Equipment design quality management system and method and electronic equipment

Abstract

The invention provides an equipment design quality management system and method and electronic equipment, and relates to the technical field of quality management, and the system comprises an information obtaining module which is used for obtaining project information; the potential risk list generation module is used for matching historical problems and generating a risk list; the distribution module is used for sending the potential risk information in the potential risk list to a designer corresponding to the potential risk information according to the project information; the quality detection module detects quality data according to a period, and judges whether the design project has an occurred design quality problem or not; the information feedback module is used for disassembling part numbers, names, descriptions, types and solutions from the problem data; and the quality index calculation module is used for generating a quality level evaluation report of the project in the preset period. According to the invention, the quality management efficiency is improved, and the quality management level is also improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quality management, in particular to an equipment design quality management system and method and electronic equipment. BACKGROUND

[0002] Currently, in the field of complete metallurgical equipment design, complete metallurgical equipment is usually produced in a single-piece small-batch mode. Due to the diversified requirements of different users for equipment parameters, it is necessary to customize the design drawing according to the specific requirements of the users. Due to the different requirements of different users, the quality management is relatively complex. The existing technology usually records the quality problems occurring in the design process in paper or scattered electronic documents. Designers often pass on and save information such as problem description and solution through email, meeting minutes or personal experience library.

[0003] In the related art, due to the scattered design quality problem data at the individual or department level, it is difficult for newly joined designers to quickly obtain historical problem information, which is prone to repeated mistakes, and it is difficult to support rapid knowledge reuse of large-scale complex equipment, resulting in low retrieval efficiency. Secondly, for large-scale complex equipment, the manual checking method adopted in the prior art is difficult to repeatedly check and correct, resulting in many design quality problems being exposed only in the subsequent stages of production, installation or debugging, increasing the project cost and affecting the project progress and product quality. SUMMARY

[0004] The problem solved by the present application is how to improve the efficiency and effectiveness of the design quality management of complete metallurgical equipment.

[0005] To solve the above problems, the present application provides an equipment design quality management system, method and electronic equipment.

[0006] In a first aspect, the present application provides an equipment design quality management system, comprising: an information acquisition module for acquiring project information of a design project; a potential risk list generation module for matching according to the project information, obtaining historical design quality problems corresponding to the design project, and generating a potential risk list of the design project according to each historical design quality problem; an allocation module for sending potential risk information in the potential risk list to a designer corresponding to the potential risk information according to the project information; a quality detection module for detecting quality data of the design project according to the potential risk list and a preset period, and judging whether the design project has an occurred design quality problem; an information feedback module configured to, when the design quality problem exists in the design project, perform a disassembled analysis on problem data of the design quality problem in the quality data to obtain a part number, a part name, a problem description, a problem type, and a solution corresponding to the design quality problem; a quality index calculation module configured to generate a quality level evaluation report of the design project in the preset period according to the part number, the part name, the problem description, the problem type, and the solution.

[0007] Optionally, the potential risk list generation module is specifically configured to: perform an analysis on the project information to obtain reference project information of the project information; determine a product major class number and a product classification number of the design project according to the reference project information, and encapsulate the product major class number and the product classification number as an index key; perform a matching search in a preset knowledge base according to the index key to obtain at least one historical design quality problem corresponding to the design project.

[0008] Optionally, the potential risk list generation module is specifically further configured to: generate the potential risk information of the historical design quality problem according to the part number, the part name, the problem description, and the problem type corresponding to each historical design quality problem; generate the potential risk list according to the potential risk information corresponding to the historical design quality problem.

[0009] Optionally, the distribution module is specifically configured to: perform an analysis on the project information to obtain a designer distribution list of the design project; perform an extraction on the designer distribution list to obtain a single machine number and / or a part number responsible for by each designer of the design project; perform a matching between the single machine number and / or the part number and the potential risk information in the potential risk list to obtain a designer corresponding to the potential risk information, and send the potential risk information to the designer.

[0010] Optionally, the quality detection module is specifically configured to: determine associated part data in the quality data of the design project according to each potential risk information in the potential risk list; compare the associated part data with a preset standard parameter according to the preset period to obtain a comparison result; Based on the comparison results, determine whether the data of the associated components is abnormal; If so, it is determined that the design project has a design quality problem in the related components that has already occurred; If not, then it is determined that the design project does not have the aforementioned design quality problem in the related components.

[0011] Optionally, the information feedback module is specifically used for: When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description and problem type corresponding to the design quality problem; Based on the part number, the part name, the problem description, and the problem type, generate the solution to the design quality problem.

[0012] Optionally, the quality index calculation module is specifically used for: Based on the component number, component name, problem description, and problem type, statistics are performed to obtain the frequency of problem occurrence, problem repetition rate, and average problem resolution time in the design project. The risk level of the design quality problem is determined based on the frequency of occurrence of the problem, the recurrence rate of the problem, and the average resolution time of the problem. Based on the risk level of the design quality problem and the solution, a quality level assessment report for the design project within the preset period is generated.

[0013] Optionally, it also includes a knowledge base module, which is used for: When the design quality problem exists in the design project, an index corresponding to the design quality problem is established based on the component number, component name, problem description, problem type, and solution of the design quality problem; The design quality problem data is stored as historical design quality problems in the preset knowledge base according to the index.

[0014] Secondly, the present invention provides a method for quality management of equipment design, comprising: Obtain project information for the design project; Matching the project information yields historical design quality issues corresponding to the design project, and a potential risk list for the design project is generated based on each historical design quality issue. Based on the project information, the potential risk information in the potential risk list will be sent to the designer corresponding to the potential risk information; Based on the potential risk list, the quality data of the design project is checked according to a preset cycle to determine whether there are any design quality problems that have occurred in the design project; When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description, problem type and solution corresponding to the design quality problem; Based on the part number, the part name, the problem description, the problem type, and the solution, a quality level assessment report for the design project within the preset period is generated.

[0015] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is used to implement the equipment design quality management method described above when executing the computer program.

