Monitoring and early warning method and system based on multi-dimensional collaborative risk identification

Abstract

The invention discloses a monitoring and early warning method and system based on multi-dimensional collaborative risk identification, and relates to the technical field of monitoring and early warning, and the system comprises an acquisition module, a data multi-dimensional fusion module, a data analysis module, a risk assessment module, an early warning release module, and an information push module. According to the monitoring and early warning system for multi-dimensional collaborative risk identification, the number of products required in the next period can be estimated in time, the required number of products can be produced according to the estimated number of products, whether the batch of products can be finished within the specified time or not can be warned in advance, and the production efficiency is improved. Meanwhile, information intercommunication is carried out on the production conditions of low-end, medium-end and high-end products, the equipment use condition and personnel transfer are faster, the number of produced products adapts to and meets the pre-estimated product number, the situation that the product number exceeds the market demand, products are unsalable and overstocked is prevented, the situation that the product number cannot meet the market demand is also prevented, and the product quality is improved. And product shortage and customer loss are caused.

Description

Technical Field

[0001] The present invention relates to the field of monitoring and early warning technology, and in particular to a monitoring and early warning method and system based on multi-dimensional collaborative risk identification. Background Art

[0002] In the current manufacturing environment, due to the uncertainty of market demand, some factories are often unable to produce the required number of products based on the estimated number of products when formulating production plans. In addition, during the production process, the damage of processing equipment and the lack of timely mobilization of personnel make it impossible to provide early warning whether the batch of products can be completed within the specified time. In addition, the information between products is not interconnected, which will lead to large fluctuations in the number of products produced. It is possible that the number of products exceeds market demand, resulting in unsold products and inventory backlogs. It is also possible that the number of products cannot meet market demand, resulting in product out-of-stock and customer loss. Summary of the Invention

[0003] The main purpose of the present invention is to provide a monitoring and early warning method based on multi-dimensional collaborative risk identification to solve the problems raised in the above background.

[0004] To achieve the above object, the technical solution adopted by the present invention is:

[0005] A monitoring and early warning system based on multi-dimensional collaborative risk identification, including an acquisition module, a multi-dimensional data fusion module, a data analysis module, a risk assessment module, an early warning release module, and an information push module;

[0006] The acquisition module collects historical data, analyzes the sales volume of products in each period of previous years, the purchasing intentions of the purchasing groups and the service life of the products, and determines the users who intend to purchase and those who do not;

[0007] The multi-dimensional data fusion module collects the company's financial information, sales volume of low-, medium-, and high-end products, and market data for the current year, and determines the number of products that potential users will purchase based on internal sales records and the years of use of consumers' purchased products collected through after-sales visits, questionnaires, and product registration information.

[0008] The data analysis module uses the sales data of previous products and the sales share of the company's low, medium and high-end products in the market this year to analyze the number of products purchased by potential customers in real time;

[0009] The risk assessment module evaluates whether the production quantity of low, medium and high-end products can meet the market demand before the end of the cycle based on the current stock quantity of the company's low, medium and high-end products, the quantity required by the mid-to-high-end market analyzed by the data analysis module, and the current daily production efficiency of the production line.

[0010] Preferably, the collection module includes a crowd collection unit, a season cycle unit, a usage cycle unit and an economic environment collection unit;

[0011] The crowd collection unit uses internal data sources, social software and telephone consultation to count the number of purchasers in different time periods, different regions, different ages and genders, and determines the number of users who intend to purchase again among the historical purchasers;

[0012] The seasonal cycle unit uses a time recorder to clearly record the sales quantity and sales data of products in each cycle by month, quarter and year, and to highlight the periods of historical hot sales of products;

[0013] The usage cycle unit collects the time of historical product purchases and actual product usage through internal data sources, sorts out products that are about to reach their service life, and uses social software and telephone consultation to determine whether the products need to be replaced;

[0014] The economic environment collection unit monitors macroeconomic indicators, industry development trends, technology updates and annual indicators of key development projects in real time through network computers, and collects corporate stock price trends and industry average financial indicator market data from financial information websites, securities trading platforms and external data sources through web crawler technology.

