processed product, It is estimated that the temperature shift characteristics of these existing treatments are also similar to the temperature shift characteristics of the new treatments.
  • the new processing material thermogravimetric change estimation unit calculates the new processing material shift characteristic, which is the temperature shift characteristic of the new processing material, based on the existing processing material shift characteristic.
  • a correction calculation based on the difference between the analysis data of the new treatment object and the analysis data of the existing treatment object is performed on the existing treatment object.
  • the shift characteristic is applied to the shift characteristic to calculate the shift characteristic of the new processing object.
  • the new processing material shift characteristics may be made to match the existing processing material shift characteristics, or, for example, if there are two different existing processing material analysis data with the new processing material analysis data in between,
  • the processing object shift characteristic may be calculated from the shift characteristics of a plurality of different existing processing objects, such as by setting the intermediate value of the shift characteristics of the new processing object as the new processing object shift characteristic.
  • the newly processed material thermogravimetric change estimation unit applies the new processed material shift characteristic to the new processed material analysis data to estimate the thermogravimetric change of the newly processed material at a predetermined temperature increase rate.
  • this threshold value setting unit calculates a critical thermogravimetric change that causes an abnormality in the newly treated material based on the degreasing result data of the existing treated material, and based on this critical thermogravimetric change, Set the threshold for thermogravimetric change during degreasing.
  • the threshold value setting unit first determines the temperature of the existing material based on the temperature increase rate in the degreasing recipe in which cracks, chips, or unexpected deformation have occurred in the existing material and the temperature shift characteristics of the existing material. Calculate the thermogravimetric change when an abnormality occurs during degreasing of the processed material.
  • the threshold value setting unit calculates a limit thermogravimetric change at which no abnormality occurs in the new processing object, based on the thermogravimetric change when an abnormality occurs in the existing processing object.
  • the calculation method is, for example, to perform a correction calculation according to the difference between the new processed material analysis data and the existing processed material analysis data (for example, the root mean square of the difference between the corresponding points of these two analytical data). Calculate the critical thermogravimetric change of the newly processed material by applying it to the thermogravimetric change when an abnormality occurs.
  • the critical thermogravimetric change of the newly processed material may be made to match the thermogravimetric change when an abnormality occurs in the existing material, or, for example, it may be calculated using analysis data of the newly processed material. If there is analysis data for two different existing processed products, the intermediate value of the thermogravimetric change at the time of abnormality of the existing processed products is set as the critical thermogravimetric change of the new processed product.
  • the critical thermogravimetric change of the newly processed material may be calculated from the thermogravimetric change at the time of generation.
  • the threshold value setting section sets the threshold value based on the limit thermogravimetric change.
  • the threshold value may match the limit thermogravimetric change, or may be a value obtained by multiplying or subtracting the critical thermogravimetric change by a safety factor.
  • This recipe setting section calculates the thermogravimetric change of the new processing material at each temperature increase rate based on the shift characteristics of the new processing material, and calculates the thermogravimetric change of the new processing material at each temperature increase rate, A temperature rate is determined and a degreasing recipe that is less than or equal to the temperature increase rate is set.
  • (1st step: data accumulation step) Degreasing result data showing the results of past degreasing of existing treated items, analysis data of existing treated items obtained by analyzing a part of the existing treated items using a differential thermal/thermogravimetric measuring device, and classification codes of the existing treated items. , is acquired by the data storage unit and stored in memory.
  • Step step of acquiring analytical data for new processed material
  • the operator analyzes a part of the newly processed material using a differential thermal/thermogravimetric measuring device, and also determines and inputs a classification code for the newly processed material.
  • the analysis section acquires the analysis data (newly processed material analysis data) and classification code.
  • the extraction unit compares the existing process product analysis data with the new process product analysis data, and extracts one or more existing process product analysis data and degreasing result data linked thereto to be used for analysis according to the extraction conditions described above.
  • the existing processing material shift characteristic calculation calculates the existing processing material shift characteristic, which is a temperature shift characteristic due to a difference in temperature increase rate of differential heat and thermogravimetric change of the existing processing material, based on the existing processing material analysis data. do.
  • the new processing material thermogravimetric change estimation unit calculates the new processing material shift characteristic, which is the temperature shift characteristic of the new processing material, based on the existing processing material shift characteristic and the new processing material analysis data, From this shift characteristic of the newly processed material, the thermogravimetric change of the newly processed material at each temperature increase rate is estimated.
  • the threshold value setting step calculates a critical thermogravimetric change at which no abnormality occurs in the newly processed material based on the degreasing result data, and sets the threshold value based on this critical thermogravimetric change.
  • the degreasing recipe setting unit determines a temperature increase rate at which the thermogravimetric change is within the threshold value from among the thermogravimetric changes of the new treatment material at each temperature increase rate, and the degreasing recipe setting unit determines a temperature increase rate at which the thermogravimetric change is within the threshold value, Set a skimming recipe.
  • thermogravimetric change during decomposition and combustion becomes steep, as shown in FIG. 4(c).
  • the temperature range in which the steepest change occurs in the estimated thermogravimetric change curve at the predetermined heating rate (A to B at 0.5°C/min in the figure)
  • a temperature increase rate is determined at which the thermogravimetric change is within the threshold value.
  • thermogravimetric change remains within the above-mentioned threshold even if the temperature increase rate is even higher, so the temperature increase rate during degreasing is not constant, and as shown in FIG. In this case, the temperature increase rate is set to be higher than that in the section from A°C to B°C.
  • the degreasing result data obtained through this process is accumulated by the data storage unit as the accumulated data together with some analysis data and classification code of the newly processed product, and is used in subsequent degreasing recipe settings for other newly processed products. used.
  • the analysis step or, in addition to this, the degreasing recipe setting step may be performed by machine learning using AI.
  • the temperature increase rate measured by a temperature sensor placed in an actual furnace and the actual temperature increase rate near the processed material stored in the actual furnace do not always match.
  • the way in which heat enters the furnace varies depending on the number of items to be processed.
  • the difference between the measured temperature increase rate and the actual temperature increase rate is smaller when the number of objects is small.
  • the degreasing result data further includes the quantity of the existing processed materials stored in the degreasing furnace at one time (the quantity of the existing processed materials in one batch), and in the degreasing recipe setting step, the existing processed materials are stored in the degreasing furnace.
  • the degreasing recipe may also be set based on the quantity of newly processed materials to be accommodated in the degreasing furnace at one time while referring to the quantity.
  • the threshold value, temperature increase rate, degreasing recipe, etc. set in the embodiment described above are corrected based on the quantity of new processing items to be processed in one batch obtained by operator input. Specifically, the larger the number of objects to be processed, the slower the rate at which heat enters the furnace for new objects to be processed, so the temperature increase rate is corrected to lower.
  • the shift characteristics were calculated from the existing processing material analysis data and the new processing material analysis data, and the thermogravimetric change was calculated from the shift characteristics.
  • the machine learning described above black Using box-like calculations, it is possible to calculate thermogravimetric changes without calculating shift characteristics, or it is also possible to set a degreasing recipe without setting a threshold value.
  • thermogravimetric change of a new treatment object when calculating the thermogravimetric change of a new treatment object, the temperature shift characteristics of the existing treatment object were calculated from the analysis data of the existing treatment object. It is also possible to calculate this existing processing material shift characteristic and store it as one of the stored data.
  • the degreasing result data when an abnormality occurs, but normal degreasing result data may also be referred to.
  • the degreasing result data may include a change in the form of the degreased product from before the degreasing process, and the critical thermogravimetric change or threshold value may be calculated based on the change in form.
  • the change in shape may be measured using a three-dimensional shape measuring device or the like.
  • a degreasing recipe is set, but the configuration may be such that the degreasing recipe is not set and a threshold value of thermogravimetric change that does not cause any abnormality in the newly processed material is calculated.
  • it may be a method or an apparatus for analyzing a degreased product. Since the threshold value of a new product to be processed can be determined using such an analysis method and analysis device, the threshold value can be used not only for setting a degreasing recipe but also for other purposes such as sintering in an industrial furnace.
  • the classification may include, for example, the material of the processed material and the type of binder.
  • one differential thermal/thermogravimetric measuring device is used, but a plurality of devices may be used to perform parallel processing.
  • each step in the embodiment was performed by the degreasing recipe setting device, a part or all of these steps may be performed by a human.
  • the following method is also possible. That is, the characteristic value of the thermogravimetric change at each temperature increase rate of the existing object to be treated is calculated in advance, and the correlation between the characteristic value and the temperature increase rate is calculated, and the predetermined value of the new object to be treated is determined based on the correlation. Estimate the thermogravimetric change at a heating rate of .
  • thermogravimetric change that does not cause any abnormality in the newly processed material is set, or a degreasing recipe for the newly processed material is set based on the correlation.
  • the correlation here corresponds to the temperature shift characteristic in the claims. This was done after the inventor discovered for the first time that there is a certain correlation between the temperature increase rate and the characteristic value.
  • the characteristic value is, for example, the temperature at the peak (if there are multiple peaks, any predetermined peak is fine) when time-differentiating part or all of the thermogravimetric change curve. be. Specifically, first, by plotting the characteristic values at each heating rate, a calibration curve/regression curve expressed by a predetermined function between the heating rate and the characteristic value is created.
  • the temperature increase rate at this time may be a set value or an actually measured value. Then, by converting this calibration curve into a table or formula, a thermogravimetric change curve when a desired heating rate is given to the newly processed material is estimated from the calibration curve. Although the peak width is not corrected here, the peak width may ride on a different curve, and this may be corrected separately. Note that the characteristic value may be based on, for example, the peak obtained by performing multiple differentiation such as quadratic or cubic differentiation on the thermogravimetric change curve, or it may be based on other values that can be calculated from the thermogravimetric change curve, such as peak area, etc. , a value that is recognized to be correlated with the temperature increase rate may be used as the characteristic value.
  • thermogravimetric change curve does not have to be a characteristic value of the thermogravimetric change curve as long as it has a correlation with the temperature increase rate.
  • characteristic values calculated from a differential thermal change curve may be used, or various parameters or physical property values of the processed material that can be obtained from a differential thermal/thermogravimetric measuring device may be used.
  • a thermomechanical analyzer may also be used. In this case, in the embodiment, the description of "thermogravimetric change" is replaced with "thermomechanical change.” Note that the present invention is not limited to the case where one of the suggestive heat/thermogravimetry device and the thermomechanical analyzer (TMA) is used, and both of these may be used.
  • thermogravimetric change measured by a thermogravimetry device a differential thermal change by a suggestive thermometer
  • thermomechanical change by a thermomechanical analyzer Any combination of two or more may be used.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analysis device, and the results of degreasing the existing processed material in a degreasing furnace. a data accumulation step of linking degreasing result data indicating the results and accumulating it in memory;
  • the newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section.
  • a method for setting a degreasing recipe comprising: a recipe setting step of setting a degreasing recipe for the new material to be processed based on the analysis result in the analysis step.
  • thermogravimetric measurement device by using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analysis device, it is possible to set a degreasing recipe based on statistical and theoretical data. Recipe verification work can be unnecessary or minimized. As a result, it is possible to save power and shorten the time involved in setting the degreasing recipe. Furthermore, since differential thermal measurement devices, thermogravimetry measurement devices, and/or thermomechanical analysis devices are cheaper and smaller than actual furnaces, degreasing recipes can be set in parallel by having multiple devices. This can further reduce time.