[0016] The equipment design quality management system, method, and electronic equipment of this invention centrally acquire project information for design projects through an information acquisition module, avoiding the inefficient information collection methods previously scattered at the individual or departmental levels, and providing unified and accurate basic data for subsequent management processes. The potential risk list generation module can quickly match historical design quality issues related to the current design project and generate a potential risk list, enabling designers to identify potential risks early in the design process and prepare in advance, reducing time delays caused by quality issues. The allocation module accurately sends potential risk information from the potential risk list to the corresponding designers, ensuring the timeliness and accuracy of information transmission, avoiding communication breakdowns or information omissions that may occur when transmitting problem information through inefficient methods such as email and meeting minutes, and improving the efficiency of designers in handling quality issues. The quality inspection module performs quality inspections on the design project according to a preset cycle, enabling timely detection of design quality issues. Compared to existing technologies where manual verification and checking are impossible and problems can only be exposed in later stages, this significantly advances the discovery time of quality issues, reducing rework and cost increases caused by quality problems in later stages, thereby improving overall quality management efficiency. After identifying design quality issues, the information feedback module can break down and analyze the problem data, obtaining detailed information such as part numbers, part names, problem descriptions, problem types, and solutions. This refined analysis helps to deeply understand the essence of quality problems, providing accurate basis for subsequent improvement measures and avoiding the previous situation of vague descriptions and unclear solutions, thus improving the level of quality management. The quality indicator calculation module generates a quality level assessment report for the design project within a preset period based on the above detailed information, realizing a quantitative assessment of the design project's quality. This allows managers to clearly understand the quality status of the design project, facilitating the development of targeted quality improvement strategies, further improving the level of quality management, and also facilitating quality comparison and evaluation of different design projects. The potential risk list generation module generates a potential risk list based on historical design quality issues. This process is essentially a reuse of knowledge from historical quality issues. New designers can quickly understand problems that occurred in similar projects in the past by reviewing the potential risk list, avoiding repeating mistakes. This solves the problem that new designers often find it difficult to quickly obtain information on historical issues in existing technologies, promoting the rapid reuse of knowledge in the design process of large-scale complex equipment. By identifying potential risks in advance and promptly addressing quality issues, rework and delays during the production, installation, or commissioning phases caused by quality problems were reduced, thereby lowering project costs and ensuring the project could proceed smoothly as planned. This also improved product quality, prevented losses to users due to quality issues, and enhanced the company's competitiveness in the market.

[0017] The information acquisition module of this invention first centrally acquires project information for the design project, providing basic data for subsequent modules and avoiding management inefficiencies caused by scattered information. The potential risk list generation module, based on this project information, matches relevant historical design quality issues and generates a potential risk list. This not only provides designers with clear risk warnings but also promotes the reuse of historical knowledge, solving the problem of new designers struggling to quickly access information on historical issues. The allocation module accurately sends the information in the potential risk list to the corresponding designers, ensuring the timeliness and accuracy of information transmission and avoiding the inefficiency and information omissions of traditional communication methods. The quality inspection module performs quality inspections on the design project according to a preset cycle, enabling timely detection of design quality issues and exposing problems before the production, installation, or commissioning stages, thereby reducing cost increases and project delays caused by quality issues in subsequent stages. Once a quality issue is detected, the information feedback module immediately breaks down and analyzes the issue data to obtain detailed issue information, including part numbers, part names, issue descriptions, issue types, and solutions. This information provides accurate input data for the quality indicator calculation module, enabling it to generate a quality level assessment report for the design project within a preset cycle, achieving quantitative assessment and scientific management of the design project quality.

[0018] This invention, through its interconnected modular design, not only improves the efficiency and level of quality management, but also reduces project costs, ensures project progress and product quality, and solves key problems in existing technologies such as data dispersion, poor information transmission, and insufficient manual verification and checking. It achieves comprehensive optimization of the design quality management of complete sets of metallurgical equipment. Attached Figure Description

[0019] Figure 1 This is a structural block diagram of the equipment design quality management system according to an embodiment of the present invention; Figure 2 This is a flowchart of the equipment design quality management method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0020] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0021] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0022] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0023] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0024] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this application are all authorized by the user or fully authorized by all parties. The collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0025] In the field of metallurgical equipment manufacturing, the design of complete sets of metallurgical equipment has distinctive characteristics. Taking hot strip rolling mills as an example, although the composition of hot strip rolling mill units and the basic structure of individual machines are generally similar, the specific structures and dimensions vary considerably due to the diverse requirements of different users for equipment parameters. This means that the design of complete sets of metallurgical equipment typically adopts a single-piece, small-batch production model with reference drawings, requiring customized design and drawing production based on the specific requirements of the users.

[0026] The quality control of metallurgical complete sets of equipment design differs fundamentally from that of manufacturing. During the design phase, due to numerous constraints, it is difficult to comprehensively and economically identify all potential problems. Unlike some small design projects, metallurgical complete sets of equipment are large-scale, encompassing a wide variety of individual machines, potentially numbering in the hundreds. Each machine is composed of numerous components, possibly reaching hundreds of parts. Each component is further subdivided into tens of thousands of parts. However, the number of personnel involved in the design of typical projects is relatively limited, usually only twenty or thirty people. With such limited human and time resources, designers cannot have the sufficient time and energy for repeated calculations and verifications as in small design projects. Therefore, many design quality problems often only surface in later stages such as production, installation, and commissioning.

[0027] Furthermore, the design cycle for complete sets of metallurgical equipment is relatively long, and the designers of different components may change. This can lead to newly joined designers lacking sufficient understanding of the design experience accumulated in previous projects, especially regarding design quality issues that have already occurred. When facing new projects, the lack of effective reference to past problems can easily lead to the recurrence of similar design quality issues, increasing project costs and potentially affecting project schedule and product quality.

[0028] Currently, in the field of metallurgical complete equipment design, although the importance of using quality issues reported from reference projects to avoid similar problems in new projects has been recognized, a systematic and efficient management approach is lacking. The collection, organization, storage, and utilization of design quality issue data are often scattered and disorganized, hindering effective knowledge sharing and transfer. Designers struggle to quickly access historical quality issue information related to current design tasks, making it difficult to take timely and targeted preventative measures, thus restricting the improvement of design quality.

[0029] To address the problems existing in the aforementioned related technologies, this embodiment provides an equipment design quality management system, method, and electronic device.

[0030] Combination Figure 1 As shown in the figure, an equipment design quality management system provided by an embodiment of the present invention includes: The information acquisition module is used to acquire project information for the design project.

[0031] Specifically, the information acquisition module receives design project information input by designers or project managers through a user-friendly interface. This information includes project name, project number, design parameters, equipment type, user requirements, etc. The module can also automatically import relevant project information from the enterprise's project management system (such as ERP, Enterprise Resource Planning, or PDM, Product Data Management), ensuring the accuracy and completeness of the information.

[0032] For example, project managers can enter the new project number "2024072701" through this interface and upload a document outlining the user's specific parameter requirements for the equipment. The information acquisition module stores this information in the system database, providing basic data support for subsequent modules.

[0033] The potential risk list generation module is used to match the project information to obtain the historical design quality issues corresponding to the design project, and generate a potential risk list for the design project based on each of the historical design quality issues.

[0034] Specifically, after receiving project information from the information acquisition module, the potential risk list generation module first parses the key parameters in the project information, such as equipment type and design parameters. Then, the module queries the system's internal knowledge base module to match historical design projects with similar equipment types and design parameters to the current project.

[0035] For example, if the current project is "rolling equipment," the module will search the knowledge base for all historical design quality issues related to "rolling equipment." For each matched historical design quality issue, the module generates a potential risk record, including the problem description, relevant part numbers, and other information, and then summarizes these records to generate a potential risk list. For example, if a "roll interference with the mill frame" issue exists in a historical project, the module will add this issue as a potential risk to the list.

[0036] The allocation module is used to send the potential risk information in the potential risk list to the designer corresponding to the potential risk information, based on the project information.

[0037] Specifically, the allocation module accurately assigns the potential risk information in the potential risk list to the corresponding designers based on the designer assignment information in the project information provided by the information acquisition module.

