Intelligent quotation method, system and device for extruder

Abstract

The invention belongs to the technical field of extruders, and provides an intelligent quotation method, system and device for an extruder, and the method comprises the steps: collecting process demand information; establishing a database, and matching the process demand information in the database to obtain a process configuration file; constructing an extruder configuration strategy by adopting a strategy mode; constructing a flow arrangement framework by adopting a rule engine; calling a configuration strategy and a process arrangement framework to obtain material configuration in combination with the process demand information; obtaining the total cost corresponding to the material configuration based on the multi-dimensional cost; and constructing a plurality of quotation strategies, and generating a plurality of quotations in combination with the total cost and the plurality of quotation strategies. According to the invention, the extruder can be flexibly configured and automatically quoted.

Description

Technical Field

[0001] This invention relates to the field of extruder technology, and more specifically to an intelligent pricing method, system, and device for extruders. Background Technology

[0002] The pricing of extruders in the current technology mainly relies on manufacturer pricing and engineers' experience-based judgment, which has the following main problems: First, it is highly dependent on human intervention: the quotation process relies on the experience and judgment of engineers, which is prone to subjective errors and omissions; Second, the configuration is highly complex: the extruder involves dozens of subsystems such as barrel, screw, heating system, and heating and cooling system, and the configuration and combination are complex; Third, process matching is difficult: different plastic processes (such as polyolefins, nylon, fluoroplastics, etc.) correspond to different equipment configuration requirements, and manual matching is inefficient; Fourth, the quotation cycle is long: it usually takes several days or even weeks from customer needs to the final quotation; Fifth, low standardization: There is a lack of unified process databases and configuration standards, and different engineers may provide different solutions; Sixth, cost control is difficult: material costs and labor costs change dynamically, and manual calculations are prone to errors.

[0003] While existing ERP and CAD systems can manage some data, they have the following limitations: First, there is a lack of intelligent applications based on process knowledge; Second, it cannot automatically recommend equipment configurations based on process requirements; Third, the quotation process is not automated enough; Fourth, it lacks a flexible configuration mechanism for strategy patterns.

[0004] Therefore, there is an urgent need for a technical solution that can flexibly configure extruders and automatically provide quotes. Summary of the Invention

[0005] In view of the above, the purpose of this invention is to achieve fully automated processing from customer needs to extruder configuration to accurate quotation, fundamentally solving the problems of low efficiency, poor accuracy and low standardization of traditional quotation methods.

[0006] According to a first aspect of the present invention, an intelligent pricing method for extruders is provided, comprising: Process Requirements Acquisition Steps: Collect process requirements information, which includes one or more of the following: customer information, single-line processing information, and raw material and formulation information. Customer information includes one or more of the following: company name, address, country, telephone number, fax number, and contact person. Single-line processing information includes one or more of the following: product name, single-line capacity requirement, processing temperature, torque, speed, specific energy consumption, melting temperature, melting pressure, and vacuum degree. Raw material and formulation information includes one or more of the following: material number, material name, addition ratio, addition location, melting point / melting range, melt index, bulk density, morphology and size, particle size distribution, shear sensitivity, temperature sensitivity, material viscosity, material abrasiveness, material corrosiveness, and material color. Database matching steps: Establish a database, and obtain process configuration files by matching the process requirement information in the database; the database includes a mapping between raw material types and process types; and a mapping between process types and process configuration files, with one process type corresponding to multiple process configuration files; Strategy mode configuration steps: Construct configuration strategies for extruder components using strategy modes; the configuration strategies include one or more of the following: C-type chuck barrel configuration strategy, flange barrel configuration strategy, screw component configuration strategy, die head component configuration strategy, drive component configuration strategy, heating and cooling system configuration strategy, installation tool configuration strategy, and time configuration strategy; Workflow orchestration engine steps: Build a workflow orchestration framework using a rules engine; Material data dynamic assembly steps: According to the process orchestration framework, the process call configuration strategy is combined with the process requirement information to obtain the materials, quantity, specifications and cost required by the extruder, thereby obtaining the material configuration; Cost calculation steps: Obtain the total cost corresponding to the material configuration based on multi-dimensional costs, which include one or more of the following: material costs, processing costs, labor costs, and management expenses; The steps to implement a pricing strategy are as follows: Build multiple pricing strategies and combine the total cost with the multiple pricing strategies to generate multiple quotes.

[0007] In one possible implementation, the cost calculation step includes: For material prices in different currencies, a currency conversion factor is used to convert the prices into RMB. The currency conversion factor includes the Euro exchange rate and / or the US dollar exchange rate. The material cost is obtained by applying different cost coefficients based on the material source; these cost coefficients include imported material coefficients and locally sourced material coefficients. The cost of imported materials is obtained using the following formula: Tax-inclusive unit price = Tax-exclusive unit price × Exchange rate × (1 + VAT rate) × Import material coefficient; The cost of local materials is obtained using the following formula: Tax-inclusive unit price = Tax-exclusive unit price × (1 + VAT rate) × local material coefficient.

[0008] One possible implementation also includes: The structured quotation generation process involves combining material configurations and multiple quotations to generate a structured quotation, which includes one or more of the following: equipment technical parameters, bill of materials, itemized price details, total price, delivery date, and service terms.

[0009] In one possible implementation, the structured quotation uses a three-level hierarchical structure to organize data, including main component categories, subcategories, and material items. When the quotation is generated, it is summarized and displayed according to the hierarchy, and the quantity and price of materials at the same level are automatically merged.

[0010] In one possible implementation, the database matching step includes: The product name and / or material number and / or material name in the raw material and form formulation information of the single-line processing information are matched with the database to obtain the raw material type; Identify process type based on raw material type; Multiple process configuration files are obtained based on the identified process type; The collected process requirements information is matched among multiple process configuration files to obtain the process configuration file that best matches the process requirements information.

[0011] In one possible implementation, the database matching step further includes: From a process perspective, determine whether the process configuration file that best matches the process requirements is reasonable; If it is unreasonable, optimize the process configuration file and return to the above steps; If appropriate, the process configuration file will be structured into a configuration list.

[0012] In one possible implementation, the database matching step further includes: Determine whether the configuration list meets customer requirements; If the customer's needs are not met, the process configuration file will be optimized, and the process configuration file that best matches the process requirements will be returned from the process perspective to determine whether it is reasonable. If the customer's requirements are met, a configuration list will be output.

[0013] In one possible implementation, the dynamic assembly step of the material data includes: Obtain process configuration parameters, which are obtained through a process configuration file; Call flow orchestration framework; Material configuration is performed by calling the configuration strategy and combining it with process configuration parameters according to the process orchestration framework.

[0014] In one possible implementation, the step of configuring materials according to the process orchestration framework by invoking the configuration strategy in conjunction with process configuration parameters includes one or more of the following steps: Determine the chuck type based on the process configuration parameters; The C-type chuck barrel configuration strategy or the flange chuck barrel configuration strategy shall be invoked according to the chuck type. Perform calculations for the barrel components; Perform calculations for the screw components; Perform calculations for the nose section components; Perform calculations for the drive components; Perform calculations for the heating and cooling system; Perform installation tool calculations; Perform work hour calculations.

[0015] In one possible implementation, the step of performing the barrel component calculation includes one or more of the following steps: Calculate the number of heating rods based on the number of barrel sections; Adjust the heating rod specifications according to the chuck type; The number of barrel supports is determined based on the barrel length; The hopper specifications are automatically selected based on the number of barrel sections. Configure the calculation plugs and the number of plugs according to the number of barrel sections; Calculate the number of thermocouples based on the number of barrel sections and the number of machine heads; Calculate the number of TCU cooling units based on the number of barrel sections and heat dissipation requirements; Calculate the number of screw components based on the barrel length and process requirements; Automatically selects motor power based on screw diameter and process requirements; The number of barrel sections and the number of connecting parts required for adjacent sections are determined based on the number of barrel sections and the quantity of connecting parts required for the machine.

[0016] In one possible implementation, the steps of calculating the barrel component, the screw component, the head component, the drive component, the heating and cooling system, the installation tool, and the working time are implemented through modular encapsulation algorithm rules.

[0017] In one possible implementation, the steps of the modular encapsulation algorithm rule implementation calculation include: A rule engine for building algorithm rules; Call the rules engine to perform one or more of the following: material quantity calculation, material specification matching, standard working hours acquisition, and cost calculation.

[0018] In one possible implementation, the step of performing the barrel component calculation includes: A process configuration parameter set is constructed based on process configuration parameters. The process configuration parameter set includes type identifiers and configuration lists of modular components. The process calls the configuration strategy from the configuration parameter set to determine the barrel body and material; The modular sub-components of the barrel are calculated using a rules engine.

[0019] In one possible implementation, the step of performing modular sub-component calculations of the barrel via a rules engine includes one or more of the following steps: The barrel connector calculation module is invoked to determine the barrel connectors. The algorithm rules include: the number of connectors depends on the total number of barrel sections and the connection type; Call the plugin and plug calculation module to determine the plugins and plugs; The injection valve calculation module is called to determine the injection valve. The algorithm rules include: the number of injection valves strictly corresponds to the number of plugs that need to be injected. The plug-in gasket calculation module is called to determine the gasket. The algorithm rules include: the gasket is divided into upper plug-in gasket and side plug-in gasket; The heating rod and thermocouple calculation module is invoked to determine the heating rod and / or thermocouple. The algorithm rules include: the number of heating rods is determined by the total length of the barrel. The exhaust component calculation module is called to determine the exhaust components. The algorithm rules include: analyzing the barrel drawing number through the feature code parser, summarizing and counting the total number of vacuum ports and natural exhaust ports, thereby determining the number of corresponding components.

