Process parameter optimization method for manufacturing microcrystalline glass

Abstract

The invention discloses a process parameter optimization method for manufacturing glass ceramics, which comprises the following steps: determining an orthogonal experiment scheme, manufacturing the glass ceramics, obtaining performance indexes, fitting the performance indexes, determining models of the performance indexes of the glass ceramics and various influence factors in the manufacturing process, and optimizing the process parameters of the glass ceramics according to the determined models. And by taking the target performance index of the to-be-manufactured glass ceramic as a response target, optimizing each parameter in the process of manufacturing the glass ceramic to obtain the optimal process parameter of each influence factor in the process of manufacturing the glass ceramic. The method has the advantages of being convenient to operate, short in consumed time, wide in application range, high in efficiency, high in flexibility, capable of effectively avoiding single consideration of a certain index, more visual and the like, and is a new method which can be widely adopted, can greatly reduce the experiment amount and can obtain the most accurate optimal experiment condition. The method is of great significance in further improving the performance of the microcrystalline glass and reducing energy consumption.

Description

Technical Field

[0001] The invention belongs to the technical field of utilizing hazardous waste to manufacture microcrystalline glass materials to realize waste recycling, and relates to a method for optimizing process parameters for manufacturing microcrystalline glass. Background Art

[0002] Incineration is an effective method for treating domestic waste. It not only utilizes the chemical heat in the waste, but also achieves waste reduction. Waste incineration will produce a certain amount of fly ash, which often contains heavy metals and soluble salts and has been included in the list of hazardous wastes. SiO2, CaO, etc. contained in fly ash are all components that constitute the structure of microcrystalline glass. The high-temperature treatment system of microcrystalline glass can effectively decompose organic compounds, and it also has a very good effect on the fixation of heavy metals. The small particle state of fly ash also creates favorable conditions for the production of microcrystalline glass. Therefore, microcrystalline glass is regarded as a way out for the harmless treatment of fly ash.

[0003] Glass-ceramics has a variety of glass systems, complex heat treatment systems and is affected by the amount of certain additives. Any different changes will produce different crystals. And with the change of influencing factors, the composition of the crystals in the glass-ceramics framework, the content of the crystals and the size of the unit cells will change to varying degrees, thus affecting the performance of the entire glass-ceramics material.

[0004] Existing experiments on fly ash-based glass-ceramics focus on a few parameters, while keeping all other parameters fixed, and subjecting the raw materials to a series of treatments to obtain glass-ceramics samples. However, the crystal growth that is crucial to glass-ceramics is a linear process, so the existing experimental scheme is an approximation for the selection of optimal conditions. At the same time, current research has done little work on multi-factor analysis, resulting in most of the research being one-sided, which is very unfavorable for a systematic understanding of a specific glass-ceramics system. Moreover, as the number of experimental conditions increases, the amount of experiments will increase exponentially. Not only that, the optimal experimental conditions obtained in this traditional way are often a certain optimal situation in the experimental design, which is a situation that approximates the optimal conditions. At the same time, the changes in the experimental environment of glass-ceramics samples produced by traditional experimental methods are not intuitive enough.

[0005] In the process of using waste as the basic material of microcrystalline glass, the experimental steps are cumbersome, the substances contained in the raw materials are very complex, and the production of microcrystalline glass requires a very long heat treatment time. If there are too many influencing factors that need to be determined, the energy consumption will also increase. Therefore, it is very necessary to obtain the experimental conditions for the best performance microcrystalline glass on the basis of reducing the amount of experiments. Therefore, it is of great significance to obtain a process parameter optimization method for making microcrystalline glass that is easy to operate, short in time, has a wide range of applications, high efficiency, strong flexibility, effectively avoids the single consideration of a certain indicator, and is more intuitive, in order to obtain the best performance microcrystalline glass. Summary of the invention

[0006] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a method for optimizing process parameters for manufacturing microcrystalline glass.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0008] A method for optimizing process parameters for making glass-ceramics, comprising the following steps:

[0009] S1. Design orthogonal test parameters and determine the orthogonal experimental scheme according to the experimental conditions related to the performance indicators of microcrystalline glass in the production process;

[0010] S2. Prepare glass-ceramics according to the orthogonal experimental scheme and obtain the performance index of the glass-ceramics;

[0011] S3. Use Minitab to fit the performance indicators of glass-ceramics obtained under different orthogonal experimental schemes, and determine the model of the performance indicators of glass-ceramics and the influencing factors in the production process;

[0012] S4. Based on the determined performance indicators of microcrystalline glass and the model of various influencing factors in the production process, taking the target performance indicators of the microcrystalline glass to be produced as the response target, optimize the various parameters in the process of producing microcrystalline glass to obtain the optimal process parameters of various influencing factors in the process of producing microcrystalline glass.