[0038] For example, if the project information specifies that designer A is responsible for the design of the "roll" section, the allocation module will assign potential risks related to "roll" (such as "roll interference with the mill frame") from the potential risk list to designer A. This allocation can be achieved through the system's internal message notification mechanism or by sending the potential risk list to the designer via email, ensuring that the designer receives and processes this potential risk information promptly.

[0039] The quality inspection module is used to inspect the quality data of the design project according to the potential risk list and at a preset cycle to determine whether there are any design quality problems in the design project.

[0040] Specifically, the quality inspection module checks the quality data of the design project according to the potential risk information in the potential risk list, following a preset cycle (such as weekly or bi-weekly). This module automatically acquires design drawings and related data through an interface with design software (such as a CAD system).

[0041] For example, regarding the potential risk of "interference between the rolls and the mill frame," the module will detect the dimensional and positional relationship between the rolls and the mill frame in the current design drawings to determine if an interference problem exists. If a problem listed in the potential risk list is detected in the actual design (such as actual interference between the rolls and the mill frame), the module will record the specific circumstances of the problem and send the relevant information to the information feedback module.

[0042] The information feedback module is used to decompose and analyze the problem data of the design quality problem in the quality data when the design quality problem exists in the design project, and obtain the part number, part name, problem description, problem type and solution corresponding to the design quality problem.

[0043] Specifically, when the quality inspection module detects a design quality issue in a design project, the information feedback module receives the issue data sent by the quality inspection module. This module then breaks down and analyzes the issue data, extracting detailed information such as the corresponding part number, part name, issue description, issue type, and solution.

[0044] For example, for a detected problem of "interference between the roll and the mill frame," the information feedback module will analyze the part number as "2407270101," the part name as "roll," the problem description as "interference exists between the roll and the mill frame in the installation position," the problem type as "interference," and the solution as "adjust the roll installation position or modify the mill frame dimensions." This detailed information will be stored in the system and displayed to the designers through the user interface, allowing them to understand the problem promptly and take appropriate measures.

[0045] The quality index calculation module is used to generate a quality level assessment report of the design project within the preset period based on the part number, the part name, the problem description, the problem type, and the solution.

[0046] Specifically, the quality indicator calculation module generates a quality level assessment report for the design project within a preset period on a regular basis (e.g., monthly or quarterly) based on detailed information provided by the information feedback module, such as part number, part name, problem description, problem type, and solution. This module statistically analyzes indicators such as the number of design quality problems found within this period, the distribution of problem types, and the recurrence rate.

[0047] For example, the statistics show that the "interference" problem occurred 5 times and the "design selection error" problem occurred 3 times in this quarter. The module also calculates the recurrence rate of each problem type. If the recurrence rate of the "interference" problem exceeds a set threshold (e.g., 20%), it is marked as a high-risk type in the report. The final evaluation report will be presented in the form of charts and tables, intuitively reflecting the quality status of the design project, and will be sent to project managers and the design team so that they can take corresponding improvement measures based on the report's content.

[0048] In a preferred embodiment of the present invention, in a new rolling equipment upgrade project, the project leader first imports the reference project number "251111" through the information acquisition module. The system automatically parses the third and fourth "1" digits of the part number to determine the product category and classification number, and accordingly matches several historical design quality issues such as interference of the width-fixing mill cover plate in the knowledge base. The potential risk list generation module encapsulates each problem record into a form containing the part number "25111100101000001", the part name "cover plate", the problem description, and the solution "adjust the cover plate size to increase the gap". The structured potential risk information of the problem type "interference" is clustered using the 7th-9th digits of the single-machine number "001" as the key. The allocation module then pushes the corresponding risk information to the designer responsible for the fixed-width machine according to the designer's allocation list. After receiving the potential risk list, the designer uses the quality inspection module to check the current design data weekly. If insufficient cover plate gap is found, the new problem record is then broken down into the same five-field format and written into the knowledge base through the information feedback module. The quality index calculation module finds that the repetition rate of "design selection error" exceeds 20% every quarter, and automatically highlights it in the quality level assessment report.

[0049] The equipment design quality management system in this embodiment centrally acquires project information for design projects through an information acquisition module, avoiding the inefficient information collection methods previously scattered at the individual or departmental levels. This provides unified and accurate basic data for subsequent management processes. The potential risk list generation module can quickly match historical design quality issues related to the current design project and generate a potential risk list. This allows designers to identify potential risks early in the design process, prepare in advance, and reduce time delays caused by quality issues. The allocation module accurately sends potential risk information from the potential risk list to the corresponding designers, ensuring timely and accurate information transmission. This avoids communication breakdowns or information omissions that may occur when transmitting problem information through inefficient methods such as email and meeting minutes, improving the efficiency of designers in handling quality issues. The quality inspection module performs quality inspections on design projects according to a preset cycle, enabling timely detection of design quality issues. Compared to existing technologies where manual verification and checks are impossible and problems are only exposed in later stages, this significantly advances the discovery time of quality issues, reducing rework and cost increases caused by quality problems in later stages, thereby improving overall quality management efficiency. After identifying design quality issues, the information feedback module can break down and analyze the problem data, obtaining detailed information such as part numbers, part names, problem descriptions, problem types, and solutions. This refined analysis helps to deeply understand the essence of quality problems, providing accurate basis for subsequent improvement measures and avoiding the previous situation of vague descriptions and unclear solutions, thus improving the level of quality management. The quality indicator calculation module generates a quality level assessment report for the design project within a preset period based on the above detailed information, realizing a quantitative assessment of the design project's quality. This allows managers to clearly understand the quality status of the design project, facilitating the development of targeted quality improvement strategies, further improving the level of quality management, and also facilitating quality comparison and evaluation of different design projects. The potential risk list generation module generates a potential risk list based on historical design quality issues. This process is essentially a reuse of knowledge from historical quality issues. New designers can quickly understand problems that occurred in similar projects in the past by reviewing the potential risk list, avoiding repeating mistakes. This solves the problem that new designers often find it difficult to quickly obtain information on historical issues in existing technologies, promoting the rapid reuse of knowledge in the design process of large-scale complex equipment. By identifying potential risks in advance and promptly addressing quality issues, rework and delays during the production, installation, or commissioning phases caused by quality problems were reduced, thereby lowering project costs and ensuring the project could proceed smoothly as planned. This also improved product quality, prevented losses to users due to quality issues, and enhanced the company's competitiveness in the market.

[0050] The information acquisition module in this embodiment first centrally acquires project information for the design project, providing foundational data for subsequent modules and avoiding management inefficiencies caused by fragmented information. The potential risk list generation module, based on this project information, matches relevant historical design quality issues and generates a potential risk list. This not only provides designers with clear risk warnings but also promotes the reuse of historical knowledge, solving the problem of new designers struggling to quickly access information on historical issues. The allocation module accurately sends the information in the potential risk list to the corresponding designers, ensuring timely and accurate information transmission and avoiding the inefficiencies and information omissions of traditional communication methods. The quality inspection module performs quality inspections on the design project according to a preset cycle, enabling timely detection of design quality issues and exposing problems before the production, installation, or commissioning stages, thereby reducing cost increases and project delays caused by quality problems in subsequent stages. Once a quality problem is detected, the information feedback module immediately breaks down and analyzes the problem data to obtain detailed problem information, including part numbers, part names, problem descriptions, problem types, and solutions. This information provides accurate input data for the quality indicator calculation module, enabling it to generate a quality level assessment report for the design project within a preset cycle, achieving quantitative assessment and scientific management of the design project quality.