[0020] In one possible implementation, the step of performing the drive component calculation includes: The technical specifications of the main components of the drive unit are derived from the received process parameter configuration according to the preset engineering rules. Perform a dynamic linkage query to obtain slave components that are compatible with the master component; The list-based optimization strategy is executed to obtain the optional configurations of the drive components; The execution condition trigger logic is combined with process configuration parameters to obtain the driving component corresponding to the functional requirements; Summarize the materials of each drive component.

[0021] In one possible implementation, the pricing strategy implementation steps include: The profit margin is set for different pricing strategies; the pricing strategy includes one or more of customized pricing, competitive pricing, preferential pricing and standard pricing, and the profit margin includes one or more of customized profit margin, competitive profit margin, preferential profit margin and standard profit margin, wherein the competitive profit margin is not greater than the preferential profit margin, and the preferential profit margin is not greater than the standard profit margin. Choose a pricing strategy; Based on the total cost, a final quote is generated by combining the pricing strategy and its profit margin. The final quote is calculated using the following formula: Final quote = Total cost / (1 - Profit margin).

[0022] According to a second aspect of the present invention, an intelligent pricing system for extruders is provided, comprising: The process requirements analysis module is configured to collect process requirements information, establish a database, and obtain process configuration files by matching the process requirements information in the database. The intelligent configuration generation module is configured to use a strategy pattern to build configuration strategies for extruder components and a rule engine to build a process orchestration framework for the component configuration order. The dynamic material calculation module is configured to call the configuration strategy and process orchestration framework of the intelligent configuration generation module and combine it with the process requirement information collected by the process requirement analysis module to obtain the materials, quantity, specifications and cost required by the extruder, thereby obtaining the material configuration. The automatic quotation calculation module is configured to obtain the total cost corresponding to the material configuration based on multi-dimensional costs, construct multiple quotation strategies, and generate multiple quotations by combining the total cost and multiple quotation strategies.

[0023] One possible implementation also includes: The quotation document generation module is configured to combine the material configuration of the dynamic material calculation module and the multiple quotations from the automatic quotation calculation module to generate a structured quotation. The structured quotation includes one or more of the following: equipment technical parameters, bill of materials, itemized price details, total price, delivery date, and service terms. The quotation uses a three-level hierarchical structure to organize the data, including main component categories, subcategories, and specific material items. The quotation document generation module is also configured to generate quotation files in Excel and PDF formats and upload the generated quotation files to the object storage service.

[0024] According to a third aspect of the present invention, an intelligent pricing system for extruders is provided, comprising a presentation layer, a business logic layer, a component layer, a strategy layer, a data layer, and an external interface layer: The presentation layer serves as the human-computer interaction entry point and data exit point, used for process requirement information input, configuration preview, and quotation display. The business logic layer is configured to modularly encapsulate business logic, dynamically select configuration strategies from the strategy layer, generate material configurations by combining process requirement information entered from the appearance layer, and build a quotation calculation engine to generate quotations based on the material configurations. The strategy layer is configured to set differentiated configuration strategies for different process types and equipment types; The component layer is configured to map the various parts of the extruder to software components based on the process orchestration engine of the business logic layer; The data layer is configured to build multiple databases for distributed data storage and real-time data synchronization. The external interface layer is configured as an external interface for integration and data exchange with third-party systems.

[0025] In one possible implementation, the presentation layer includes one or more of the following dynamic functional controls: Web front-end interface, used for visual configuration; Application programming interfaces (APIs) provide standardized interfaces for terminals. Access control is used to control the access permissions of different roles to configuration functions.

[0026] In one possible implementation, the business logic layer includes: Process configuration service: Calls the database in the data layer and matches the process requirement information entered in the appearance layer to obtain the process configuration file. The process configuration file supports version management and automatically increments the version number with each modification. Strategy Factory: Dynamically selects the configuration strategy for the strategy layer. Through the material configuration strategy factory and the price configuration strategy factory, the corresponding configuration strategy implementation class is dynamically selected according to the material type or price type. The strategy implementation class includes one or more of the following: C-type chuck barrel strategy, flange barrel strategy, and process segment strategy. LiteFlow orchestration engine: It uses a rule engine to build a process orchestration framework and defines the component call order through configuration files. The components include one or more of the following: barrel component, cooling system component, drive component, gearbox barrel connection section component, head component, heat shield component, installation tool component, frame component, screw component, threaded element component, time component, control system component, and side feeder component. The material configuration is obtained by executing them in sequence in combination with process configuration files and strategy configuration. Quotation Calculation Engine: Generates quotations based on material configuration and pricing strategies, supporting multi-currency exchange rate conversion and the application of differentiated cost coefficients.

[0027] In one possible implementation, the strategy layer includes a material configuration strategy interface and multiple configuration strategy building modules. The configuration strategy of the configuration strategy building modules is called through the material configuration strategy interface. The configuration strategy includes one or more of the following: C-type chuck barrel configuration strategy, flange barrel configuration strategy, screw component configuration strategy, head component configuration strategy, drive component configuration strategy, heating and cooling system configuration strategy, installation tool configuration strategy, and working time configuration strategy.

[0028] In one possible implementation, the database includes a process database, a materials database, a price database, and a configuration database. The process database stores a mapping between raw material types and process types, and also stores machine barrel section configuration parameters. The machine barrel section configuration parameters include one or more of the following: machine barrel section number, machine barrel section type, maximum temperature, cooling method, heating method, exhaust port type, and machine barrel material. The machine barrel section type is mapped to the corresponding machine barrel drawing number. The configuration database stores a mapping between process types and process configuration files. The process configuration files include one or more of the following: process type, machine model, chuck type, screw diameter, and version number. The material database stores a mapping between process configuration files and materials; The price database stores a mapping between materials and prices, where the prices include material prices in different currencies.

[0029] According to a fourth aspect of the present invention, a computing device is provided, including a memory and a processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-described intelligent pricing method for extruders.

[0030] According to a fifth aspect of the present invention, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the above-described intelligent pricing method for extruders.

[0031] This invention collects process requirement information from customer terminals, automatically obtains process configuration files based on this information and database matching; it employs a strategy pattern to achieve flexible extruder configuration; it constructs a process orchestration framework for the extruder configuration sequence based on a rule engine; and it automatically generates material configurations by calling configuration strategies and combining them with the process configuration files, including the materials (here, materials are a broad concept, including components and the materials used in those components) of the extruder (quantity, specifications, and cost); and it intelligently quotes for the material configurations by combining pricing strategies and multi-dimensional costs. This achieves fully automated processing from customer needs to material configuration to accurate pricing, fundamentally solving the problems of low efficiency, poor accuracy, and low standardization in traditional pricing methods.

[0032] The present invention also has the following technical advantages: it supports multi-currency exchange rate conversion and the application of differentiated cost coefficients; it supports multi-currency international quotations; it automatically generates quotation documents in Excel and PDF formats and uploads them to the object storage service; and it performs version management of process configurations, making it easy to trace historical configurations. Attached Figure Description

[0033] Figure 1 This is a flowchart illustrating an embodiment of the intelligent pricing method for extruders described in this invention; Figure 2 This is a flowchart illustrating an embodiment of the database matching step described in this invention; Figure 3 This is a flowchart illustrating one embodiment of the dynamic assembly steps for material data described in this invention. Figure 4 This is a flowchart illustrating an embodiment of the cost calculation steps and pricing strategy implementation steps described in this invention; Figure 5 This is a schematic block diagram of an embodiment of the intelligent pricing system for extruders described in this invention; Figure 6 This is a schematic block diagram of another embodiment of the intelligent pricing system for extruders described in this invention; Figure 7 This is a schematic diagram illustrating the structure of an embodiment of the apparent layer described in this invention; Figure 8 This is a schematic diagram of the structure of an embodiment of the review process interface described in this invention; Figure 9 This is a schematic block diagram of one embodiment of the computing device described in this invention. Detailed Implementation

[0034] Extruder configuration is highly complex, and existing technology cannot automatically generate extruder configurations based on customer needs, nor can it automatically quote prices for extruder configurations.

[0035] This invention achieves fully automated processing from customer needs to material configuration and accurate pricing by constructing an intelligent data flow and an automated configuration algorithm.

[0036] Figure 1 This is a flowchart illustrating an embodiment of the intelligent pricing method for extruders described in this invention, as follows: Figure 1 As shown, the intelligent pricing method for extruders includes: Step S1, Process Requirements Collection Step: Collect process requirements information and establish a standardized process requirements form. The process requirements information includes one or more of the following: customer information, single-line processing information, and raw material and formulation information. The customer information includes one or more of the following: company name, address, country, telephone number, fax number, and contact person. The single-line processing information includes one or more of the following: product name, single-line capacity requirement, processing temperature, torque, speed, specific energy consumption, melting temperature, melting pressure, and vacuum degree. The raw material and formulation information includes one or more of the following: material number, material name, addition ratio, addition location (main feed, side feed), melting point / melting range, melt index, bulk density, morphology and size, particle size distribution, shear sensitivity, temperature sensitivity, material viscosity, material abrasiveness, material corrosiveness, and material color.

