A design and control method for producing PET foam board system using bottle flakes

Abstract

The present application provides a design and control method for a system for producing PET foam boards using bottle flakes, which belongs to the field of PET foam board production and is used to solve the problem of high PET foam production costs in related technologies. The method realizes the design of a system for producing PET foam boards using bottle flakes. The designed system can adapt to the bottle flake property parameters and expected recycling probability of the bottle flakes to be recycled, and has a good overall production effect.

Description

Technical Field

[0001] The present application relates to the field of PET foam board production, and in particular to a design and control method of a system for producing PET foam boards using bottle flakes. Background Art

[0002] The existing PET foam board production line includes a raw material box, a feeding pipe, a fan and a drying box. The raw material is PET particles prepared from petroleum. The PET particles are added to the raw material box. The fan causes the feeding pipe to extract the PET particles in the raw material box. The PET particles are output after passing through the drying box. The output PET particles will enter the subsequent extruder, melt and finally be formed into PET foam boards.

[0003] PET pellets, produced from petroleum, are relatively expensive. The applicant discovered that recycled bottle flakes on the market could replace PET pellets as a raw material for producing foam boards. Existing production lines that produce foam boards using PET pellets cannot be directly used to produce PET foam boards from recycled bottle flakes. The applicant needed to design a production line suitable for producing PET foam boards from bottle flakes, thereby achieving the goal of producing PET foam boards from bottle flakes. Summary of the Invention

[0004] The present application provides a design and control method for a system for producing PET foam boards using bottle flakes, which can reasonably design a production line to support the realization of the work of producing PET foam boards using bottle flakes.

[0005] In a first aspect, the present application provides a method for designing a system for producing PET foam boards using bottle flakes. The method comprises:

[0006] Obtaining a bottle flake attribute parameter group of the bottle flakes to be recycled and an expected recycling probability of each bottle flake attribute parameter group;

[0007] Substituting each of the bottle flake attribute parameter groups into a pre-built production process simulation model to obtain a production effect parameter group under each production system parameter group;

[0008] Determine the comprehensive effect evaluation value of each bottle flake attribute parameter group by combining the expected recovery probability of the bottle flake attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle flake attribute parameter group;

[0009] An optional system parameter group is determined by analyzing a predetermined number of relatively high comprehensive effect evaluation values ​​and a preset parameter width range for each system parameter dimension of the production system parameter group. The optional system parameter group is centered on the system parameter value of the corresponding system parameter dimension in one of the production system parameter groups corresponding to the predetermined number of relatively high comprehensive effect evaluation values, and the parameter range width of each system parameter dimension is within the corresponding parameter width range.

[0010] The system design evaluation value of each optional system parameter group is analyzed, and a recommended design scheme is determined in the optional system parameter group based on the system design evaluation value. The system design evaluation value is positively correlated with the production effect parameter value and the corresponding expected recovery probability of the optimal production effect parameter group for each bottle flake attribute parameter group in the optional system parameter group, and is negatively correlated with the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group, as well as the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group.

[0011] By adopting the above technical solution, the design of a system for producing PET foam boards using bottle flakes was realized. The designed system can adapt to the bottle flake property parameters and expected recycling probability of the bottle flakes to be recycled, and has a good overall production effect.

[0012] Furthermore, the bottle flake parameter dimensions of the bottle flake attribute parameter group include bottle flake particle size, bottle flake density and bottle flake humidity;

[0013] The system parameter dimensions of the production system parameter group include feeding fan power, feeding pipe inner diameter and drying box power;

[0014] The effect parameter dimensions of the production effect parameter group include bottle flake conveying speed and bottle flake drying effect.

[0015] Furthermore, the method of determining the comprehensive effect evaluation value of each bottle flake attribute parameter group by combining the expected recovery probability of the bottle flake attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle flake attribute parameter group includes:

[0016] Analyze and determine a production effect parameter value for each production effect parameter group of each bottle tablet attribute parameter group, and the production effect parameter value is positively correlated with the effect parameter value of each effect parameter dimension of the production effect parameter group;

[0017] Determine the highest production effect parameter value for each bottle tablet attribute parameter, and calculate the highest production effect parameter value multiplied by the corresponding expected recovery probability as the comprehensive effect evaluation value.