  • the degreasing recipe set in this way is based on analysis data of existing processed materials using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and degreasing in an actual furnace. Since it has theoretical and statistical support set based on result data, it is possible to reduce wasted time and energy loss in the actual degreasing process performed according to the set recipe.
  • the linked existing processed material analysis data and degreasing result data are stored in a memory separately for each classification of the corresponding existing processed material, further performing an extraction step of extracting existing processed product analysis data and degreasing result data of one or more existing processed products that belong to a common classification with the new processed product classification,
  • the analysis step new processed material analysis data is analyzed based on the existing processed material analysis data and the degreasing result data extracted in the extraction step.
  • a new processed product can be analyzed using the analysis data and degreasing result data of an existing processed product that has a similar shape, so the accuracy is further improved.
  • the existing processed product analysis data and the new processed product analysis data are compared, and one or more existing processed product analysis data and degreasing result data linked thereto are further extracted for use in the analysis step [2 ] or the skimming recipe setting method described in [3].
  • a newly processed product can be analyzed using analysis data and degreasing result data of existing processed products that have similar thermal reaction characteristics, so the accuracy is further improved. Specifically, it is preferable to extract one or more existing processed material analysis data that match or approximate the new processed material analysis data.
  • a new treated product thermogravimetric change estimation step is performed to estimate a thermogravimetric change of the new treated product at a predetermined temperature rise rate based on the existing treated product shift characteristic and the new treated product analysis data;
  • a degreasing recipe setting method according to any one of [1] to [4], in which in the recipe setting step, a degreasing recipe for a new degreasing treatment object in a degreasing furnace is set so that the thermogravimetric change estimated in the new treatment object thermogravimetric change estimation step is within a predetermined threshold value.
  • thermogravimetric change at a desired heating rate based on the temperature shift characteristics calculated from analytical data, so the degreasing recipe is set based on that. This not only ensures the reliability of the system, but also enables accurate identification and correction of any defects that occur during verification in an actual reactor.
  • thermogravimetric change estimation step a new processing material shift characteristic, which is a temperature shift characteristic of the new processing material, is calculated based on the existing processing material shift characteristic, and this new processing material shift characteristic and the new processing material shift characteristic are calculated.
  • a threshold value setting step is further performed in which a critical thermogravimetric change at which an abnormality may occur in the newly processed material is calculated based on the degreasing result data, and the threshold value is set based on this critical thermogravimetric change. 5] or the skimming recipe setting method described in [6].
  • the degreasing result data includes information indicating whether the degreasing process has ended normally or abnormally,
  • the degreasing result data includes the quantity of the existing processed material stored in the degreasing furnace at one time, and in the degreasing recipe setting step, the quantity of the existing processed material is stored in the degreasing furnace once.
  • the evaluation results for a small amount of processed material can be reflected in the actual production recipe for degreasing a larger amount of processed material.
  • thermogravimetric changes In advance, calculate characteristic values of thermogravimetric changes at each temperature increase rate, calculate the correlation between the characteristic values and the temperature increase rate, and use the correlation as the temperature shift characteristic [5] to [8]
  • the configuration [10] was created when the present inventor discovered for the first time that there is a certain correlation between the temperature increase rate and the characteristic value. This enables highly accurate estimation of thermogravimetric changes due to differences in heating rates.
  • the degreasing recipe setting method according to [6] wherein the characteristic value is a temperature at a peak obtained by time-differentiating a thermogravimetric change curve. According to the configuration [11], it is possible to estimate thermogravimetric changes with high accuracy without performing complicated calculations.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace.
  • a data storage unit that stores degreasing result data indicating the results;
  • the newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section.
  • a degreasing recipe setting device comprising: a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace.
  • a data storage unit that stores degreasing result data indicating the results;
  • the newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section.
  • an analysis section that performs analysis based on physical analysis data and degreasing result data;
  • a program that causes a computer to function as a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace.
  • the degreasing result data showing the results is stored in memory
  • the newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. 1.
  • a method for analyzing a degreased product characterized in that analysis is performed based on physical analysis data and degreasing result data, and a threshold value of thermogravimetric change is set at which no abnormality occurs in the newly processed product.
  • the same effects as those described in [1] to [11] can be achieved, and the calculated threshold value can be used to reduce energy consumption in recipe verification of other processes such as sintering in industrial furnaces. It is possible to reduce costs and time.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace.
  • a data storage unit that stores degreasing result data indicating the results;
  • the newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section.
  • An analysis device for degreased products comprising: an analysis section that performs analysis based on physical analysis data and degreasing result data, and sets a threshold value of thermogravimetric change at which no abnormality occurs in the newly processed products.
  • Existing processed material analysis data which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace.
  • a data storage unit that stores degreasing result data indicating the results;
  • Newly processed material analysis data which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measuring device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section.
  • a program that causes a computer to function as an analysis section that performs analysis based on physical analysis data and degreasing result data and sets a threshold value of thermogravimetric change at which no abnormality occurs in the newly processed material.
  • the recipe is theoretically and statistically backed up by analysis data of past processed products using a differential calorimeter, thermogravimeter, and/or thermomechanical analyzer, as well as data on degreasing results in an actual furnace, so time and energy loss can be reduced during the actual degreasing process performed according to this degreasing recipe.

Abstract

The present invention is capable of setting a debinding recipe with low power consumption and in a short period of time, and minimizes time consumption and energy loss in an actual debinding treatment performed according to the set recipe.　The present invention performs: a data accumulation step for associating existing treatment target analysis data that is obtained by using a differential thermal measurement device, a thermogravimetry device, and/or a thermomechanical analysis device to analyze part of an existing treatment target with debinding result data that indicates the result of debinding the existing treatment target in a debinding furnace, and for accumulating the data in a memory; an analysis step for analyzing, on the basis of the existing treatment target analysis data and the debinding result data which are accumulated in a data accumulation unit, new treatment target analysis data that is obtained by using the differential thermal measurement device, the thermogravimetry device, and/or the thermomechanical analysis device 300 to analyze part of a new treatment target; and a recipe setting step for setting a debinding recipe for the new treatment target on the basis of the analysis result in the analysis step.

Description

脱脂レシピ設定方法How to set the skimming recipe
　本発明は、セラミック成形体等に対する脱脂レシピの設定装置、脱脂レシピ設定方法等に関するものである。 The present invention relates to a device for setting a degreasing recipe for ceramic molded bodies, etc., and a method for setting a degreasing recipe.
　この種の脱脂装置では、特許文献１に示すように、所定のレシピにしたがって、セラミック成形体などの処理物に対する脱脂処理が行われる。 In this type of degreasing apparatus, as shown in Patent Document 1, a degreasing process is performed on a processed material such as a ceramic molded body according to a predetermined recipe.
　レシピとは、圧力・温度の時間変化、脱脂ガス種、脱脂ガス導出入のタイミングなどといった脱脂処理手順のことであり、従来、このようなレシピは、主観的な経験則で初期レシピを設定した後、実際の脱脂炉（実炉）を用いた検証を行うことによって決定される。 A recipe is a degreasing procedure such as changes in pressure and temperature over time, type of degreasing gas, timing of degreasing gas introduction/extraction, etc. Conventionally, such recipes were created by setting the initial recipe based on subjective rules of thumb. After that, it will be determined by conducting verification using an actual degreasing furnace (actual furnace).
特開平１１－４３７０４号公報Japanese Patent Application Publication No. 11-43704
　しかしながら、上述した手法では、レシピの検証は、実炉を用いて１回以上行わなければならないため、電力消費量が大きくなる。 However, in the above-mentioned method, recipe verification must be performed at least once using an actual furnace, which increases power consumption.
　また、レシピの検証は１回で終わるとは限らず、複数回行わなければならない場合があるし、異なる処理物に対してそれぞれレシピを決定しなければならない場合もある。このような場合に、複数の実炉を保有していない限り、シリーズで検証作業を進めなければならず、時間とコストがかかるなどといった問題点が生じる。かといって、複数の実炉を保有するには、相当の設備投資が必要となり、現実的には難しい。 In addition, recipe verification may not be completed in just one time, but may have to be performed multiple times, or recipes may need to be determined for different products to be processed. In such a case, unless you have multiple actual reactors, you will have to carry out verification work in series, which will cause problems such as time and cost. However, owning multiple actual reactors requires considerable capital investment, which is difficult in reality.
　さらに、このようにして決定されたレシピが、処理時間や消費電力等の観点から最適なものかどうかについては、理論的、統計的な裏づけがないため、このレシピにしたがってその後行われる実際の脱脂処理において、無視できないエネルギロスや時間ロスが生じている可能性もある。 Furthermore, there is no theoretical or statistical support as to whether the recipe determined in this way is the optimal one in terms of processing time, power consumption, etc. There is a possibility that energy loss and time loss that cannot be ignored occur in the processing.
　本発明は、かかる問題点に着目してなされたものであって、脱脂レシピを、低消費電力かつ短時間で設定でき、かつ、設定されたレシピに従って行われる実際の脱脂処理における時間浪費やエネルギ損失を可及的に小さくすることを主たる課題とするものである。 The present invention has been made with attention to such problems, and it is possible to set a degreasing recipe with low power consumption and in a short time, and to reduce wasted time and energy in the actual degreasing process performed according to the set recipe. The main objective is to minimize losses as much as possible.
　すなわち、本発明に係る脱脂レシピ設定方法は、
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを紐づけてメモリに蓄積するデータ蓄積ステップと、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析する解析ステップと、
　前記解析ステップでの解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定ステップと、が行われることを特徴とする。 That is, the skimming recipe setting method according to the present invention is as follows:
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data accumulation step of linking with degreasing result data indicating the results and accumulating them in memory;
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis step for analyzing based on physical analysis data and degreasing result data;
A recipe setting step of setting a degreasing recipe for the newly processed material based on the analysis result in the analysis step is performed.
　以上の構成によれば、示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いることにより、統計的かつ理論的なデータに基づく脱脂レシピを設定できるため、その後の実炉でのレシピ検証作業を不要または最小限にとどめることができる。その結果、脱脂レシピの設定に係る省電力化と時間短縮を図ることができる。示差熱測定装置および熱重量測定装置は、示差熱・熱重量測定装置という形態で提供されても良い。 According to the above configuration, by using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analysis device, it is possible to set a degreasing recipe based on statistical and theoretical data. Recipe verification work can be unnecessary or minimized. As a result, it is possible to save power and shorten the time involved in setting the degreasing recipe. The differential thermal measuring device and the thermogravimetric measuring device may be provided in the form of a differential thermal/thermogravimetric measuring device.
　さらに、示差熱測定装置、熱重量測定装置や熱機械分析装置は、実炉に比べ安価かつ小型であるため、これを複数台揃えることにより、パラレルでの脱脂レシピの設定を行うことができ、時間短縮をさらに促進することができる。 Furthermore, differential thermal measurement devices, thermogravimetry measurement devices, and thermomechanical analysis devices are cheaper and smaller than actual furnaces, so by having multiple devices, it is possible to set degreasing recipes in parallel. Time reduction can be further promoted.