[0015] Preferably, the data multi-dimensional fusion module includes a financial data collection unit, a product grade ratio analysis unit, a market data collection unit and an internal management data unit;

[0016] The financial data acquisition unit obtains the company's balance sheet, income statement, cash flow statement, financial statement data, and various financial indicator data through the internal database;

[0017] The market data collection unit calculates the proportion of sales of low-, medium-, and high-quality products of an enterprise in a specific market to the total market sales, and measures the brand influence, market recognition, and market competitiveness of the enterprise through evaluation data from market research institutions and brand exposure on social media;

[0018] Through the interaction between the financial data collection unit and the market data collection unit, the changes in product sales in the next cycle are estimated, and the data indicator curve chart is generated through the multi-dimensional data fusion module.

[0019] Preferably, the product grade proportion analysis unit calculates the market share of the low-end, mid-end and high-end products that have been sold by exchanging data between the financial data collection unit and the market data collection unit;

[0020] The internal management data unit also includes a sales data analysis unit, an after-sales service data analysis unit and a production data unit;

[0021] The sales data analysis unit determines the sales records of the sales department for low-, medium-, and high-priced products through the internal resource record library;

[0022] The after-sales service data analysis unit determines the handover service and after-sales service records of all sold products by the after-sales service department through the internal resource record library;

[0023] The production data unit determines the production quantity of low-, medium- and high-end products and the normal daily output quantity of products by the production department through the internal resource record library.

[0024] Preferably, the data analysis module centrally stores and manages the data from the acquisition module and the data multi-dimensional fusion module through the data warehouse system, provides a unified data view, obtains historical data and current data through analysis of the time period dimension and performs comparative analysis to derive the production quantities of low, medium and high-end products required.

[0025] Preferably, the risk assessment module includes a risk type unit, a risk prevention unit, a production scheduling unit and a production monitoring unit;

[0026] The risk type unit assesses the stability and reliability of raw material supply, as well as the supplier's reputation and delivery capabilities, and evaluates the technical difficulties and time delays in the application of new technologies that may be encountered in the production of low-, medium-, and high-end products;

[0027] The risk prevention unit formulates a reasonable inventory management strategy, safety stock quantity and order point setting, and responds to the uncertainty of market demand through effective inventory management to ensure that production quantity is consistent with the estimate;

[0028] The production monitoring unit uses modern information technology to monitor production equipment in real time, collects production data and equipment working intensity, and promptly analyzes the number of products produced that day;

[0029] The production scheduling unit rationally arranges production tasks based on real-time monitoring of equipment status, employee skill assessment levels, and production capacity to ensure that production quantities are consistent with estimates;

[0030] The risk assessment module is based on the current stock quantities of the company's low, medium and high-end products and the quantities required by the low, medium and high-end markets analyzed by the data analysis module, as well as the current daily production efficiency of the production line.

[0031] Preferably, the risk assessment module evaluation formula is:

[0032]

[0033] Among them, α represents the production capacity utilization rate, M represents the actual output, which is the number of products actually completed within a specified time, and m represents the theoretical production capacity, which is the maximum output that the factory can achieve;

[0034]

[0035] Where T represents the time schedule compliance rate, T 实 Indicates the actual completion time, the actual time spent on completing the current production task, t 规 Indicates the time limit originally planned for completing the production task;

[0036]

[0037] in The difference between the estimated and actual products, S represents the number of estimated products, and P represents the actual number of completed products;

[0038]

[0039] Among them, ω represents the comprehensive evaluation index;

[0040] According to the inventory quantity of the product, the comprehensive evaluation index range of the product production is set to [90%~94%]. When the ω value of the product is between [90%~94%], the quantity of product production plus the quantity of inventory products meet the estimated product demand, and the quantity of products produced is adapted to the estimated quantity of products required for production. When the ω value of the product is less than 90%, the quantity of product production plus the quantity of inventory products is lower than the estimated product quantity demand, and the output needs to be increased. When the ω value of the product is greater than 94%, the quantity of product production plus the quantity of inventory products is higher than the estimated product quantity demand, and the production quantity is in excess.

