Excavator problem solving system and method based on intelligent terminal big data problem management

Abstract

The invention discloses an excavator problem solving system and method based on intelligent terminal big data problem management, and the system comprises an APP which provides a template for problem feedback and is used for transmitting a reported problem to a cloud platform after a user fills in the reported problem according to the template; the cloud platform is used for analyzing and processing the collected submitted problems, dividing the submitted problems into two categories, namely a product competitiveness improvement category and a fault problem category, processing the product competitiveness improvement category and the fault problem category in different modes, determining solutions corresponding to the submitted problems, and pushing the solutions to the user; and the server is used for storing the reported problem into a corresponding database according to the type of the excavator. According to the method, problems are quickly solved through problem classification and level-to-level management and borrowing of big data and expert groups, the user can monitor the whole process to increase the sense of participation and improve the use feeling of the user, and a database of the user is established to provide forward research and development input for product upgrading iteration.

Description

Technical Field

[0001] The present invention relates to an excavator problem-solving system and method based on intelligent terminal big data problem management, belonging to the technical field of excavator design. Background Art

[0002] Ultimately, all designs must serve the market. Only designs recognized by market users can truly enhance product competitiveness and improve product efficiency. Forward R&D design input must come from the market. Existing excavator design processes are largely based on basic functional knowledge and experience. After the product is designed and released to the market, feedback and design adjustments are made, often resulting in significant waste of manpower and materials. Problems reported by users are typically handled through traditional warranty repairs, which lacks real-time tracking and results in a low sense of participation in problem resolution.

[0003] The current excavator design user-reported issues have the following defects: (1) Problems reported by users cannot be managed due to the lack of classification and grading, and a large number of problem solutions cannot be used as input for product design.

[0004] (2) There is no database management for the problems, so they cannot be converted into design experience for iterative model design.

[0005] (3) When users report problems, they cannot see the process, and some problems cannot be solved for various reasons. However, there is no response, which gives users a very bad experience. Summary of the Invention

[0006] The purpose of the present invention is to provide an excavator problem-solving system and method based on smart terminal big data problem management, which can effectively manage problems raised by customers and ultimately form a product upgrade database, effectively improving the user experience.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: The present invention provides an excavator problem solving system based on intelligent terminal big data problem management, comprising: The app provides a template for problem feedback, which users can fill out according to the template and then transmit the reported problem to the cloud platform; The cloud platform is used to analyze and process the collected reported issues, classify the reported issues, determine the corresponding solutions for the reported issues, and push them to users; The server is used to store the reported issues into the corresponding database according to the excavator product model.

[0008] Preferably, the template for problem feedback includes the reporting time, the content of the reported problem, as well as the problem classification option and the problem level option; the problem level is the degree of urgency; the content of the reported problem includes the region, service provider, product model, vehicle number, faulty part stamp number, supplier, problem description and improvement suggestion options.

[0009] Preferably, the cloud platform is specifically used to: Generate internal numbers for transmitted reports; Compare the submitted questions with the pre-stored database on the cloud platform, calculate the scores of the submitted questions, and send the submitted questions with scores exceeding the set value to the question experts for scoring; Based on the final results of the experts' scoring, the reported issues are divided into two categories: product competitiveness improvement and failure issues; Different approaches are used to handle issues related to product competitiveness improvement and fault problems, and solutions corresponding to the reported problems are determined and pushed to users.

[0010] Preferably, the cloud platform calculates the score of the reported question, including: Different basic scores are assigned based on the business impact of the problem type; Set different weighting coefficients according to the urgency of the problem; Set timeliness bonus for submission time; The final comprehensive score of the reported problem = basic score × weighting coefficient + timeliness bonus; If the overall score exceeds 60 points, the question will be sent to the question experts for scoring.

[0011] Preferably, the reported issues are divided into two categories based on the final results of the expert scoring: product competitiveness improvement and fault problem categories, including: Score the reported issues based on four dimensions: technology, service, sales, and cost, and calculate a weighted score; The product competitiveness improvement categories include: configuration improvement, function improvement and performance improvement; The types of fault problems include design defects, quality defects and workmanship defects.