[0013] The above-mentioned process parameter optimization method for manufacturing microcrystalline glass is further improved. In step S3, the model of the performance index of the microcrystalline glass and the influencing factors in the manufacturing process is:

[0014] G=a+bX1+cX3+dX4+eX5+fX1×X3+gX1×X5+hX4×X4;

[0015] In the above formula, G is the target performance index of glass-ceramics, X 1-5 are the influencing factors in the production process, and a~h are the constants obtained after fitting.

[0016] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved, in which in step S4, the target performance index includes at least one of micro-Vickers hardness, bending strength, density, crystal content, and unit cell size.

[0017] The above-mentioned process parameter optimization method for manufacturing microcrystalline glass is further improved. In step S3, when the target performance index is micro-Vickers hardness, the corresponding model of micro-Vickers hardness of microcrystalline glass and various influencing factors in the manufacturing process is:

[0018] G1=-18446+540.0X1+63.47X2-12.695X3-216.7X1×X1-0.040556X2×X2+0.006533X3×X3 (1);

[0019] In formula (1), G1 is the microscopic Vickers hardness of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0020] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved, in step S3,

[0021] When the target performance index is the crystal content, the corresponding model of the pyroxene ratio of the microcrystalline glass and the influencing factors in the production process is:

[0022] G2=-943+3.00 X1+2.438 X2+0.02267 X3-0.001520 X2×X2 (2);

[0023] In formula (2), G2 is the proportion of pyroxene in the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0024] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved. In step S3, when the target performance index is the unit cell size, the corresponding model of the pyroxene unit cell size of the microcrystalline glass and the influencing factors in the production process is:

[0025] G3=246119+3665X1-279.7X2-285.2X3-1183X1×X1+0.1766X2×X2+0.1483X3×X3 (3);

[0026] In formula (3), G3 is the size of the pyroxene unit cell of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0027] The above-mentioned process parameter optimization method for manufacturing microcrystalline glass is further improved, and in step S3, specifically:

[0028] S3-1. Calculate the mean value and range of the evaluation index of each factor at each level based on the performance data value of the microcrystalline glass corresponding to the evaluation index;

[0029] S3-2. Calculate the order of factors affecting the degree of each evaluation index based on the range of the evaluation index;

[0030] S3-3. Based on the mean value of the evaluation index and the factors affecting the degree of each evaluation index, the optimal combination and optimal orthogonal test parameter ratio of each factor are selected in order to determine the model of performance index and test factors.

[0031] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved, in step S1, the experimental conditions include the following influencing factors: raw material ratio, nucleation temperature, crystallization temperature and heating rate.

[0032] The above-mentioned process parameter optimization method for manufacturing microcrystalline glass is further improved, and in step S2, the manufacturing process of the microcrystalline glass is as follows:

[0033] S2-1, mixing waste incineration fly ash and waste glass, melting them, and obtaining molten glass liquid;

[0034] S2-2, quenching the molten glass liquid with water to obtain cullet;

[0035] S2-3, drying, dispersing and sieving the broken glass to obtain glass powder;

[0036] S2-4, pressing the glass powder and the binder into a shape;

[0037] S2-5. Perform nucleation treatment and crystallization treatment on the pressed product to obtain microcrystalline glass.

[0038] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved. In step S2-1, the mass ratio of the waste incineration fly ash to the waste glass is 1.2-1.6:1; the melting temperature is 1200-1400°C, and the melting time is 0.5h-2h.

[0039] The above-mentioned process parameter optimization method for producing microcrystalline glass is further improved, in step S2-3, the particle size of the glass powder is 0.075mm~20mm.

[0040] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved. In step S2-4, the amount of the binder added is 1% to 10% of the mass of the glass powder; the binder is at least one of paraffin or PVA; during the pressing process, the pressure is between 10MPa and 50MPa, the degreasing temperature is between 200℃ and 400℃, and the degreasing time is 0.5h to 1h.