[0037] Step S2, Database Matching Step: Establish a multi-dimensional database, and obtain the process configuration file by matching the process requirement information in the database. The database includes mappings between raw material types and process types; and mappings between process types and process configuration files. One process type corresponds to multiple process configuration files. For example, nine raw material types—polyolefins, nylon, fluoroplastics, specialty engineering plastics, elastomers, polysulfones, polyesters, and PC & ABS (an alloy of polycarbonate and acrylonitrile-butadiene-styrene copolymer (ABS))—correspond to nine process types, and these nine process types have hundreds of process configurations. The database can be used to match the product name and / or the material name in the raw material and form formulation information of the single-line processing information to obtain the raw material type. A process configuration file is a document that guides the setting of process parameters, operation of equipment, and quality control during product manufacturing. A process configuration file represents the process parameters, product specifications, product requirements, special process requirements, and equipment configurations in a process configuration corresponding to a process type. Preferably, the process configuration file is formed by storing process area configuration information in JSON format. The product specifications include the specifications of the manufactured products; product specifications can be obtained by matching single-line processing information in the database, for example, by matching the product name of single-line processing information in the database. The product requirements include output, quality standards, and special performance requirements; product requirements can be obtained by matching single-line processing information in the database, for example, by matching the single-line capacity requirements of single-line processing information in the database to obtain output. The process parameters include screw parameters and performance parameters. The screw parameters include diameter, length-to-diameter ratio, screw groove depth, screw edge thickness, screw speed, etc.; the performance parameters include motor power, heating power, pressure range, processing temperature range, etc. The process parameters can be obtained by matching single-line processing information in a database. For example, the screw parameters and performance parameters can be obtained by matching the torque, speed, specific energy consumption, processing temperature, melting temperature and melting pressure, and vacuum degree of single-line processing information in a database. Specialized process requirements include high-precision temperature control (temperature-sensitive materials, low-temperature extrusion processes, segmented temperature control, etc.), high torque and wear resistance (high-viscosity materials, corrosive media, etc.), process function requirements (reactive extrusion, co-extrusion molding), safety and stability requirements (melt pressure control, overload protection, etc.), and industry-specific customization requirements (medical-grade products, precision extrusion, etc.). Specialized process requirements can be obtained by matching raw material and formulation information in a database. For example, high-precision temperature control requirements can be obtained by matching the temperature sensitivity of raw materials and formulation information in the database, and high torque and wear resistance requirements can be obtained by matching the wear resistance, viscosity, and corrosivity of the materials. The equipment configuration includes a cooling configuration, a drive configuration, a head configuration, a screw configuration, and a barrel configuration.

[0038] Step S3, Strategy Mode Configuration Step: Construct the configuration strategy for the extruder components using the strategy mode: The configuration strategy includes one or more of the following: C-type chuck barrel configuration strategy, flange barrel configuration strategy, screw component configuration strategy, die head component configuration strategy, drive component configuration strategy, heating and cooling system configuration strategy, installation tool configuration strategy, and time configuration strategy; Step S4, Process Orchestration Engine Steps: Implement intelligent process configuration using a process orchestration framework: Construct a process orchestration framework (e.g., LiteFlow) using a rule engine. The process orchestration framework includes one or more of the following: process segment-barrel configuration, process segment-screw configuration, process segment-head assembly, drive component configuration, heating and cooling system configuration, installation tool configuration, and time configuration. The process segment includes accessories (hopper, gearbox connector, barrel connector, thermocouple, heating rod, etc.), inserts, screw, and head assembly. Step S5, Dynamic Material Data Assembly Step: Dynamically calculate the required materials based on process requirements: Combine the configuration strategy from Step S3 and the process orchestration framework from Step S4 with the process requirements from Step S1 to obtain the quantity, specifications, and cost of the required materials, thereby obtaining the material configuration; for example: select the barrel material (B65, B19, NST, etc.) based on processing temperature and corrosiveness; select the screw material based on wear requirements; calculate the number and power of heating rods based on the barrel length; configure the TCU cooling unit based on heat dissipation requirements; Step S6, Cost Calculation Step: Calculate multi-dimensional costs, including material costs, processing costs, labor costs, and management expenses; Step S7, Implementation steps of pricing strategy: Construct multiple pricing strategies, and generate multiple quotes by combining multi-dimensional costs and multiple pricing strategies; Step S8, Structured Quotation Generation Step: Combine the process configuration file from Step S2, the material configuration from Step S5, and the multiple quotations from Step S6 to generate a structured quotation. The structured quotation includes one or more of the following: equipment technical parameters, bill of materials, itemized price details, total price, delivery period, and service terms.

[0039] This invention improves quotation efficiency: the quotation cycle is shortened from the traditional 3-7 days to 2-4 hours, increasing efficiency by more than 80%; the configuration generation time is shortened from several hours to several minutes, achieving near real-time response; and repetitive manual operations are reduced by more than 90%.

[0040] This invention improves accuracy by reducing human error by over 90% through a standardized process database and intelligent algorithms; achieving a material quantity calculation accuracy of over 99%; and establishing a comprehensive quality control mechanism to ensure accurate pricing.

[0041] This invention enhances standardization by establishing unified process configuration standards and procedures; ensuring consistency in configuration results across different engineers; and supporting the accumulation and transfer of corporate knowledge assets.

[0042] This invention improves system scalability: it supports rapid access and configuration of new process types; it enables flexible expansion and customization of configuration strategies; and it supports the integration and synchronization of multiple data sources.

[0043] In one feasible embodiment, the database includes a process database, a materials database, a price database, and a configuration database: The process database stores a mapping between raw material types and process types; The configuration database stores a mapping between process types and process configuration files; The material database stores a mapping between process configuration files and materials; The price database stores a mapping between materials and prices.

[0044] In one feasible embodiment, such as Figure 2 As shown, step S1 includes: Step S11, Input process requirements information: Step S12, requirement parameter verification, the requirement parameter verification refers to the verification of one or more mandatory fields set in the process requirement information; Step S13: Determine if the parameters are complete; If the parameters are incomplete, return to step S11; If the parameters are complete, proceed to step S2.

[0045] In one feasible embodiment, such as Figure 2 As shown, step S2 includes: Step S21, Process type identification: The process type is identified by matching the process requirement information in the process database. The process type is also identified by the input raw material type. For example, if the product name in the single-line processing information and / or the material number and / or the material name in the raw material and form formulation information are polyolefins, then the process type is a polyolefin process. Step S22, process configuration matching: obtain multiple corresponding process configuration files based on the identified process type; Step S23, Process configuration file generation: Match the process requirement information collected in step S1 with multiple process configuration files to obtain the process configuration file that best matches the process requirements.

[0046] In a preferred embodiment, such as Figure 2 As shown, step S2 further includes: step S24, process configuration check step, including: The process configuration file is sent to at least one terminal device to determine its rationality. When all terminal devices determine the process configuration is rational, step S6 is executed. The terminal devices include a process agent and / or a sales agent. The process agent determines the rationality of the process configuration from a process perspective, while the sales agent determines the rationality based on customer needs (e.g., budget, which can be obtained from the process configuration information). (Adding human roles increases the risk that the rules governing intellectual activity are not patentable; therefore, an agent is used instead.) In a preferred embodiment, step S24 includes: Step S241: Determine whether the process configuration is reasonable from a process perspective. Determine whether the process configuration is reasonable based on process requirement information and process configuration file. If the process configuration is unreasonable, proceed to step S242: optimize the process configuration, for example: adjust the process configuration according to the capacity, and return to step S241; If the process configuration is appropriate, proceed to step S243: generate a configuration list.

[0047] In a preferred embodiment, such as Figure 2 As shown, step S24 further includes customer requirement review, which includes: Step S244: Determine whether the customer's requirements have been approved; If the customer's requirements are not approved, return to step S242 to modify the process configuration. For example, adjust the brand of the motor inverter according to the customer's budget, remove non-essential equipment, and add spare parts. If the customer's requirements are approved, proceed to step S245 to output the configuration list, which can be a configuration table (e.g., an Excel-formatted configuration table) and technical documentation.

[0048] In one feasible embodiment, step S2 uses JSON format to store the process area configuration information to form a process configuration file, as shown below: { "name": "Polyolefin Processes", "sheetIndex": 1, "sections": [ { "name": "PP material + talc + GF", "bigClass": "Polyolefins", "midClass": "I. PP Modification Process Combination", "fieldIndex": { "machineSketch": 0, "segmentType": 1, "maxTemp": 3, "barrelMaterial": 9, "screwMaterial": 10 } } ] }

[0049] In one feasible embodiment, such as Figure 3 As shown, step S5 includes: Step S501: Obtain process configuration parameters. The process parameter configuration can be obtained by using the corresponding process configuration file obtained in step S23 as the process configuration parameters, or by using the process configuration file obtained after adjusting the process configuration in step S23 by the process agent and / or the sales agent as the process configuration parameters. Step S502: Call the process orchestration framework of step S4, and start material configuration according to the process configuration parameters according to the process orchestration framework; Step S503: Determine the chuck type according to the process configuration parameters. The chuck type includes C-type chuck and flange chuck. Step S504: Based on the chuck type determined in step S503, the configuration strategy of step S3 is invoked. The configuration strategy includes the flange barrel configuration strategy and the C-type chuck barrel configuration strategy. Step S505: Calculate the barrel component based on the configuration strategy invoked in step S504 and the process orchestration framework of step S4 to obtain the material quantity, material specifications, and material cost of the barrel component. Step S506: Call the configuration strategy of step S3 and combine it with the process orchestration framework of step S4 to calculate the screw component, and obtain the material quantity, material specifications and material cost of the screw component. Step S507: The configuration strategy of step S3 is called in combination with the process orchestration framework of step S4 to calculate the nose section component and obtain the material quantity, material specifications and material cost of the nose section component. Step S508: Call the configuration strategy of step S3 and combine it with the process orchestration framework of step S4 to calculate the driving component and obtain the material quantity, material specifications and material cost of the driving component. Step S509: Call the configuration strategy of step S3 and combine it with the process orchestration framework of step S4 to calculate the heating and cooling system, and obtain the material quantity, material specifications and material cost of the heating and cooling system. Step S510: In step S3, the configuration strategy is called in combination with the process orchestration framework of step S4 to calculate the installation tool and obtain the material quantity, material specifications and material cost of the installation tool. Step S511: Call the configuration strategy of step S3 and combine it with the process orchestration framework of step S4 to calculate the working hours and obtain the standard working hour cost. Step S512: Save the data. Step S513: Generate a bill of materials.