[0041] Preferably, the after-sales service data analysis unit includes a fault type analysis unit and an after-sales processing unit;

[0042] The fault type analysis unit includes an after-sales service recording unit, a product fault code recording unit and a background service software fault recording unit;

[0043] The after-sales service recording unit records the product model, serial number, and fault code as a company record report after the after-sales personnel have resolved the fault;

[0044] The product fault code recording unit reports the product model, serial number, and fault code through the product management program downloaded on the customer's mobile phone and the mobile phone program downloaded by the area service personnel, and serves as a company record report;

[0045] The back-end service software fault recording unit records the product model, serial number, and fault code through the data updated in real time by the company's back-end, and uses it as a company record report.

[0046] Preferably, the after-sales processing unit includes a telephone communication processing unit, a manual customer service connection unit and an on-site service processing unit;

[0047] The telephone communication processing unit displays an alarm on the service personnel program based on the fault alarm information. The service personnel independently contacts the management personnel of the product in the area to resolve the fault alarm. The customer sees the fault alarm information and informs the service personnel or manual customer service by phone. The customer directly contacts the manual customer service by phone. The customer service informs the service personnel in the area of the customer's contact information and solves the customer's problem. Fault alarms that cannot be resolved by phone require on-site repairs by service personnel in the area where the product is located.

[0048] A monitoring and early warning method based on multi-dimensional collaborative risk identification, the steps of which are as follows:

[0049] S1: The acquisition module collects historical data and analyzes product sales volume, purchasing demographics, product lifecycles, and the current economic environment in each past cycle. This helps identify potential buyers and non-buyers, as well as the sales share of low-, mid-, and high-end products.

[0050] S2: Through the multi-dimensional data fusion module, the company's financial information, sales volume of low-, mid-, and high-end products, and market data for the current year are collected. Internal sales records are analyzed along with information on the years of use of consumer products collected through after-sales visits, questionnaires, and product registration information. This helps identify potential buyers and further analyzes the market share of low-, mid-, and high-end products.

[0051] S3: The data analysis module uses historical product sales data and the company's current year's market share of low-, medium-, and high-end products to analyze the number of products purchased by potential customers in real time and calculate the production volume of low-, medium-, and high-end products to be produced in the next cycle.

[0052] S4: Risk Assessment Module: This module assesses whether the production quantities of low-, medium-, and high-end products can meet market demand by the end of the cycle based on the company's current inventory quantities of low-, medium-, and high-end products, the quantities required by the low-, medium-, and high-end markets as analyzed by the data analysis module, and the current daily production efficiency of the production lines.

[0053] S5: The results obtained after the risk assessment module's evaluation need to be analyzed in multiple dimensions to determine the production speed and personnel deployment of each product within the specified period, and to formulate respective predetermined solutions for low, medium and high-end products, which will be released through the early warning release module and then automatically pushed to the production managers of each of the low, medium and high-end products.

[0054] The present invention has the following beneficial effects:

[0055] 1. In the present invention, the monitoring and early warning system for collaborative risk identification from multiple dimensions can timely estimate the number of products required for the next cycle, can produce the required number of products based on the estimated number of products required, and can give early warning of whether the batch of products can be completed within the specified time. At the same time, it enables information exchange on the production status of low-, medium- and high-end products, and is more efficient in equipment usage and personnel mobilization, so that the number of products produced can adapt to meet the estimated number of products required, prevent the number of products from exceeding market demand, resulting in unsalable products and inventory backlogs, and also prevent the number of products from failing to meet market demand, resulting in product out-of-stock and customer loss.