[0051] Through this interconnected modular design, this embodiment not only improves the efficiency of quality management but also enhances the level of quality management, reduces project costs, ensures project progress and product quality, and solves key problems in existing technologies such as scattered design quality data, poor information transmission, and insufficient manual verification and checking, thus achieving comprehensive optimization of the design quality management of complete sets of metallurgical equipment.

[0052] Optionally, the potential risk list generation module is specifically used for: The project information is parsed to obtain reference project information. Based on the reference project information, determine the product category number and product classification number of the design project, and encapsulate the product category number and the product classification number into an index key; Based on the index key, a matching search is performed in the preset knowledge base to obtain at least one of the historical design quality issues corresponding to the design project.

[0053] Specifically, the potential risk list generation module first receives project information from the information acquisition module. This information includes basic project parameters (such as project name, number, equipment type, etc.) and reference project information. Reference project information refers to historical project information similar to the current design project. This information helps the system identify potential risks related to the current project. For example, if the current project is a "rolling equipment upgrade project," the reference project information might be "previous similar rolling equipment projects."

[0054] The module parses reference project information, extracting the product category number and product classification number. These numbers are generated according to preset coding rules and are used to identify the product category and specific classification to which the project belongs. For example, product category number "1" might represent rolling mill equipment, and classification number "1" might represent hot rolling mill equipment. These two numbers are encapsulated as index keys, such as "1_1," for quick searching in the knowledge base. The module uses the encapsulated index keys to search the preset knowledge base. The knowledge base stores design quality problem data from historical design projects, indexed by product category number and classification number. For example, when the index key is "1_1," the knowledge base will return all historical design quality problems related to hot rolling mill equipment under the category of rolling mill equipment. These historical problems include detailed information such as problem descriptions, part numbers, and solutions, used to generate a potential risk list for the current design project.

[0055] For example, the part number consists of 11 or 16 digits, and the coding rules include: The first two digits represent the project year; the third digit represents the product category number; the fourth digit represents the product classification number; the fifth digit represents the ordering method; the sixth digit represents the annual contract sequence number; the seventh to ninth digits represent the unit number; the tenth to eleventh digits represent the component number; and the twelfth to sixteenth digits represent the part number. The workflow of the potential risk list generation module includes: parsing reference project information and matching historical issues with the same product category number and classification number in the knowledge base; and assigning issues to the corresponding designers based on the division of labor in the equipment list, either by unit number (digits 7–9) or component number (digits 10–11). The metallurgical complete equipment design quality information management system also includes a quality index calculation module, used to periodically count the number of design quality issues in the knowledge base, generate quality level assessment reports by issue type, product category number, and time period, and mark high-risk types with a recurrence rate exceeding a threshold.

[0056] In this optional embodiment, by parsing the project information to obtain reference project information, the product category number and product classification number of the design project are determined and encapsulated as index keys. A matching search is then performed in a preset knowledge base, which can accurately identify at least one historical design quality issue related to the current design project. This index key-based matching search method ensures the accuracy of search results, avoids the omission of potential risks due to inaccurate information, provides designers with targeted risk warnings, and helps to take preventative measures in advance to reduce the recurrence of problems.

[0057] This module avoids a comprehensive search of all historical design quality issues. Instead, it directly locates issues relevant to the current project using an index key, significantly reducing the computational overhead of data processing. This makes the risk identification process more efficient, saving time and computing resources, improving the overall operational efficiency of the design quality management system, facilitating the rapid generation of potential risk lists, providing timely risk information to designers, and ensuring the smooth progress of design work. The potential risk list generation module of this invention can also accurately identify historical design quality issues related to the characteristics of different design projects. This helps designers to manage potential risks in a refined manner, developing corresponding prevention and response strategies based on the characteristics and severity of different issues, thereby significantly improving the risk management level of design projects, enhancing design quality, reducing project costs, and ensuring project progress and product quality.

[0058] Optionally, the potential risk list generation module is further configured to: Based on the component number, component name, problem description, and problem type corresponding to each historical design quality problem, generate the potential risk information of the historical design quality problem; Based on the potential risk information corresponding to the historical design quality issues, the potential risk list is generated.

[0059] Specifically, after extracting historical design quality issues matching the current design project from the knowledge base, the module analyzes each historical issue in detail, including the component number, component name, problem description, and problem type. For example, if the matched historical issue is "interference between the roll and the mill frame," the module will extract the component number (e.g., "2407270101"), component name (e.g., "roll"), problem description (e.g., "interference exists between the roll and the mill frame in the installation position"), and problem type (e.g., "interference"). Based on this detailed information, the module generates potential risk information corresponding to the historical issue, including a description of the potential risk (e.g., "risk of interference between the roll and the mill frame"), the component numbers and names that may be affected, and the problem type to which the risk belongs. All extracted and generated potential risk information is summarized to form a potential risk list. This list details all potential risks related to the current design project, including a description, component number, component name, and problem type for each potential risk. For example, the potential risk list might include the following: Potential Risk 1: Part number "2407270101", part name "roll", potential risk description "there is a risk of interference between the roll and the mill frame", problem type "interference".

[0060] Potential Risk 2: Part number "2407270201", part name "rolling mill frame", potential risk description "the size of the rolling mill frame may not match the rolls", problem type "design interface error".

[0061] The generated list of potential risks will be organized in a specific format (such as a table) so that designers can clearly view and understand the details of each potential risk. This list will serve as an important basis for the subsequent allocation module to send potential risk information to the corresponding designers, ensuring that designers are aware of and pay attention to these potential risks in advance, and thus take appropriate preventive measures during the design process to avoid similar problems from recurring.

[0062] In this optional embodiment, by transforming historical design quality issues into specific potential risk information, the module can provide designers with clear and detailed risk warnings. Designers can clearly understand the specific details of each potential risk, including part number, part name, problem description, and problem type. This clear warning enables designers to take targeted preventative measures during the design phase to avoid similar problems from recurring, thereby significantly improving design quality.

[0063] The generation of a potential risk list provides designers with a comprehensive overview of risks. Designers can quickly understand all potential risks associated with the current design project without having to sift through large amounts of historical data themselves. This not only saves time and effort but also improves design efficiency, allowing designers to focus more on the design task itself rather than spending a significant amount of time on risk identification.

[0064] By transforming historical design quality issues into potential risk information and generating a list, the module enables effective knowledge sharing and transfer. New designers can quickly understand problems encountered in previous projects by reviewing the potential risk list, avoiding repeating mistakes due to lack of experience. This knowledge-sharing mechanism helps improve the overall level of the design team, especially for the design of large-scale, complex equipment, significantly reducing the risks associated with personnel changes.

[0065] The potential risk list generation module not only identifies potential risks but also supports refined risk management through detailed information such as part numbers, part names, problem descriptions, and problem types. Designers can use this information to develop targeted preventative measures, such as adjusting design parameters, optimizing design structures, or adding verification steps. This refined management helps reduce the incidence of design quality issues and improves design reliability.