[0012] Preferably, the product competitiveness improvement category and the fault problem category are handled in different ways, including: For fault issues, we will push them to the corresponding service engineers as soon as possible according to the problem level, solve the problem, and push the solution to the customer; And according to the problem solutions, the problems are classified and stored in the problem library as positive input for product iteration; the problem library includes the agent problem library, the design problem library and the process problem library.

[0013] Preferably, the product competitiveness improvement category and the fault problem category are handled in different ways, including: For issues related to improving product competitiveness, technical, financial, service, and marketing experts will design and evaluate improvement plans and calculate scores for product competitiveness improvement issues; Determine whether product competitiveness needs to be improved based on the product competitiveness improvement question score; If necessary, the question will be stored in the market design input library and the result will be pushed to the user of the question.

[0014] Preferably, the calculating of the product competitiveness improvement problem score includes: Construct a multi-dimensional quantitative scoring model, set scoring criteria and weights for each indicator, and then use weighted calculations to derive a score for product competitiveness improvement issues; the indicators include technical feasibility, service accessibility, sales impact, and financial cost; If the score is greater than 70 out of 100, the product competitiveness needs to be improved.

[0015] The present invention also provides a method for solving excavator problems based on intelligent terminal big data problem management. Based on the above-mentioned excavator problem solving system based on intelligent terminal big data problem management, the method includes: Users submit their own questions by filling out the feedback template on the APP and transmitting it to the cloud platform; The cloud platform generates an internal number for the transmitted reported issues; Compare the submitted questions with the pre-stored database on the cloud platform, calculate the scores of the submitted questions, and send the submitted questions with scores exceeding the set value to the question experts for scoring; Based on the final results of the experts' scoring, the reported issues are divided into two categories: product competitiveness improvement and failure issues; Different approaches are used to handle issues related to product competitiveness improvement and fault problems, and solutions corresponding to the reported problems are determined and pushed to users.

[0016] Preferably, the product competitiveness improvement category and the fault problem category are handled in different ways, including: For fault issues, we will push them to the corresponding service engineers as soon as possible according to the problem level, solve the problem, and push the solution to the customer; And according to the problem solutions, the problems are classified and stored in the problem library as positive input for product iteration; the problem library includes the agent problem library, the design problem library and the process problem library; For issues related to improving product competitiveness, technical, financial, service, and marketing experts will design and evaluate improvement plans and calculate scores for product competitiveness improvement issues; Determine whether product competitiveness needs to be improved based on the product competitiveness improvement question score; If necessary, the question will be stored in the market design input library and the result will be pushed to the user of the question.

[0017] The beneficial effects brought about by the technical solution of the present invention are as follows: The present invention provides an excavator problem-solving system and method based on intelligent terminal big data problem management. Through problem classification and hierarchical management, problems can be quickly solved by leveraging big data and expert groups. Users can monitor the entire process to increase their sense of participation, improve user experience, and establish their own database to provide positive R&D input for product upgrades and iterations.

[0018] The present invention provides problem database management, collects all user experience to form a unique database, converts it into design experience, and performs model design iteration. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of the architecture of an excavator problem-solving system based on intelligent terminal big data problem management provided by an embodiment of the present invention; Figure 2 A flowchart of a method for solving an excavator problem based on big data problem management of smart terminals is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0021] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, the accompanying drawings only show structures and / or processing steps closely related to the solutions according to the present invention, while other details that are not closely related to the present invention are omitted.

[0022] It should be emphasized that the term "include / comprises" when used herein refers to the existence of features, elements, steps or components, but does not exclude the existence or addition of one or more other features, elements, steps or components.

[0023] It should also be noted that, unless otherwise specified, the term "connection" herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0024] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0025] It should be emphasized here that the step marks mentioned below do not limit the order of the steps, but it should be understood that the steps can be executed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be executed simultaneously.