　加えて、このようにして設定された脱脂レシピには、過去の処理物の示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置による既存処理物分析データと、実炉での脱脂結果データとに基づいて設定された理論的・統計的な裏付けがあるので、この脱脂レシピに従って行われる実際の脱脂処理における時間浪費やエネルギ損失の低減を図れる。 In addition, the degreasing recipe set in this way includes analysis data of past processed materials using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and analysis data of existing processed materials using an actual furnace. Since there is theoretical and statistical support established based on the degreasing result data, it is possible to reduce wasted time and energy loss in the actual degreasing process performed according to this degreasing recipe.
本発明の一実施形態における脱脂レシピ設定方法で用いられる脱脂レシピ設定装置、脱脂炉および示差熱・熱重量測定装置を示す全体模式図である。1 is an overall schematic diagram showing a degreasing recipe setting device, a degreasing furnace, and a differential heat/thermogravimetric measuring device used in a degreasing recipe setting method in an embodiment of the present invention.
同実施形態における脱脂レシピ設定装置の機能ブロック図である。It is a functional block diagram of the degreasing recipe setting device in the same embodiment.
同実施形態における蓄積データの一例を示すデータ説明図である。It is a data explanatory diagram showing an example of accumulated data in the same embodiment.
同実施形態における温度シフト特性およびそれに基づいて算出される、各昇温レートでの示差熱・熱重量変化を示すグラフである。It is a graph which shows the temperature shift characteristic in the same embodiment, and the differential heat/thermogravity change calculated based on it at each temperature increase rate.
同実施形態における脱脂レシピ設定方法を説明するフローチャートである。It is a flowchart explaining the degreasing recipe setting method in the same embodiment.
同実施形態において設定された脱脂レシピの一例である。This is an example of a degreasing recipe set in the same embodiment.
　以下、本実施形態に係る脱脂レシピ設定装置を、図面を参照して説明する。
＜構成＞
　この脱脂レシピ設定装置１００は、図１に示すように、処理物を脱脂炉２００で脱脂処理する際の脱脂レシピを、示差熱・熱重量測定装置３００を用いて設定する装置である。示差熱・熱重量測定装置３００は、示差熱測定装置および熱重量測定装置が一体となった分析装置であるが、これが個別の分析装置として用意されてもよい。 Hereinafter, a degreasing recipe setting device according to this embodiment will be explained with reference to the drawings.
<Configuration>
As shown in FIG. 1, this degreasing recipe setting device 100 is a device that uses a differential thermal/thermogravimetric measuring device 300 to set a degreasing recipe for degreasing a processed material in a degreasing furnace 200. The differential thermal/thermogravimetric measuring device 300 is an analysis device in which a differential thermal measuring device and a thermogravimetric measuring device are integrated, but this may be prepared as a separate analytical device.
　まず、この脱脂レシピ設定装置１００の詳細説明に先だって、前記脱脂炉２００と示差熱・熱重量測定装置３００とについて簡単に説明する。 First, prior to a detailed explanation of the degreasing recipe setting device 100, the degreasing furnace 200 and the differential thermal/thermogravimetric measuring device 300 will be briefly explained.
　脱脂炉２００は、詳細は図示しないが、セラミック成形体などの処理物を収容する加熱炉（以下、実炉ともいう。）と、この加熱炉内の温度、圧力、ガス種などを制御する制御装置とを備えたものであり、この制御装置に組み込まれた脱脂レシピにしたがって加熱炉内の処理物が加熱され、脱脂処理される。 Although details are not shown, the degreasing furnace 200 includes a heating furnace (hereinafter also referred to as an actual furnace) that accommodates a processed material such as a ceramic molded body, and a controller that controls the temperature, pressure, gas type, etc. in this heating furnace. The object to be processed in the heating furnace is heated and degreased according to the degreasing recipe incorporated in this control device.
　示差熱・熱重量測定装置３００は、詳細は図示しないが、測定対象物を収容する炉と、この炉内の温度、ガス種などを制御する制御装置と、測定対象物の熱重量変化量を測定する熱重量変化量測定機構と、測定対象物を示差熱分析する示差熱分析機構とを備えたものであり、測定対象物の分析結果を示す分析データ、すなわち熱重量変化データおよび示差熱データを出力する。この示差熱・熱重量測定装置３００は、机上にも載せられるほどの容量及び重量であり、脱脂炉２００に比べて極めて小さく低価格のものである。 Although the details are not shown, the differential thermal/thermogravimetric measuring device 300 includes a furnace that houses the object to be measured, a control device that controls the temperature, gas type, etc. in the furnace, and a thermogravimetric change amount of the object to be measured. It is equipped with a thermogravimetric change measurement mechanism for measuring and a differential thermal analysis mechanism for differential thermal analysis of the object to be measured, and it generates analysis data indicating the analysis results of the object to be measured, that is, thermogravimetric change data and differential thermal data. Output. This differential heat/thermogravimetry measuring device 300 has a capacity and weight that can be placed on a desk, and is extremely small and inexpensive compared to the degreasing furnace 200.
　この実施形態では、この示差熱・熱重量測定装置３００の測定対象物として、前記処理物の一部、例えば、処理物の一片や処理物を砕いた粉体が用いられる。 In this embodiment, a part of the processed material, for example, a piece of the processed material or a powder obtained by crushing the processed material, is used as the object to be measured by the differential thermal/thermogravimetric measuring device 300.
　次に、脱脂レシピ設定装置１００について説明する。 Next, the degreasing recipe setting device 100 will be explained.
　この脱脂レシピ設定装置１００は、ＣＰＵ、メモリ、通信インタフェース、入出力インタフェースなどを備えた所謂コンピュータであり、前記メモリに記憶された所定のプログラムに従ってＣＰＵおよびその周辺機器が協動することにより、図２に示すように、データ蓄積部、抽出部、解析部、レシピ設定部等としての機能を発揮する。 This degreasing recipe setting device 100 is a so-called computer equipped with a CPU, a memory, a communication interface, an input/output interface, etc., and the CPU and its peripheral devices cooperate according to a predetermined program stored in the memory. 2, it functions as a data storage section, extraction section, analysis section, recipe setting section, etc.
　なお、この脱脂レシピ設定装置１００は、物理的に単一のコンピュータで形成されるものに限られない。例えば、サーバ／クライアントシステムなどといった複数のコンピュータを無線ないし有線で通信可能に接続したものでもよいし、その機能の一部ないし全部を前記脱脂炉２００や示差熱・熱重量測定装置３００の制御装置が兼ねるようにしたものでもかまわない。 Note that this degreasing recipe setting device 100 is not limited to being physically formed by a single computer. For example, a plurality of computers such as a server/client system may be connected to enable wireless or wired communication, and some or all of the functions may be implemented by the control device of the degreasing furnace 200 or the differential thermal/thermogravimetric measuring device 300. It doesn't matter if it is made to double as a.
　次にこの脱脂レシピ設定装置１００の各部について図２等を参照して詳述する。 Next, each part of this degreasing recipe setting device 100 will be described in detail with reference to FIG. 2 and the like.
（１）データ蓄積部
　データ蓄積部は、過去に脱脂炉で脱脂処理された処理物（以下、既存処理物ともいう。）に関するデータである蓄積データを当該処理物ごとに受け付けて前記メモリの所定領域に蓄積するものである。 (1) Data storage unit The data storage unit receives accumulated data, which is data related to processed items that have been degreased in the past in a degreasing furnace (hereinafter also referred to as existing processed items), for each processed item, and stores it in the memory. It is something that accumulates in a region.
　蓄積データは、図３に示すように、既存処理物を脱脂処理した結果を示す脱脂結果データ、脱脂処理前の当該既存処理物の一部を示差熱・熱重量測定装置で分析した分析データ（以下、既存処理物分析データともいう。）および当該既存処理物の分類コードから構成されている。 As shown in Figure 3, the accumulated data includes degreasing result data showing the results of degreasing the existing treated material, and analysis data obtained by analyzing a part of the existing treated material before degreasing using a differential thermal/thermogravimetric measuring device ( (hereinafter also referred to as existing processing product analysis data) and the classification code of the existing processing product.
　前記既存処理物分析データは、グラフ表示すると、同図に示すようなものであり、当該既存処理物の一部を異なる昇温レートで昇温したときのそれぞれの熱重量変化データおよび示差熱分析データを含んでいる。 When the existing processing material analysis data is displayed in a graph, it is as shown in the same figure, and the respective thermogravimetric change data and differential thermal analysis when a part of the existing processing material is heated at different heating rates. Contains data.
　前記脱脂結果データには、同図に示すように、脱脂処理が正常終了したか、異常終了したかを示す事項と、脱脂レシピとが含まれる。異常とは、処理物の割れ、欠け、許容を越えた変形などが含まれる。 As shown in the figure, the degreasing result data includes items indicating whether the degreasing process has ended normally or abnormally, and a degreasing recipe. Abnormalities include cracks, chips, and unacceptable deformation of the processed material.
　これら既存処理物分析データおよび脱脂結果データは、示差熱・熱重量測定装置および脱脂炉からそれぞれ有線または無線で送信され、オンラインで受け付けられるが、オフライン、すなわち、ＵＳＢなどの携帯記録媒体を用いたりオペレータによる入力を利用したりして受け付けるようにしてもよい。 These existing processed product analysis data and degreasing result data are transmitted by wire or wirelessly from the differential thermal/thermogravimetric measuring device and the degreasing furnace, respectively, and are accepted online. It may also be accepted using input by an operator.
　前記分類コードは、当該既存処理物が、予め定められた分類のどこに属するかを示すものであり、例えば、重量が予め定められた複数の範囲のうちのどれか、形状が予め定められた所定形状のどれに類似するか、容量が予め定められた範囲のうちのどれか、を規定する。すなわち、分類とは、処理物の重量、形状および容量で定められたものであり、１つの分類には一定程度の範囲が設定されている。ここではオペレータが、分類コードを入力するが、三次元形状測定機や重量計などを用いて自動入力するようにしてもよい。 The classification code indicates to which of the predetermined classifications the existing processed material belongs; for example, the weight falls within a plurality of predetermined ranges, or the shape falls within a predetermined range. The shape is similar and the capacity is within a predetermined range. That is, the classification is determined by the weight, shape, and volume of the processed material, and each classification has a certain range. Although the operator inputs the classification code here, it may be automatically input using a three-dimensional shape measuring machine, a weight scale, or the like.
（２）抽出部
　この抽出部は、前記データ蓄積部に蓄積された複数の蓄積データから、後述する新規処理物の解析に用いられる、既存処理物の蓄積データを抽出するものである。 (2) Extraction unit This extraction unit extracts accumulated data of existing processing items, which will be used for analysis of new processing items to be described later, from a plurality of accumulated data accumulated in the data storage unit.
　抽出条件は、分類コードが一致、すなわち、新規処理物と重量、形状および容量が同一又は近似する既存処理物の蓄積データであること、およびその既存処理物の分析データが、前記新規処理物分析データと合致または近似することである。分析データ同士が合致または近似するかどうかの判断には、例えば、これら分析データが示す示差熱曲線および熱重量曲線において、対応する各ポイントの差分の二乗平均が所定値以下になるなど、統計学的手法が用いられる。 The extraction conditions are that the classification code matches, that is, it is the accumulated data of an existing processed product that is the same or similar in weight, shape, and volume to the newly processed product, and that the analysis data of the existing processed product is the same as the newly processed product analysis. Matching or approximating data. In order to judge whether the analytical data match or approximate each other, for example, in the differential thermal curve and thermogravimetric curve shown by these analytical data, statistical methods are used, such as checking that the root mean square of the difference of each corresponding point is less than a predetermined value. A method is used.