[0018] Furthermore, the analysis of each production effect parameter group of each bottle flake attribute parameter group to determine a production effect parameter value, the production effect parameter value being positively correlated with the effect parameter value of each effect parameter dimension of the production effect parameter group including:

[0019] Normalize the effect parameter values ​​of all effect parameter dimensions in the production effect parameter group;

[0020] Assume that the production effect parameter group contains effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is , the production effect parameter value is z, then , where is a preset constant, .

[0021] Furthermore, the analysis of determining the optional system parameter group by combining a specified number of relatively high comprehensive effect evaluation values ​​and a preset parameter width range for each system parameter dimension of the relative production system parameter group includes:

[0022] Sort the comprehensive effect evaluation values ​​from large to small, and select the production system parameter group corresponding to the first specified number of comprehensive effect evaluation values ​​as the reference system parameter group;

[0023] All optional system parameter groups are determined by combining the parameter width range preset for each system parameter dimension of the reference system parameter group and the pre-acquired production system parameter group.

[0024] Furthermore, analyzing the system design evaluation value of each optional system parameter group includes: for each optional system parameter group,

[0025] Determine the highest production effect parameter value for each bottle flake attribute parameter group within the optional system parameter group, calculate the product of the production effect parameter value and the expected recovery probability of the corresponding bottle flake attribute parameter group as a comprehensive effect evaluation value, and determine the positive phase evaluation value of the optional system parameter group based on the comprehensive effect evaluation value of each bottle flake attribute parameter group;

[0026] Determine the negative phase evaluation value of the optional system parameter group by analyzing the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group;

[0027] The system design evaluation value of the optional system parameter group is determined by combining the positive phase evaluation value and the negative phase evaluation value analysis.

[0028] Furthermore, analyzing the system design evaluation value of each optional system parameter group includes:

[0029] Assume that the bottle piece attribute parameter group has The expected recovery probability of the i-th bottle flake attribute parameter group is The highest production effect parameter value determined by the optional system parameter group for the i-th bottle piece attribute parameter group is , the positive phase evaluation value is ,but ;

[0030] Assume that the optional system parameter group has system parameter dimensions, and the system parameter value of the i-th system parameter dimension is , is the parameter range width, and the system parameter value of the i-th system parameter dimension of the system reference parameter group is , the negative phase evaluation value is ,but , where 、 、 All are preset constants greater than zero;

[0031] Assume that the system design evaluation value is y, then .

[0032] Furthermore, determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes:

[0033] The optional system parameter group with the highest system design evaluation value is selected as the recommended design scheme.

[0034] Furthermore, determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes:

[0035] Constructing a recommended design solution list, wherein the recommended design solution list can accommodate a preset number of recommended design solutions;

[0036] Constructing a set of optional design solutions, wherein the set of optional design solutions includes all optional system parameter groups;

[0037] The scheme recommendation method is executed cyclically until the recommended design scheme list is full or the set of optional design schemes is empty;

[0038] The scheme recommendation method includes: selecting an optional system parameter group with the highest system design evaluation value from a set of optional design schemes, adding it to the first accommodation position in a recommended design scheme list, and removing the selected optional system parameter group and the optional system parameter group whose difference in system design evaluation value with the selected optional system parameter group is less than a preset evaluation difference threshold from the set of optional design schemes.

[0039] In a second aspect, the present application provides a control method for a system for producing PET foam boards using bottle flakes. The method comprises:

[0040] Obtaining the bottle flake attribute parameter group and bottle flake attribute ratio for each type of bottle flake used in production;

[0041] determining all adjustable production system parameter groups in a pre-acquired production system parameter plan;

[0042] Analyze the production effect parameter values ​​of each production system parameter group for each type of bottle flake attribute parameter;

[0043] Determine the expected production effect value of all bottle flakes used in production based on the proportion of bottle flake attributes;

[0044] Adjust the system to the production system parameter group with the highest expected production effect value.

