How to set up a 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

Technical Field

[0001] The present invention relates to a device for setting a debinding recipe for a ceramic compact or the like, a method for setting a debinding recipe, and the like.

Background Art

[0002] In this type of debinding device, as shown in Patent Document 1, a debinding process is performed on a workpiece such as a ceramic compact according to a predetermined recipe.

[0003] A recipe refers to a debinding process procedure such as the time change of pressure and temperature, the type of debinding gas, the timing of introducing and discharging the debinding gas, etc. Conventionally, such a recipe is determined by setting an initial recipe based on subjective rules of thumb and then performing verification using an actual debinding furnace (actual furnace).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in the above-described method, since the verification of the recipe must be performed one or more times using an actual furnace, the power consumption increases.

[0006] In addition, the verification of the recipe may not be completed in one time and may need to be performed multiple times, or the recipe may need to be determined for different workpieces. In such cases, unless a plurality of actual furnaces are owned, the verification work must be carried out in series, resulting in problems such as time and cost. However, to own a plurality of actual furnaces, a considerable amount of equipment investment is required, which is difficult in reality.

[0007] Furthermore, since there is no theoretical or statistical support for whether the recipe determined in this way is optimal in terms of processing time, power consumption, etc., there is a possibility that significant energy and time losses may occur in the actual degreasing process that follows this recipe.

[0008] This invention was made in view of the aforementioned problems, and its main objective is to enable the setting of a degreasing recipe with low power consumption and in a short time, and to minimize the time wasted and energy loss in the actual degreasing process carried out according to the set recipe. [Means for solving the problem]

[0009] In other words, the degreasing recipe setting method according to the present invention is A data storage step involves linking existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, with degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace, and storing them in memory. An analysis step in which new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, is analyzed based on existing processed material analysis data and degreasing result data stored in the data storage unit, The system is characterized by the following steps: a recipe setting step in which a degreasing recipe for the new processed material is set based on the analysis results in the aforementioned analysis step; and so on. [Effects of the Invention]

[0010] With the above configuration, by using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, a degreasing recipe can be set based on statistical and theoretical data, thus eliminating or minimizing the need for subsequent recipe verification work in an actual furnace. As a result, power consumption and time related to setting the degreasing recipe can be reduced. The differential thermal analyzer and the thermogravimetric analyzer may also be provided in the form of a differential thermal / thermogravimetric analyzer.

[0011] Furthermore, differential thermal analyzers, thermogravimetric analyzers, and thermomechanical analyzers are less expensive and more compact than actual furnaces. By using multiple of these devices, it is possible to set up degreasing recipes in parallel, further reducing processing time.

[0012] In addition, the degreasing recipes established in this manner are backed by theoretical and statistical evidence derived from existing analysis data of processed materials obtained from differential thermal measurement devices, thermogravimetric measurement devices, and / or thermomechanical analyzers, as well as degreasing result data from actual furnaces. Therefore, it is possible to reduce time wasted and energy loss in actual degreasing processes carried out according to these recipes. [Brief explanation of the drawing]

[0013] [Figure 1] This is a schematic diagram showing the degreasing recipe setting device, degreasing furnace, and differential thermal / thermogravimetric measuring device used in the degreasing recipe setting method according to one embodiment of the present invention.

[0014] [Figure 2] This is a functional block diagram of the degreasing recipe setting device in the same embodiment.

[0015] [Figure 3] This is a data diagram illustrating an example of the accumulated data in the same embodiment.

[0016] [Figure 4] This graph shows the temperature shift characteristics in the embodiment and the differential thermal and thermogravimetric changes at each heating rate calculated based on them.

[0017] [Figure 5] This is a flowchart illustrating the method for setting the degreasing recipe in the same embodiment.

[0018] [Figure 6] This is an example of a degreasing recipe set in the same embodiment.

Best Mode for Carrying Out the Invention

[0019] Hereinafter, the degreasing recipe setting device according to this embodiment will be described with reference to the drawings. <Configuration> As shown in FIG. 1, this degreasing recipe setting device 100 is a device for setting a degreasing recipe when degreasing a workpiece in a degreasing furnace 200 using a differential thermal - thermogravimetric measuring device 300. The differential thermal - thermogravimetric measuring device 300 is an analytical device in which a differential thermal measuring device and a thermogravimetric measuring device are integrated, but it may be prepared as individual analytical devices.

[0020] First, prior to a detailed description of this degreasing recipe setting device 100, the degreasing furnace 200 and the differential thermal - thermogravimetric measuring device 300 will be briefly described.