（３）解析部
　この解析部は、未だ脱脂レシピが定められていない新たな処理物（以下、新規処理物という。）の一部を、示差熱・熱重量測定装置３００を用いて分析したデータである新規処理物分析データを受け付け、この新規処理物分析データを、前記抽出部が抽出した既存処理物分析データおよび脱脂結果データに基づいて解析するものである。この新規処理物分析データは当該新規処理物の分類コードと紐づけられている。なお、これら新規処理物分析データ及び分類コードの受け付け態様は、既存処理物分析データ及びその分類コードと同様である。 (3) Analysis section This analysis section analyzes data using the differential thermal/thermogravimetric measuring device 300 on a part of the newly processed material for which no degreasing recipe has been determined yet (hereinafter referred to as the newly processed material). The newly processed product analysis data is received, and the new processed product analysis data is analyzed based on the existing processing product analysis data and degreasing result data extracted by the extraction section. This newly processed material analysis data is linked to the classification code of the new processed material. Note that the manner in which these newly processed material analysis data and classification codes are accepted is the same as that for existing processed material analysis data and their classification codes.
　しかして、この解析部は、次に説明するように、既存処理物シフト特性算出部、新規処理物熱重量変化推定部および閾値設定部を備えている。 As described below, this analysis section includes an existing processing material shift characteristic calculation section, a new processing material thermogravimetric change estimation section, and a threshold value setting section.
（３－１）既存処理物シフト特性算出部
　この既存処理物シフト特性算出部は、前記既存処理物分析データに基づいて当該既存処理物の示差熱および熱重量変化の昇温レートの違いによる温度シフト特性（以下、既存処理物シフト特性ともいう。）を算出するものである。 (3-1) Existing Processing Material Shift Characteristic Calculation Unit This existing processing material shift characteristic calculation unit calculates the temperature of the existing processing material based on the difference in heating rate of differential heat and thermogravimetric change of the existing processing material based on the existing processing material analysis data. Shift characteristics (hereinafter also referred to as existing processing material shift characteristics) are calculated.
　前記既存処理物分析データには、前述したように、当該既存処理物について、複数の異なる昇温レートでの示差熱および熱重量変化が含まれている。 As described above, the existing processing material analysis data includes differential heat and thermogravimetric changes at a plurality of different heating rates for the existing processing material.
　この既存処理物シフト特性算出部は、図４に示すように、これらの互いに異なる昇温レートでそれぞれ実測した示差熱および熱重量変化の差分に基づいて、所望の各昇温レートにおける示差熱および熱重量変化の実測値からのシフト量である既存処理物シフト特性を算出する。 As shown in FIG. 4, this existing processing material shift characteristic calculating section calculates the differential heat and thermogravimetric change at each desired heating rate based on the difference in the differential heat and thermogravimetric change actually measured at these different heating rates. The shift characteristic of the existing processed material, which is the amount of shift from the actual measured value of thermogravimetric change, is calculated.
（３－２）新規処理物熱重量変化推定部
　前記抽出部によって抽出された既存処理物は、新規処理物の形態（重量、形状、容量）と分析データの点において近似するものであるから、これら既存処理物の温度シフト特性も新規処理物の温度シフト特性に近似すると推定される。 (3-2) Newly processed product thermogravimetric change estimating unit Since the existing processed product extracted by the extraction unit is similar in terms of the form (weight, shape, capacity) and analysis data of the new processed product, It is estimated that the temperature shift characteristics of these existing treatments are also similar to the temperature shift characteristics of the new treatments.
　これを前提として、この新規処理物熱重量変化推定部は、既存処理物シフト特性に基づき、当該新規処理物の温度シフト特性である新規処理物シフト特性を算出する。 Based on this assumption, the new processing material thermogravimetric change estimation unit calculates the new processing material shift characteristic, which is the temperature shift characteristic of the new processing material, based on the existing processing material shift characteristic.
　算出方法としては、例えば、新規処理物分析データと既存処理物分析データの差分（例えば、これら２つの分析データの対応する各ポイントの差分の二乗平均など）に基づいた補正演算を前記既存処理物シフト特性に施して、新規処理物シフト特性を算出する。 As a calculation method, for example, a correction calculation based on the difference between the analysis data of the new treatment object and the analysis data of the existing treatment object (for example, the root mean square of the difference of each corresponding point of these two analysis data) is performed on the existing treatment object. The shift characteristic is applied to the shift characteristic to calculate the shift characteristic of the new processing object.
　その他に、新規処理物シフト特性を前記既存処理物シフト特性と一致させてもよいし、また、例えば、新規処理物分析データを挟んで２つの異なる既存処理物分析データがあった場合に、それらのシフト特性の中間値を新規処理物シフト特性とするなど、複数の異なる既存処理物のシフト特性から処理物シフト特性を算出するようにしてもよい。 In addition, the new processing material shift characteristics may be made to match the existing processing material shift characteristics, or, for example, if there are two different existing processing material analysis data with the new processing material analysis data in between, The processing object shift characteristic may be calculated from the shift characteristics of a plurality of different existing processing objects, such as by setting the intermediate value of the shift characteristics of the new processing object as the new processing object shift characteristic.
　そして、この新規処理物熱重量変化推定部は、前記新規処理物シフト特性を前記新規処理物分析データに適用して、所定の昇温レートでの当該新規処理物の熱重量変化を推定する。 Then, the newly processed material thermogravimetric change estimation unit applies the new processed material shift characteristic to the new processed material analysis data to estimate the thermogravimetric change of the newly processed material at a predetermined temperature increase rate.
（３－３）閾値設定部
　抽出された既存処理物と新規処理物は、形態（分類コード）と分析データの点において近似するから、昇温時の挙動においても近似すると考えられ、既存処理物に異常が生じた際の熱重量変化が新規処理物に与えられると、同様に異常が生じると推定される。 (3-3) Threshold value setting section Since the extracted existing processed material and the newly processed material are similar in terms of morphology (classification code) and analysis data, it is thought that they are similar in behavior when the temperature is increased. It is presumed that if the thermogravimetric change that occurs when an abnormality occurs is applied to a newly treated product, a similar abnormality will occur.
　これを前提として、この閾値設定部は、既存処理物の脱脂結果データに基づいて前記新規処理物に異常が生じる限界熱重量変化を算出し、この限界熱重量変化に基づいて、該新規処理物の脱脂処理時における熱重量変化の閾値を設定する。 On this premise, this threshold value setting unit calculates a critical thermogravimetric change that causes an abnormality in the newly treated material based on the degreasing result data of the existing treated material, and based on this critical thermogravimetric change, Set the threshold for thermogravimetric change during degreasing.
　具体的には、この閾値設定部は、まず、既存処理物に割れ、欠けまたは想定外変形が生じた脱脂レシピでの昇温レートと当該既存処理物の温度シフト特性とに基づいて、当該既存処理物の脱脂処理中に異常が生じたときの熱重量変化を算出する。 Specifically, the threshold value setting unit first determines the temperature of the existing material based on the temperature increase rate in the degreasing recipe in which cracks, chips, or unexpected deformation have occurred in the existing material and the temperature shift characteristics of the existing material. Calculate the thermogravimetric change when an abnormality occurs during degreasing of the processed material.
　次に、閾値設定部は、この既存処理物の異常発生時の熱重量変化に基づき、新規処理物に異常が生じない限界熱重量変化を算出する。 Next, the threshold value setting unit calculates a limit thermogravimetric change at which no abnormality occurs in the new processing object, based on the thermogravimetric change when an abnormality occurs in the existing processing object.
　その算出方法としては、例えば、新規処理物分析データと既存処理物分析データの差分（例えば、これら２つの分析データの対応する各ポイントの差分の二乗平均など）に応じた補正演算を既存処理物の異常発生時の熱重量変化に施して、新規処理物の限界熱重量変化を算出する。 The calculation method is, for example, to perform a correction calculation according to the difference between the new processed material analysis data and the existing processed material analysis data (for example, the root mean square of the difference between the corresponding points of these two analytical data). Calculate the critical thermogravimetric change of the newly processed material by applying it to the thermogravimetric change when an abnormality occurs.
　新規処理物の限界熱重量変化の算出方法としては、その他に、例えば前記既存処理物の異常発生時の熱重量変化と一致させてもよいし、また、例えば、新規処理物分析データを挟んで２つの異なる既存処理物分析データがあった場合に、それら既存処理物の異常発生時の熱重量変化の中間値を新規処理物の限界熱重量変化とするなど、複数の異なる既存処理物の異常発生時の熱重量変化から新規処理物の限界熱重量変化を算出してもよい。 In addition, as a method for calculating the critical thermogravimetric change of the newly processed material, for example, it may be made to match the thermogravimetric change when an abnormality occurs in the existing material, or, for example, it may be calculated using analysis data of the newly processed material. If there is analysis data for two different existing processed products, the intermediate value of the thermogravimetric change at the time of abnormality of the existing processed products is set as the critical thermogravimetric change of the new processed product. The critical thermogravimetric change of the newly processed material may be calculated from the thermogravimetric change at the time of generation.
　次に閾値設定部は、前記限界熱重量変化に基づいて前記閾値を設定する。 Next, the threshold value setting section sets the threshold value based on the limit thermogravimetric change.
　閾値は、前記限界熱重量変化と合致させてもよいし、限界熱重量変化に安全係数を乗じた、あるいは差し引いた値を閾値としてもよい。 The threshold value may match the limit thermogravimetric change, or may be a value obtained by multiplying or subtracting the critical thermogravimetric change by a safety factor.
（４）レシピ設定部
　このレシピ設定部は、新規処理物シフト特性に基づいて各昇温レートでの当該新規処理物の熱重量変化を算出し、そのうちから熱重量変化が前記閾値以内となる昇温レートを定め、その昇温レート以下となる脱脂レシピを設定するものである。 (4) Recipe setting section This recipe setting section calculates the thermogravimetric change of the new processing material at each temperature increase rate based on the shift characteristics of the new processing material, and calculates the thermogravimetric change of the new processing material at each temperature increase rate, A temperature rate is determined and a degreasing recipe that is less than or equal to the temperature increase rate is set.
＜レシピ設定方法＞
　次に、このレシピ設定装置を利用したレシピ設定方法について説明する。 <How to set recipe>
Next, a recipe setting method using this recipe setting device will be described.
（第１ステップ：データ蓄積ステップ）
　既存処理物の過去においてなされた脱脂処理の結果を示す脱脂結果データ、当該既存処理物の一部を示差熱・熱重量測定装置によって分析した既存処理物分析データおよび当該既存処理物の分類コードを、データ蓄積部が取得し、メモリに蓄積する。 (1st step: data accumulation step)
Degreasing result data showing the results of past degreasing of existing treated items, analysis data of existing treated items obtained by analyzing a part of the existing treated items using a differential thermal/thermogravimetric measuring device, and classification codes of the existing treated items. , is acquired by the data storage unit and stored in memory.