[0045] In summary, this application has at least the following beneficial effects:

[0046] 1. Provides a design and control method for a system for producing PET foam boards from bottle flakes. This method enables the design of a system for producing PET foam boards from bottle flakes to adapt to the conditions of recycling bottle flakes and improve the expected production results.

[0047] 2. The algorithm for determining the specific production effect parameter values ​​is highly compatible, and adding or removing effect parameter dimensions will not affect the calculation;

[0048] 3. The algorithm for determining the specific system design evaluation value is more rational, which is conducive to the accurate evaluation of the optional system parameter group, so as to design a better system for producing PET foam boards using bottle flakes.

[0049] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0051] Figure 1 It shows the principle diagram of the system for producing PET foam board using bottle flakes in the embodiment of the present application;

[0052] Figure 2 A flow chart showing a method for designing a system for producing PET foam boards using bottle flakes according to an embodiment of the present application is shown;

[0053] Figure 3 A flow chart showing a method for controlling a system for producing PET foam boards using bottle flakes in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0055] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the related objects are in an "or" relationship.

[0056] The present application provides a design and control method for a system for producing PET foam boards using bottle flakes, which can adapt to the scenario of producing PET foam boards using recycled bottle flakes and enable the production process to meet production needs.

[0057] Figure 1 The schematic diagram of the system for producing PET foam boards using bottle flakes in an embodiment of the present application is shown.

[0058] Referring to Figure 1, the system for producing PET foam boards using bottle flakes includes a raw material box, a feeding pipe, a fan and a drying box. The raw material box is used to hold recycled bottle flakes. Under the action of the fan, the bottle flakes in the raw material box are transported through the feeding pipe to the drying box for drying, and then transported to subsequent steps such as melting, compacting, and preparing foam boards.

[0059] The subsequent improvements in the embodiments of this application are mainly aimed at improving the process from the raw material box to the post-drying process, and do not include improvements to other steps. Of course, if the design of other steps is required, they can be analogous to the method disclosed in this application. The steps of implementing the PET production system using bottle flakes in this application are specifically described based on the following method.

[0060] In a first aspect, an embodiment of the present application discloses a method for designing a system for producing PET foam boards using bottle flakes.

[0061] Figure 2 A flow chart showing a method for designing a system for producing PET foam boards using bottle flakes in an embodiment of the present application is shown.

[0062] Reference Figure 2 , the design method specifically includes the following steps:

[0063] S210: Obtaining bottle flake attribute parameter groups of the bottle flakes to be recycled and the expected recycling probability of each bottle flake attribute parameter group.

[0064] In this step, the flake attribute parameter group includes flake particle size, flake density, and flake humidity. Of course, the evaluation attribute parameter group can also include more flake attribute dimensions, as long as they can reflect the properties of the recycled flakes. This application only introduces the above dimensions.

[0065] The expected recycling probability can be determined based on data experience and / or expert experience, which reflects the probability of each type of bottle flakes being recycled. For example, what proportion of this type of bottle flakes exists in the market, so what is the recycling probability of this type of bottle flakes when recycled. Of course, the specific method of determining the expected recycling probability of recycled bottle flakes is not the specific content discussed in this application, so it will not be elaborated here.

[0066] S220: Substituting each of the bottle flake attribute parameter groups into a pre-built production process simulation model to obtain a production effect parameter group under each production system parameter group.

[0067] In the method of this step, the system parameter dimensions of the production system parameter group include the feeding fan power, the feeding pipe inner diameter and the drying box power; the effect parameter dimensions of the production effect parameter group include the bottle flake conveying speed and the bottle flake drying effect.

[0068] Under the constraints of production requirements, namely the feeding fan, the inner diameter of the feeding pipe, and the air drying power, a production system model can be constructed, and the parameters of the production system model are adjustable. When different bottle flakes enter the production system model, the movement laws of the bottle flakes in the production system model can be simulated based on models such as mechanics and flow relations, and then the conveying efficiency and drying effect can be determined.

[0069] That is, based on the production process simulation model, the production process simulation model can be constructed based on a known principle model. Under the production process simulation model, the production effect parameter group can be determined based on the bottle piece attribute parameter group and the production system parameter group.