[0021] Although not shown in detail, the degreasing furnace 200 includes a heating furnace (hereinafter also referred to as a practical furnace) for accommodating a workpiece such as a ceramic molded body, and a control device for controlling the temperature, pressure, gas species, etc. inside this heating furnace. The workpiece inside the heating furnace is heated and degreased according to the degreasing recipe incorporated in this control device.

[0022] Although not shown in detail, the differential thermal - thermogravimetric measuring device 300 includes a furnace for accommodating a measurement object, a control device for controlling the temperature, gas species, etc. inside this furnace, a thermogravimetric change amount measuring mechanism for measuring the thermogravimetric change amount of the measurement object, and a differential thermal analysis mechanism for performing differential thermal analysis on the measurement object. It outputs analysis data indicating the analysis results of the measurement object, that is, thermogravimetric change data and differential thermal data. This differential thermal - thermogravimetric 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.

[0023] In this embodiment, as the measurement object of this differential thermal - thermogravimetric measuring device 300, a part of the workpiece, for example, a piece of the workpiece or powder obtained by crushing the workpiece, is used.

[0024] Next, the degreasing recipe setting device 100 will be described.

[0025] This degreasing recipe setting device 100 is a so-called computer equipped with a CPU, memory, communication interface, input / output interface, etc., and the CPU and its peripheral devices cooperate according to a predetermined program stored in the memory to perform functions such as a data storage unit, extraction unit, analysis unit, recipe setting unit, etc., as shown in Figure 2.

[0026] Furthermore, this degreasing recipe setting device 100 is not limited to being physically formed by a single computer. For example, it may be a server / client system or other system in which multiple computers are connected wirelessly or via wired communication, or some or all of its functions may be performed by the control device of the degreasing furnace 200 or the differential thermal / thermogravimetric analyzer 300.

[0027] Next, the various parts of this degreasing recipe setting device 100 will be described in detail with reference to Figure 2, etc.

[0028] (1) Data storage unit The data storage unit receives stored data, which is data relating to processed materials that have been degreased in the degreasing furnace in the past (hereinafter also referred to as existing processed materials), for each processed material and stores it in a predetermined area of ​​the memory.

[0029] As shown in Figure 3, the accumulated data consists of degreasing result data showing the results of degreasing the existing processed material, analysis data obtained by analyzing a portion of the existing processed material before degreasing using a differential thermal / thermogravimetric analyzer (hereinafter also referred to as existing processed material analysis data), and the classification code of the existing processed material.

[0030] The aforementioned analysis data of the existing processed material, when displayed graphically, is as shown in the figure, and includes thermogravimetric change data and differential thermal analysis data for when a portion of the existing processed material is heated at different heating rates.

[0031] The degreasing result data includes, as shown in the figure, information indicating whether the degreasing process was completed successfully or abnormally, as well as the degreasing recipe. Abnormalities include cracking, chipping, and deformation exceeding the allowable limits of the processed material.

[0032] These existing processed material analysis data and degreasing result data are transmitted via wired or wireless connection from the differential thermal / thermogravimetric analyzer and the degreasing furnace, respectively, and are received online. However, they may also be received offline, i.e., using portable storage media such as USB drives or through operator input.

[0033] The aforementioned classification code indicates which of the predetermined classifications the existing processed material belongs to. For example, it specifies which of several predetermined weight ranges the weight falls into, which of the predetermined shapes the shape resembles, or which of the predetermined ranges the volume falls into. In other words, the classification is defined by the weight, shape, and volume of the processed material, and each classification has a certain range. Here, the operator inputs the classification code, but it may also be automated using a three-dimensional shape measuring machine or weighing scale.

[0034] (2) Extraction part This extraction unit extracts accumulated data of existing processed materials from multiple accumulated data stored in the data storage unit, which will be used for the analysis of new processed materials described later.

[0035] The extraction criteria are that the classification codes match, i.e., that the data is accumulated from existing processed materials that are identical or similar in weight, shape, and volume to the new processed material, and that the analysis data of the existing processed material matches or approximates the analysis data of the new processed material. To determine whether the analysis data matches or approximates, statistical methods are used, for example, by checking that the mean square of the differences at each corresponding point in the differential heat curve and thermogravimetric curve shown by these analysis data is less than or equal to a predetermined value.

[0036] (3) Analysis section This analysis unit receives new processed material analysis data, which is data obtained by analyzing a portion of new processed materials for which a degreasing recipe has not yet been established (hereinafter referred to as "new processed materials") using a differential thermal / thermogravimetric analyzer 300. This new processed material analysis data is then analyzed based on the existing processed material analysis data and degreasing result data extracted by the extraction unit. This new processed material analysis data is linked to the classification code of the new processed material. The method of receiving this new processed material analysis data and classification code is the same as that for existing processed material analysis data and its classification code.