[0066] By identifying and preventing potential design problems in advance, the module effectively reduces errors during the design phase, preventing these issues from surfacing during production, installation, or commissioning. This not only reduces additional costs associated with rework and corrections but also mitigates the risk of project delays, ensuring project schedule and product quality. In the long term, this preventative mechanism can significantly reduce overall project costs and improve the company's economic efficiency. The generated list of potential risks is presented in a clear format (such as tables), facilitating quick review and understanding by designers. This user-friendly design makes the system more practical, better meeting the actual needs of designers and increasing system acceptance and usage frequency.

[0067] Optionally, the allocation module is specifically used for: The project information is parsed to obtain the list of designers assigned to the design project; Extract the designer assignment list to obtain the unit number and / or component number that each designer is responsible for in the design project; The unit number and / or the component number are matched with the potential risk information in the potential risk list to obtain the designer corresponding to the potential risk information, and the potential risk information is sent to the designer.

[0068] Specifically, the allocation module first receives project information from the information acquisition module. This project information includes a designer allocation list, which details the responsibilities of each designer in the current design project. For example, the project information might contain a table listing designer A as responsible for the design of the "roll" section, designer B as responsible for the design of the "mill frame" section, and so on. By parsing this information, the allocation module extracts a complete designer allocation list, providing a basis for subsequent allocation of potential risk information.

[0069] After extracting the designer assignment list, the assignment module further parses the list to obtain the specific unit number and / or part number for each designer. For example, designer A is responsible for the design work of part number "01" (rack) under unit number "001" (fixed width machine). The assignment module extracts this information and stores it in a temporary data structure for subsequent matching operations. For example, the module will record that designer A is responsible for unit number "001" and part number "01".

[0070] The allocation module matches the extracted unit number and / or part number with the potential risk information in the potential risk list. The potential risk list contains information such as the part number, part name, and problem description for each potential risk.

[0071] For example, the potential risk list contains a record with part number "2407270101", part name "roll", and potential risk description "risk of interference between the roll and the mill frame". The allocation module checks the unit number and component number corresponding to this part number (e.g., unit number "001", component number "01") and compares it with the information in the designer's allocation list. If it is found that designer A is responsible for component number "01" under unit number "001", then the potential risk information is assigned to designer A.

[0072] After matching is complete, the allocation module will send potential risk information to the corresponding designer via internal system notification mechanisms or email. For example, the system might send a message to designer A stating: "There is a potential risk in the frame (part number 01) of the width-fixing mill (unit number 001) you are responsible for: the rolls may interfere with the mill frame. Please check the design drawings and take appropriate measures." This method ensures that designers receive timely information about potential risks related to their assigned parts, allowing them to take preventative measures in advance and avoid problems.

[0073] In this optional embodiment, the allocation module parses the project information, extracts the designer allocation list, and accurately matches potential risk information to the corresponding designers. This precise allocation mechanism avoids the problem in traditional methods where inaccurate information transmission prevents designers from obtaining relevant risk information in a timely manner. For example, if designer A is responsible for the design of the "roll" section, the allocation module can directly send potential risks related to the "roll" (such as "interference between the roll and the mill frame") to designer A, ensuring that he can understand and handle related issues in a timely manner.

[0074] Through an automated allocation mechanism, designers no longer need to spend significant time sifting through massive amounts of historical data to find potential risks relevant to their assigned areas. The allocation module directly pushes potential risk information to designers, enabling them to quickly focus on the issues they need to address, thereby improving work efficiency and reducing the additional workload associated with information retrieval and filtering. The allocation module not only ensures the accurate transmission of potential risk information but also promotes collaboration within the design team. Designers can promptly access potential risk information relevant to their assigned areas, facilitating better communication and collaboration with other designers. For example, designer A, when addressing the potential risk of "roll interference with the mill frame," may need to communicate with designer B, responsible for the "mill frame," to jointly resolve the issue. This collaborative mechanism helps improve the overall efficiency and design quality of the design team. By accurately matching potential risk information, designers are ensured to understand potential risks related to their assigned areas in advance and take targeted preventative measures. This not only reduces errors in the design phase but also prevents similar problems from recurring in subsequent projects. For example, by identifying potential risks of "roll interference with the mill frame" in advance, designers can adjust design parameters or optimize the design structure to avoid this problem from surfacing in actual production. For large-scale, complex equipment design projects, the allocation module can effectively manage a large amount of potential risk information and ensure that this information is accurately transmitted to the corresponding designers. This mechanism not only improves the efficiency of design management but also enhances the design team's control over complex equipment design projects, contributing to improved quality and reliability throughout the design process.

[0075] Optionally, the quality inspection module is specifically used for: Based on each potential risk in the potential risk list, determine the associated component data in the quality data of the design project; According to the preset cycle, the data of the associated components are compared with the preset standard parameters to obtain the comparison results; Based on the comparison results, determine whether the data of the associated components is abnormal; If so, it is determined that the design project has a design quality problem in the related components that has already occurred; If not, then it is determined that the design project does not have the aforementioned design quality problem in the related components.

[0076] Specifically, the quality inspection module first receives a list of potential risks, which includes information for each potential risk, such as part number, part name, and problem description. The module analyzes this information to determine the component data associated with each potential risk. For example, if the potential risk information mentions "interference between the roll and the mill frame," the module extracts component data related to the "roll" and "mill frame" from the design project's quality data, including dimensions, location, and material properties. The quality inspection module inspects the extracted associated component data at a preset time interval (e.g., weekly or bi-weekly). The module compares this data with preset standard parameters. These standard parameters are pre-set based on design specifications and historical experience to determine whether the component data meets design requirements. For example, for the "roll and mill frame" interference problem, the standard parameters might include the minimum clearance requirement between them. The module calculates the clearance between the roll and the mill frame in the actual design and compares it with the standard parameters to obtain the comparison result.

[0077] The module determines whether the data of related components is abnormal based on the comparison results. If the actual data deviates from the standard parameters, and the deviation exceeds the allowable range, it is judged as abnormal. For example, if the standard parameters require a minimum gap of 10mm between the roll and the mill frame, but the actual design gap is 5mm, it is judged as abnormal. The module records the specific details of the abnormality, including the name of the abnormal component, the type of abnormality (such as dimensional deviation, positional deviation, etc.), and the deviation value.

[0078] If the data of a related component is deemed abnormal, the quality inspection module will further determine if there are design quality issues with the related component in the design project. For example, if the gap between the roll and the mill frame is abnormal, the design project is determined to have a "roll-mill frame interference" design quality issue. The module will record detailed information about the problem, including the problem description, relevant part numbers, and problem type, and send this information to the information feedback module for subsequent problem analysis and processing.

[0079] If no anomalies are found after comparing the data of the associated components with the standard parameters, the quality inspection module will determine that the design project does not have any design quality issues with the associated components that have occurred. For example, if the gap between the roll and the mill frame meets the standard parameter requirements, it will be determined that the design project does not have a design quality issue of "roll and mill frame interference" within the current inspection cycle. The module will record this inspection result and continue to perform subsequent inspections according to the preset cycle.