（第２ステップ：新規処理物の分析データ取得ステップ）
　オペレータが、新規処理物の一部を、示差熱・熱重量測定装置を用いて分析するとともに、当該新規処理物の分類コードを定めて入力する。 (Second step: step of acquiring analytical data for new processed material)
The operator analyzes a part of the newly processed material using a differential thermal/thermogravimetric measuring device, and also determines and inputs a classification code for the newly processed material.
　その分析データ（新規処理物分析データ）および分類コードを前記解析部が取得する。 The analysis section acquires the analysis data (newly processed material analysis data) and classification code.
（第３ステップ：抽出ステップ）
　前記抽出部が、前記既存処理物分析データと新規処理物分析データとを比較し、前述した抽出条件によって、解析に用いる１以上の既存処理物分析データおよびそれに紐づけられた脱脂結果データを抽出する。 (Third step: Extraction step)
The extraction unit compares the existing process product analysis data with the new process product analysis data, and extracts one or more existing process product analysis data and degreasing result data linked thereto to be used for analysis according to the extraction conditions described above.
（第４ステップ：既存処理物シフト特性算出ステップ）
　他方、前記既存処理物シフト特性算出が、既存処理物分析データに基づいて、当該既存処理物の示差熱および熱重量変化の昇温レートの違いによる温度シフト特性である既存処理物シフト特性を算出する。 (Fourth step: existing processing material shift characteristic calculation step)
On the other hand, the existing processing material shift characteristic calculation calculates the existing processing material shift characteristic, which is a temperature shift characteristic due to a difference in temperature increase rate of differential heat and thermogravimetric change of the existing processing material, based on the existing processing material analysis data. do.
（第５ステップ：新規処理物熱重量変化推定ステップ）
　次に、新規処理物熱重量変化推定部が、前記既存処理物シフト特性と前記新規処理物分析データとに基づいて、当該新規処理物の温度シフト特性である新規処理物シフト特性を算出し、この新規処理物シフト特性から、各昇温レートでの当該新規処理物の熱重量変化を推定算出する。 (Fifth step: Estimation step of thermogravimetric change of new processed material)
Next, the new processing material thermogravimetric change estimation unit calculates the new processing material shift characteristic, which is the temperature shift characteristic of the new processing material, based on the existing processing material shift characteristic and the new processing material analysis data, From this shift characteristic of the newly processed material, the thermogravimetric change of the newly processed material at each temperature increase rate is estimated.
（第６ステップ：閾値設定ステップ）
　次に前記閾値設定ステップが、前記脱脂結果データに基づいて前記新規処理物に異常が生じない限界熱重量変化を算出し、この限界熱重量変化に基づいて前記閾値を設定する。 (6th step: threshold setting step)
Next, the threshold value setting step calculates a critical thermogravimetric change at which no abnormality occurs in the newly processed material based on the degreasing result data, and sets the threshold value based on this critical thermogravimetric change.
（第７ステップ：脱脂レシピ設定ステップ）
　次に、前記脱脂レシピ設定部が、各昇温レートでの当該新規処理物の熱重量変化のうちから、熱重量変化が前記閾値以内となる昇温レートを定め、その昇温レート以下となる脱脂レシピを設定する。 (7th step: Skimming recipe setting step)
Next, the degreasing recipe setting unit determines a temperature increase rate at which the thermogravimetric change is within the threshold value from among the thermogravimetric changes of the new treatment material at each temperature increase rate, and the degreasing recipe setting unit determines a temperature increase rate at which the thermogravimetric change is within the threshold value, Set a skimming recipe.
　その具体例を、図４を参照して説明する。 A specific example will be explained with reference to FIG. 4.
　炉内の昇温レートを一定に保った場合でも、処理物中のバインダー等が分解・燃焼等する際に熱を発生するので、当該処理物の時間経過に伴う温度変化は、示差熱分析によれば、図４（ｃ）のようになり、分解・燃焼の間の熱重量変化が急峻なものとなる。 Even if the temperature increase rate in the furnace is kept constant, heat is generated when the binder, etc. in the processed material decomposes and burns, so temperature changes over time of the processed material cannot be measured by differential thermal analysis. According to this, the thermogravimetric change during decomposition and combustion becomes steep, as shown in FIG. 4(c).
　そこで、脱脂レシピ設定ステップでは、推定算出した所定の昇温レートでの熱重量変化曲線において、もっとも急峻な変化が生じる温度範囲（同図では０．５℃／ｍｉｎでのＡ℃～Ｂ℃）において、その間の熱重量変化が前記閾値以内となる昇温レートを定める。 Therefore, in the degreasing recipe setting step, the temperature range in which the steepest change occurs in the estimated thermogravimetric change curve at the predetermined heating rate (A to B at 0.5°C/min in the figure) In this step, a temperature increase rate is determined at which the thermogravimetric change is within the threshold value.
　他方、他の温度範囲においては、さらに大きな昇温レートとしても熱重量変化は前記閾値以内となるので、脱脂処理時の昇温レートを一定とせず、図４に示すように、他の温度範囲では、Ａ℃～Ｂ℃の区間より高い昇温レートに設定する。 On the other hand, in other temperature ranges, the thermogravimetric change remains within the above-mentioned threshold even if the temperature increase rate is even higher, so the temperature increase rate during degreasing is not constant, and as shown in FIG. In this case, the temperature increase rate is set to be higher than that in the section from A°C to B°C.
（第８ステップ：検証ステップ）
　前記脱脂レシピにしたがって、新規処理物を実炉で脱脂し、その結果を検証する。 (8th step: Verification step)
In accordance with the above degreasing recipe, the newly treated material will be degreased in an actual furnace and the results will be verified.
　このことによって得られた脱脂結果データは、当該新規処理物の一部の分析データ及び分類コードとともに前記蓄積データとして前記データ蓄積部が蓄積し、それ以降の別の新規処理物の脱脂レシピ設定に利用される。 The degreasing result data obtained through this process is accumulated by the data storage unit as the accumulated data together with some analysis data and classification code of the newly processed product, and is used in subsequent degreasing recipe settings for other newly processed products. used.
＜他の実施形態＞
　以下では、他の実施形態について説明する。 <Other embodiments>
Other embodiments will be described below.
　示差熱、熱重量変化は、脱脂ガスの種類によっても変動する。そこで、脱脂ガスごとに分析データを蓄積しておき、レシピ設定においては、脱脂ガス種を考慮するようにしてもよい。 Differential heat and thermogravimetric changes also vary depending on the type of degreasing gas. Therefore, analysis data may be accumulated for each degreasing gas, and the type of degreasing gas may be taken into consideration when setting the recipe.
　解析ステップまたはこれに加えて脱脂レシピ設定ステップを、ＡＩを利用した機械学習で行ってもよい。 The analysis step or, in addition to this, the degreasing recipe setting step may be performed by machine learning using AI.
　実炉内に配置された温度センサで測定された昇温レートと、実炉に収容された処理物近傍での実際の昇温レートとは、常に一致するわけではなく、例えば、実炉に一度に収容される処理物の数量に応じて、処理物に対する炉内温度の熱の入り方が変動する。処理物の数量が少ない場合と、多い場合とでは、少ない場合の方が測定昇温レートと実際の昇温レートとの差は小さくなる。 The temperature increase rate measured by a temperature sensor placed in an actual furnace and the actual temperature increase rate near the processed material stored in the actual furnace do not always match. Depending on the number of items to be processed stored in the furnace, the way in which heat enters the furnace varies depending on the number of items to be processed. When the number of objects to be processed is small or large, the difference between the measured temperature increase rate and the actual temperature increase rate is smaller when the number of objects is small.
　そこで、前記脱脂結果データに、脱脂炉内に一度に収容された既存処理物の数量（１バッチでの既存処理物の数量）をさらに含むようにし、前記脱脂レシピ設定ステップでは、前記既存処理物の数量を参照しながら、脱脂炉内に一度に収容される新規処理物の数量にも基づいて脱脂レシピを設定するようにしてもよい。例えば、前記実施形態で設定した閾値や昇温レート、脱脂レシピ等を、オペレータの入力によって取得した１バッチで処理する新規処理物の数量に基づいて補正するといった態様が考えられる。具体的には、処理物の数量が多いほど、新規処理物に対する炉内熱の入り方は緩やかになるので、昇温レートを下げる方向に補正する。 Therefore, the degreasing result data further includes the quantity of the existing processed materials stored in the degreasing furnace at one time (the quantity of the existing processed materials in one batch), and in the degreasing recipe setting step, the existing processed materials are stored in the degreasing furnace. The degreasing recipe may also be set based on the quantity of newly processed materials to be accommodated in the degreasing furnace at one time while referring to the quantity. For example, it is conceivable that the threshold value, temperature increase rate, degreasing recipe, etc. set in the embodiment described above are corrected based on the quantity of new processing items to be processed in one batch obtained by operator input. Specifically, the larger the number of objects to be processed, the slower the rate at which heat enters the furnace for new objects to be processed, so the temperature increase rate is corrected to lower.
　このようにすれば、少量の処理物の評価結果からより多くの処理物を脱脂する実際の生産レシピに反映することができる。 In this way, the evaluation results for a small amount of processed material can be reflected in the actual production recipe for degreasing a larger amount of processed material.
　前記実施形態では、既存処理物分析データ及び新規処理物分析データからそれぞれのシフト特性を算出し、このシフト特性から熱重量変化を算出していたが、例えば、前記機械学習を利用すれば、ブラックボックス的な演算により、シフト特性を算出せず、熱重量変化を算出することもできるし、あるいは閾値を設定することなく、脱脂レシピを設定することも可能である。 In the above embodiment, the shift characteristics were calculated from the existing processing material analysis data and the new processing material analysis data, and the thermogravimetric change was calculated from the shift characteristics. For example, if the machine learning described above is used, black Using box-like calculations, it is possible to calculate thermogravimetric changes without calculating shift characteristics, or it is also possible to set a degreasing recipe without setting a threshold value.
　前記実施形態では、新規処理物の熱重量変化を算出する際に、既存処理物の分析データから当該既存処理物の温度シフト特性を算出していたが、予め各既存処理物の温度シフト特性を算出しておき、この既存処理物シフト特性を蓄積データの１つとして蓄積しておいてもかまわない。 In the embodiment described above, when calculating the thermogravimetric change of a new treatment object, the temperature shift characteristics of the existing treatment object were calculated from the analysis data of the existing treatment object. It is also possible to calculate this existing processing material shift characteristic and store it as one of the stored data.
　前記実施形態では、新規処理物に異常が生じ得る限界熱重量変化または閾値の算出にあたって、異常が生じた場合の脱脂結果データを参照していたが、正常な脱脂結果データを参照してもよい。その場合、脱脂結果データに、脱脂した処理物の脱脂処理前からの形態変化を含めておき、その形態変化に基づいて限界熱重量変化または閾値を算出するようにしてもよい。形態変化は三次元形状測定機などを用いて測定すればよい。 In the embodiment described above, in calculating the critical thermogravimetric change or threshold value at which an abnormality may occur in a newly processed product, reference is made to the degreasing result data when an abnormality occurs, but normal degreasing result data may also be referred to. . In that case, the degreasing result data may include a change in the form of the degreased product from before the degreasing process, and the critical thermogravimetric change or threshold value may be calculated based on the change in form. The change in shape may be measured using a three-dimensional shape measuring device or the like.