[0037] However, this analysis unit includes, as will be explained below, an existing processed material shift characteristic calculation unit, a new processed material thermogravimetric change estimation unit, and a threshold setting unit.

[0038] (3-1) Existing processed material shift characteristic calculation unit This existing processed material shift characteristic calculation unit calculates the temperature shift characteristics (hereinafter also referred to as existing processed material shift characteristics) of the existing processed material based on the existing processed material analysis data, due to the difference in the heating rate of the differential heat and thermogravimetric change of the existing processed material.

[0039] As mentioned above, the analysis data of the existing processed material includes differential heat and thermogravimetric changes at multiple different heating rates for the said existing processed material.

[0040] As shown in Figure 4, this existing processed material shift characteristic calculation unit calculates the existing processed material shift characteristic, which is the amount of shift from the measured values ​​of differential heat and thermogravimetric change at each desired heating rate, based on the difference in differential heat and thermogravimetric change measured at each of these different heating rates.

[0041] (3-2) New thermogravimetric change estimation unit for processed materials Since the existing processed material extracted by the extraction unit is similar to the new processed material in terms of its form (weight, shape, volume) and analytical data, it is presumed that the temperature shift characteristics of these existing processed materials will also be similar to those of the new processed material.

[0042] Based on this premise, the new processed material thermogravimetric change estimation unit calculates the new processed material shift characteristics, which are the temperature shift characteristics of the new processed material, based on the existing processed material shift characteristics.

[0043] As a calculation method, for example, a correction calculation based on the difference between the new processed material analysis data and the existing processed material analysis data (for example, the mean square of the differences between the corresponding points in these two sets of analysis data) is applied to the existing processed material shift characteristics to calculate the new processed material shift characteristics.

[0044] In addition, the shift characteristics of the new processed material may be matched with the shift characteristics of the existing processed material. Alternatively, if there are two different existing processed material analysis data sets separated by the new processed material analysis data, the midpoint of their shift characteristics may be used as the shift characteristics of the new processed material. In other words, the shift characteristics of the processed material may be calculated from the shift characteristics of multiple different existing processed materials.

[0045] The new processed material thermogravimetric change estimation unit then applies the new processed material shift characteristics to the new processed material analysis data to estimate the thermogravimetric change of the new processed material at a predetermined heating rate.

[0046] (3-3) Threshold setting section Since the extracted existing and new processed materials are similar in terms of morphology (classification code) and analytical data, it is assumed that their behavior during heating will also be similar. Therefore, if the thermogravimetric change that occurs when an abnormality occurs in the existing processed material is applied to the new processed material, it is presumed that a similar abnormality will occur.

[0047] Based on this premise, the threshold setting unit calculates the critical thermogravimetric change at which an abnormality occurs in the new processed material based on the degreasing result data of the existing processed material, and sets a threshold for the thermogravimetric change during the degreasing process of the new processed material based on this critical thermogravimetric change.

[0048] Specifically, this threshold setting unit first calculates the thermogravimetric change when an abnormality occurs during the degreasing process of an existing processed material, based on the heating rate in the degreasing recipe in which cracks, chips, or unexpected deformations occurred in the existing processed material, and the temperature shift characteristics of the existing processed material.

[0049] Next, the threshold setting unit calculates the critical thermogravimetric change at which no abnormality occurs in the new processed material, based on the thermogravimetric change when an abnormality occurs in the existing processed material.

[0050] The calculation method involves, for example, applying a correction calculation to the thermogravimetric change of the existing processed material when an abnormality occurs, based on the difference between the analysis data of the new processed material and the analysis data of the existing processed material (for example, the mean square of the differences at corresponding points in these two sets of analysis data), to calculate the critical thermogravimetric change of the new processed material.

[0051] As for the method of calculating the critical thermogravimetric change of the new processed material, for example, it may be matched with the thermogravimetric change of the existing processed material when an abnormality occurs, or, for example, if there are two different analysis data of existing processed materials separated by the analysis data of the new processed material, the critical thermogravimetric change of the new processed material may be calculated from the thermogravimetric changes of multiple different existing processed materials when an abnormality occurs, such as using the median value of the thermogravimetric changes of those existing processed materials when an abnormality occurs as the critical thermogravimetric change of the new processed material.

[0052] Next, the threshold setting unit sets the threshold based on the critical thermogravimetric change.

[0053] The threshold value may be matched to the critical thermogravimetric change, or it may be a value obtained by multiplying or subtracting a safety factor from the critical thermogravimetric change.