[0080] In this optional embodiment, the quality inspection module can promptly identify design quality issues that have occurred in the design project by periodically comparing the data of related components with preset standard parameters. This automated inspection mechanism avoids the subjectivity and untimeliness of manual inspection, ensuring that design problems can be detected at an early stage, thereby reducing the risk of problems surfacing in subsequent production, installation, or commissioning stages. For example, by detecting the problem of "interference between the roll and the mill frame" in advance, difficulties in equipment installation or operational failures caused by interference can be avoided, reducing project costs and delay risks. Furthermore, it operates automatically according to a preset cycle without manual intervention, greatly improving inspection efficiency. Simultaneously, through precise comparison with preset standard parameters, the module can accurately determine whether the data of related components is abnormal, reducing misjudgments caused by human negligence or lack of experience. This highly efficient and accurate inspection mechanism ensures the stability and reliability of design quality, contributing to improved overall design management.

[0081] The quality inspection module not only identifies quality issues in design projects but also records detailed information about each problem, including part number, part name, problem description, and problem type. This refined inspection result provides designers with clear directions for improvement, facilitating the development of targeted solutions and enabling sophisticated quality management. For example, the module can record the specific numerical deviation of "insufficient clearance between the roll and the mill frame," providing designers with accurate adjustment guidelines. By promptly identifying and recording design quality issues, the quality inspection module provides data support for continuous design quality improvement. Designers can analyze the causes of problems based on the detailed information provided by the module, take corrective measures, and prevent similar problems from recurring in subsequent projects. This data-driven continuous improvement mechanism helps to gradually improve design quality, reduce recurring problems, and enhance the company's design capabilities and market competitiveness.

[0082] By identifying and resolving quality issues promptly during the design phase, the quality inspection module effectively reduces production delays, rework, and equipment failures caused by design errors, thereby lowering project costs and risks. For example, early detection and resolution of "roll interference with the mill frame" can prevent schedule delays and additional costs due to equipment installation difficulties, ensuring the smooth progress of the project. The automated inspection mechanism of the quality inspection module reduces manual intervention and improves the system's intelligence level. The module can automatically extract data from related components, compare it with standard parameters, and generate inspection results. This automated process not only improves work efficiency but also reduces human error, enhancing the overall performance of the system.

[0083] Optionally, the information feedback module is specifically used for: When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description and problem type corresponding to the design quality problem; Based on the part number, the part name, the problem description, and the problem type, generate the solution to the design quality problem.

[0084] Specifically, when the quality inspection module determines that there is a design quality problem in the design project, the information feedback module will receive the problem data sent by the quality inspection module. The module first breaks down and analyzes the problem data to extract key information about the design quality problem, including part number, part name, problem description, and problem type.

[0085] For example, if the quality inspection module detects a problem of "interference between the roll and the mill frame", the information feedback module will extract the following information from the problem data: Part number: 2407270101 (roll); Component name: Roll; Problem description: There is interference between the rolling mill rolls and the mill frame in their installation positions; Problem type: Interference.

[0086] The information feedback module generates a solution for the design quality issue based on the extracted part number, part name, problem description, and problem type. The module combines historical data and a pre-set solution strategy library to provide specific solutions. For example, for the problem of "interference between the roll and the mill frame," the module might generate the following solution: move the roll's installation position back 5 mm to ensure the minimum clearance with the mill frame meets design requirements. Appropriately increase the size of the mill frame to ensure the roll can be installed smoothly and without interference during operation. The generated solution will detail the operating steps and precautions to ensure designers can clearly understand and implement them. For example, the solution may include specific dimensional adjustment values, revised design drawing reference numbers, and related verification steps.

[0087] In this optional embodiment, the information feedback module can extract detailed error information by breaking down and analyzing design quality issues in the quality data, including part numbers, part names, problem descriptions, and problem types. This detailed error analysis provides designers with a clear location of the problem, enabling them to quickly understand its specific content and root cause. For example, the module can explicitly indicate that "there is interference between the roll and the mill frame in the installation position" and provide specific part numbers and names, helping designers quickly focus on the problem.

[0088] The information feedback module not only provides a detailed description of the problem but also generates targeted solutions. These solutions combine historical data with a pre-set solution strategy library, providing designers with clear operational guidance. For example, for the problem of "roll interference with the mill frame," the module can suggest "adjusting the roll's installation position by moving it back 5 mm" or "appropriately increasing the size of the mill frame." This targeted approach reduces the amount of trial and error required by designers during problem-solving, improving efficiency.

[0089] Through automated error analysis and solution generation, the feedback module significantly reduces the workload of designers. Designers no longer need to spend excessive time on problem localization and solution searching; instead, they can directly adjust and improve based on the information provided by the module. This automation improves designer efficiency, allowing them to focus more on the design task itself rather than being bogged down in problem-solving. The automated processing mechanism of the feedback module ensures that design quality issues are detected and resolved promptly, reducing errors caused by human negligence or lack of experience. By providing detailed error information and targeted solutions, the module helps designers avoid the recurrence of similar problems, thereby improving the stability and reliability of design quality. For example, by identifying and resolving the "roll and mill frame interference" problem early, installation difficulties or operational failures caused by interference can be avoided, improving the overall performance of the equipment. The detailed error information and solutions generated by the feedback module can be stored in the system for other designers to reference. This knowledge-sharing mechanism helps new designers quickly understand and learn how to handle similar problems, avoiding knowledge gaps caused by personnel changes. For example, new designers can learn how to handle problems such as "roll and mill frame interference" by reviewing historical issues and their solutions, thereby improving the overall level of the design team. The information feedback module's detailed error analysis and targeted solutions support refined quality management. Designers can use the information provided by the module to conduct in-depth analysis of design problems and formulate more effective improvement measures. For example, the module can record the specific numerical deviation of "insufficient clearance between the roll and the mill frame," providing designers with accurate adjustment basis, thereby achieving refined quality management.

[0090] Optionally, the quality index calculation module is specifically used for: Based on the component number, component name, problem description, and problem type, statistics are performed to obtain the frequency of problem occurrence, problem repetition rate, and average problem resolution time in the design project. The risk level of the design quality problem is determined based on the frequency of occurrence of the problem, the recurrence rate of the problem, and the average resolution time of the problem. Based on the risk level of the design quality problem and the solution, a quality level assessment report for the design project within the preset period is generated.

[0091] Specifically, the quality indicator calculation module first obtains all design quality issue data from the information feedback module, including part numbers, part names, problem descriptions, problem types, and solutions. The module then categorizes and statistically analyzes this data, calculating the frequency of occurrence, recurrence rate, and average resolution time for each problem. For example: Problem frequency: This counts the number of times each problem type occurs within a preset period. For example, the problem of "interference between the roll and the mill frame" occurred 5 times in one quarter.

[0092] Problem recurrence rate: Calculates the recurrence rate of each problem type within a preset period. For example, the recurrence rate of the "roll interference with mill frame" problem among all design quality problems is 20%.

[0093] Average problem resolution time: This is the average time from discovery to resolution for each problem type. For example, the average resolution time for the problem of "interference between the roll and the mill frame" is 3 days.