[0026] like Figure 1 As shown, the first embodiment of the present invention provides an excavator problem solving system based on intelligent terminal big data problem management, which is mainly composed of a mobile phone APP, a cloud platform and a server; Among them, the mobile APP provides a template for users to report problems. After users fill in the template and submit the problem, the reported problem will be transmitted to the cloud platform; The template for problem feedback in the embodiment of the present invention includes the reporting time, the content of the reported problem, as well as the problem classification option and the problem level (urgency) option. The content of the reported problem includes options such as region, service provider, product model, vehicle number, faulty part stamp number, supplier, problem description and improvement suggestions.

[0027] The cloud platform is used to analyze and process the collected reported issues, classify the reported issues, determine the corresponding solutions to the reported issues, and push them to users; The server is used to store the reported issues in a corresponding database by machine model. The machine model refers to the excavator product model, and the stored information is the report content filled in according to the template.

[0028] In the embodiment of the present invention, the cloud platform analyzes and processes the collected reported issues, classifies the reported issues, and determines the corresponding solutions to the reported issues. The specific implementation process is as follows: 1. Generate internal numbers for transmitted reported issues to facilitate issue management; 2. Quickly compare the reported issues against the pre-stored database on the cloud platform, calculate the score of the reported issues, and obtain a result. This result is then sent to problem experts for scoring. It should be noted that problem experts are mainly experienced designers and service personnel. Specifically, the reported problem is expressed as: T=f(X1,X2,X3…,t), where X1,X2,X3…represent each item filled in the template, such as problem level, problem classification, problem importance, etc., and t represents the feedback time; the feedback time refers to the interval between the time the problem occurs and the time of reporting, that is, the feedback timeliness.

[0029] In this embodiment, a quantitative scoring system based on multi-dimensional indicators converts the reported issues into computable score values, and then divides the problem levels into score ranges, specifically: Different basic scores are assigned based on the business impact of the problem type; Set different weighting coefficients according to the urgency of the problem; To encourage timely feedback, timeliness bonus points are set for submission time; Finally, we get: The comprehensive score of the reported issue = basic score × weighting coefficient + timeliness bonus.

[0030] If the comprehensive score exceeds 60 points, the result of this question will be sent to the question expert for scoring.

[0031] 3. Based on the final results of the experts’ scoring, the problems are divided into two categories: product competitiveness improvement and failure problems. See also Figure 2 ,Product competitiveness improvement categories include: a. Configuration improvement, mainly considering that the configuration of products with the same tonnage is weaker than that of competitors. b. Function improvement: First, there may be additional functions and redundancy, and secondly, the functions cannot meet user requirements. c. Performance improvement: The overall performance of the machine is weaker than that of competitors; Failure issues include: a. Design defects: Failures caused by design. b. Quality defects: Failures caused by product quality issues, primarily quality issues between different suppliers for the same product, and batch quality issues. c. Process defects: Failures caused by errors in the process routing, assembly, or welding.

[0032] In this embodiment, classification rules are established by using indicator weight differences or threshold judgments to set differentiated evaluation indicators and weights for the two types of problems: Experts score each submitted question and calculate a weighted score: Product competitiveness improvement score = technology score × 0.3 + service score × 0.25 + sales score × 0.3 + cost score × 0.15; Fault problem category score = technical score × 0.3 + service score × 0.25 + sales score × 0.3 + cost score × 0.15; If the score of product competitiveness improvement category is greater than the score of fault problem category, it will be classified as product competitiveness improvement category; If the score of the fault problem category is greater than the score of the product competitiveness improvement category, it will be classified as the fault problem category.