　前記実施形態では、脱脂レシピを設定していたが、脱脂レシピを設定せず、新規処理物に異常が生じない熱重量変化の閾値を算出するところまでの構成でもかまわない。すなわち、脱脂処理物の解析方法ないし解析装置であってもかまわない。このような解析方法、解析装置によって新規処理物の閾値が判定できるので、脱脂レシピの設定のみならず、工業炉における焼結などの他の用途にもその閾値を用いることができる。 In the embodiment described above, a degreasing recipe is set, but the configuration may be such that the degreasing recipe is not set and a threshold value of thermogravimetric change that does not cause any abnormality in the newly processed material is calculated. In other words, it may be a method or an apparatus for analyzing a degreased product. Since the threshold value of a new product to be processed can be determined using such an analysis method and analysis device, the threshold value can be used not only for setting a degreasing recipe but also for other purposes such as sintering in an industrial furnace.
　前記分類には、例えば処理物の素材やバインダーの種類などを含めるようにしてもよい。 The classification may include, for example, the material of the processed material and the type of binder.
　前記実施形態では、１台の示差熱・熱重量測定装置を用いた構成であったが、これを複数台用いて、並列処理してもかまわない。
　前記実施形態での各ステップは、脱脂レシピ設定装置が行っていたが、これら各ステップの一部または全部を人間が行うようにしてもよい。
　また、次のような方法も可能である。
　すなわち、予め既存処理物の各昇温レートでの熱重量変化の特徴値をそれぞれ算出するとともに、該特徴値と昇温レートとの相関を算出しておき、前記相関に基づき新規処理物の所定の昇温レートでの熱重量変化を推定する。そして、その相関に基づいて、当該新規処理物に異常が生じない熱重量変化の閾値を設定し、あるいは、その相関に基づいて新規処理物の脱脂レシピを設定する。ここでの相関が請求項でいう温度シフト特性に相当する。
　これは、昇温レートと特徴値との間には一定の相関があることを本発明者は初めて見出してなされたものである。
　特徴値とは、例えば、熱重量変化曲線の一部または全部を時間微分した際のピーク（複数のピークがある場合は、いずれか所定のピークで、どのピークでもかまわない。）での温度である。
　具体的には、まず、各昇温レートでの特徴値をプロットすることにより、昇温レートと特徴値との間に所定関数で表される検量線／回帰曲線を作成する。このときの昇温レートは、設定値でもよいし実測値でもかまわない。
　そして、この検量線をテーブルや式にすることにより、新規処理物において、所望の昇温レートを与えた時の熱重量変化曲線を前記検量線から推定する。なお、ピーク幅に関してはここでは補正していないが、ピーク幅は別の曲線に乗ることもあり、これに関して別に補正してもよい。
　なお、特徴値としては、例えば熱重量変化曲線を二次微分や三次微分など複次微分したときのピークに基づいてもかまわないし、熱重量変化曲線から算出可能な他の値、例えばピーク面積など、昇温レートとの相関が認められる値を特徴値としてもかまわない。
　また、昇温レートとの相関が認められる値であれば、熱重量変化曲線の特徴値でなくともよい。例えば、示差熱変化曲線から算出される特徴値を用いてもよいし、示差熱・熱重量測定装置から取得できる各種パラメータや処理物の物性値などを用いてもよい。
　さらに、示唆熱・熱重量測定装置のみならず、熱機械分析装置（ＴＭＡ）を用いてもかまわない。この場合、前記実施形態において、「熱重量変化」という記載を「熱機械変化」に読み替える。なお、示唆熱・熱重量測定装置と熱機械分析装置（ＴＭＡ）との一方を用いる場合に限られず、これらの両方を用いてもよい。言い換えると、熱重量測定装置によって測定された熱重量変化、示唆熱測定装置による示差熱変化、及び、熱機械分析装置による熱機械変化の３つの分析結果のうちの１つ、又は、これらの２つ以上の任意の組合せを用いてもよい。 In the embodiment described above, one differential thermal/thermogravimetric measuring device is used, but a plurality of devices may be used to perform parallel processing.
Although each step in the embodiment was performed by the degreasing recipe setting device, a part or all of these steps may be performed by a human.
Further, the following method is also possible.
That is, the characteristic value of the thermogravimetric change at each temperature increase rate of the existing object to be treated is calculated in advance, and the correlation between the characteristic value and the temperature increase rate is calculated, and the predetermined value of the new object to be treated is determined based on the correlation. Estimate the thermogravimetric change at a heating rate of . Then, based on the correlation, a threshold value of thermogravimetric change that does not cause any abnormality in the newly processed material is set, or a degreasing recipe for the newly processed material is set based on the correlation. The correlation here corresponds to the temperature shift characteristic in the claims.
This was done after the inventor discovered for the first time that there is a certain correlation between the temperature increase rate and the characteristic value.
The characteristic value is, for example, the temperature at the peak (if there are multiple peaks, any predetermined peak is fine) when time-differentiating part or all of the thermogravimetric change curve. be.
Specifically, first, by plotting the characteristic values at each heating rate, a calibration curve/regression curve expressed by a predetermined function between the heating rate and the characteristic value is created. The temperature increase rate at this time may be a set value or an actually measured value.
Then, by converting this calibration curve into a table or formula, a thermogravimetric change curve when a desired heating rate is given to the newly processed material is estimated from the calibration curve. Although the peak width is not corrected here, the peak width may ride on a different curve, and this may be corrected separately.
Note that the characteristic value may be based on, for example, the peak obtained by performing multiple differentiation such as quadratic or cubic differentiation on the thermogravimetric change curve, or it may be based on other values that can be calculated from the thermogravimetric change curve, such as peak area, etc. , a value that is recognized to be correlated with the temperature increase rate may be used as the characteristic value.
Further, the value does not have to be a characteristic value of the thermogravimetric change curve as long as it has a correlation with the temperature increase rate. For example, characteristic values calculated from a differential thermal change curve may be used, or various parameters or physical property values of the processed material that can be obtained from a differential thermal/thermogravimetric measuring device may be used.
Furthermore, in addition to the suggestive heat/thermogravimetry device, a thermomechanical analyzer (TMA) may also be used. In this case, in the embodiment, the description of "thermogravimetric change" is replaced with "thermomechanical change." Note that the present invention is not limited to the case where one of the suggestive heat/thermogravimetry device and the thermomechanical analyzer (TMA) is used, and both of these may be used. In other words, one or two of the following three analysis results: a thermogravimetric change measured by a thermogravimetry device, a differential thermal change by a suggestive thermometer, and a thermomechanical change by a thermomechanical analyzer. Any combination of two or more may be used.
　その他、本発明は前記実施形態に限られるものではなく、その趣旨を逸脱しない範囲において種々の変形が可能である。 In addition, the present invention is not limited to the embodiments described above, and various modifications can be made without departing from the spirit thereof.
＜まとめ＞
　上述した構成の特徴をまとめると次の通りとなる。 <Summary>
The characteristics of the above-mentioned configuration are summarized as follows.
［１］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データおよび当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データを紐づけてメモリに蓄積するデータ蓄積ステップと、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析する解析ステップと、
　前記解析ステップでの解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定ステップと、が行われることを特徴とする脱脂レシピ設定方法。 [1]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analysis device, and the results of degreasing the existing processed material in a degreasing furnace. a data accumulation step of linking degreasing result data indicating the results and accumulating it in memory;
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis step for analyzing based on physical analysis data and degreasing result data;
A method for setting a degreasing recipe, comprising: a recipe setting step of setting a degreasing recipe for the new material to be processed based on the analysis result in the analysis step.
　［１］によれば、示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いることにより、統計的かつ理論的なデータに基づく脱脂レシピを設定できるため、その後の実炉でのレシピ検証作業を不要または最小限にとどめることができる。その結果、脱脂レシピの設定に係る省電力化と時間短縮を図ることができる。
　さらに、示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置は、実炉に比べ安価かつ小型であるため、これを複数台揃えることにより、パラレルでの脱脂レシピの設定を行うことができ、時間短縮をさらに促進することができる。
　加えて、このようにして設定された脱脂レシピは、過去の処理物の示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置による既存処理物分析データと、実炉での脱脂結果データとに基づいて設定された理論的・統計的な裏付けがあるものなので、設定されたレシピに従って行われる実際の脱脂処理における時間浪費やエネルギ損失の低減を図ることができる。 According to [1], by using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analysis device, it is possible to set a degreasing recipe based on statistical and theoretical data. Recipe verification work can be unnecessary or minimized. As a result, it is possible to save power and shorten the time involved in setting the degreasing recipe.
Furthermore, since differential thermal measurement devices, thermogravimetry measurement devices, and/or thermomechanical analysis devices are cheaper and smaller than actual furnaces, degreasing recipes can be set in parallel by having multiple devices. This can further reduce time.
In addition, the degreasing recipe set in this way is based on analysis data of existing processed materials using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and degreasing in an actual furnace. Since it has theoretical and statistical support set based on result data, it is possible to reduce wasted time and energy loss in the actual degreasing process performed according to the set recipe.
［２］
　前記データ蓄積ステップでは、紐づけられた前記既存処理物分析データおよび脱脂結果データが、対応する既存処理物の分類ごとに区別してメモリに蓄積され、
　前記新規処理物の分類と共通の分類に属する１以上の既存処理物の既存処理物分析データ及び脱脂結果データを抽出する抽出ステップがさらに行われ、
　前記解析ステップでは、前記抽出ステップで抽出された既存処理物分析データ及び脱脂結果データに基づいて新規処理物分析データが解析される［１］に記載の脱脂レシピ設定方法。 [2]
In the data accumulation step, the linked existing processed material analysis data and degreasing result data are stored in a memory separately for each classification of the corresponding existing processed material,
further performing an extraction step of extracting existing processed product analysis data and degreasing result data of one or more existing processed products that belong to a common classification with the new processed product classification,
In the degreasing recipe setting method according to [1], in the analysis step, new processed material analysis data is analyzed based on the existing processed material analysis data and the degreasing result data extracted in the extraction step.
　［２］によれば、新規処理物の解析にあたって、分類を利用することによって、より近しい既存処理物を参照することができるので、解析精度が向上し、脱脂レシピをより適切に設定することができる。 According to [2], when analyzing a new product, by using classification, it is possible to refer to existing products that are closer to each other, improving analysis accuracy and setting the degreasing recipe more appropriately. can.
［３］
　前記分類が、処理物の重量、形状、容量またはそれらの２以上の組み合わせで定められている［２］に記載の脱脂レシピ設定方法。 [3]
The degreasing recipe setting method according to [2], wherein the classification is defined by the weight, shape, capacity, or a combination of two or more of these.
。
　［３］の分類によれば、形態の近しい既存処理物の分析データや脱脂結果データを用いて新規処理物を解析できるので、その精度がさらに向上する。 .
According to the classification [3], a new processed product can be analyzed using the analysis data and degreasing result data of an existing processed product that has a similar shape, so the accuracy is further improved.