[0050] In one feasible embodiment, step S505 includes one or more of the following steps: Step S5050: Calculate the number of heating rods based on the number of barrel sections; Step S5051: Adjust the heating rod specifications according to the chuck type; Step S5052: Determine the number of barrel supports based on the barrel length; Step S5053: Automatically select the hopper specification based on the number of barrel sections; Step S5054: Configure the calculation plug and plug quantity according to the number of barrel sections; Step S5055: Calculate the number of thermocouples based on the number of barrel sections and the number of machine heads; Step S5056: Calculate the number of TCU cooling units based on the number of barrel sections and heat dissipation requirements; Step S5057: Calculate the number of screw components based on the barrel length and process requirements; Step S5058: Automatically select the motor power based on the screw diameter and process requirements; Step S5059: Based on the number of barrel sections and the number of connecting parts required for adjacent sections, the number of barrel connecting parts is determined.

[0051] In one feasible embodiment, step S5050 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Number of heating rods = Number of barrel sections String modelType = extProcessConfig.getModelType(); String length = modelType.substring(modelType.indexOf("×") + 1,modelType.indexOf("D")); int heaterCount = Integer.parseInt(length).

[0052] In one feasible embodiment, step S5051 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Adjust the heating rod specifications according to the chuck type if ("C".equals(chuckType)) { / / C-type chuck uses a single heating rod heaterCount = heaterCount } else { / / Flange chuck uses dual heating rods heaterCount = heaterCount * 2; }

[0053] In one feasible embodiment, step S5052 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / The number of barrel supports is determined by the barrel length. long barrelLen = extProcessConfig.getBarrelLen(); long supportCount? if (barrelLen <= 32) { supportCount = 1; / / Short barrel uses 1 support. } else if (barrelLen<= 44) { supportCount = 2; / / Medium barrel uses 2 supports. } else { supportCount = 3; / / The long barrel uses 3 supports. } long amount = barrelLen>44 ? 2 : 1.

[0054] In one feasible embodiment, step S5053 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Hopper specifications are automatically selected based on the configuration of the machine barrel section for (ExtProcessBarrelConfigVo config : extProcessConfig.getBarrelConfigList()) { String machineSketch = config.getMachineSketch(); if (barrelUtils.isFeederSegment(machineSketch)) { if (barrelUtils.isLargeOpening(machineSketch)) { / / Large opening feed section uses 6D hopper hopperType = "Hopper-6D"; } else { / / Small-opening feed section uses 4D hopper hopperType = "Hopper-4D"; } } }

[0055] In one feasible embodiment, step S5054 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / The number of inserts and plugs is calculated based on the configuration of the barrel section. int pluginCount = 0; int plugCount = 0; for (ExtProcessBarrelConfigVo config : extProcessConfig.getBarrelConfigList()) { String ventPlugin = config.getVentPlugin(); if ("Exhaust".equals(ventPlugin)) { pluginCount++; / / Exhaust section requires plugins } else if ("plug".equals(ventPlugin)) { plugCount++; / / Non-exhaust sections need plugs } }

[0056] In one feasible embodiment, step S5055 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Number of thermocouples = Number of barrel sections + Number of thermocouple heads int thermocoupleCount = extProcessConfig.getBarrelConfigList().size() + 1; / / Adjust the thermocouple type according to process requirements String processType = extProcessConfig.getProcessType(); if (processType.contains("High Temperature")) { thermocoupleType = "Type K thermocouple"; / / Type K thermocouple is used in high-temperature processes } else { thermocoupleType = "J-type thermocouple"; / / J-type thermocouples are used in conventional processes. }

[0057] In one feasible embodiment, step S5056 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / The number of TCU cooling units is calculated based on the number of barrel sections and heat dissipation requirements. int barrelSegments = extProcessConfig.getBarrelConfigList().size(); int tcuCount; if (barrelSegments <= 24) { tcuCount = 1; / / Small barrel uses 1 TCU } else if (barrelSegments<= 48) { tcuCount = 2; / / Medium-sized barrel uses 2 TCUs } else { tcuCount = 3; / / Large barrels use 3 TCUs } Number of TCU piping sections = Number of barrel sections - 1 (adjacent sections share piping) int pipelineCount = barrelSegments – 1.

[0058] In one feasible embodiment, step S5057 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / The number of screw components is calculated based on the barrel length and process requirements. long screwElementCount = 0; String processCategory = extProcessConfig.getProcessCategory(); / / Number of basic screw components = Barrel length * Component density coefficient double densityFactor; if ("polyolefins".equals(processCategory)) { densityFactor = 1.2; / / Density factor for polyolefins } else if ("Nylon".equals(processCategory)) { densityFactor = 1.5; / / Density factor for nylon } else if ("fluoroplastics".equals(processCategory)) { densityFactor = 1.8; / / Density coefficient of fluoroplastics } else { densityFactor = 1.0; / / Default density factor } screwElementCount = Math.round(barrelLen * densityFactor).

[0059] In one feasible embodiment, step S5058 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Motor power is automatically selected based on screw diameter and process requirements. long screwDiameter = extProcessConfig.getScrewDiameter(); String processType = extProcessConfig.getProcessType(); long motor power; if (screwDiameter <= 35) { motorPower = processType.contains("High Fill") ? 75 : 55; } else if (screwDiameter<= 50) { motorPower = processType.contains("High Fill") ? 110 : 90; } else if (screwDiameter<= 65) { motorPower = processType.contains("High Fill") ? 160 : 132; } else { motorPower = processType.contains("High Fill") ? 220 : 185; }

[0060] In one feasible embodiment, step S5059 is implemented through modular encapsulation algorithm rules in JSON format, for example: / / Number of barrel connectors = Number of barrel sections - 1 (connectors are required between adjacent sections) int connectionCount = extProcessConfig.getBarrelConfigList().size()- 1; / / Adjust the connector type according to the connection method String connectionType; if ("C".equals(chuckType)) { connectionType = "C-type connector"; / / C-type connectors require additional locating pins int positionPinCount = connectionCount * 2; } else { connectionType = "Flange connector"; / / Flange connections require bolts int boltCount = connectionCount * 8; / / 8 bolts per flange }

[0061] The following is a detailed explanation of step S505, referring to the modular packaging algorithm described above. Step S505 includes: Step S505a: Receive and initialize process configuration parameters to obtain a process parameter configuration set, the process configuration parameter set including: chuckType: Global connection type (e.g., C-clamp or flange). This parameter has a decisive influence on the selection of multiple downstream components.

[0062] barrelConfigList: A barrel section configuration sequence that describes the detailed attributes of each barrel section from front to back, such as the barrel drawing number (machineSketch), plug model (ventPlugin), cap model (capModel), heating requirement (heating), and maximum temperature (maxTemp). Step S505b, determine the barrel body and general materials: Based on the global connection type (chuckType), the base material of the barrel body is determined through a strategy pattern (typeC...Strategy vsflange...Strategy, configuration strategy). Simultaneously, all base material data related to this process segment is loaded as the data source for subsequent rule filtering. Step S505c: Calculate the modular sub-components of the barrel using the rule engine; Step S505d: Generate and output a structured bill of materials, wherein the items in the bill of materials include material codes, descriptions, and exact quantities.

[0063] In one feasible embodiment, step S505c includes one or more of the following steps: The barrel connection calculation module (barrelConnect) is called to determine the number of barrel connections. The algorithm rules include: the number of connections depends on the total number of barrel segments and the connection type. When the connection type is "flange", the number is the number of barrel segments minus one; when it is "L" type, the number is 1; otherwise, it is the total number of barrel segments. The barrelConfigList.size() function is adjusted based on the value of chuckType. The plugin and plug calculation module (pluginAndPlug) is invoked to determine the plugins and plugs. The algorithm rules include: traversing each barrel section, firstly decoding the opening size from the barrel drawing number (machineSketch) using the feature code parser (BarrelUtils); then, based on the plugin model (ventPlugin) and plug model (capModel), combined with the opening size and global connection type, to accurately filter the materials. Specifically, the system can recognize special identifiers (such as + or I) in the capModel to determine whether additional "plugs with injection holes" or "plug rods" are needed. This achieves automatic mapping from abstract engineering drawing numbers to specific materials.

[0064] The injection valve calculation module (injectValve) is invoked to determine the injection valves. The algorithm rules include: the number of injection valves strictly corresponds to the number of plugs requiring injection. The number of injection valves is determined by scanning the plug model (capModel) parameters of all barrel sections and counting the number of occurrences of the injection identifier (+ or I). This demonstrates the inter-component linkage and ensures the completeness of the function.

[0065] The plug-in gasket calculation module is invoked to determine the gaskets. The algorithm rules include: gaskets are divided into "top plug-in gaskets" and "side plug-in gaskets". The feature code parser (BarrelUtils) analyzes the machine sketch numbers (machineSketch) of all barrel sections, summarizing the total number of top openings (U) and side openings (S) to determine the accurate quantity of both types of gaskets. This demonstrates the system's ability to aggregate and analyze geometric features.

[0066] Call the heating rod and thermocouple calculation module to determine the heating rod and / or thermocouple: The algorithm rules include: the number of heating rods is determined by the total length of the barrel, which is calculated by the feature code parser (BarrelUtils). Thermocouples are selected based on the heating requirement and maximum temperature (maxTemp) parameter of each barrel section: those requiring heating and exceeding 400°C are configured as "high-temperature thermocouples," otherwise, they are configured as ordinary "thermocouples." This achieves automatic selection from process parameters (temperature) to material grades (standard / high-temperature).