[0041] The above-mentioned process parameter optimization method for making microcrystalline glass is further improved. In step S2-5, the temperature of the nucleation treatment is 650℃~850℃; the time of the nucleation treatment is 0.5h~3h; the temperature of the crystallization treatment is 850℃~1050℃; the time of the crystallization treatment is 0.5h~3h.

[0042] Compared with the prior art, the advantages of the present invention are:

[0043] The present invention provides a method for optimizing process parameters for manufacturing microcrystalline glass. First, according to experimental conditions related to performance indicators of microcrystalline glass in the manufacturing process, orthogonal experimental parameters are designed to determine the orthogonal experimental scheme, and microcrystalline glass is manufactured according to the orthogonal experimental scheme, and the performance indicators of the microcrystalline glass are obtained. Minitab is used to fit the performance indicators of the microcrystalline glass obtained under different orthogonal experimental schemes, and a model of the performance indicators of the microcrystalline glass and various influencing factors in the manufacturing process is determined. Finally, according to the determined performance indicators of the microcrystalline glass and the model of various influencing factors in the manufacturing process, the target performance indicators of the microcrystalline glass to be manufactured are used as the response target to obtain the optimal process parameters of various influencing factors in the process of manufacturing microcrystalline glass. In the method of the present invention, according to the determined performance indicators of microcrystalline glass and the model of various influencing factors in the production process, the target performance indicators of the microcrystalline glass to be produced are taken as the response target, so that the optimal process parameters of various influencing factors in the process of producing microcrystalline glass can be quickly obtained. It has the advantages of convenient operation, short time consumption, wide application range, high efficiency, strong flexibility, effective avoidance of single consideration of a certain indicator, and more intuitiveness. It is a new method that can be widely adopted, can greatly reduce the amount of experiments, and can obtain the most accurate optimal experimental conditions. It is of great significance for further improving the performance of microcrystalline glass and reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0045] Figure 1 Schematic diagram of the process parameter optimization process for producing microcrystalline glass in Example 1 of the present invention.

[0046] Figure 2a-d is a fitting effect diagram of the performance indicators of the microcrystalline glass obtained under different orthogonal experimental schemes in Example 1 of the present invention.

[0047] Figure 3 The Pareto diagram of the standardized effect of the pyroxene proportion, micro-Vickers hardness, and pyroxene unit cell size after fitting in Example 1 of the present invention.

[0048] Figure 4 This is a distribution diagram of the micro-Vickers hardness changing with various factors based on the model fitting results in Example 1 of the present invention.

[0049] Figure 5 This is a SEM image of the microcrystalline glass produced under the optimal process parameter conditions in Example 1 of the present invention.

[0050] Figure 6 This is a porosity distribution diagram of the microcrystalline glass produced under the optimal process parameter conditions in Example 1 of the present invention.

[0051] Figure 7 This is a performance test result diagram of the microcrystalline glass produced under the optimal process parameter conditions in Example 1 of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0053] Example 1

[0054] A method for optimizing process parameters for making glass-ceramics, wherein the optimization process is as follows: Figure 1 As shown, the following steps are included:

[0055] S1. According to the experimental conditions related to the performance indicators of microcrystalline glass in the production process, design orthogonal test parameters and determine the orthogonal experimental plan, as follows:

[0056] Select a suitable ratio of fly ash to waste glass as the mixing condition, select a temperature within the nucleation temperature range as the nucleation condition, select a temperature within the crystallization temperature range as the crystallization condition, and establish an orthogonal table based on these three experimental conditions, as shown in Table 1.

[0057] Table 1 Orthogonal experimental design

[0058]

[0059] S2. Prepare glass-ceramics according to the orthogonal experimental scheme and obtain the performance indicators of the glass-ceramics.

[0060] According to the orthogonal experimental scheme in Table 1, glass-ceramics were prepared. Their preparation process is as follows:

[0061] S2-1. Mix unwashed waste incineration fly ash and waste glass in the proportions shown in Table 1, heat to 1400°C, and keep the temperature for 2 hours to melt the materials under high temperature conditions to obtain molten glass.

[0062] S2-2, quenching the molten glass with water to obtain cullet.

[0063] S2-3. Dry, disperse and sieve the broken glass to obtain glass powder with a particle size of 0.075 mm to 20 mm.

[0064] S2-4. The glass powder and the binder are pressed into shape according to the addition amount of the binder being 10% of the mass of the glass powder, wherein the binder is PVA. During the pressing process, the pressure is 40 MPa, the degreasing temperature is 400° C., and the degreasing time is 0.5 h to 1 h.