[0054] (4) Recipe setting section This recipe setting unit calculates the thermogravimetric change of the new processed material at each heating rate based on the new processed material shift characteristics, determines the heating rate at which the thermogravimetric change falls within the threshold, and sets a degreasing recipe that is below that heating rate.

[0055] <How to set up a recipe> Next, we will explain how to set recipes using this recipe setting device.

[0056] (Step 1: Data storage step) The data storage unit acquires and stores in memory degreasing result data showing the results of degreasing treatments previously performed on existing processed materials, existing processed material analysis data obtained by analyzing a portion of the existing processed material using a differential thermal / thermogravimetric analyzer, and the classification code of the existing processed material.

[0057] (Step 2: Step to obtain analytical data for the new processed material) The operator analyzes a portion of the new material using a differential thermal / thermogravimetric analyzer and determines and inputs a classification code for the new material.

[0058] The analysis unit acquires the analysis data (new processed material analysis data) and classification code.

[0059] (Step 3: Extraction Step) The extraction unit compares the existing processed material analysis data with the new processed material analysis data and extracts one or more existing processed material analysis data and associated degreasing result data to be used for analysis according to the extraction conditions described above.

[0060] (Step 4: Calculation step for existing processed material shift characteristics) On the other hand, the calculation of the existing processed material shift characteristics calculates the existing processed material shift characteristics, which are temperature shift characteristics due to differences in the heating rate of the differential heat and thermogravimetric change of the existing processed material, based on the analysis data of the existing processed material.

[0061] (Step 5: Estimation of the thermogravimetric change of the new processed material) Next, the new processed material thermogravimetric change estimation unit calculates the new processed material shift characteristics, which are the temperature shift characteristics of the new processed material, based on the existing processed material shift characteristics and the new processed material analysis data, and estimates the thermogravimetric change of the new processed material at each heating rate from these new processed material shift characteristics.

[0062] (Step 6: Threshold setting step) Next, the threshold setting step calculates the critical thermogravimetric change at which no abnormality occurs in the new processed material based on the degreasing result data, and sets the threshold based on this critical thermogravimetric change.

[0063] (Step 7: Setting the degreasing recipe) Next, the degreasing recipe setting unit determines a heating rate from among the thermogravimetric changes of the new material at each heating rate such that the thermogravimetric change is within the threshold, and sets a degreasing recipe that is below that heating rate.

[0064] A specific example will be explained with reference to Figure 4.

[0065] Even if the heating rate inside the furnace is kept constant, heat is generated when binders and other substances in the processed material decompose and burn. Therefore, according to differential thermal analysis, the temperature change of the processed material over time will be as shown in Figure 4(c), with a steep thermogravimetric change during decomposition and combustion.

[0066] Therefore, in the degreasing recipe setting step, the heating rate is determined such that the thermogravimetric change during the temperature range where the steepest change occurs in the thermogravimetric change curve at the estimated predetermined heating rate (A°C to B°C at 0.5°C / min in the same figure) is within the threshold.

[0067] On the other hand, in other temperature ranges, even with a higher heating rate, the thermogravimetric change remains within the threshold. Therefore, instead of keeping the heating rate constant during the degreasing process, as shown in Figure 4, a higher heating rate is set in other temperature ranges than in the A°C to B°C range.

[0068] (Step 8: Verification Step) The new material is degreased in an actual furnace according to the aforementioned degreasing recipe, and the results are verified.

[0069] The degreasing result data obtained in this way, along with some analysis data and classification codes of the new processed material, is stored in the data storage unit as accumulated data and used to set degreasing recipes for subsequent new processed materials.

[0070] <Other Embodiments> Other embodiments will be described below.

[0071] Differential heat and thermogravimetric changes also vary depending on the type of degreasing gas. Therefore, it may be advisable to accumulate analytical data for each type of degreasing gas and take the type of degreasing gas into consideration when setting recipes.

[0072] The analysis step, or in addition to that, the degreasing recipe setting step, may be performed using AI-powered machine learning.

[0073] The heating rate measured by temperature sensors placed inside the furnace does not always match the actual heating rate near the workpiece inside the furnace. For example, the rate at which heat enters the workpiece varies depending on the quantity of workpiece placed in the furnace at one time. The difference between the measured heating rate and the actual heating rate is smaller when the quantity of workpiece is small compared to when the quantity is large.

[0074] Therefore, the degreasing result data may be further modified to include the quantity of existing materials to be processed at once in the degreasing furnace (quantity of existing materials in one batch), and in the degreasing recipe setting step, the degreasing recipe may be set based on the quantity of new materials to be processed at once in the degreasing furnace, while referring to the quantity of existing materials. For example, the threshold, heating rate, degreasing recipe, etc. set in the above embodiment may be corrected based on the quantity of new materials to be processed in one batch, which is obtained by operator input. Specifically, the larger the quantity of materials to be processed, the slower the heat from the furnace will enter the new materials, so the heating rate may be corrected to decrease.