[0067] The exhaust component calculation module (vacuum) is invoked to determine the exhaust components. The algorithm rules include: The system analyzes the machine sketch number (machineSketch) using a feature code parser (BarrelUtils), summarizing the total number of vacuum ports and natural exhaust ports to determine the quantity of corresponding components. For example, the feature code parser uses regular expressions to identify the "VE" identifier in the machine sketch number string as representing a vacuum exhaust port and the "NE" identifier as representing a natural exhaust port, determining the quantity of corresponding exhaust components by counting the occurrences of these identifiers. This also demonstrates the system's deep analysis and aggregation capabilities for engineering code.

[0068] The above describes in detail several embodiments of step S505 of the present invention implemented by modular encapsulation algorithm rules. However, the present invention is not limited thereto. S506-S511 can also be implemented by modular encapsulation algorithm rules.

[0069] In one feasible embodiment, step S506 includes: The materials, quantities, mandrels, connectors, and costs of screw components are selected from the process parameter configuration, including: Select the mandrel and quantity from the process configuration parameters, and add the mandrel quotation item to the bill of materials based on the cost. For example, filter the obtained basic material data (materialDataList) according to the filtering conditions: the material name (ItemName) contains "mandrel" and the material number (MaterialNum) is a valid number; obtain the quantity of mandrels according to the quantity calculation logic. For example, if the quantity is hardcoded as 2 (BigDecimal.valueOf(2)), then it is a twin-screw extruder with a mandrel quantity of 2; generate a "mandrel" quotation item with a quantity of 2 and add it to the bill of materials. The process configuration parameters are used to filter out the spline sleeves and quantities that connect the mandrel and the transmission system. Combined with cost, the spline sleeve quotation item is added to the bill of materials. For example, spline sleeves are filtered from the basic material data based on the filter criteria: the item name (ItemName) is exactly equal to "screw spline sleeve, etc." and the material number (MaterialNum) is a valid number. The quantity is calculated according to the quantity calculation logic (consistent with the mandrel). A quotation item for "Spline Sleeve Assembly" with a quantity of 2 is generated and added to the bill of materials. Obtain the mandrel cutting processing fee from the process configuration parameters and add it to the bill of materials. For example, use the material name (ItemName) containing "mandrel cutting processing fee" and the unit price (UnitPriceWithTax) being a valid number as the filter criteria to obtain the mandrel cutting processing unit price from the basic material data, and obtain the total mandrel cutting price based on the number of mandrels; generate a quotation item for "mandrel cutting processing fee" with a quantity of 2 and add it to the bill of materials.

[0070] In one feasible embodiment, step S507 includes: A chuck-type-based classification filter identifies die head components from the die head component configuration strategy. The die head components include a die head body, a transition plate, and a die template. The die head body achieves the final material forming; the transition plate connects the barrel and the die head; the die template controls the product cross-sectional shape, including: Identify chuck type; Filter the head components corresponding to the chuck type. For example, filter the corresponding head components from the material database based on the chuck type. Generate a quotation for the head unit and add it to the bill of materials.

[0071] The algorithm rules of this invention are based on the engineering design principles and actual production experience of extruders. Through parametric calculation, the quantity of each component is intelligently determined, avoiding errors in manual calculation and improving the accuracy and efficiency of configuration.

[0072] In one feasible embodiment, the drive component includes a motor, a gearbox, and a coupling. The motor provides power, the power of which is selected according to the screw diameter and process requirements. The gearbox amplifies torque and controls speed. The coupling connects the motor and the gearbox. Step S508 includes: Receive process parameter configurations and derive technical specifications, including: receiving process parameter configurations containing motor power (deviceConfigList) and screw speed (screwSpeed), and through the parameter derivation module (calculatePoles), applying preset engineering rules (e.g., speed 600rpm -> 6 levels, others -> 4 levels) to convert the macroscopic process parameter "speed" into the key electrical technical specification "number of motor levels"; Perform dynamic linkage queries to ensure compatibility, such as the compatibility between motors and frequency converters: The derived motor rating, specified power, and brand information are packaged and sent to the Component Compatibility Service (extMotorFrequencyConverterService). The Component Compatibility Service performs a key linked query and returns a data object. The data object contains not only detailed information (model, price) of the main component (e.g., motor) that meets the conditions, but also a list of fully compatible slave components (e.g., frequency converters). The main component information is extracted from the returned data object to generate a material entry. From the list of compatible slave components, information is extracted according to preset rules (e.g., selecting the brand "ABB") or by selecting the first one to generate another material entry. Through a single query, the selection and compatibility verification of two key components are resolved. Execute a list-based optimization strategy, such as a gearbox and coupling optimization strategy: For gearboxes, all materials with matching names are filtered from the material database: the first material in the list is set as the default quotation item, and the entire list is appended as an "optional configuration" to the drive component quotation item; this provides efficient default configuration and necessary customization space for standardized components; Execution condition triggers logic, such as extracting additional components later: To check if a specific functional requirement exists in the parameter set, you can check if a specific functional requirement exists by meeting certain conditions. For example, a compound conditional statement (if ("1".equals(extProcessConfig.getBackDraw())&&extProcessConfig.getModelType().startsWith("ZE26"))) will trigger the addition of the material item "26 machine back draw accessories" only if the "back draw" function is activated and the machine model is "ZE26" series.

[0073] Assemble and output to the bill of materials: The material items generated through the above steps are summarized and output to the bill of materials. For example, the technical description generator (generateEquipmentDescription) is called to automatically generate a readable and detailed equipment description based on the key parameters of each component (such as brand, model, power, and number of stages), and finally outputs a bill of materials with a complete structure and accurate information.

[0074] In one feasible embodiment, the heating and cooling system includes heating rods, thermocouples, and a TCU cooling unit. The heating rods perform distributed heating, with each barrel section equipped with one heating rod. The thermocouples monitor the temperature to achieve closed-loop control. The TCU cooling unit performs cyclic cooling to control the processing temperature. Step S509 includes: Receive process configuration parameters and load the material database: Receive a set of process configuration parameters describing the details of the main equipment, and load all alternative materials (materialDataList) related to the cooling system from the material database; Processing a fixed number of main units: Process the main units in the cooling system sequentially. For example, for "TCU" and "TCU main circuit", invoke the standardized material addition procedure (toExtQuoteItemsBo) and specify a preset fixed value (e.g., 1) for their quantity parameters to add these components to the bill of materials; Extract key structural parameters of the main equipment: From the received process configuration parameter set, locate the list describing the segmented structure of the main equipment (extProcessConfig.getBarrelConfigList()), and extract the core parameter "total number of barrel segments" by calculating the length of the list (.size()); The number of subordinate units is calculated using a quantitative relationship model: a preset mathematical relationship is used, such as the number of subordinate units = the total number of barrel segments - 1. The key structure of the main equipment is extracted and input into the mathematical relationship to obtain an accurate value, which is the required number of "TCU pipelines - barrel". Handling dynamically quantified dependent units: The same standardized material addition procedure (toExtQuoteItemsBo) is called again, but this time the quantity parameter is specified as the value dynamically calculated in the above steps, so that the correct number of dependent units are added to the bill of materials. Summarize and output the bill of materials: Summarize all processed components to form a complete bill of materials for the cooling system, in which the quantity of each component has been precisely determined according to its type (main / subordinate) and preset rules.

[0075] In one feasible embodiment, step S510 includes: Receive configuration context and load database: Receive process configuration context containing the unique identifier (configId) of the current configuration and load all alternative auxiliary material data.

[0076] Apply fixed rules to process global auxiliary materials: Iterate through the predefined global auxiliary material list (e.g., "screw installation tool", "main unit nameplate"); for each item in the list, the system calls a standardized material addition program (toExtQuoteItemsBo) and passes in a preset fixed quantity value (e.g., 1) to add it to the bill of materials; Applying a relational query estimation strategy to process dependent auxiliary materials: When processing an auxiliary material marked as "dependent" (e.g., "side feed nameplate"), perform the following sub-steps: Construct a related query: Construct a database query that uses the unique identifier (configId) of the current configuration and the name of the main functional component associated with the auxiliary material ("side feed") as key conditions; Execute real-time query: Execute the query in the materials database through the database access interface (extProcessDeviceConfigMapper); Processing query results: If the query returns no records, it indicates that the main functional component does not exist in the current configuration, and the processing of the auxiliary material is terminated; if the query returns one or more records, the configured quantity of the main functional component is extracted from the records. Generate material entry: Call the standardized material addition procedure to add the auxiliary material to the list and set its quantity precisely to the value extracted in the previous step; Summarize and output: All material items calculated through fixed rules and related queries are summarized to form the final material list for auxiliary materials.

[0077] In one feasible embodiment, step S511 includes: Define a configurable work time structure: It includes a built-in structured text configuration (such as JSON) to define all work time types involved in billing; each type entry must contain at least: a unique work time identifier, a name, a category, and a "rate field name" pointing to the rate parameter; Obtain context-dependent quotas and rates: Based on the context of the current project (such as product model and project ID), send queries to the "Work Quota Database" and "Work Rate Database" respectively to obtain the standard work quota table and hourly rate parameter table that match the context; Perform iterative data fusion and computation: traverse each defined time type: Use the unique identifier of the current work time type to find the corresponding standard work hours in the work time quota table; Use the "rate field name" defined for the current work time type to find the corresponding hour rate in the hour rate parameter table; Multiply the obtained working hours by the rate to calculate the itemized cost for that type of working hour; Information such as work type identifier, name, category, number of work hours, rate, and itemized cost is stored in a structured data record; Aggregate data and generate structured output: Group all generated data records according to their "category". For each group, perform the following steps: The total cost of this category is the sum of the costs of all the individual items recorded in the group. Create a quote entry and set the total cost as its price; Serialize all detailed data records in the group into a string and store it in the remarks field of the quotation item for traceability; Summarize and output: Summarize all generated quote items to form the final labor cost list.