[0065] S2-5. According to the conditions shown in Table 1, the pressed product is subjected to nucleation treatment and crystallization treatment, wherein the time for nucleation treatment is 2 h, the time for crystallization treatment is 2 h, and the heating rates during the nucleation treatment and crystallization treatment are both 5°C / min, to obtain microcrystalline glass.

[0066] The properties of the microcrystalline glass prepared under different experimental conditions were tested, as shown in Table 2. In the present invention, the crystal content and the unit cell size are also free variables, which can be replaced according to different crystals. In Example 1, the pyroxene proportion and the pyroxene unit cell size are used.

[0067] Table 2 Performance indicators of glass-ceramics prepared under different experimental conditions

[0068]

[0069] S3. Use Minitab to fit the performance indicators of glass-ceramics obtained under different orthogonal experimental schemes, and determine the model of the performance indicators of glass-ceramics and the influencing factors in the production process, as follows:

[0070] S3-1. Use functions to fit the data obtained in Table 1 and Table 2 in Minitab, and calculate the mean and range of the evaluation index for each factor at each level based on the performance data values ​​of the microcrystalline glass corresponding to the evaluation index.

[0071] Figure 2a -d is a fitting effect diagram of the performance indexes of the microcrystalline glass obtained under different orthogonal experimental schemes in Example 1 of the present invention. Figure 2a-d shows that the fitting effect diagram can intuitively show the variation patterns of various performance indicators with experimental conditions, which can better understand how different experimental conditions affect the composition and performance of microcrystalline glass. The crystal content, unit cell size and micro-Vickers hardness all have obvious variation trends, and all have extreme values ​​within the designed experimental conditions.

[0072] S3-2. Based on the extreme values ​​of the evaluation indicators, calculate the order of factors that influence the degree of each evaluation indicator.

[0073] S3-3. Based on the mean value of the evaluation index and the factors affecting the degree of each evaluation index, the optimal combination and optimal orthogonal test parameter ratio of each factor are selected in order to determine the model of performance index and test factors.

[0074] When the performance index is micro-Vickers hardness, the model of the micro-Vickers hardness of glass-ceramics and the influencing factors in the production process is finally determined as follows:

[0075] G1=-18446+540.0X1+63.47X2-12.695X3-216.7X1×X1-0.040556X2×X2+0.006533X3×X3 (1);

[0076] In formula (1), G1 is the microscopic Vickers hardness of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0077] When the target performance index is the crystal content, the model of the final determined pyroxene ratio of microcrystalline glass and the influencing factors in the production process is:

[0078] G2=-943+3.00 X1+2.438 X2+0.02267 X3-0.001520 X2×X2 (2);

[0079] In formula (2), G2 is the proportion of pyroxene in the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0080] When the target performance index is the unit cell size, the model of the final determined pyroxene unit cell size of glass-ceramics and the influencing factors in the production process is:

[0081] G3=246119+3665X1-279.7X2-285.2X3-1183X1×X1+0.1766X2×X2+0.1483X3×X3 (3);

[0082] In formula (3), G3 is the size of the pyroxene unit cell of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

[0083] The above-determined model was subjected to factorial experimental variance analysis, and the results are shown in Table 3-5.

[0084] Table 3 Analysis of variance of pyroxene proportion

[0085] source Degrees of Freedom Adj SS Adj MS F-number P-value return 4 38.349 9.5872 11.19 0.019 Ratio 1 2.160 2.1600 2.52 0.188 Nucleation temperature 1 6.911 6.9114 8.07 0.047 Crystallization temperature 1 7.707 7.7067 9.00 0.040 Nucleation temperature*Nucleation temperature 1 6.608 6.6076 7.71 0.050 error 4 3.427 0.8567 total 8 41.776

[0086] Table 4 Variance analysis of micro Vickers hardness

[0087]

[0088]

[0089] Table 5 Analysis of variance of pyroxene unit cell size

[0090] source Degrees of Freedom Adj SS Adj MS F-number P-value return 6 539712 89952 28.80 0.034 Ratio 1 5473 5473 1.75 0.317 Nucleation temperature 1 90993 90993 29.13 0.033 Crystallization temperature 1 270161 270161 86.49 0.011 Ratio*Ratio 1 4481 4481 1.43 0.354 Nucleation temperature*Nucleation temperature 1 89241 89241 28.57 0.033 Crystallization temperature*Crystallization temperature 1 274788 274788 87.98 0.011 error 2 6247 3123 total 8 545959

[0091] According to the model summary (Table 6), the standard deviation S is relatively small, R-sq and R-sq adjustment are relatively close, and R-sq prediction is relatively large. Based on the above, it is believed that the model has a high degree of fit.