[0033] 4. Use different methods to deal with product competitiveness improvement and fault problems respectively. For fault issues, they are pushed to the corresponding service engineers according to the problem level as soon as possible, and the problem solutions are pushed to the customers as soon as possible. Based on the final solutions, the problems are classified and stored in the problem library of the cloud platform as positive input for product iteration. The problem library includes the agent problem library, the design problem library, and the process problem library. To improve product competitiveness, the technical department will provide a design plan, the financial department will provide a plan and the cost of the reform, and the service experts and marketing experts will evaluate and calculate the problem score. Based on the problem score, it will be determined whether the product competitiveness needs to be improved. If so, the problem will be stored in the server as a market-side design input, and the result will be pushed to the user of the problem.

[0034] In this example, a multi-dimensional quantitative scoring model is constructed, with scoring criteria and weights set for each indicator. The problem score is then calculated through weighted calculation. The four indicators are scored by departments such as technology, service, sales, and finance. Management sets weights for each indicator based on the nature of the project. The system automatically captures the scores for each indicator and calculates a comprehensive problem score.

[0035] For example: Technical feasibility: 28 points (weight 25%) → 28×0.25=7 points; Service accessibility: 22 points (weight 25%) → 22 × 0.25 = 5.5 points; Sales influence: 18 points (25% weight) → 18 × 0.25 = 4.5 points; Cost: 16 points (25% weight) → 16 × 0.25 = 4 points; Comprehensive question score: 7+5.5+4.5+4=21 points (84 points out of 100 points).

[0036] If the score is greater than 70 out of 100, the product competitiveness needs to be improved.

[0037] Based on the same inventive concept, the second embodiment of the present invention provides a solution to the excavator problem based on intelligent terminal big data problem management, see Figure 2 , the method comprises the following steps: Step 1: Users submit their own questions and fill in the feedback template on the mobile app; Step 2: After the report is submitted, the issue is transmitted to the cloud platform and an internal number is generated to facilitate issue management; Step 3: Quickly compare the questions based on the pre-stored database on the cloud platform and calculate the score of the reported questions. Questions with scores exceeding the set value are sent to experts for scoring. It should be noted that the calculation method of the reported question score is the same as in the above embodiment. Step 4: Based on the final results of the experts' scoring, the issues are divided into two categories: product competitiveness improvement and failure issues; Step 5: Use different methods to handle product competitiveness improvement and fault problem types, specifically: For fault issues, they are pushed to the corresponding service engineers according to the problem level as soon as possible, and the problem solutions are pushed to the customers as soon as possible. Based on the final solutions, the problems are classified and stored in the problem library as positive input for product iteration. The problem library includes the agent problem library, the design problem library, and the process problem library. For product competitiveness enhancement issues, the technical team will provide a design plan, the financial team will provide a plan and the cost of the modification, and the service and marketing experts will evaluate and calculate a problem score. Based on the problem score, the team will determine whether the product's competitiveness needs to be improved. If so, the problem will be stored in the server as a market-side design input, and the results will be pushed to the user who raised the issue. It should be noted that the problem score calculation method is the same as in the above embodiment.

[0038] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An excavator problem solving system based on intelligent terminal big data problem management, characterized in that: include: The app provides a template for problem feedback, which users can fill out according to the template and then transmit the reported problem to the cloud platform; The cloud platform is used to analyze and process the collected reported issues, classify the reported issues, determine the corresponding solutions for the reported issues, and push them to users; The server is used to store the reported issues into the corresponding database according to the excavator product model.

2. The excavator problem solving system based on intelligent terminal big data problem management according to claim 1 is characterized in that: The template for problem feedback includes the reporting time, the content of the reported problem, as well as the problem classification options and problem level options; the problem level is the degree of urgency; the content of the reported problem includes the region, service provider, product model, vehicle number, faulty part stamp number, supplier, problem description and improvement suggestion options.

3. The excavator problem solving system based on intelligent terminal big data problem management according to claim 1 is characterized in that: The cloud platform is specifically used to: Generate internal numbers for transmitted reports; Compare the submitted questions with the pre-stored database on the cloud platform, calculate the scores of the submitted questions, and send the submitted questions with scores exceeding the set value to the question experts for scoring; Based on the final results of the experts' scoring, the reported issues are divided into two categories: product competitiveness improvement and failure issues; Different approaches are used to handle issues related to product competitiveness improvement and fault problems, and solutions corresponding to the reported problems are determined and pushed to users.