[0075] In this way, the evaluation results of small amounts of processed material can be reflected in actual production recipes that degrease larger amounts of material.

[0076] In the above embodiment, the shift characteristics were calculated from the existing processed material analysis data and the new processed material analysis data, and the thermogravimetric change was calculated from these shift characteristics. However, by using machine learning, for example, it is possible to calculate the thermogravimetric change without calculating the shift characteristics through black-box calculations, or to set a degreasing recipe without setting a threshold.

[0077] In the above embodiment, when calculating the thermogravimetric change of a new processed material, the temperature shift characteristics of the existing processed material were calculated from the analysis data of the existing processed material. However, the temperature shift characteristics of each existing processed material may be calculated in advance and stored as one of the accumulated data.

[0078] In the above embodiment, when calculating the critical thermogravimetric change or threshold at which an abnormality may occur in a newly processed material, degreasing result data in the case of an abnormality was referred to. However, normal degreasing result data may also be referred to. In that case, the degreasing result data may include the morphological changes of the degreased processed material from before the degreasing process, and the critical thermogravimetric change or threshold may be calculated based on these morphological changes. The morphological changes can be measured using a three-dimensional shape measuring machine or the like.

[0079] In the above embodiment, a degreasing recipe was set, but it is also acceptable to have a configuration that does not set a degreasing recipe, but only calculates a threshold for thermogravimetric change that does not cause abnormalities in the new processed material. In other words, it may be an analysis method or analysis device for the degreasing processed material. Since the threshold for the new processed material can be determined by such an analysis method or analysis device, the threshold can be used not only for setting a degreasing recipe, but also for other applications such as sintering in industrial furnaces.

[0080] The aforementioned classification may include, for example, the material of the processed object and the type of binder used.

[0081] In the above embodiment, a single differential thermal / thermogravimetric analyzer was used, but multiple analyzers may be used for parallel processing. In the above embodiment, each step was performed by the degreasing recipe setting device, but some or all of these steps may be performed by a human. The following methods are also possible. In other words, characteristic values ​​of the thermogravimetric change of an existing processed material at each heating rate are calculated in advance, and the correlation between these characteristic values ​​and the heating rate is calculated. Based on this correlation, the thermogravimetric change of a new processed material at a predetermined heating rate is estimated. Based on this correlation, a threshold for the thermogravimetric change at which no abnormality occurs in the new processed material is set, or a degreasing recipe for the new processed material is set based on this correlation. The correlation here corresponds to the temperature shift characteristics referred to in the claim. This was achieved by the inventors, who were the first to discover that there is a certain correlation between the heating rate and characteristic values. A characteristic value is, for example, the temperature at the peak (if there are multiple peaks, any of the specified peaks will do) obtained by differentiating part or all of the thermogravimetric change curve with respect to time. Specifically, first, a calibration curve / regression curve is created by plotting the characteristic values ​​at each heating rate, which is then expressed as a predetermined function between the heating rate and the characteristic values. The heating rate at this time can be either a set value or an actual measured value. Then, by representing this calibration curve in a table or equation, the thermogravimetric change curve for a new treatment material when a desired heating rate is applied can be estimated from the calibration curve. Note that the peak width is not corrected here, but the peak width may lie on a different curve, and this may be corrected separately. Furthermore, the characteristic values ​​can be based on, for example, the peak obtained by taking the second or third derivative of the thermogravimetric change curve, or other values ​​that can be calculated from the thermogravimetric change curve, such as the peak area, or other values ​​that show a correlation with the heating rate. Furthermore, any value that shows a correlation with the heating rate does not necessarily have to be a characteristic value of the thermogravimetric change curve. For example, characteristic values ​​calculated from differential thermal change curves may be used, or various parameters or physical properties of the processed material that can be obtained from a differential thermal / thermogravimetric analyzer may be used. Furthermore, in addition to the suggestive thermal / thermogravimetric analyzer, a thermomechanical analyzer (TMA) may also be used. In this case, the description "thermogravimetric change" in the above embodiment should be read as "thermomechanical change." It should be noted that the method is not limited to using either the suggestive thermal / thermogravimetric analyzer or the thermomechanical analyzer (TMA), but both may be used. In other words, one of the three analytical results—thermogravimetric change measured by the thermogravimetric analyzer, differential thermal change measured by the suggestive thermal analyzer, and thermomechanical change measured by the thermomechanical analyzer—or any combination of two or more of these may be used.