[0092] Table 6 Model summary

[0093] S R-sq R-sq(adjustment) R-sq(prediction) 55.8878 98.86％ 95.42％ 76.83％

[0094] Figure 3 The Pareto diagram of the standardized effect of the pyroxene proportion, micro-Vickers hardness, and pyroxene unit cell size after fitting in Example 1 of the present invention. Figure 3 It can be seen that as the color becomes darker, the microscopic Vickers hardness of the glass-ceramics becomes higher accordingly, and it has stronger performance. Figure 3 The table on the right shows the optimal conditions.

[0095] S4. Based on the performance indicators of the microcrystalline glass determined in S3 and the model of various influencing factors in the production process, taking the target performance indicators of the microcrystalline glass to be produced as the response target, optimize the various parameters in the process of producing microcrystalline glass to obtain the optimal process parameters of various influencing factors in the process of producing microcrystalline glass.

[0096] Figure 4 This is a distribution diagram of the micro-Vickers hardness as a function of various factors in the model fitting results in Example 1 of the present invention. Figure 4It can be seen that when the micro-Vickers hardness of microcrystalline glass is between 500-650hv, the corresponding final process parameters of each influencing factor in the process of making microcrystalline glass are: the ratio is 1.4, the nucleation temperature is 786.667℃, and the crystallization temperature is 970℃.

[0097] Verification test

[0098] According to the optimized process parameters, specifically: the ratio is 1.4, the nucleation temperature is 786.667°C, the crystallization temperature is 970°C, and the other process conditions remain unchanged, microcrystalline glass is produced.

[0099] The newly produced microcrystalline glass was tested and the results were as follows: Figures 5 to 7 shown.

[0100] Figure 5 This is a SEM image of the glass-ceramics produced under the optimal process parameters of Example 1 of the present invention. Figure 5 It can be seen that the pores on its surface are evenly distributed, and the pore size is very small, without any transparent holes, which leads to low water absorption and extremely strong physical properties. Secondly, the crystallization of the microcrystalline glass is also very uniform.

[0101] Figure 6 This is the porosity distribution diagram of the glass-ceramics produced under the optimal process parameters of Example 1 of the present invention. Figure 6 It can be seen that the porosity distribution is very uniform, which greatly improves the performance of the microcrystalline glass.

[0102] Figure 7 This is a performance test result diagram of the microcrystalline glass produced under the optimal process parameter conditions in Example 1 of the present invention. Figure 7 It can be seen that the micro-Vickers hardness of glass-ceramics is 591.6Hv, pyroxene accounts for 65.9%, and the pyroxene unit cell size is

[0103] It can be seen from the above results that in the present invention, according to the determined performance indicators of microcrystalline glass and the model of various influencing factors in the production process, the target performance indicators of the microcrystalline glass to be produced are taken as the response target, and the optimal process parameters of various influencing factors in the process of producing microcrystalline glass can be quickly obtained. It has the advantages of convenient operation, short time consumption, wide application range, high efficiency, strong flexibility, effective avoidance of single consideration of a certain indicator, and more intuitiveness. It is a new method that can be widely adopted, can greatly reduce the amount of experiments, and can obtain the most accurate optimal experimental conditions. It is of great significance for further improving the performance of microcrystalline glass and reducing energy consumption.

[0104] The above embodiments are only preferred implementations of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for optimizing process parameters for making glass-ceramics, characterized in that: The following steps are involved: S1. Design orthogonal test parameters and determine the orthogonal experimental scheme according to the experimental conditions related to the performance indicators of microcrystalline glass in the production process; S2. Prepare glass-ceramics according to the orthogonal experimental scheme and obtain the performance index of the glass-ceramics; S3. Use Minitab to fit the performance indicators of glass-ceramics obtained under different orthogonal experimental schemes, and determine the model of the performance indicators of glass-ceramics and the influencing factors in the production process; S4. Based on the determined performance indicators of microcrystalline glass and the model of various influencing factors in the production process, taking the target performance indicators of the microcrystalline glass to be produced as the response target, optimize the various parameters in the process of producing microcrystalline glass to obtain the optimal process parameters of various influencing factors in the process of producing microcrystalline glass.