［４］
　前記抽出ステップでは、前記既存処理物分析データと新規処理物分析データとを比較して、解析ステップで用いる１以上の既存処理物分析データおよびそれに紐づけられた脱脂結果データをさらに抽出する［２］または［３］に記載の脱脂レシピ設定方法。 [4]
In the extraction step, the existing processed product analysis data and the new processed product analysis data are compared, and one or more existing processed product analysis data and degreasing result data linked thereto are further extracted for use in the analysis step [2 ] or the skimming recipe setting method described in [3].
　［４］によれば、熱反応特性が近しい既存処理物の分析データや脱脂結果データを用いて新規処理物を解析できるので、その精度がさらに向上する。具体的には、前記新規処理物分析データと合致または近似する１以上の既存処理物分析データを抽出することが好ましい。 According to [4], a newly processed product can be analyzed using analysis data and degreasing result data of existing processed products that have similar thermal reaction characteristics, so the accuracy is further improved. Specifically, it is preferable to extract one or more existing processed material analysis data that match or approximate the new processed material analysis data.
［５］
　前記解析ステップでは、
　前記既存処理物分析データに基づいて、当該既存処理物の示差熱および熱重量変化の昇温レートの違いによる温度シフト特性である既存処理物シフト特性を算出する既存処理物シフト特性算出ステップと、
　前記既存処理物シフト特性と前記新規処理物分析データとに基づいて、当該新規処理物の所定の昇温レートでの熱重量変化を推定する新規処理物熱重量変化推定ステップが行われ、
　前記レシピ設定ステップでは、前記新規処理物熱重量変化推定ステップで推定された熱重量変化が所定の閾値以内となるように、新規脱脂処理物の脱脂炉での脱脂レシピを設定する［１］ないし［４］いずれかに記載の脱脂レシピ設定方法。 [5]
In the analyzing step,
An existing treatment product shift characteristic calculation step of calculating an existing treatment product shift characteristic, which is a temperature shift characteristic due to a difference in a temperature rise rate of the differential heat and thermogravimetric change of the existing treatment product, based on the existing treatment product analysis data;
A new treated product thermogravimetric change estimation step is performed to estimate a thermogravimetric change of the new treated product at a predetermined temperature rise rate based on the existing treated product shift characteristic and the new treated product analysis data;
A degreasing recipe setting method according to any one of [1] to [4], in which in the recipe setting step, a degreasing recipe for a new degreasing treatment object in a degreasing furnace is set so that the thermogravimetric change estimated in the new treatment object thermogravimetric change estimation step is within a predetermined threshold value.
　［５］によれば、分析データから算出した温度シフト特性に基づいて所望の昇温レートでの熱重量変化を推定するという理論的な手法を用いているので、それに基づいて設定される脱脂レシピの信頼性を担保できるだけでなく、実炉での検証時に不具合が生じた際に、その原因解明や修正を的確に行うことができる。 According to [5], a theoretical method is used to estimate the thermogravimetric change at a desired heating rate based on the temperature shift characteristics calculated from analytical data, so the degreasing recipe is set based on that. This not only ensures the reliability of the system, but also enables accurate identification and correction of any defects that occur during verification in an actual reactor.
［６］
　前記新規処理物熱重量変化推定ステップでは、前記既存処理物シフト特性に基づいて、新規処理物の温度シフト特性である新規処理物シフト特性を算出し、この新規処理物シフト特性と前記新規処理物分析データとに基づいて、当該新規処理物の熱重量変化を推定する［５］に記載の脱脂レシピ設定方法。 [6]
In the new processing material thermogravimetric change estimation step, a new processing material shift characteristic, which is a temperature shift characteristic of the new processing material, is calculated based on the existing processing material shift characteristic, and this new processing material shift characteristic and the new processing material shift characteristic are calculated. The degreasing recipe setting method according to [5], wherein the thermogravimetric change of the newly processed material is estimated based on the analysis data.
　［６］によれば、［５］による効果がより顕著なものとなる。 According to [6], the effect of [5] becomes more remarkable.
［７］
　前記解析ステップでは、前記脱脂結果データに基づいて前記新規処理物に異常が生じ得る限界熱重量変化を算出し、この限界熱重量変化に基づいて前記閾値を設定する閾値設定ステップがさらに行われる［５］または［６］に記載の脱脂レシピ設定方法。 [7]
In the analysis step, a threshold value setting step is further performed in which a critical thermogravimetric change at which an abnormality may occur in the newly processed material is calculated based on the degreasing result data, and the threshold value is set based on this critical thermogravimetric change. 5] or the skimming recipe setting method described in [6].
　［７］によれば、新規処理物に異常が生じない閾値の設定を行うことができる。 According to [7], it is possible to set a threshold value at which no abnormality occurs in the newly processed object.
［８］
　前記脱脂結果データには、脱脂処理が正常終了したか異常終了したかを示す事項が含まれており、
　前記閾値設定ステップでは、異常終了の場合の脱脂結果データに基づいて前記閾値を設定する［７］に記載の脱脂レシピ設定方法。 [8]
The degreasing result data includes information indicating whether the degreasing process has ended normally or abnormally,
The degreasing recipe setting method according to [7], wherein in the threshold value setting step, the threshold value is set based on degreasing result data in the case of abnormal termination.
　［８］によれば、新規処理物に異常が生じない閾値の設定をより確実に行うことができる According to [8], it is possible to more reliably set a threshold value that does not cause abnormalities in newly processed items.
［９］
　前記脱脂結果データには、脱脂炉内に一度に収容された既存処理物の数量が含まれており、前記脱脂レシピ設定ステップでは、前記既存処理物の数量を参照しながら、脱脂炉内に一度に収容される新規処理物の数量にも基づいて、脱脂レシピが設定される［１］～［８］のいずれかに記載の脱脂レシピ設定方法。 [9]
The degreasing result data includes the quantity of the existing processed material stored in the degreasing furnace at one time, and in the degreasing recipe setting step, the quantity of the existing processed material is stored in the degreasing furnace once. The method for setting a degreasing recipe according to any one of [1] to [8], wherein the degreasing recipe is also set based on the quantity of the newly processed material to be accommodated.
　［９］によれば、少量の処理物の評価結果からより多くの処理物を脱脂する実際の生産レシピに反映することができる。 According to [9], the evaluation results for a small amount of processed material can be reflected in the actual production recipe for degreasing a larger amount of processed material.
［１０］
　予め、各昇温レートでの熱重量変化の特徴値をそれぞれ算出するとともに、該特徴値と昇温レートとの相関を算出し、該相関を前記温度シフト特性とする［５］ないし［８］のいずれかに記載の脱脂レシピ設定方法。
　［１０］の構成は、昇温レートと特徴値との間に一定の相関があることを本発明者が初めて見出してなされたものである。このことにより、昇温レートの違いによる熱重量変化の精度の高い推定が可能となる。
［１１］
　前記特徴値は、熱重量変化曲線を時間微分したピークでの温度である［６］に記載の脱脂レシピ設定方法。
　［１１］の構成によれば、複雑な演算をすることなく、熱重量変化の精度の高い推定が可能となる。
［１２］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データと脱脂結果データとに基づいて解析する解析部と、
　前記解析部の解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定部と、を備えていることを特徴とする脱脂レシピ設定装置。 [10]
In advance, calculate characteristic values of thermogravimetric changes at each temperature increase rate, calculate the correlation between the characteristic values and the temperature increase rate, and use the correlation as the temperature shift characteristic [5] to [8] The skimming recipe setting method described in any of the above.
The configuration [10] was created when the present inventor discovered for the first time that there is a certain correlation between the temperature increase rate and the characteristic value. This enables highly accurate estimation of thermogravimetric changes due to differences in heating rates.
[11]
The degreasing recipe setting method according to [6], wherein the characteristic value is a temperature at a peak obtained by time-differentiating a thermogravimetric change curve.
According to the configuration [11], it is possible to estimate thermogravimetric changes with high accuracy without performing complicated calculations.
[12]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis section that performs analysis based on physical analysis data and degreasing result data;
A degreasing recipe setting device comprising: a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
　［１２］の構成によれば、上記［１］～［１１］同様の作用効果を奏し得る。 According to the configuration [12], the same effects as in the above [1] to [11] can be achieved.
［１３］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データと脱脂結果データとに基づいて解析する解析部と、
　前記解析部の解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定部と、としての機能をコンピュータに発揮させることを特徴とするプログラム。 [13]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis section that performs analysis based on physical analysis data and degreasing result data;
A program that causes a computer to function as a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
　［１３］の構成によれば、上記［１］～［１１］同様の作用効果を奏し得る。 According to the configuration [13], the same effects as in the above [1] to [11] can be achieved.
［１４］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとをメモリに蓄積し、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定することを特徴とする脱脂処理物解析方法。 [14]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. The degreasing result data showing the results is stored in memory,
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. 1. A method for analyzing a degreased product, characterized in that analysis is performed based on physical analysis data and degreasing result data, and a threshold value of thermogravimetric change is set at which no abnormality occurs in the newly processed product.
　［１４］の構成によれば、上記［１］～［１１］同様の作用効果を奏し得るうえ、算出した閾値を用いて工業炉における焼結などの他の工程のレシピ検証等での消費エネルギ削減や時間短縮等を図ることができる。 According to the configuration [14], the same effects as those described in [1] to [11] can be achieved, and the calculated threshold value can be used to reduce energy consumption in recipe verification of other processes such as sintering in industrial furnaces. It is possible to reduce costs and time.
［１５］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定する解析部と、を備えていることを特徴とする脱脂処理物解析装置。 [15]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. What is claimed is: 1. An analysis device for degreased products, comprising: an analysis section that performs analysis based on physical analysis data and degreasing result data, and sets a threshold value of thermogravimetric change at which no abnormality occurs in the newly processed products.
　［１５］の構成によれば、上記［１４］同様の作用効果を奏し得る。 According to the configuration [15], the same effects as the above [14] can be achieved.
［１６］
　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定する解析部と、としての機能をコンピュータに発揮させることを特徴とするプログラム。 [16]
Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
Newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measuring device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. A program that causes a computer to function as an analysis section that performs analysis based on physical analysis data and degreasing result data and sets a threshold value of thermogravimetric change at which no abnormality occurs in the newly processed material.
　［１６］の構成によれば、上記［１４］同様の作用効果を奏し得る。 According to the configuration [16], the same effects as the above [14] can be achieved.
　過去の処理物の示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置による既存処理物分析データと、実炉での脱脂結果データとに基づいて設定された理論的・統計的な裏付けがあるので、この脱脂レシピに従って行われる実際の脱脂処理における時間浪費やエネルギ損失の低減を図れる。 The recipe is theoretically and statistically backed up by analysis data of past processed products using a differential calorimeter, thermogravimeter, and/or thermomechanical analyzer, as well as data on degreasing results in an actual furnace, so time and energy loss can be reduced during the actual degreasing process performed according to this degreasing recipe.
１００・・・脱脂レシピ設定装置
２００・・・脱脂炉
３００・・・示差熱・熱重量測定装置

  100... Degreasing recipe setting device 200... Degreasing furnace 300... Differential thermal/thermogravimetric measuring device

Claims (16)

  1. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データおよび当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データを紐づけてメモリに蓄積するデータ蓄積ステップと、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析する解析ステップと、
    　前記解析ステップでの解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定ステップと、が行われることを特徴とする脱脂レシピ設定方法。     Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analysis device, and the results of degreasing the existing processed material in a degreasing furnace. a data accumulation step of linking degreasing result data indicating the results and accumulating it in memory;
    The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis step for analyzing based on physical analysis data and degreasing result data;
    A method for setting a degreasing recipe, comprising: a recipe setting step of setting a degreasing recipe for the new material to be processed based on the analysis result in the analysis step.