[0082] Furthermore, the present invention is not limited to the embodiments described above, and various modifications are possible without departing from the spirit of the invention.

[0083] <Summary> The characteristics of the above-mentioned configuration can be summarized as follows:

[0084] [1] A data storage step involves storing data in memory, linked together with existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material 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 material in a degreasing furnace. An analysis step in which new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, is analyzed based on existing processed material analysis data and degreasing result data stored in the data storage unit, A degreasing recipe setting method characterized by performing a recipe setting step of setting a degreasing recipe for a new processed material based on the analysis results in the aforementioned analysis step.

[0085] [1] According to this, by using differential thermal analyzers, thermogravimetric analyzers, and / or thermomechanical analyzers, degreasing recipes can be set based on statistical and theoretical data, thus eliminating or minimizing the need for subsequent recipe verification in the actual furnace. As a result, power consumption and time related to setting degreasing recipes can be reduced. Furthermore, differential thermal analyzers, thermogravimetric analyzers, and / or thermomechanical analyzers are less expensive and more compact than actual furnaces. By using multiple of these devices, parallel degreasing recipes can be set, further reducing processing time. In addition, the degreasing recipes established in this manner are theoretically and statistically supported by existing analysis data of processed materials obtained from differential thermal measurement devices, thermogravimetric measurement devices, and / or thermomechanical analysis devices, as well as degreasing result data from actual furnaces. Therefore, it is possible to reduce time wasted and energy loss in the actual degreasing process carried out according to the established recipes.

[0086] [2] In the data storage step, the associated existing processed material analysis data and degreasing result data are stored in memory separately for each classification of the corresponding existing processed material. Further extraction steps are performed to extract existing processed material analysis data and degreasing result data for one or more existing processed materials belonging to the same classification as the newly processed material classification. The degreasing recipe setting method described in [1], wherein in the analysis step, new processed material analysis data is analyzed based on the existing processed material analysis data and degreasing result data extracted in the extraction step.

[0087] [2] According to this, by using classification when analyzing new processed materials, it is possible to refer to existing processed materials that are more similar, thereby improving the accuracy of the analysis and allowing for a more appropriate setting of the degreasing recipe.

[0088] [3] The degreasing recipe setting method described in [2], wherein the classification is determined by the weight, shape, volume or a combination of two or more of these of the material to be processed.

[0089] . According to the classification in [3], new processed materials can be analyzed using analytical data and degreasing result data of existing processed materials with similar morphology, thus further improving accuracy.

[0090] [4] The degreasing recipe setting method according to [2] or [3], wherein the extraction step further extracts one or more existing processed material analysis data and associated degreasing result data to be used in the analysis step by comparing the existing processed material analysis data with the new processed material analysis data.

[0091] According to [4], the accuracy can be further improved by using analysis data and degreasing result data of existing processed materials with similar thermal reaction characteristics to analyze the new processed material. Specifically, it is preferable to extract one or more existing processed material analysis data that matches or approximates the analysis data of the new processed material.

[0092] [5] In the aforementioned analysis step, A step of calculating existing processed material shift characteristics, which is the temperature shift characteristics of the existing processed material due to the difference in heating rate of differential heat and thermogravimetric change of the existing processed material, based on the aforementioned analysis data of the existing processed material, Based on the existing processed material shift characteristics and the new processed material analysis data, a new processed material thermogravimetric change estimation step is performed to estimate the thermogravimetric change of the new processed material at a predetermined heating rate. A degreasing recipe setting method according to any one of [1] to [4], wherein the recipe setting step sets a degreasing recipe in the degreasing furnace for the new degreasing material so that the thermogravimetric change estimated in the new material thermogravimetric change estimation step is within a predetermined threshold.

[0093] [5] According to this method, a theoretical approach is used in which the thermogravimetric change at the desired heating rate is estimated based on the temperature shift characteristics calculated from the analysis data. This not only ensures the reliability of the degreasing recipe set based on this method, but also allows for accurate identification and correction of the cause of any problems that occur during verification in an actual furnace.

[0094] [6] The degreasing recipe setting method described in [5], wherein in the step of estimating the thermogravimetric change of the new processed material, a new processed material shift characteristic, which is the temperature shift characteristic of the new processed material, is calculated based on the existing processed material shift characteristic, and the thermogravimetric change of the new processed material is estimated based on this new processed material shift characteristic and the new processed material analysis data.

[0095] [6] indicates that the effect of [5] is more pronounced.

[0096] [7] The degreasing recipe setting method according to [5] or [6], wherein the analysis step further involves calculating a critical thermal weight change at which an abnormality may occur in the new processed material based on the degreasing result data, and setting the threshold based on this critical thermal weight change.

