Method for improving product reliability
By installing fixed sensors in mining equipment and using 5G network for real-time reliability analysis, the problem of low reliability in traditional equipment design is solved, real-time monitoring and prediction of fatigue life is achieved, product safety and customer trust are improved. Extends the service life of the equipment and reduces the failure rate.
Patent Information
- Application Number
- CN202411539793.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2024-12-24
AI Technical Summary
The lack of simulation analysis in the design process of traditional mining equipment leads to low product reliability and high manufacturing difficulty, and the company cannot understand the actual situation of the equipment in a timely manner, which affects customer trust and product upgrades, and affects corporate development.
Install fixed sensors in the equipment production, use 5G network to connect to cloud storage and data processing, conduct real-time reliability analysis, optimize design through simulation analysis and customer feedback, monitor fatigue life in real time, and decide whether to continue running or repair based on the analysis results.
Real-time monitoring and prediction of fatigue life is achieved, product safety and reliability is improved, service life is extended, faults are reduced, customer satisfaction and trust are improved, and product upgrades and enterprise-customer relationships are closer.
Smart Images
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Abstract
Description
Technical Field
[0001] The invention relates to the field of mechanical production, and in particular to a method for improving product reliability. Background Art
[0002] Mining equipment has a complex structure, and most of its main structures are welded, which makes it difficult to manufacture and requires high reliability.
[0003] like Figure 1 As shown, in most traditional product development processes, companies do not use simulation analysis before completing the final design of structural parts, resulting in low product reliability. When a product fails during operation, customers need to stop work and repair the equipment to maintain subsequent operation, resulting in great losses and reduced product reliability. At the same time, after product development is completed, it is necessary to wait for customer feedback before optimization. As a result, companies are unable to effectively understand the actual situation of the equipment, unable to optimize and upgrade the product, and reducing customer trust in the product and recognition of reliability, affecting company development. Summary of the invention
[0004] In view of the problems existing in the above-mentioned prior art, the present invention provides a method for improving product reliability. When an enterprise produces equipment, a fixed (not temporarily on the client) sensor is installed, and a 5G network is used and connected to cloud storage and data processing, such as Figure 3 As shown, the sensor can provide stable signal transmission; real-time reliability analysis can be implemented during equipment operation, and customers can decide the corresponding processing method based on the analysis feedback to solve the above problems.
[0005] In order to achieve the above object, the technical solution adopted by the present invention is: a method for improving product reliability, performing process optimization on the enterprise side and the client side, wherein the process optimization on the enterprise side includes the following steps: Step 1: Initial structural design: Improve the structural design of the product based on customer or market feedback; Step 2: Simulation analysis: Conduct simulation analysis on the structural design; Step 3: Verification: Verify according to simulation analysis. If it meets the requirements, jump to step 5. If it does not meet the requirements, jump to step 4. Step 4: Design iteration: Redesign the structure, and after the design is completed, jump to step 2 for simulation analysis; Step 5: Manufacturing: Produce and manufacture according to the final design and install the required sensors, which transmit information back to the data processing center via the 5G network; Step 6: On-site testing: After the final designed product is tested on-site, if it meets the requirements, it will be the final product. If it does not meet the requirements, jump to step 4 to redesign the structure.
[0006] Furthermore, the empirical load in the simulation analysis in step 2 is obtained from actual measurements of existing similar products at the client end, and is obtained by installing temporary sensors on the tested product at the client end and testing the tested product.
[0007] Furthermore, the client process optimization includes the following steps: Step 1: Run: Use the enterprise-side process to optimize the final product; Step 2: Sensor information reliability analysis: The sensor will continuously measure and provide real-time data, and transmit the data back to the data processing center through the 5G network for processing and analysis, converting it into stress, calculating the stress range, and comparing it with the existing information in the data processing center database to estimate the possible fatigue life. If the estimated fatigue life is higher than the product design target, the reliability is normal, and the product will continue to operate in step 1. If the estimated fatigue life is lower than the product design target, jump to the next step; Step 3. Choose whether to continue working: Make a decision on whether to continue running based on the needs.
[0008] Furthermore, the feedback of the reliability analysis results of the sensor information in the client process optimization will be transmitted to the software installed on the product, and the corresponding processing method will be determined according to the user-defined conditions, and the defined conditions are the design target values of the product.
[0009] Furthermore, the design target value of the product is a non-mandatory value or a mandatory value.
[0010] Furthermore, if the design target of the product is a mandatory value, if the estimated fatigue life is less than the design target of the product, a negative decision is directly selected.
[0011] Furthermore, when the design target of the product is not a mandatory value, if you choose to continue running, you need to reduce the operating load of the product before continuing to run it. At the same time, you will conduct simulation analysis and then optimize the solution based on the simulation analysis results.