4. The excavator problem solving system based on intelligent terminal big data problem management according to claim 3 is characterized in that: The cloud platform calculates the score of the reported issue, including: Different basic scores are assigned based on the business impact of the problem type; Set different weighting coefficients according to the urgency of the problem; Set timeliness bonus for submission time; The final comprehensive score of the reported problem = basic score × weighting coefficient + timeliness bonus; If the overall score exceeds 60 points, the question will be sent to the question experts for scoring.

5. The excavator problem solving system based on intelligent terminal big data problem management according to claim 4 is characterized in that: According to the final results of the experts' scoring, the reported issues are divided into two categories: product competitiveness improvement and failure issues, including: Score the reported issues based on four dimensions: technology, service, sales, and cost, and calculate a weighted score; The product competitiveness improvement categories include: configuration improvement, function improvement and performance improvement; The types of fault problems include design defects, quality defects and workmanship defects.

6. The excavator problem solving system based on intelligent terminal big data problem management according to claim 4 is characterized in that: The product competitiveness improvement and fault problem categories are handled in different ways, including: For fault issues, we will push them to the corresponding service engineers as soon as possible according to the problem level, solve the problem, and push the solution to the customer; And according to the problem solutions, the problems are classified and stored in the problem library as positive input for product iteration; the problem library includes the agent problem library, the design problem library and the process problem library.

7. The excavator problem solving system based on intelligent terminal big data problem management according to claim 6 is characterized in that: The product competitiveness improvement and fault problem categories are handled in different ways, including: For issues related to improving product competitiveness, technical, financial, service, and marketing experts will design and evaluate improvement plans and calculate scores for product competitiveness improvement issues; Determine whether product competitiveness needs to be improved based on the product competitiveness improvement question score; If necessary, the question will be stored in the market design input library and the result will be pushed to the user of the question.

8. The excavator problem solving system based on intelligent terminal big data problem management according to claim 7 is characterized in that: The calculation of the product competitiveness improvement problem score includes: Construct a multi-dimensional quantitative scoring model, set scoring criteria and weights for each indicator, and then use weighted calculations to derive a score for product competitiveness improvement issues; the indicators include technical feasibility, service accessibility, sales impact, and financial cost; If the score is greater than 70 out of 100, the product competitiveness needs to be improved.

9. A solution to excavator problems based on intelligent terminal big data problem management, characterized in that: The excavator problem solving system based on intelligent terminal big data problem management according to any one of claims 1 to 8 is implemented, and the method includes: Users submit their own questions by filling out the feedback template on the APP and transmitting it to the cloud platform; The cloud platform generates an internal number for the transmitted reported issues; Compare the submitted questions with the pre-stored database on the cloud platform, calculate the scores of the submitted questions, and send the submitted questions with scores exceeding the set value to the question experts for scoring; Based on the final results of the experts' scoring, the reported issues are divided into two categories: product competitiveness improvement and failure issues; Different approaches are used to handle issues related to product competitiveness improvement and fault problems, and solutions corresponding to the reported problems are determined and pushed to users.

10. The excavator problem solving method based on intelligent terminal big data problem management according to claim 9 is characterized in that: The product competitiveness improvement and fault problem categories are handled in different ways, including: For fault issues, we will push them to the corresponding service engineers as soon as possible according to the problem level, solve the problem, and push the solution to the customer; And according to the problem solutions, the problems are classified and stored in the problem library as positive input for product iteration; the problem library includes the agent problem library, the design problem library and the process problem library; For issues related to improving product competitiveness, technical, financial, service, and marketing experts will design and evaluate improvement plans and calculate scores for product competitiveness improvement issues; Determine whether product competitiveness needs to be improved based on the product competitiveness improvement question score; If necessary, the question will be stored in the market design input library and the result will be pushed to the user of the question.

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