[0070] S230: Determine a comprehensive effect evaluation value for each bottle flake attribute parameter group by combining the expected recycling probability of the bottle flake attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle flake attribute parameter group.

[0071] The method of this step specifically includes: analyzing and determining a production effect parameter value for each production effect parameter group of each bottle flake attribute parameter group, where the production effect parameter value is positively correlated with the effect parameter value of each effect parameter dimension of the production effect parameter group; determining the highest production effect parameter value for each bottle flake attribute parameter, and calculating the highest production effect parameter value multiplied by the corresponding expected recovery probability as the comprehensive effect evaluation value.

[0072] The production effect parameter value may be determined by combining the production effect parameter dimension values ​​of all production effect parameter dimensions of the production effect parameter group, for example, by weighted summation or other methods.

[0073] In a specific example, the method of this step specifically includes: normalizing the effect parameter values ​​of all effect parameter dimensions in the production effect parameter group; assuming that the production effect parameter group contains effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is , the production effect parameter value is z, then , where is a preset constant, .

[0074] S240: Determine an optional system parameter group by analyzing a specified number of relatively high comprehensive effect evaluation values ​​and a preset parameter width range of each system parameter dimension relative to the production system parameter group.

[0075] The optional system parameter group is centered on the system parameter value of the corresponding system parameter dimension in one of the production system parameter groups corresponding to a specified number of higher comprehensive effect evaluation values, and the parameter range width of each system parameter dimension is within the corresponding parameter width range.

[0076] In the method of this step, the analysis of determining the optional system parameter group by combining a specified number of higher comprehensive effect evaluation values ​​and the parameter width range preset for each system parameter dimension of the relative production system parameter group includes: sorting the comprehensive effect evaluation values ​​from large to small, and selecting the production system parameter group corresponding to the first specified number of comprehensive effect evaluation values ​​as the reference system parameter group; and determining all optional system parameter groups by combining the reference system parameter group and the parameter width range preset for each system parameter dimension of the pre-acquired production system parameter group.

[0077] S250: Analyze the system design evaluation value of each optional system parameter group, and determine a recommended design solution in the optional system parameter group based on the system design evaluation value.

[0078] The system design evaluation value is positively correlated with the production effect parameter value and the corresponding expected recovery probability of the optimal production effect parameter group for each bottle flake attribute parameter group in the optional system parameter group, and is negatively correlated with the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group.

[0079] In the method of this step, the analysis of the system design evaluation value of each optional system parameter group includes: for each optional system parameter group, determining the highest production effect parameter value for each bottle flake attribute parameter group within the optional system parameter group, calculating the product of the production effect parameter value and the expected recovery probability of the corresponding bottle flake attribute parameter group as a comprehensive effect evaluation value, and determining the positive evaluation value of the optional system parameter group in combination with the comprehensive effect evaluation value of each bottle flake attribute parameter group; determining the negative evaluation value of the optional system parameter group in combination with the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group; and determining the system design evaluation value of the optional system parameter group in combination with the positive evaluation value and the negative evaluation value.

[0080] In a specific example, analyzing the system design evaluation value of each optional system parameter group includes: assuming that the bottle piece attribute parameter group has The expected recovery probability of the i-th bottle flake attribute parameter group is The highest production effect parameter value determined by the optional system parameter group for the i-th bottle piece attribute parameter group is , the positive phase evaluation value is ,but ; Assume that the optional system parameter group has system parameter dimensions, and the system parameter value of the i-th system parameter dimension is , is the parameter range width, and the system parameter value of the i-th system parameter dimension of the system reference parameter group is , the negative phase evaluation value is ,but , where 、 、 are all preset constants greater than zero; let the system design evaluation value be y, then .

[0081] In an example of the method of this step, determining the recommended design solution from the optional system parameter groups based on the system design evaluation value includes: selecting the optional system parameter group with the highest system design evaluation value as the recommended design solution.

[0082] In another example of the method of this step, determining a recommended design solution from the optional system parameter group based on the system design evaluation value includes: constructing a recommended design solution list, wherein the recommended design solution list can accommodate a preset number of recommended design solutions; constructing an optional design solution set, wherein the optional design solution set includes all optional system parameter groups; and looping through the solution recommendation method until the recommended design solution list is full or the optional design solution set is empty.