[0012] Furthermore, when the design target of the product is not a mandatory value, if a "no" decision is selected, the maintenance process will be carried out directly. After the process is completed, a simulation analysis will be carried out, and then the solution will be optimized based on the simulation analysis results.
[0013] Furthermore, the placement of the sensors is based on feedback from simulation analysis, which is installed before the painting stage of the manufacturing process.
[0014] Furthermore, a protective device is provided on the sensor.
[0015] The beneficial effects of the present invention are: 1) Real-time monitoring can predict fatigue life at any time, improve the safety of product use, and determine whether to continue to operate according to specific circumstances, ensuring that the product can be used effectively and extending its service life; 2) Feedback during operation can improve product reliability; 3) Prevent failures, eliminate unplanned field testing, and improve customer satisfaction and trust in the product; 4) Products can be upgraded and modified based on the continuous feedback information, which can improve customer satisfaction and trust in the products, bring the company and customers closer together through product quality, and improve competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] Figure 1 A schematic diagram of the operation flow of a traditional product design in the background technology; Figure 2 Improve process flow diagrams for product design; Figure 3 Design process diagram for enterprise-side sensor embedded products; Figure 4 Schematic diagram of the operation process of client sensor embedded products. DETAILED DESCRIPTION
[0017] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below through the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of the present invention.
[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.
[0019] like Figure 2-3 As shown, a method for improving product reliability is to optimize processes at the enterprise side and the client side, and the process optimization at the enterprise side includes the following steps: Step 1: Initial structural design: Improve the structural design of the product based on customer or market feedback; Step 2: Simulation analysis: Conduct simulation analysis on the structural design; Step 3: Verification: Verify according to simulation analysis. If it meets the requirements, jump to step 5. If it does not meet the requirements, jump to step 4. Step 4: Design iteration: Redesign the structure, and after the design is completed, jump to step 2 for simulation analysis; Step 5: Manufacturing: Produce and manufacture according to the final design and install the required sensors, which transmit information back to the data processing center via the 5G network; Step 6: On-site testing: After the final designed product is tested on-site, if it meets the requirements, it will be the final product. If it does not meet the requirements, jump to step 4 to redesign the structure.
[0020] Furthermore, in this example, the empirical load in the simulation analysis in step 2 is obtained from actual measurements of existing similar products at the client side, and is obtained by installing temporary sensors on the tested product at the client side and testing the tested product.
[0021] For example, if you want to develop a new 800-ton hydraulic shovel, the load can refer to the existing 700-ton hydraulic shovel. When the 800-ton hydraulic shovel rolls off the production line and starts running at the client, the actual load condition of the new product can be measured, which can be used as an empirical load for simulation analysis of product upgrades at the same level.
[0022] In step 2, the company will improve the product design based on customer feedback. Usually, simulation analysis is performed, and the installation location of the temporary sensor is determined based on the analysis results. The sensor is installed at the client (removed after testing), and the information obtained from the test is used for simulation analysis. The design is iterated based on the analysis results to produce an improved product with improved reliability, such as Figure 2 shown.
[0023] like Figure 4 As shown, the client process optimization includes the following steps: Step 1: Run: Use the enterprise-side process to optimize the final product; Step 2: Sensor information reliability analysis: The sensor will continuously measure and provide real-time data, and transmit the data back to the data processing center through the 5G network for processing and analysis, converting it into stress, calculating the stress range, and comparing it with the existing information in the data processing center database to estimate the possible fatigue life. If the estimated fatigue life is higher than the product design target, the reliability is normal, and the product will continue to operate in step 1. If the estimated fatigue life is lower than the product design target, jump to the next step; Step 3. Choose whether to continue working: Make a decision on whether to continue running based on the needs.
[0024] In step 2, taking welded structural parts as an example, the sensor is a strain gauge that continuously measures and provides real-time strain. The information is transmitted back to the data processing center via the 5G network and converted into stress. The stress range is calculated based on the adopted theoretical formula; The calculated stress range will be compared with the existing information in the data processing center database to estimate the possible fatigue life. If the estimated fatigue life is higher than the design target of the product, the reliability is normal and the product will continue to operate. If the product has the possibility of failure, a decision needs to be made whether to continue to operate.
[0025] Furthermore, in this example, the feedback of the reliability analysis results of the sensor information in the client process optimization will be transmitted to the software installed on the product, and the corresponding processing method will be determined according to the user-defined conditions, and the defined conditions are the design target values of the product.
[0026] Furthermore, in this example, the design target value of the product is a non-mandatory value or a mandatory value.
[0027] If the design target of the product is a mandatory value, if the estimated fatigue life is less than the design target of the product, directly select the "no" decision.