[0078] In one feasible embodiment, such as Figure 4 As shown, step S6 includes: Step S61: Obtain the material cost of each configuration in the process orchestration framework from the bill of materials in step S5. Step S62, obtain labor costs; Step S63, adjust other expenses. This step is not mandatory. Other expenses may include administrative expenses. Step S64: Summarize the material costs by summarizing the material costs of each configuration obtained in step S61. Step S65, Total Cost: Total the costs from steps S62-S64.

[0079] In one feasible embodiment, step S61, obtaining material costs, includes multi-currency exchange rate conversion and application of differential cost coefficients: For material prices in different currencies, a currency conversion factor is used to uniformly convert the prices to RMB. The currency conversion factor includes one or more of the Euro and US Dollar exchange rates. For example: if the material price is in Euro (EUR), then the RMB price = (unit price excluding tax) × Euro exchange rate; if the material price is in US Dollar (USD), then the RMB price = (unit price excluding tax) × US Dollar exchange rate; if the material price is in RMB (CNY), then the unit price excluding tax is used directly. Different cost coefficients are applied based on the source of the materials. These cost coefficients include imported material coefficients and local material coefficients. For example: the unit price of imported materials including tax = unit price excluding tax × exchange rate × (1 + VAT rate) × imported material coefficient; the unit price of local materials including tax = unit price excluding tax × (1 + VAT rate) × local material coefficient; where the VAT rate is assumed to be 13%, the imported material coefficient is greater than 1 to reflect the import cost, and the local material coefficient is usually close to 1. Differentiated profit margins can be applied to specific component categories, such as setting the profit margin for main components at 5% and using standard profit margins for other components, thereby enabling flexible pricing strategies.

[0080] In one feasible embodiment, step S6 further includes: Step S60: Configuration list confirmation step, where the process intelligence agent re-determines the rationality of the configuration list, including: Check if the configuration list is confirmed: If the configuration list is confirmed, proceed to step S61; If the configuration list is not confirmed, return to step S242.

[0081] In one feasible embodiment, such as Figure 4 As shown, step S7 includes: Step S71: Set profit margins. Set profit margins for different pricing strategies. The pricing strategies include customized pricing, competitive pricing, preferential pricing, and standard pricing. The profit margins include customized profit margins, competitive profit margins, preferential profit margins, and standard profit margins. The competitive profit margin is no greater than the preferential profit margin, and the preferential profit margin is no greater than the standard profit margin. Preferably, the competitive profit margin is 5%-10%, the preferential profit margin is 10%-15%, and the standard profit margin is 15%-20%. The default profit margin is 25%, which can be adjusted according to the pricing strategy. Step S72: Select a pricing strategy. Choose an appropriate pricing strategy based on market conditions, customer type, and competitive landscape. Step S73, calculate the price: Obtain the corresponding profit margin according to the selected pricing strategy, add the profit to the total cost in step S65 to calculate the price. The calculation formula is: final price = total cost / (1 - profit margin). For example, if the total cost is 1 million yuan and the profit margin is 25%, then the final price = 100 / (1 - 0.25) = 1,333,300 yuan. Step S74, Generate Final Quotation: Generate a final quotation based on the price calculated in step S73. For example, final quotation = total cost / (1 - profit margin). The final quotation uses a three-level hierarchical structure to organize data, including main component categories, subcategories, and specific material items. When the quotation is generated, it is summarized and displayed according to the hierarchy. Materials at the same level are automatically combined in quantity and price. The final quotation supports generating quotation files in both Excel and PDF formats and is automatically uploaded to the object storage service. Step S75, Generate final quote: Combine the quoted price and taxes to generate a final quote.

[0082] In one feasible embodiment, such as Figure 4 As shown, step S8 also includes a sales review step, including: Step S76, determine whether the sales review is passed: the sales agent determines whether the final quote meets the customer's needs; If the sales review fails, return to step S61.

[0083] If the sales review is passed, proceed to step S77 to generate a formal quotation. The formal quotation can be in formats such as Excel, PDF, or Word, but preferably Excel. Step S78: Send the formal quotation.

[0084] This invention enables full-process quality control, establishes a multi-approval mechanism for processes and customer requirements, achieves automatic verification and optimization of configuration rationality, and supports full traceability and quality monitoring of the quotation process.

[0085] Figure 5 This is a schematic block diagram of an embodiment of the intelligent pricing system for extruders described in this invention, as shown below. Figure 5 As shown, the intelligent pricing system 100 for extruders includes: The process requirements analysis module 10 is configured to collect process requirements information, establish a database, and obtain process configuration files by matching the process requirements information in the database. The intelligent configuration generation module 20 is configured to use a strategy pattern to build configuration strategies for different configurations of extruder components and a process orchestration framework to use a rule engine to build the component configuration order. The dynamic material calculation module 30 is configured to call the configuration strategy and process orchestration framework of the intelligent configuration generation module and combine it with the process requirement information collected by the process requirement analysis module to obtain the materials, quantity, specifications and cost required by the extruder, thereby obtaining the material configuration. The automatic quotation calculation module 40 is configured to obtain the total cost corresponding to the material configuration based on multi-dimensional cost, construct multiple quotation strategies, and generate multiple quotations by combining the total cost and multiple quotation strategies. The quotation document generation module 50 is configured to generate a structured quotation by combining the process configuration file of the process requirements analysis module, the material configuration of the dynamic material calculation module, and the various quotations of the automatic quotation calculation module.

[0086] The process requirements analysis module of this invention establishes an intelligent process knowledge system, constructs a standardized process database covering nine major process categories such as polyolefins, nylon, and fluoroplastics, establishes an intelligent mapping relationship between process parameters, process types, and process configurations, and realizes an automated equipment recommendation mechanism based on process characteristics.

[0087] The intelligent configuration generation module of this invention implements a modular configuration strategy architecture, adopts a strategy pattern to design a flexible material configuration strategy system, supports different types of differentiated configurations such as C-type chucks and flange chucks, and realizes hot-swappable and dynamic expansion of configuration strategies; it builds a process orchestration engine, realizes component-based configuration process orchestration based on LiteFlow technology, supports collaborative configuration of subsystems such as barrel, screw, head, drive, and cooling, and realizes visual management and dynamic adjustment of configuration process.

[0088] The dynamic material calculation module and automatic price calculation module of this invention develop intelligent calculation algorithms, establish an intelligent calculation model for material quantity based on process parameters, realize multi-dimensional cost calculation and dynamic price adjustment mechanism to support the flexible application of various pricing strategies.

[0089] Figure 6 This is a schematic diagram of another embodiment of the intelligent pricing system for extruders described in this invention, as shown below. Figure 6 As shown, the intelligent pricing system 100 for extruders includes: Presentation layer 110 serves as the human-computer interaction entry point and data exit point, used for process requirement information input, configuration preview, and quotation display, including a web front-end interface, application programming interface (e.g., RESTful API), and access control (e.g., SaToken). The business logic layer 120 is configured to modularly encapsulate business logic, build a quotation calculation engine and an orchestration engine, dynamically select the configuration strategy of the strategy layer, and generate material configuration and quotation based on the process requirement information entered in the appearance layer, including process configuration service, strategy factory, LiteFlow orchestration engine and quotation calculation engine. Strategy layer 130 is configured to set differentiated configuration strategies for different process types and equipment types, including a material configuration strategy interface and a configuration strategy construction module. The configuration strategy construction module includes configuration strategies for C-type chuck barrels, flange barrels, screws, head components, heating and cooling systems, installation tools, and working hours. The material configuration interface of the strategy layer is triggered through the strategy factory of the business logic layer. Component layer 140 is configured to map various parts of the extruder to software components based on the business logic layer's process orchestration engine, including barrel configuration components, screw configuration components, die head configuration components, drive component components, heating and cooling system configuration components, installation tool components, formula components, and data storage components; and triggers each software component in the component layer through the LiteFlow orchestration engine; Data layer 150 is configured to build multiple data sources for distributed data storage and real-time data synchronization, including process database, material database, price database, and configuration database; any component in the component layer triggers the data layer. External interface 160 is configured to set up external interfaces for integration and data exchange with third-party systems, including Excel import / export interfaces, Word / PDF generation interfaces, and data synchronization interfaces.

[0090] This invention features a six-layer architecture: innovatively introducing a component layer and a strategy layer to achieve highly modular business logic and dynamic strategy management; LiteFlow process orchestration: mapping the physical components of the extruder to software components, supporting visual orchestration and dynamic adjustment of the process; independent layering of strategy modes: making configuration strategies an independent layer, supporting hot-swapping, version management, and dynamic expansion of strategies; and an intelligent rule engine: based on a dynamic calculation algorithm of process parameters, realizing intelligent determination of the quantity and specifications of each component.