[0083] The scheme recommendation method includes: selecting an optional system parameter group with the highest system design evaluation value from a set of optional design schemes, adding it to the first accommodation position in a recommended design scheme list, and removing the selected optional system parameter group and the optional system parameter group whose difference in system design evaluation value with the selected optional system parameter group is less than a preset evaluation difference threshold from the set of optional design schemes.

[0084] Combining the above content, it is possible to determine how to design production system parameters based on the data experience of recycled bottle flakes and the expected recycling effect constraints for production, and ensure that the production system plan is reasonable and feasible, which is conducive to better production results.

[0085] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to the embodiments of this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required for this application.

[0086] In a second aspect, an embodiment of the present application discloses a control method for a system for producing PET foam boards using bottle flakes.

[0087] Figure 3 A flow chart showing a method for controlling a system for producing PET foam boards using bottle flakes in an embodiment of the present application is shown.

[0088] Reference Figure 3 , the method comprising:

[0089] S310: Obtaining a bottle flake attribute parameter group and a bottle flake attribute ratio for each type of bottle flake used for production; determining all adjustable production system parameter groups in the pre-acquired production system parameter scheme;

[0090] S320: Analyze the production effect parameter values ​​of the bottle flake attribute parameters of each production system parameter group for each type of bottle flake;

[0091] S330: Determine the expected production effect value of all bottle flakes used for production based on the bottle flake attribute ratio; and adjust the system to the production system parameter group with the highest expected production effect value.

[0092] Among them, the production system parameter scheme represents a specific range of production system parameter groups. Each production system parameter group is determined as a set of definite production system parameter groups. Each clear production system parameter group can determine the expected production effect of each bottle flake attribute parameter group, and then combine all the production effects and the composition probability of the bottle flakes to determine the preferred production system parameter group for regulation and determination.

[0093] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0094] In summary, this application has at least the following beneficial effects:

[0095] 1. A design and control method for a system for producing PET foam sheets from bottle flakes is provided. This method enables the design of a system for producing PET foam sheets from bottle flakes to adapt to the conditions of recycled bottle flakes and improve the expected production results.

[0096] 2. The algorithm for determining the production effect parameter values ​​is highly compatible, and adding or removing effect parameter dimensions will not affect the calculation;

[0097] 3. The algorithm for determining the specific system design evaluation value is relatively rational, which is conducive to the accurate evaluation of the optional system parameter group, so as to design a better system for producing PET foam boards using bottle flakes.

[0098] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this application is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the aforementioned disclosed concepts. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A design method for producing a PET foam board system using bottle flakes, characterized in that: include: Obtaining a bottle flake attribute parameter group of the bottle flakes to be recycled and an expected recycling probability of each bottle flake attribute parameter group; Substituting each of the bottle flake attribute parameter groups into a pre-built production process simulation model to obtain a production effect parameter group under each production system parameter group; Determine the comprehensive effect evaluation value of each bottle flake attribute parameter group by combining the expected recovery probability of the bottle flake attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle flake attribute parameter group; An optional system parameter group is determined by analyzing a predetermined number of relatively high comprehensive effect evaluation values ​​and a preset parameter width range for each system parameter dimension of the production system parameter group. The optional system parameter group is centered on the system parameter value of the corresponding system parameter dimension in one of the production system parameter groups corresponding to the predetermined number of relatively high comprehensive effect evaluation values, and the parameter range width of each system parameter dimension is within the corresponding parameter width range. The system design evaluation value of each optional system parameter group is analyzed, and a recommended design scheme is determined in the optional system parameter group based on the system design evaluation value. The system design evaluation value is positively correlated with the production effect parameter value and the corresponding expected recovery probability of the optimal production effect parameter group for each bottle flake attribute parameter group in the optional system parameter group, and is negatively correlated with the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group, as well as the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group.