[0056] 2. In the present invention, after-sales service personnel can obtain product failure information in a timely manner, and can quickly solve product failure problems, thereby improving the speed at which after-sales service personnel can solve product problems, thereby improving the service quality of service personnel, and at the same time maintaining potential purchasing customers. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flowchart of the steps of a monitoring and early warning system based on multi-dimensional collaborative risk identification of the present invention;

[0058] Figure 2 This is an overall flow chart of a monitoring and early warning system based on multi-dimensional collaborative risk identification according to the present invention;

[0059] Figure 3 This is a flow chart of the acquisition module of a monitoring and early warning system based on multi-dimensional collaborative risk identification according to the present invention;

[0060] Figure 4 This is a flow chart of a data multi-dimensional fusion module of a monitoring and early warning system based on multi-dimensional collaborative risk identification according to the present invention;

[0061] Figure 5 This is a flow chart of an after-sales service data analysis unit of a monitoring and early warning system based on multi-dimensional collaborative risk identification according to the present invention;

[0062] Figure 6 This is a flow chart of the risk assessment module of a monitoring and early warning system based on multi-dimensional collaborative risk identification in the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0064] Example 1: Please refer to Figures 1 to 6 ,The present invention provides a technical solution including: an acquisition module, a data multi-dimensional fusion module, a data analysis module, a risk assessment module, an early warning release module, and an information push module;

[0065] The acquisition module collects historical data, analyzes product sales volume, purchasing intentions, and product lifespan in previous years, and identifies potential buyers and non-buyers.

[0066] The multi-dimensional data fusion module collects the company's financial information, sales volume of low-, medium-, and high-end products, and market data for the current year. Based on internal sales records and the years of use of consumer products collected through after-sales visits, questionnaires, and product registration information, it determines the number of products that potential users intend to purchase.

[0067] The data analysis module uses the sales data of previous products and the market share of the company's low-, medium- and high-end products this year to analyze the number of products purchased by potential customers in real time;

[0068] The risk assessment module evaluates whether the production quantity of low, medium and high-end products can meet the market demand before the end of the cycle based on the current inventory quantity of the company's low, medium and high-end products, the quantity required by the mid-to-high-end market analyzed by the data analysis module, and the current daily production efficiency of the production line.

[0069] The collection module includes crowd collection unit, seasonal cycle unit, usage cycle unit and economic environment collection unit;

[0070] The crowd collection unit uses internal data sources, social software, and telephone consultations to count the number of purchasers in different time periods, regions, ages, and genders, and to determine the number of users who intend to purchase again among the historical purchasers.

[0071] The seasonal cycle unit uses a time recorder to clearly record the sales quantity and sales data of products in each cycle by month, quarter and year, and to highlight the periods of historical hot sales of products;

[0072] The usage cycle unit collects historical product purchase times and actual product usage times through internal data sources, organizes products that are about to reach their service life, and uses social software and telephone consultations to determine whether the products need to be replaced;

[0073] The economic environment collection unit monitors macroeconomic indicators, industry development trends, technology updates and annual indicators of key development projects in real time through network computers, and collects corporate stock price trends and industry average financial indicator market data from financial information websites, securities trading platforms and external data sources through web crawler technology.

[0074] The data multi-dimensional fusion module includes financial data collection unit, product grade ratio analysis unit, market data collection unit and internal management data unit;

[0075] The financial data collection unit obtains the company's balance sheet, income statement, cash flow statement, financial statement data, and various financial indicator data through the internal database;

[0076] The market data collection unit calculates the proportion of sales of low-, medium-, and high-quality products in a company's specific market to the total market sales. It also measures the company's brand influence, market recognition, and market competitiveness through evaluation data from market research institutions and brand exposure on social media.

[0077] Through the interaction between the financial data collection unit and the market data collection unit, the changes in product sales in the next cycle are estimated, and the data indicator curve chart is generated through the multi-dimensional data fusion module.

[0078] The product grade proportion analysis unit calculates the market share of low-end, mid-range and high-end products that have been sold through the interactive data of the financial data collection unit and the market data collection unit;

[0079] The internal management data unit also includes a sales data analysis unit, an after-sales service data analysis unit, and a production data unit;

[0080] The sales data analysis unit uses the internal resource record library to determine the sales records of the sales department for low, medium and high-end products;

[0081] The after-sales service data analysis unit uses the internal resource record library to determine the handover service and after-sales service records of all products sold by the after-sales service department;

[0082] The production data unit uses the internal resource record library to determine the production department's production quantities of low, medium, and high-end products, as well as the normal daily output quantity of products.