[0091] This invention's appearance layer achieves front-end / back-end separation and multi-terminal adaptation through a unified API interface design, providing a flexible access control mechanism. The business logic layer modularly encapsulates complex business logic, implementing dynamic selection and expansion of configuration strategies through the strategy factory pattern. The component layer, based on the LiteFlow framework's component-based design, maps each physical component of the extruder to an independent software component, enabling visual orchestration and dynamic adjustment of the configuration process. This component layer design is not found in traditional MVC architectures, enabling: loose coupling and high cohesion between components; dynamic orchestration and real-time adjustment of the configuration process; modular encapsulation and reuse of business logic; rapid access and expansion of new equipment types. The strategy layer, through an independent layered design using the strategy pattern, implements differentiated configuration strategies for different process types and equipment types, supporting hot-swapping and dynamic expansion of strategies. Unlike traditional systems that embed strategy logic into the business layer, this application separates strategy logic into an independent layer, achieving: independent encapsulation and management of strategy algorithms; rapid access to new process types; version control and rollback of configuration strategies; monitoring and optimization of strategy execution; the data layer adopts a multi-data source design, supporting distributed data storage and real-time data synchronization, providing stable data support for upper-layer businesses; and the external interface layer achieves seamless integration and data exchange with third-party systems through standardized external interface design.

[0092] The inter-layer collaboration in this invention is as follows: Presentation Layer → Business Logic Layer: Through a unified service interface, standardized processing of front-end requests and encapsulation of business logic are achieved; Business Logic Layer → Component Layer: Through the LiteFlow orchestration engine, component-based decomposition and dynamic scheduling of business processes are achieved; Component Layer → Strategy Layer: Each component obtains the corresponding configuration strategy through the strategy factory, achieving separation of component logic and strategy algorithm; Strategy Layer → Data Layer: During strategy execution, the required data is dynamically queried and calculated, achieving decoupling of strategy algorithm and data storage; Data Layer → External Interface Layer: Provides standardized data access interfaces for external systems, achieving secure data sharing and synchronization.

[0093] Compared to the three-tier architecture (presentation layer, business layer, and data layer), this invention innovatively introduces two independent architectural layers: the component layer and the strategy layer. The component layer maps the physical components of the extruder to software components, supporting process orchestration and dynamic adjustment. The strategy layer separates the configuration strategy into an independent layer, supporting hot-swapping and version management of strategies. Compared to the three-tier architecture, the six-layer architecture design has stronger scalability, maintainability, and business adaptability.

[0094] Figure 7 This is a schematic diagram illustrating the structural block of one embodiment of the apparent layer described in this invention, as shown below. Figure 7As shown, the appearance layer 110 includes a main interface 111, a process requirement input interface 112, a process configuration interface 113, a first sales review interface 114, a quotation interface 115, and a second sales review interface 116. Each interface is equipped with one or more dynamic function controls to realize interface display, interface navigation, input, and feedback. The main interface is equipped with a navigation bar, user information (login account information), and dynamic function controls corresponding to the function menu. The process requirement input interface is equipped with dynamic functional controls for customer information input, plastic type selection, product specification input, product requirement input, special requirement remarks, and a submit button. The process configuration interface includes a review process interface, configuration parameter display, barrel configuration table, screw configuration table, head configuration table, and dynamic function controls corresponding to the submit button. The first sales review interface is set up with dynamic functional controls corresponding to the review process interface, process requirement information, and process configuration information. The quotation interface includes a review process interface, quotation header information, configuration summary table, price details table, total price display, special requirements annotation, and dynamic functional controls corresponding to the submit button. The second sales review interface includes a review process interface, process requirement information, process configuration information, quotation information, and dynamic function controls corresponding to the documents. Among them, such as Figure 8 As shown: The review process interface is equipped with dynamic functional controls for passing / rejecting buttons, a list of items to be reviewed, review details, and input of review comments.

[0095] In one feasible embodiment, such as Figure 7 and Figure 8 As shown: The dynamic function controls corresponding to the function menu on the main interface trigger the process requirement input interface. The dynamic function control corresponding to the submit button on the process requirements input interface triggers the review process interface on the process configuration interface. The process configuration review process interface is triggered by the rejection status of the / reject button, which returns to the process requirement input interface. The status triggers the submit button; the dynamic function control corresponding to the submit button triggers the review process interface of the first sales review interface. The first sales review interface's review process is triggered by the rejection status of the / reject button, which returns to the process requirement input interface. The status then triggers the review process interface of the quotation form. The approval process interface of the quotation form is triggered by the rejection status of the / reject button, which returns to the process requirement input interface. The status triggers the submit button; the dynamic function control corresponding to the submit button triggers the approval process interface of the second sales approval interface. The second sales review interface's review process is triggered by the rejection status of the / reject button, returning to the quotation page.

[0096] Figure 9 A schematic diagram illustrating an application scenario of the intelligent pricing method for extruders described in this invention is shown.

[0097] exist Figure 9 In the application scenario, the computing device 200 includes a memory 210 and a processor 220: The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-described intelligent pricing method for extruders.

[0098] The aforementioned computing devices can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster of multiple servers or terminal devices, or as a single server or terminal device. When the computing device is software, it can be installed on the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.

[0099] Computing devices can be any type of stationary or mobile device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). Electronic devices can also be mobile or stationary servers.

[0100] The present invention also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described intelligent pricing method for extruders.

[0101] The present invention also provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the above-described intelligent pricing method for extruders.

[0102] The technical solutions of the computing device, computer-readable storage medium, computer program, and extruder intelligent pricing method and system belong to the same concept. For details not described in detail in the technical solutions of the computing device, computer-readable storage medium, and computer program, please refer to the description of the above-mentioned technical solutions of the extruder intelligent pricing method and system.

[0103] The plastics processing equipment market is huge, and there is an urgent need for intelligent quotation systems, especially as: large equipment manufacturers need to improve quotation efficiency; customers demand faster response times and more accurate configurations; and the industry is becoming increasingly standardized.

[0104] This invention can meet the above-mentioned market demands, specifically in the following ways: Efficiency Improvement: Quotation time has been reduced from several days to several hours, improving efficiency by over 80%; Improved accuracy: Based on a standardized process database, human error is reduced by more than 90%; High degree of standardization: unified configuration standards and quotation process; Highly flexible: the strategy mode supports rapid adoption of new processes; Traceability: Complete records of the configuration and quotation process; Enhancing business competitiveness: The ability to provide fast and accurate quotations; Reduce operating costs: Reduce labor costs and error costs; Improving customer satisfaction: rapid response and professional service; Promote industry development: Drive the intelligent transformation of the equipment manufacturing industry.

[0105] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments of the present invention.

[0106] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0107] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments of the present invention. These embodiments are selected and specifically described to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention.

Claims

1. An extruder intelligent quoting method, characterized in that, The method comprises the following steps: Process requirement collection step: collecting process requirement information, which comprises one or more of customer information, single-line processing information, and raw material and form recipe information; the customer information comprises one or more of company name, address, country, telephone, fax, and contact person; the single-line processing information comprises one or more of product name, single-line production capacity requirement, processing temperature, torque, rotating speed, specific energy consumption, melting temperature, melting pressure, and vacuum degree; the raw material information and form recipe information comprises one or more of material number, material name, addition proportion, addition position, melting point / melting range, melting index, bulk density, form and size, particle size distribution, shear sensitivity, temperature sensitivity, material viscosity, material abrasiveness, material corrosiveness, and material color; Database matching step: establishing a database, and matching in the database based on the process requirement information to obtain a process configuration file; the database comprises a mapping between raw material types and process types; A mapping between process types and process configuration files, one process type corresponding to multiple process configuration files; Strategy mode configuration step: adopting a strategy mode to construct a configuration strategy of an extruder assembly; the configuration strategy comprises one or more of C-type chuck barrel configuration strategy, flange barrel configuration strategy, screw component configuration strategy, head component configuration strategy, driving component configuration strategy, heating and cooling system configuration strategy, installation tool configuration strategy, and work hour configuration strategy; Process arrangement engine step: adopting a rule engine to construct a process arrangement framework; Material data dynamic assembly step: calling the configuration strategy according to the process of the process arrangement framework, combining the process requirement information to obtain the materials, quantity, specification, and cost of the extruder, and thus obtaining material configuration; Cost calculation step: obtaining the total cost corresponding to the material configuration based on multi-dimensional cost, which comprises one or more of material cost, processing cost, labor cost, and management fee; Quotation strategy implementation step: constructing multiple quotation strategies, and generating multiple quotations in combination with the total cost and the multiple quotation strategies.

2. The extruder intelligent quoting method of claim 1, wherein, The cost calculation step comprises: For different currency material prices, adopting an exchange rate conversion coefficient to uniformly convert the prices into RMB, wherein the exchange rate conversion coefficient comprises a euro exchange rate or / and a US dollar exchange rate; According to the material source, applying different cost coefficients to obtain material cost; the cost coefficients comprise an imported material coefficient and a local material coefficient: The cost of imported material is obtained by the following formula: Tax-included cost unit price = tax-free unit price × exchange rate × (1 + value-added tax rate) × imported material coefficient; The cost of local material is obtained by the following formula: Tax-included cost unit price = tax-free unit price × (1 + value-added tax rate) × local material coefficient.

3. The extruder intelligent quoting method of claim 1, wherein, Further comprising: Structured quotation sheet generation step: generating a structured quotation sheet in combination with the material configuration and the multiple quotations, wherein the structured quotation sheet comprises one or more of equipment technical parameters, material list, itemized price details, total price, delivery period, and service terms.

4. The extruder intelligent quoting method of claim 3, wherein, The structured quotation sheet organizes data in a three-level hierarchical structure, including main component categories, sub-categories, and material items, and the quotation sheet is generated and displayed according to the hierarchy, and the quantities and prices of the same level materials are automatically combined.

5. The extruder intelligent quoting method of claim 1, wherein, The database matching step includes: The product name or / and the material number or / and the material name in the raw material and form formula information of the single-wire processing information are matched in the database to obtain the raw material type; The process type is identified based on the raw material type; A plurality of process configuration files corresponding to the identified process type are obtained; The collected process requirement information is matched in the plurality of process configuration files to obtain the process configuration file most consistent with the process requirement information.