[0094] The quality indicator calculation module determines the risk level of each design quality issue based on statistically obtained data such as the frequency of occurrence, recurrence rate, and average resolution time. The module sets a series of risk assessment criteria, for example: High risk: The problem occurs frequently (e.g., more than 10 times / quarter), the problem recurrence rate is high (e.g., more than 20%), and the average resolution time is long (e.g., more than 5 days).

[0095] Medium risk: The frequency of problems is moderate (e.g., 5-10 times / quarter), the recurrence rate of problems is moderate (e.g., 10%-20%), and the average resolution time is moderate (e.g., 3-5 days).

[0096] Low risk: The frequency of problems is low (e.g., less than 5 times / quarter), the recurrence rate of problems is low (e.g., less than 10%), and the average resolution time is short (e.g., less than 3 days).

[0097] For example, if the problem of "interference between the roll and the mill frame" occurs 5 times within a preset period, with a recurrence rate of 20% and an average resolution time of 3 days, then the problem is assessed as medium risk.

[0098] Specifically, the quality indicator calculation module generates a quality level assessment report for the design project within a preset period, based on the risk level and solutions to design quality issues. The report includes: Problem Overview: Lists all design quality issues discovered within the preset period, including problem type, frequency of occurrence, recurrence rate, and average resolution time.

[0099] Risk assessment: Mark the risk level of each issue, highlighting high-risk issues.

[0100] Solutions: Provide solutions for each problem, including specific operational steps and suggestions.

[0101] Improvement Recommendations: Based on the statistical results of the problems, propose suggestions for improving the design process and quality control measures. For example, for high-risk problems, it is recommended to add a design review step or optimize design parameters. The report will be presented visually in the form of charts and tables, allowing management and designers to quickly understand the overall quality status of the design project. For example, the report may include bar charts to show the frequency of different problem types, line graphs to show the trend of problem recurrence rates, and tables listing detailed information and solutions for each problem.

[0102] In a preferred embodiment of the invention, during project execution, the quality indicator calculation module periodically (e.g., quarterly) extracts design quality issue data from the knowledge base. Statistics reveal that design selection errors under the rolling equipment category occurred multiple times within the quarter, with a recurrence rate exceeding a set threshold (20%), thus marking it as a high-risk type. A quality level assessment report is generated based on the statistical results. The report uses a bar chart to display the total number of quality issues for different product categories in the quarter and a line graph to show the trend of design selection errors over different time periods, highlighting design selection errors as a high-risk type. The report is sent to management and relevant designers, who then decide to organize a special meeting to conduct an in-depth analysis of the design selection errors and implement improvement measures, such as strengthening the design selection review process and improving designers' selection capabilities.

[0103] In this optional embodiment, the quality indicator calculation module can quantitatively analyze design quality issues by statistically analyzing the frequency of occurrence, recurrence rate, and average resolution time of problems. This quantitative method makes design quality issues no longer vague but presented in concrete data form, facilitating management and designers to intuitively understand the quality status of design projects. For example, statistics show that the problem of "interference between the roll and the mill frame" occurred 5 times in a quarter, with a recurrence rate of 20% and an average resolution time of 3 days. These data provide a clear basis for subsequent quality improvements.

[0104] The quality indicator calculation module accurately assesses the risk level of each design quality issue based on quantified data and pre-defined risk assessment standards. This assessment method considers not only the frequency and recurrence rate of the problem but also the average resolution time, making the risk assessment more comprehensive and accurate. For example, a problem with high frequency, high recurrence rate, and long resolution time will be assessed as high risk, while a problem with low frequency, low recurrence rate, and short resolution time will be assessed as low risk. This precise risk assessment helps management and designers quickly identify and address high-risk issues, prioritizing improvement measures.

[0105] The quality indicator calculation module generates a quality level assessment report that not only displays quantitative data and risk levels of the problem but also provides targeted improvement suggestions. These suggestions, based on the specific circumstances of the problem and incorporating historical data and a solution library, offer clear operational guidance to designers. For example, for the high-risk problem of "roll interference with the mill frame," the report might recommend adding a design review process or optimizing design parameters to reduce the recurrence of similar problems. This targeted improvement advice helps designers quickly take effective measures to improve design quality.

[0106] By generating detailed quality level assessment reports, the quality indicator calculation module provides data support for management, enabling more scientific and rational decision-making. Management can use the data and recommendations in the report to develop targeted quality improvement plans, optimize design processes, and enhance overall design management. For example, management can adjust the division of labor within the design team, add quality control steps, or conduct specialized training based on high-risk issues reported in the report, thereby improving the skills of designers. The automated statistical and evaluation mechanism of the quality indicator calculation module ensures that design quality problems are identified and recorded in a timely manner, providing strong support for continuous improvement of design quality. Designers can analyze the causes of problems, take corrective measures, and avoid recurring similar problems in subsequent projects based on the detailed data and improvement suggestions provided by the module. This data-driven continuous improvement mechanism helps to gradually improve design quality, reduce the occurrence of recurring problems, and enhance the company's design level and market competitiveness. The implementation of the quality indicator calculation module is simple, clear, and easy to operate. Designers and management can intuitively view the quality level assessment reports through the system interface. This user-friendly design makes the system more practical, better meets user needs, and increases system acceptance and usage frequency.

[0107] Optionally, it also includes a knowledge base module, which is used for: When the design quality problem exists in the design project, an index corresponding to the design quality problem is established based on the component number, component name, problem description, problem type, and solution of the design quality problem; The design quality problem data is stored as historical design quality problems in the preset knowledge base according to the index.

[0108] Specifically, when the information feedback module detects a design quality issue in a design project, the knowledge base module receives relevant information, including part number, part name, problem description, problem type, and solution. The module first establishes a unique index based on this information to quickly retrieve and manage design quality issue data.

[0109] For example, an index can be composed of a part number and a problem type, in the format "part number_problem type". Suppose a design quality problem involves a roll with part number "2407270101" and a problem type of "interference", then the index can be represented as "2407270101_interference".

[0110] The knowledge base module stores detailed data on design quality issues into a pre-defined knowledge base based on the established index. The knowledge base is a structured database used to store and manage historical design quality issues. Each record for a design quality issue includes information such as part number, part name, problem description, problem type, solution, and a timestamp of the problem's occurrence.

[0111] For example, regarding the issue of "interference between the rolls and the mill frame" mentioned above, the knowledge base module would create a record with the following content: Index: 2407270101_Interference; Part number: 2407270101; Component name: Roll; Problem description: There is interference between the rolling mill rolls and the mill frame in their installation positions; Problem type: Interference; Solution: Adjust the installation position of the rolls and move them back 5 mm; Timestamp: 2024-07-27 10:00:00.

[0112] In this way, the knowledge base module can efficiently store and manage design quality issue data, ensuring data integrity and retrievability. The stored data can then be used for subsequent stages such as generating potential risk lists, problem analysis, and quality assessment.

[0113] The knowledge base module supports rapid retrieval and reuse of historical design quality issues through indexing. When the potential risk list generation module needs to query historical issues related to a new project, it can quickly locate the relevant records through the index. For example, when a new project involves the same part number and issue type, the module can directly find detailed information about the previously stored "roll and mill frame interference" issue through the index "2407270101_interference," including the issue description and solution. This rapid retrieval mechanism not only improves the system's operational efficiency but also promotes knowledge accumulation and reuse, reduces repetitive work, and improves design quality.