2. The method according to claim 1, characterized in that The bottle flake parameter dimensions of the bottle flake attribute parameter group include bottle flake particle size, bottle flake density and bottle flake humidity; The system parameter dimensions of the production system parameter group include feeding fan power, feeding pipe inner diameter and drying box power; The effect parameter dimensions of the production effect parameter group include bottle flake conveying speed and bottle flake drying effect.

3. The method according to claim 1, characterized in that The method of determining the comprehensive effect evaluation value of each bottle flake attribute parameter group by combining the expected recovery probability of the bottle flake attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle flake attribute parameter group includes: Analyze and determine a production effect parameter value for each production effect parameter group of each bottle tablet attribute parameter group, and the production effect parameter value is positively correlated with the effect parameter value of each effect parameter dimension of the production effect parameter group; Determine the highest production effect parameter value for each bottle tablet attribute parameter, and calculate the highest production effect parameter value multiplied by the corresponding expected recovery probability as the comprehensive effect evaluation value.

4. The method according to claim 3, characterized in that The analysis of each production effect parameter group of each bottle flake attribute parameter group to determine a production effect parameter value, the production effect parameter value being positively correlated to the effect parameter value of each effect parameter dimension of the production effect parameter group includes: Normalize the effect parameter values ​​of all effect parameter dimensions in the production effect parameter group; Assume that the production effect parameter group contains effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is , the production effect parameter value is z, then , where is a preset constant, .

5. The method according to claim 1, wherein The optional system parameter groups determined by combining a specified number of relatively high comprehensive effect evaluation values ​​and the preset parameter width range of each system parameter dimension relative to the production system parameter group include: Sort the comprehensive effect evaluation values ​​from large to small, and select the production system parameter group corresponding to the first specified number of comprehensive effect evaluation values ​​as the reference system parameter group; All optional system parameter groups are determined by combining the parameter width range preset for each system parameter dimension of the reference system parameter group and the pre-acquired production system parameter group.

6. The method according to claim 1, characterized in that The analyzing the system design evaluation value of each optional system parameter group includes: for each optional system parameter group, Determine the highest production effect parameter value for each bottle flake attribute parameter group within the optional system parameter group, calculate the product of the production effect parameter value and the expected recovery probability of the corresponding bottle flake attribute parameter group as a comprehensive effect evaluation value, and determine the positive phase evaluation value of the optional system parameter group based on the comprehensive effect evaluation value of each bottle flake attribute parameter group; Determine the negative phase evaluation value of the optional system parameter group by analyzing the system parameter value and parameter range width of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group; The system design evaluation value of the optional system parameter group is determined by combining the positive phase evaluation value and the negative phase evaluation value analysis.

7. The method according to claim 6, characterized in that The analyzing of the system design evaluation value of each optional system parameter group includes: Assume that the bottle piece attribute parameter group has The expected recovery probability of the i-th bottle flake attribute parameter group is The highest production effect parameter value determined by the optional system parameter group for the i-th bottle piece attribute parameter group is , the positive phase evaluation value is ,but ; Assume that the optional system parameter group has system parameter dimensions, and the system parameter value of the i-th system parameter dimension is , is the parameter range width, and the system parameter value of the i-th system parameter dimension of the system reference parameter group is , the negative phase evaluation value is ,but , where 、 、 All are preset constants greater than zero; Assume that the system design evaluation value is y, then .

8. The method according to claim 1, characterized in that Determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes: The optional system parameter group with the highest system design evaluation value is selected as the recommended design scheme.

9. The method according to claim 1, characterized in that Determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes: Constructing a recommended design solution list, wherein the recommended design solution list can accommodate a preset number of recommended design solutions; Constructing a set of optional design solutions, wherein the set of optional design solutions includes all optional system parameter groups; The scheme recommendation method is executed cyclically until the recommended design scheme list is full or the set of optional design schemes is empty; The scheme recommendation method includes: selecting an optional system parameter group with the highest system design evaluation value from a set of optional design schemes, adding it to the first accommodation position in a recommended design scheme list, and removing the selected optional system parameter group and the optional system parameter group whose difference in system design evaluation value with the selected optional system parameter group is less than a preset evaluation difference threshold from the set of optional design schemes.

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