[0097] [7] According to this, a threshold can be set so that no abnormalities occur in new processed materials.

[0098] [8] The aforementioned degreasing result data includes information indicating whether the degreasing process was completed successfully or abnormally. The degreasing recipe setting method described in [7], wherein the threshold setting step sets the threshold based on the degreasing result data in the case of abnormal termination.

[0099] [8] According to this, it is possible to more reliably set a threshold that does not cause abnormalities in new processed materials.

[0100] [9] The degreasing result data includes the quantity of existing material to be processed at one time in the degreasing furnace, and in the degreasing recipe setting step, the degreasing recipe is set based on the quantity of new material to be processed at one time in the degreasing furnace, while referring to the quantity of existing material to be processed at one time, according to any of the degreasing recipe setting methods described in [1] to [8].

[0101] [9] According to this, the results of evaluating small amounts of processed material can be reflected in actual production recipes that degrease larger amounts of processed material.

[0102]

[10] A degreasing recipe setting method according to any one of [5] to [8], wherein characteristic values ​​of the thermogravimetric change at each heating rate are calculated in advance, and the correlation between said characteristic values ​​and the heating rate is calculated, and said correlation is used as the temperature shift characteristic. The configuration in

[10] was made possible by the inventor's first discovery that there is a certain correlation between the heating rate and the characteristic value. This makes it possible to estimate the thermogravimetric change due to differences in heating rates with high accuracy.

[11] The aforementioned characteristic value is the temperature at the peak obtained by differentiating the thermogravimetric curve with respect to time [6] Degreasing recipe setting method. The configuration in

[11] allows for highly accurate estimation of thermogravimetric changes without complex calculations.

[12] A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace. An analysis unit analyzes new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data stored in the data storage unit. A degreasing recipe setting device characterized by comprising a recipe setting unit that sets a degreasing recipe for the new processed material based on the analysis results of the analysis unit.

[0103] The configuration in

[12] can produce the same effects as those described in [1] to

[11] above.

[0104]

[13] A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace. An analysis unit analyzes new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data stored in the data storage unit. A program characterized by having a computer perform the functions of a recipe setting unit, which sets a degreasing recipe for the new processed material based on the analysis results of the aforementioned analysis unit.

[0105] The configuration in

[13] can produce the same effects as those described in [1] to

[11] above.

[0106]

[14] The system stores in memory data of existing processed material analysis, which is data obtained by analyzing a portion of the existing processed material 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 material in a degreasing furnace. A method for analyzing degreased processed materials, characterized by analyzing new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data stored in the data storage unit, and setting a threshold for thermogravimetric change at which no abnormality occurs in the new processed material.

[0107] The configuration in

[14] can produce the same effects as those in [1] to

[11] above, and the calculated threshold can be used to reduce energy consumption and shorten the time required for recipe verification in other processes such as sintering in industrial furnaces.

[0108]

[15] A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace. A degreasing processed material analysis apparatus characterized by comprising: an analysis unit that analyzes new processed material analysis data, which is data obtained by analyzing a portion of a new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data stored in the data storage unit, and sets a threshold for thermogravimetric change in which no abnormality occurs in the new processed material.

[0109] The configuration in

[15] can produce the same effects as in

[14] above.

[0110]

[16] A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace. A program characterized by having a computer perform the function of an analysis unit, which analyzes new processed material analysis data, which is data obtained by analyzing a portion of a new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data stored in the data storage unit, and sets a threshold for thermogravimetric change in which no abnormality occurs in the new processed material.

[0111] The configuration in

[16] can produce the same effects as in

[14] above. [Industrial applicability]

[0112] Based on theoretical and statistical backing derived from existing analysis data of previously processed materials using differential thermal measurement devices, thermogravimetric analyzers, and / or thermomechanical analyzers, as well as degreasing result data from actual furnaces, this degreasing recipe can reduce wasted time and energy losses in actual degreasing processes. [Explanation of Symbols]

[0113] 100... Degreasing recipe setting device 200... Degreasing furnace 300...Differential thermal / thermogravimetric measuring device

Claims

1. A data storage step involves storing data in memory, linked together with existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material 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 material in a degreasing furnace. An analysis step in which new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, is analyzed based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in memory in the data storage step, A degreasing recipe setting method characterized by performing a recipe setting step of setting a degreasing recipe for a new processed material based on the analysis results in the aforementioned analysis step.

2. In the data storage step, the associated existing processed material analysis data and degreasing result data are stored in memory separately for each classification of the corresponding existing processed material. Further extraction steps are performed to extract existing processed material analysis data and degreasing result data for one or more existing processed materials belonging to the same classification as the classification of the new processed material. The degreasing recipe setting method according to claim 1, wherein in the analysis step, new processed material analysis data is analyzed based on the existing processed material analysis data and degreasing result data extracted in the extraction step.