2. The process parameter optimization method for producing glass-ceramics according to claim 1, characterized in that: In step S3, the model of the performance index of the microcrystalline glass and the influencing factors in the production process is: G=a+bX1+cX3+dX4+eX5+fX1×X3+gX1×X5+hX4×X4; In the above formula, G is the target performance index of glass-ceramics, X 1-5 are the influencing factors in the production process, and a~h are the constants obtained after fitting.

3. The process parameter optimization method for producing glass-ceramics according to claim 2, characterized in that: In step S4, the target performance index includes at least one of micro-Vickers hardness, bending strength, density, crystal content, and unit cell size.

4. The process parameter optimization method for producing glass-ceramics according to claim 3, characterized in that: In step S3, when the target performance index is micro-Vickers hardness, the corresponding model of micro-Vickers hardness of glass-ceramics and various influencing factors in the production process is: G1=-18446+540.0X1+63.47X2-12.695X3-216.7X1×X1-0.040556X2×X2+0.006533 X3×X3(1); In formula (1), G1 is the microscopic Vickers hardness of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

5. The process parameter optimization method for producing glass-ceramics according to claim 3, characterized in that: In step S3, When the target performance index is the crystal content, the corresponding model of the pyroxene ratio of the microcrystalline glass and the influencing factors in the production process is: G2=-943 + 3.00 X1 + 2.438 X2 + 0.02267 X3 - 0.001520 X2× X2 (2); In formula (2), G2 is the proportion of pyroxene in the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

6. The process parameter optimization method for producing glass-ceramics according to claim 3, characterized in that: In step S3, when the target performance index is the unit cell size, the corresponding model of the pyroxene unit cell size of the micro-ceramic glass and the influencing factors in the production process is: G3=246119+3665X1-279.7X2-285.2X3-1183X1×X1+0.1766X2×X2+0.1483X3× X3(3)； In formula (3), G3 is the size of the pyroxene unit cell of the microcrystalline glass, X1 is the raw material ratio used in the production process, X2 is the nucleation temperature used in the production process, and X3 is the crystallization temperature used in the production process.

7. The process parameter optimization method for producing glass-ceramics according to any one of claims 1 to 6, characterized in that: In step S3, specifically: S3-1. Calculate the mean value and range of the evaluation index of each factor at each level based on the performance data value of the microcrystalline glass corresponding to the evaluation index; S3-2. Calculate the order of factors affecting the degree of each evaluation index based on the range of the evaluation index; S3-3. Based on the mean value of the evaluation index and the factors affecting the degree of each evaluation index, the optimal combination and optimal orthogonal test parameter ratio of each factor are selected in order to determine the model of performance index and test factors.

8. The process parameter optimization method for producing glass-ceramics according to any one of claims 1 to 6, characterized in that: In step S1, the experimental conditions include the following influencing factors: raw material ratio, nucleation temperature, crystallization temperature and heating rate.

9. The process parameter optimization method for producing glass-ceramics according to claim 8, characterized in that: In step S2, the manufacturing process of the microcrystalline glass is as follows: S2-1, mixing waste incineration fly ash and waste glass, melting them, and obtaining molten glass liquid; S2-2, quenching the molten glass liquid with water to obtain cullet; S2-3, drying, dispersing and sieving the broken glass to obtain glass powder; S2-4, pressing the glass powder and the binder into a shape; S2-5. Perform nucleation treatment and crystallization treatment on the pressed product to obtain microcrystalline glass.

10. The process parameter optimization method for producing glass-ceramics according to claim 9, characterized in that: In step S2-1, the mass ratio of the waste incineration fly ash to the waste glass is 1.2-1.6:1; the melting temperature is 1200-1400°C, and the melting time is 0.5h-2h; In step S2-3, the particle size of the glass powder is 0.075 mm to 20 mm; In step S2-4, the amount of the binder added is 1% to 10% of the mass of the glass powder; the binder is at least one of paraffin wax and PVA; during the pressing process, the pressure is between 10MPa and 50MPa, the degreasing temperature is between 200°C and 400°C, and the degreasing time is 0.5h to 1h; In step S2-5, the temperature of the nucleation treatment is 650°C to 850°C; the time of the nucleation treatment is 0.5h to 3h; The temperature of the crystallization treatment is 850° C. to 1050° C.; the time of the crystallization treatment is 0.5 h to 3 h.

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