  2. 　前記データ蓄積ステップでは、紐づけられた前記既存処理物分析データおよび脱脂結果データが、対応する既存処理物の分類ごとに区別してメモリに蓄積され、
    　前記新規処理物の分類と共通の分類に属する１以上の既存処理物の既存処理物分析データ及び脱脂結果データを抽出する抽出ステップがさらに行われ、
    　前記解析ステップでは、前記抽出ステップで抽出された既存処理物分析データ及び脱脂結果データに基づいて新規処理物分析データが解析される請求項１に記載の脱脂レシピ設定方法。     In the data accumulation step, the linked existing processed material analysis data and degreasing result data are stored in a memory separately for each classification of the corresponding existing processed material,
    further performing an extraction step of extracting existing processed product analysis data and degreasing result data of one or more existing processed products that belong to a common classification with the new processed product,
    2. The degreasing recipe setting method according to claim 1, wherein in said analyzing step, new processed material analysis data is analyzed based on existing processed material analysis data and degreasing result data extracted in said extraction step.
  3. 　前記分類が、処理物の重量、形状、容量またはそれらの２以上の組み合わせで定められている請求項２に記載の脱脂レシピ設定方法。 The degreasing recipe setting method according to claim 2, wherein the classification is defined by the weight, shape, capacity, or a combination of two or more of these.
  4. 　前記抽出ステップでは、前記既存処理物分析データと新規処理物分析データとを比較して、解析ステップで用いる１以上の既存処理物分析データおよびそれに紐づけられた脱脂結果データをさらに抽出する請求項２または３に記載の脱脂レシピ設定方法。 In the extraction step, the existing processed material analysis data and the newly processed material analysis data are compared, and one or more existing processed material analysis data and degreasing result data linked thereto are further extracted for use in the analysis step. The skimming recipe setting method described in 2 or 3.
  5. 　前記解析ステップでは、
    　前記既存処理物分析データに基づいて、当該既存処理物の示差熱、熱重量変化、および／または、熱機械変化の昇温レートの違いによる温度シフト特性である既存処理物シフト特性を算出する既存処理物シフト特性算出ステップと、
    　前記既存処理物シフト特性と前記新規処理物分析データとに基づいて、当該新規処理物の所定の昇温レートでの熱重量変化および／または熱機械変化を推定する新規処理物変化推定ステップが行われ、
    　前記レシピ設定ステップでは、前記新規処理物熱重量変化推定ステップで推定された熱重量変化および／または熱機械変化が所定の閾値以内となるように、新規脱脂処理物の脱脂炉での脱脂レシピを設定する請求項１に記載の脱脂レシピ設定方法。     In the analysis step,
    Based on the existing processing material analysis data, the existing processing material shift characteristic, which is a temperature shift characteristic due to a difference in temperature increase rate of differential heat, thermogravimetric change, and/or thermomechanical change, of the existing processing material is calculated. Processing material shift characteristic calculation step;
    A new processing material change estimation step of estimating a thermogravimetric change and/or thermomechanical change at a predetermined temperature increase rate of the new processing material is performed based on the existing processing material shift characteristic and the new processing material analysis data. I,
    In the recipe setting step, a recipe for degreasing the new degreased product in the degreasing furnace is set such that the thermogravimetric change and/or thermomechanical change estimated in the new process product thermogravimetric change estimation step is within a predetermined threshold. The method of setting a skimming recipe according to claim 1.
  6. 　前記新規処理物変化推定ステップでは、前記既存処理物シフト特性に基づいて、新規処理物の温度シフト特性である新規処理物シフト特性を算出し、この新規処理物シフト特性と前記新規処理物分析データとに基づいて、当該新規処理物の熱重量変化および／または熱機械変化を推定する請求項５に記載の脱脂レシピ設定方法。 In the new processing material change estimation step, a new processing material shift characteristic, which is a temperature shift characteristic of the new processing material, is calculated based on the existing processing material shift characteristic, and this new processing material shift characteristic and the new processing material analysis data are calculated. 6. The degreasing recipe setting method according to claim 5, wherein the thermogravimetric change and/or thermomechanical change of the newly processed material is estimated based on the above.
  7. 　前記解析ステップでは、前記脱脂結果データに基づいて前記新規処理物に異常が生じ得る限界熱重量変化を算出し、この限界熱重量変化に基づいて前記閾値を設定する閾値設定ステップがさらに行われる請求項５または６に記載の脱脂レシピ設定方法。 In the analysis step, a threshold value setting step is further performed in which a critical thermogravimetric change that can cause an abnormality in the newly processed material is calculated based on the degreasing result data, and the threshold value is set based on this critical thermogravimetric change. The skimming recipe setting method according to item 5 or 6.
  8. 　前記脱脂結果データには、脱脂処理が正常終了したか異常終了したかを示す事項が含まれており、
    　前記閾値設定ステップでは、異常終了の場合の脱脂結果データに基づいて前記閾値を設定する請求項７に記載の脱脂レシピ設定方法。     The degreasing result data includes information indicating whether the degreasing process has ended normally or abnormally,
    8. The degreasing recipe setting method according to claim 7, wherein in the threshold value setting step, the threshold value is set based on degreasing result data in the case of abnormal termination.
  9. 　前記脱脂結果データには、脱脂炉内に一度に収容された既存処理物の数量が含まれており、前記脱脂レシピ設定ステップでは、前記既存処理物の数量を参照しながら、脱脂炉内に一度に収容される新規処理物の数量にも基づいて、脱脂レシピが設定される請求項１に記載の脱脂レシピ設定方法。 The degreasing result data includes the quantity of the existing processed material stored in the degreasing furnace at one time, and in the degreasing recipe setting step, the quantity of the existing processed material is stored in the degreasing furnace once. 2. The method for setting a degreasing recipe according to claim 1, wherein the degreasing recipe is also set based on the quantity of the newly processed material accommodated in the degreasing recipe.
  10. 　前記既存処理物分析データには、既存処理物シフト特性算出ステップにおいて、予め、各昇温レートでの熱重量変化の特徴値および／または熱機械変化の特徴値をそれぞれ算出するとともに、該特徴値と昇温レートとの相関を算出し、該相関を前記温度シフト特性とする請求項５に記載の脱脂レシピ設定方法。 In the existing processing material analysis data, in the existing processing material shift characteristic calculation step, characteristic values of thermogravimetric changes and/or thermomechanical changes at each temperature increase rate are calculated in advance, and the characteristic values are calculated in advance. 6. The degreasing recipe setting method according to claim 5, wherein a correlation between and a temperature increase rate is calculated, and the correlation is used as the temperature shift characteristic.
  11. 　前記特徴値は、熱重量変化曲線のおよび／または熱機械変化曲線を時間微分したピークでの温度である請求項１０に記載の脱脂レシピ設定方法。 The degreasing recipe setting method according to claim 10, wherein the characteristic value is a temperature at a peak obtained by time-differentiating a thermogravimetric change curve and/or a thermomechanical change curve.
  12. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データと脱脂結果データとに基づいて解析する解析部と、
    　前記解析部の解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定部と、を備えていることを特徴とする脱脂レシピ設定装置。     Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
    The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis section that performs analysis based on physical analysis data and degreasing result data;
    A degreasing recipe setting device comprising: a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
  13. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データと脱脂結果データとに基づいて解析する解析部と、
    　前記解析部の解析結果に基づいて当該新規処理物の脱脂レシピを設定するレシピ設定部と、としての機能をコンピュータに発揮させることを特徴とするプログラム。     Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
    The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. an analysis section that performs analysis based on physical analysis data and degreasing result data;
    A program that causes a computer to function as a recipe setting section that sets a degreasing recipe for the newly processed material based on the analysis result of the analysis section.
  14. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとをメモリに蓄積し、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定することを特徴とする脱脂処理物解析方法。     Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. The degreasing result data showing the results is stored in memory,
    The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. 1. A method for analyzing a degreased product, characterized in that analysis is performed based on physical analysis data and degreasing result data, and a threshold value of thermogravimetric change is set at which no abnormality occurs in the newly processed product.
  15. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定する解析部と、を備えていることを特徴とする脱脂処理物解析装置。     Existing processed material analysis data, which is data obtained by analyzing a part of the existing processed material using a differential thermal measurement device, thermogravimetric measurement device, and/or thermomechanical analyzer, and data obtained by degreasing the existing processed material in a degreasing furnace. a data storage unit that stores degreasing result data indicating the results;
    The newly processed material analysis data, which is data obtained by analyzing a part of the newly processed material using a differential thermal measurement device, a thermogravimetric measurement device, and/or a thermomechanical analyzer, is added to the existing processing data accumulated in the data storage section. What is claimed is: 1. An analysis device for degreased products, comprising: an analysis section that performs analysis based on physical analysis data and degreasing result data, and sets a threshold value of thermogravimetric change at which no abnormality occurs in the newly processed products.
  16. 　既存処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである既存処理物分析データと、当該既存処理物を脱脂炉で脱脂した結果を示す脱脂結果データとを蓄積するデータ蓄積部と、
    　新規処理物の一部を示差熱測定装置、熱重量測定装置、および／または、熱機械分析装置を用いて分析したデータである新規処理物分析データを、前記データ蓄積部に蓄積された既存処理物分析データおよび脱脂結果データに基づいて解析し、当該新規処理物に異常が生じない熱重量変化の閾値を設定する解析部と、としての機能をコンピュータに発揮させることを特徴とするプログラム。

          A data storage unit that stores existing processed product analysis data, which is data obtained by analyzing a part of the existing processed product using a differential thermal analyzer, a thermogravimetric analyzer, and/or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed product in a degreasing furnace;
    A program that causes a computer to function as an analysis unit that analyzes new processed product analysis data, which is data obtained by analyzing a portion of a new processed product using a differential thermal analyzer, a thermogravimetric analyzer, and/or a thermomechanical analyzer, based on existing processed product analysis data and degreasing result data stored in the data storage unit, and sets a threshold value for thermogravimetric changes that will not cause abnormalities in the new processed product.
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Citations (3)

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JPH10153560A (en) * 1996-11-25 1998-06-09 Rigaku Corp Degreasing-condition decision method for metal-powder molding method
JPH11152501A (en) * 1997-11-17 1999-06-08 Shimazu Mectem Kk Heat treatment furnace
WO2021098234A1 (en) * 2019-11-22 2021-05-27 中南大学 In-situ acquired information-based method for heat treatment regulation and control, and application thereof

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Publication number Priority date Publication date Assignee Title
JPH10153560A (en) * 1996-11-25 1998-06-09 Rigaku Corp Degreasing-condition decision method for metal-powder molding method
JPH11152501A (en) * 1997-11-17 1999-06-08 Shimazu Mectem Kk Heat treatment furnace
WO2021098234A1 (en) * 2019-11-22 2021-05-27 中南大学 In-situ acquired information-based method for heat treatment regulation and control, and application thereof

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