6. The extruder intelligent quoting method of claim 5, wherein, The database matching step further includes: It is judged from the perspective of the process whether the process configuration file most consistent with the process requirement information is reasonable; If not, the process configuration file is optimized and returned to the above step; If it is reasonable, the process configuration file is structured into a configuration list.

7. The extruder intelligent quoting method of claim 6, wherein, The database matching step further includes: It is judged whether the configuration list meets the customer's demand; If it does not meet the customer's demand, the process configuration file is optimized and returned to the step of judging from the perspective of the process whether the process configuration file most consistent with the process requirement information is reasonable; If it meets the customer's demand, the configuration list is output.

8. The extruder intelligent quoting method of claim 1, wherein, The material data dynamic assembly step includes: Obtaining process configuration parameters, the process configuration parameters being obtained through the process configuration file; Calling a process arrangement framework; According to the process arrangement framework, a configuration strategy is called to combine the process configuration parameters for material configuration.

9. The extruder intelligent quoting method of claim 8, wherein, The step of calling the configuration strategy according to the process arrangement framework to combine the process configuration parameters for material configuration includes one or more of the following steps: According to the process configuration parameters, the chuck type is determined; According to the chuck type, a C-type chuck barrel configuration strategy or a flange chuck barrel configuration strategy is called; Carrying out barrel component calculation; Carrying out screw component calculation; Carrying out head component calculation; Carrying out driving component calculation; Carrying out heating and cooling system calculation; Carrying out installation tool calculation; Carrying out work hour calculation.

10. The extruder intelligent quoting method of claim 9, wherein, The step of carrying out barrel component calculation includes one or more of the following steps: According to the number of barrel segments, the number of heating rods is calculated; According to the chuck type, the heating rod specification is adjusted; According to the barrel length, the number of barrel support bodies is determined; According to the barrel segment number, the automatic selection hopper specification is configured; According to the barrel segment number, the number of inserts and plugs is calculated; According to the barrel segment number and the number of heads, the number of thermocouples is calculated; According to the barrel segment number and the heat dissipation requirement, the number of TCU cooling units is calculated; According to the barrel length and the process requirement, the number of screw elements is calculated; According to the screw diameter and the process requirement, the motor power is automatically selected; According to the barrel segment number and the number of connecting pieces required by adjacent segments, the number of barrel connecting pieces is calculated.

11. The extruder intelligent quoting method of claim 9, wherein, The steps of carrying out barrel component calculation, carrying out screw component calculation, carrying out head component calculation, carrying out driving component calculation, carrying out heating and cooling system calculation, carrying out installation tool calculation, and carrying out work hour calculation are realized by modular packaging algorithm rules.

12. The extruder intelligent quoting method of claim 11, wherein, The step of realizing calculation by modular packaging algorithm rules includes: Building a rule engine of algorithm rules; The rule engine is called to perform one or more of material quantity calculation, material specification matching, standard man-hour acquisition, and cost calculation.

13. The extruder intelligent quoting method of claim 12, wherein, The step of performing barrel component calculation includes: A process configuration parameter set is constructed based on process configuration parameters, the process configuration parameter set including a type identification and a configuration list of modular components; The process configuration parameter set is called to determine a barrel main body and materials; Modular sub-component calculation of the barrel is performed by the rule engine.

14. The extruder intelligent quoting method of claim 13, wherein, The step of performing modular sub-component calculation of the barrel by the rule engine includes one or more of the following steps: A barrel connector calculation module is called to determine barrel connectors, algorithm rules including: the number of connectors depends on the total number of barrel segments and the connection type; A plug and plug calculation module is called to determine the plug and plug; A liquid injection valve calculation module is called to determine the liquid injection valve, algorithm rules including: the number of liquid injection valves corresponds to the number of plugs that need to be injected; A plug gasket calculation module is called to determine the gasket, algorithm rules including: the gasket is divided into upper plug gaskets and side plug gaskets; A heating rod and thermocouple calculation module is called to determine the heating rod or / and thermocouple, algorithm rules including: the number of heating rods is determined by the total length of the barrel; An exhaust component calculation module is called to determine the exhaust component, algorithm rules including: analyzing the barrel figure number by a feature code parser, and summarizing the total number of vacuum ports and natural exhaust ports to determine the number of corresponding components.

15. The extruder intelligent quoting method of claim 9, wherein, The step of performing drive component calculation includes: Receiving process parameter configuration to derive the technical specifications of the main part of the drive component according to the preset engineering rules; Performing dynamic linkage query to obtain slave parts compatible with the main part; Executing list optimization strategy to obtain optional configurations of the drive component; Executing condition triggering logic to obtain the drive component corresponding to the functional requirement in combination with the process configuration parameter; Summarizing the materials of the drive component.

16. The extruder intelligent quoting method of claim 1, wherein, The quotation strategy implementation step includes: Setting different quotation strategies and profits; the quotation strategies include one or more of custom quotation, competitive quotation, preferential quotation, and standard quotation, the profit rates include one or more of custom profit rate, competitive profit rate, preferential profit rate, and standard profit rate, the competitive profit rate is not greater than the preferential profit rate, and the preferential profit rate is not greater than the standard profit rate; Selecting a quotation strategy; Generating a final quotation based on the total cost in combination with the quotation strategy and the profit rate thereof.

17. An extruder intelligent quoting system characterized by, It includes: A process demand analysis module configured to collect process demand information, establish a database, and perform matching in the database based on the process demand information to obtain a process configuration file; An intelligent configuration generation module configured to construct a configuration strategy of an extruder component using a strategy mode and construct a process arrangement framework of component configuration order using a rule engine; A dynamic material calculation module configured to call the configuration strategy and the process arrangement framework of the intelligent configuration generation module to obtain the materials, quantity, specification, and cost of the extruder required in combination with the process demand information collected by the process demand analysis module, thereby obtaining material configuration; An automatic quotation calculation module is configured to obtain a total cost corresponding to a material configuration based on multi-dimensional costs, construct multiple quotation strategies, and generate multiple quotations in combination with the total cost and the multiple quotation strategies.

18. The extruder intelligent quoting system of claim 17, wherein, Further comprising: A quotation document generation module is configured to generate a structured quotation sheet in combination with the material configuration of the dynamic material calculation module and the multiple quotations of the automatic quotation calculation module, wherein the structured quotation sheet includes one or more of equipment technical parameters, a material list, a detailed item price, a total price, a delivery period, and service terms.

19. The extruder intelligent quoting system of claim 18, wherein, The quotation document generation module is further configured to generate quotation files in Excel and PDF formats and upload the generated quotation files to an object storage service.

20. An extruder intelligent quoting system characterized by, Comprising: A presentation layer, a business logic layer, a component layer, a strategy layer, a data layer, and an external interface layer: The presentation layer is a human-computer interaction entrance and a data outlet for process requirement information input, configuration preview, and quotation sheet display. The business logic layer is configured to modularize business logic, dynamically select configuration strategies of the strategy layer, and generate a material configuration in combination with process requirement information input by the presentation layer; and to construct a quotation calculation engine to generate a quotation sheet based on the material configuration; The strategy layer is configured to set differentiated configuration strategies for different process types and equipment types. The component layer is configured to map each part of an extruder to a software component based on a process orchestration engine of the business logic layer; The data layer is configured to construct multiple databases for distributed data storage and real-time data synchronization; The external interface layer is configured to integrate with third-party systems and exchange data through external interfaces.

21. The extruder intelligent quoting system of claim 20, wherein, The presentation layer includes one or more of the following dynamic function controls: A web front-end interface for a visual configuration interface; An application program interface to provide standardized interfaces for terminals; Permission management for controlling access permissions of different roles to configuration functions.

22. The extruder intelligent quoting system of claim 20, wherein, The business logic layer includes: A process configuration service that calls databases of the data layer to obtain a process configuration file based on process requirement information input by the presentation layer; A strategy factory that dynamically selects configuration strategies of the strategy layer; A LiteFlow orchestration engine that constructs a process orchestration framework using a rule engine, defines component calling sequences through a configuration file, and executes a material configuration obtained in combination with a process configuration file and a strategy configuration in sequence, wherein the components include one or more of barrel part components, cooling system components, drive part components, gearbox-barrel connection segment components, head part components, heat shielding components, installation tool components, total frame components, screw components, threaded element components, work hour components, control system components, and side feeder components. A quotation calculation engine that generates a quotation sheet based on the material configuration and quotation strategies.

23. The extruder intelligent quoting system of claim 20, wherein, The strategy layer includes a material configuration strategy interface and multiple configuration strategy construction modules, and the configuration strategies of the configuration strategy construction modules are called through the material configuration strategy interface, wherein the configuration strategy construction modules include one or more of a C-type chuck barrel configuration strategy module, a flange barrel configuration strategy module, and a process segment configuration strategy module.

24. The extruder intelligent quoting system of claim 20, wherein, The databases include a process database, a material database, a price database, and a configuration database: The process database stores a mapping between raw material types and process types, and stores barrel segment configuration parameters, the barrel segment configuration parameters including one or more of barrel segment serial number, barrel segment type, maximum temperature, cooling method, heating method, vent type, and barrel material, the barrel segment type being mapped to a corresponding barrel drawing number; The configuration database stores a mapping between process types and process configuration files, the process configuration files including one or more of process type, machine type, chuck type, screw diameter, and version number; The material database stores a mapping between process configuration files and materials; The price database stores a mapping between materials and prices, the prices including material prices in different currencies.

25. A computing device, comprising: comprising a memory and a processor; The memory is configured to store computer-executable instructions, and the processor is configured to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the extruder intelligent pricing method according to any one of claims 1 to 19.

26. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the extruder intelligent pricing method according to any one of claims 1 to 19.

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