[0114] In this optional embodiment, the knowledge base module stores detailed data on design quality issues (including part numbers, part names, problem descriptions, problem types, solutions, etc.) in a pre-defined knowledge base by creating an index. This structured storage method not only ensures the integrity and accuracy of the data but also facilitates subsequent rapid retrieval and management. For example, by indexing "part number_problem type," design quality issues related to a specific part can be quickly located, improving the efficiency of data management.

[0115] The knowledge base module stores historical design quality issues that can be reused multiple times. When a new project starts, the potential risk list generation module can quickly retrieve past issues related to the new project through an index, thereby generating a potential risk list. This knowledge reuse mechanism avoids designers repeatedly solving the same or similar problems, reducing repetitive work and improving design efficiency. For example, if the problem of "roll interference with the mill frame" reappears in a new project, designers can directly refer to the solution in the knowledge base without having to re-analyze and solve it. The indexing mechanism supports rapid retrieval, enabling quick location of historical design quality issues related to the new project. This rapid retrieval capability not only improves the system's operational efficiency but also ensures that the potential risk list generation module can obtain accurate information in a timely manner, providing designers with precise risk warnings. For example, by indexing "2407270101_interference," detailed information on the previously stored "roll interference with the mill frame" problem can be quickly found, including the problem description and solution. By storing and reusing historical design quality issues, the knowledge base module helps designers identify potential risks in advance and avoid repeating mistakes. For example, when designers are working on a new project, they can quickly learn about the problems and solutions that have occurred in similar projects in the past through a knowledge base, so as to take preventive measures during the design phase, reduce design errors and the occurrence of repeated problems, and improve design quality.

[0116] Combination Figure 2 As shown, the present invention provides a method for equipment design quality management, comprising: Obtain project information for the design project; Matching the project information yields historical design quality issues corresponding to the design project, and a potential risk list for the design project is generated based on each historical design quality issue. Based on the project information, the potential risk information in the potential risk list will be sent to the designer corresponding to the potential risk information; Based on the potential risk list, the quality data of the design project is checked according to a preset cycle to determine whether there are any design quality problems that have occurred in the design project; When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description, problem type and solution corresponding to the design quality problem; Based on the part number, the part name, the problem description, the problem type, and the solution, a quality level assessment report for the design project within the preset period is generated.

[0117] The equipment design quality management method of the present invention has the same advantages over the prior art as the equipment design quality management system described above, and will not be repeated here.

[0118] Combination Figure 3 As shown, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is used to implement the equipment design quality management method described above when executing the computer program.

[0119] The electronic device of the present invention has the same advantages over the prior art as the aforementioned equipment design quality management system, and will not be repeated here.

[0120] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. An equipment design quality management system, characterized in that, include: The information acquisition module is used to acquire project information for the design project; The potential risk list generation module is used to match the project information to obtain the historical design quality issues corresponding to the design project, and generate a potential risk list for the design project based on each historical design quality issue. The allocation module is used to send the potential risk information in the potential risk list to the designer corresponding to the potential risk information, based on the project information; The quality inspection module is used to inspect the quality data of the design project according to the potential risk list and at a preset cycle, and to determine whether there are any design quality problems that have occurred in the design project. The information feedback module is used to decompose and analyze the problem data of the design quality problem in the quality data when the design quality problem exists in the design project, and obtain the part number, part name, problem description, problem type and solution corresponding to the design quality problem; The quality index calculation module is used to generate a quality level assessment report of the design project within the preset period based on the part number, the part name, the problem description, the problem type, and the solution.

2. The equipment design quality management system according to claim 1, characterized in that, The potential risk list generation module is specifically used for: The project information is parsed to obtain reference project information. Based on the reference project information, determine the product category number and product classification number of the design project, and encapsulate the product category number and the product classification number into an index key; Based on the index key, a matching search is performed in the preset knowledge base to obtain at least one of the historical design quality issues corresponding to the design project.

3. The equipment design quality management system according to claim 2, characterized in that, The potential risk list generation module is further used for: Based on the component number, component name, problem description, and problem type corresponding to each historical design quality problem, generate the potential risk information of the historical design quality problem; Based on the potential risk information corresponding to the historical design quality issues, the potential risk list is generated.

4. The equipment design quality management system according to claim 1, characterized in that, The allocation module is specifically used for: The project information is parsed to obtain the list of designers assigned to the design project; Extract the designer assignment list to obtain the unit number and / or component number that each designer is responsible for in the design project; The unit number and / or the component number are matched with the potential risk information in the potential risk list to obtain the designer corresponding to the potential risk information, and the potential risk information is sent to the designer.

5. The equipment design quality management system according to claim 1, characterized in that, The quality inspection module is specifically used for: Based on each potential risk in the potential risk list, determine the associated component data in the quality data of the design project; According to the preset cycle, the data of the associated components are compared with the preset standard parameters to obtain the comparison results; Based on the comparison results, determine whether the data of the associated components is abnormal; If so, it is determined that the design project has a design quality problem in the related components that has already occurred; If not, then it is determined that the design project does not have the aforementioned design quality problem in the related components.

6. The equipment design quality management system according to claim 2, characterized in that, The information feedback module is specifically used for: When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description and problem type corresponding to the design quality problem; Based on the part number, the part name, the problem description, and the problem type, generate the solution to the design quality problem.

7. The equipment design quality management system according to claim 1, characterized in that, The quality index calculation module is specifically used for: Based on the component number, component name, problem description, and problem type, statistics are performed to obtain the frequency of problem occurrence, problem repetition rate, and average problem resolution time in the design project. The risk level of the design quality problem is determined based on the frequency of occurrence of the problem, the recurrence rate of the problem, and the average resolution time of the problem. Based on the risk level of the design quality problem and the solution, a quality level assessment report for the design project within the preset period is generated.

8. The equipment design quality management system according to claim 6, characterized in that, It also includes a knowledge base module, which is used for: When the design quality problem exists in the design project, an index corresponding to the design quality problem is established based on the component number, component name, problem description, problem type, and solution of the design quality problem; The design quality problem data is stored as historical design quality problems in the preset knowledge base according to the index.

9. A method for quality management in equipment design, characterized in that, include: Obtain project information for the design project; Matching the project information yields historical design quality issues corresponding to the design project, and a potential risk list for the design project is generated based on each historical design quality issue. Based on the project information, the potential risk information in the potential risk list will be sent to the designer corresponding to the potential risk information; Based on the potential risk list, the quality data of the design project is checked according to a preset cycle to determine whether there are any design quality problems that have occurred in the design project; When the design quality problem exists in the design project, the problem data of the design quality problem in the quality data is decomposed and analyzed to obtain the part number, part name, problem description, problem type and solution corresponding to the design quality problem; Based on the part number, the part name, the problem description, the problem type, and the solution, a quality level assessment report for the design project within the preset period is generated.

10. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to implement the equipment design quality management method as described in claim 9 when executing the computer program.

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