3. The degreasing recipe setting method according to claim 2, wherein the classification is determined by the weight, shape, volume, or a combination of two or more of these of the processed material.

4. The degreasing recipe setting method according to claim 2 or 3, wherein the extraction step further extracts one or more existing processed material analysis data and associated degreasing result data to be used in the analysis step by comparing the existing processed material analysis data with the new processed material analysis data.

5. In the aforementioned analysis step, A step to calculate existing processed material shift characteristics, which are temperature shift characteristics due to differences in the heating rate of differential heat, thermogravimetric change, and / or thermomechanical change of the existing processed material, based on the aforementioned analysis data of the existing processed material, Based on the existing processed material shift characteristics and the new processed material analysis data, a new processed material change estimation step is performed to estimate the thermogravimetric and / or thermomechanical changes of the new processed material at a predetermined heating rate. The degreasing recipe setting method according to claim 1, wherein in the recipe setting step, the degreasing recipe for the new degreasing material in the degreasing furnace is set such that the thermogravimetric change and / or thermomechanical change estimated in the new material change estimation step is within a predetermined threshold.

6. The degreasing recipe setting method according to claim 5, wherein in the step of estimating the change in the new processed material, a new processed material shift characteristic, which is the temperature shift characteristic of the new processed material, is calculated based on the existing processed material shift characteristic, and the thermogravimetric change and / or thermomechanical change of the new processed material is estimated based on this new processed material shift characteristic and the new processed material analysis data.

7. The degreasing recipe setting method according to claim 5 or 6, wherein the analysis step further involves calculating the critical thermal weight change at which an abnormality may occur in the new processed material based on the degreasing result data, and setting the threshold based on this critical thermal weight change.

8. The degreasing result data includes information indicating whether the degreasing process was completed successfully or abnormally. The degreasing recipe setting method according to claim 7, wherein the threshold setting step sets the threshold based on the degreasing result data in the case of abnormal termination.

9. The degreasing recipe setting method according to claim 1, wherein the degreasing result data includes the quantity of existing processed material contained in the degreasing furnace at one time, and in the recipe setting step, the degreasing recipe is set based on the quantity of new processed material contained in the degreasing furnace at one time, while referring to the quantity of existing processed material.

10. The degreasing recipe setting method according to claim 5, wherein, in the step of calculating the existing processed material shift characteristics, characteristic values ​​of the thermogravimetric change and / or thermomechanical change at each heating rate are calculated in advance, and the correlation between said characteristic values ​​and the heating rate is calculated, and said correlation is used as the temperature shift characteristics.

11. The degreasing recipe setting method according to claim 10, wherein the characteristic value is the temperature at the peak obtained by the time derivative of the thermogravimetric change curve and / or the thermomechanical change curve.

12. A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace, An analysis unit analyzes new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in the data storage unit. A degreasing recipe setting device characterized by comprising a recipe setting unit that sets a degreasing recipe for the new processed material based on the analysis results of the analysis unit.

13. A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace, An analysis unit analyzes new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal analyzer, a thermogravimetric analyzer, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in the data storage unit. A program characterized by having a computer perform the functions of a recipe setting unit, which sets a degreasing recipe for the new processed material based on the analysis results of the aforementioned analysis unit.

14. The system stores in memory data of existing processed material analysis, which is data obtained by analyzing a portion of the existing processed material 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 material in a degreasing furnace. A method for analyzing degreased processed materials, characterized by analyzing new processed material analysis data, which is data obtained by analyzing a portion of the new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in the memory, and setting a threshold for thermogravimetric change at which no abnormality occurs in the new processed material.

15. A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace, A degreasing processed material analysis apparatus characterized by comprising: an analysis unit that analyzes new processed material analysis data, which is data obtained by analyzing a portion of a new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in the data storage unit, and sets a threshold for thermogravimetric change in which no abnormality occurs in the new processed material.

16. A data storage unit that stores existing processed material analysis data, which is data obtained by analyzing a portion of the existing processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, and degreasing result data, which shows the result of degreasing the existing processed material in a degreasing furnace, A program characterized by causing a computer to perform the function of an analysis unit, which analyzes new processed material analysis data, which is data obtained by analyzing a portion of a new processed material using a differential thermal measuring device, a thermogravimetric measuring device, and / or a thermomechanical analyzer, based on existing processed material analysis data and degreasing result data that match or approximate the new processed material analysis data stored in the data storage unit, and sets a threshold for thermogravimetric change in which no abnormality occurs in the new processed material.

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