[0028] When the design target of the product is not a mandatory value, if you choose to continue running, you need to reduce the operating load of the product before continuing to run. At the same time, you will conduct simulation analysis and then optimize the solution based on the simulation analysis results.
[0029] When the design target of the product is not a mandatory value, if you choose "no", the repair process will be carried out directly. After the process is completed, a simulation analysis will be carried out, and then the solution will be optimized based on the simulation analysis results.
[0030] Take a heavy-duty mining truck as an example. If the design goal is to load 200 tons of materials and run for 10 years, if a driver often overloads 250 tons, the operating life will be reduced to less than 6 years, which means that the fatigue life will be reduced and failure may occur earlier. If the customer software is pre-set to require the product to run for 10 years, the software will force (or continuously feedback) the driver and the customer to reduce the load to avoid failure. This technical solution improves the reliability of the product.
[0031] If the customer insists on loading 250 tons of materials and running it for 10 years, the software will feedback the information to the company for future product upgrades; this information can also be used as a basis for handling product failures before the warranty period.
[0032] Furthermore, in this example, the placement of the sensor is based on feedback from the simulation analysis, and it is installed before the painting stage of the manufacturing process. During the processing stage of the manufacturing process, the surface near the location where the sensor is placed is well treated.
[0033] Furthermore, in this example, a protective device is provided on the sensor to prevent damage. The sensor needs to be able to transmit data stably. The sensor is also provided with a separate power supply device so that the sensor can provide stable signal transmission.
[0034] The data processing center is a cloud center, and operations are performed through the cloud center. The settings of the cloud center can only be operated by the enterprise side to prevent client personnel from tampering with parameters.
[0035] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent substitution or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for improving product reliability, characterized in that: The process optimization is performed on the enterprise side and the client side. The process optimization on the enterprise side includes the following steps: Step 1: Initial structural design: Improve the structural design of the product based on customer or market feedback; Step 2: Simulation analysis: Conduct simulation analysis on the structural design; Step 3: Verification: Verify according to simulation analysis. If it meets the requirements, jump to step 5. If it does not meet the requirements, jump to step 4. Step 4: Design iteration: Redesign the structure, and after the design is completed, jump to step 2 for simulation analysis; Step 5: Manufacturing: Produce and manufacture according to the final design and install the required sensors, which transmit information back to the data processing center via the 5G network; Step 6: On-site testing: After the final designed product is tested on-site, if it meets the requirements, it will be the final product. If it does not meet the requirements, jump to step 4 to redesign the structure.
2. A method for improving product reliability according to claim 1, characterized in that: The empirical load in the simulation analysis in step 2 is obtained from actual measurements of existing similar products at the client end, and is obtained by installing temporary sensors on the tested product at the client end and testing the tested product.
3. A method for improving product reliability according to claim 1, characterized in that: The client process optimization includes the following steps: Step 1: Run: Use the enterprise-side process to optimize the final product; Step 2: Sensor information reliability analysis: The sensor will continuously measure and provide real-time data, and transmit the data back to the data processing center through the 5G network for processing and analysis, converting it into stress, calculating the stress range, and comparing it with the existing information in the data processing center database to estimate the possible fatigue life. If the estimated fatigue life is higher than the product design target, the reliability is normal, and the product will continue to operate in step 1. If the estimated fatigue life is lower than the product design target, jump to the next step; Step 3. Choose whether to continue working: Make a decision on whether to continue running based on the needs.
4. A method for improving product reliability according to claim 3, characterized in that: The feedback of the reliability analysis results of the sensor information in the client process optimization will be transmitted to the software installed on the product, and the corresponding processing method will be determined according to the user-defined conditions. The defined conditions are the design target values of the product.
5. A method for improving product reliability according to claim 4, characterized in that: The design target value of the product is a non-mandatory value or a mandatory value.
6. A method for improving product reliability according to claim 5, characterized in that: If the design target of the product is a mandatory value, if the estimated fatigue life is less than the design target of the product, directly select the "no" decision.
7. A method for improving product reliability according to claim 5, characterized in that: When the design target of the product is not a mandatory value, if you choose to continue running, you need to reduce the operating load of the product before continuing to run. At the same time, you will conduct simulation analysis and then optimize the solution based on the simulation analysis results.
8. A method for improving product reliability according to claim 5, characterized in that: When the design target of the product is not a mandatory value, if you choose "no", the repair process will be carried out directly. After the process is completed, a simulation analysis will be carried out, and then the solution will be optimized based on the simulation analysis results.
9. A method for improving product reliability according to claim 1, characterized in that: The placement of the sensors is based on feedback from simulation analysis and they are installed before the painting stage of the manufacturing process.
10. A method for improving product reliability according to claim 1, characterized in that: The sensor is equipped with a protective device.