[0083] The data analysis module centrally stores and manages the data from the acquisition module and the data multi-dimensional fusion module through the data warehouse system, provides a unified data view, obtains historical data and current data through analysis of the time period dimension, and conducts comparative analysis to derive the production quantities of low-, medium-, and high-end products required.

[0084] The risk assessment module includes risk type unit, risk prevention unit, production scheduling unit and production monitoring unit;

[0085] The risk type unit assesses the stability and reliability of raw material supply, as well as the supplier's reputation and delivery capabilities, and evaluates the technical difficulties and time delays in the application of new technologies that may be encountered in the production of low-, medium-, and high-end products;

[0086] The risk prevention unit formulates reasonable inventory management strategies, sets safety stock quantities and reorder points, and responds to market demand uncertainties through effective inventory management to ensure that production quantities are consistent with estimates;

[0087] The production monitoring unit uses modern information technology to monitor production equipment in real time. By collecting production data and equipment working intensity, it can promptly analyze the number of products produced that day.

[0088] The production scheduling unit rationally arranges production tasks based on real-time monitoring of equipment conditions, employee skill assessment levels, and production capacity to ensure that production quantities are consistent with estimates;

[0089] The risk assessment module is based on the company's current inventory quantities of low-, medium- and high-end products, the quantities required by the low-, medium- and high-end markets analyzed by the data analysis module, and the current daily production efficiency of the production line.

[0090] Risk assessment module evaluation formula:

[0091]

[0092] Among them, α represents the production capacity utilization rate, M represents the actual output, which is the number of products actually completed within a specified time, and m represents the theoretical production capacity, which is the maximum output that the factory can achieve;

[0093]

[0094] Where T represents the time schedule compliance rate, T 实 Indicates the actual completion time, the actual time spent on completing the current production task, t 规 Indicates the time limit originally planned for completing the production task;

[0095]

[0096] in The difference between the estimated and actual products, S represents the number of estimated products, and P represents the actual number of completed products;

[0097]

[0098] Among them, ω represents the comprehensive evaluation index;

[0099] According to the inventory quantity of the product, the comprehensive evaluation index range of the product production is set to [90%~94%]. When the ω value of the product is between [90%~94%], the quantity of product production plus the quantity of inventory products meet the estimated product demand, and the quantity of products produced is adapted to the estimated quantity of products required for production. When the ω value of the product is less than 90%, the quantity of product production plus the quantity of inventory products is lower than the estimated product quantity demand, and the output needs to be increased. When the ω value of the product is greater than 94%, the quantity of product production plus the quantity of inventory products is higher than the estimated product quantity demand, and the production quantity is in excess.

[0100] In the present invention, a monitoring and early warning method based on multi-dimensional collaborative risk identification collects the company's financial information, low-, medium- and high-end product sales and market data for this year through a multi-dimensional data fusion module, analyzes internal sales records and the years of use of consumer products collected through after-sales return visits, questionnaires, and product registration information, determines the intended purchasing users, and then analyzes the market share of low-, medium- and high-end products. The data analysis module uses the sales data of historical products and the company's low-, medium- and high-end products in the market this year to analyze the number of products purchased by intended customers in real time, and analyzes the low-, medium- and high-end products to be produced in the next cycle. The risk assessment module evaluates the output of each product based on the current stock quantity of the company's low, medium and high-end products and the quantity required by the low, medium and high-end markets analyzed by the data analysis module, as well as the current daily production efficiency of the production line. It evaluates whether the production quantity of low, medium and high-end products can meet the quantity of products required by the market before the end of the cycle. According to the inventory quantity of the products, the comprehensive evaluation index range of the required product production is set to [90%~94%]. When the ω value of the product is between [90%~94%], the production quantity of the product plus the inventory quantity of the products meet the estimated product demand, and the production quantity of the products is appropriate to the estimated production quantity. When the ω value of a product is less than 90%, the quantity of product production plus the quantity of inventory products is lower than the estimated quantity demand, and the output needs to be increased. When the ω value of a product is greater than 94%, the quantity of product production plus the quantity of inventory products is higher than the estimated quantity demand, and the production quantity is in excess. The results obtained after the risk assessment module evaluates the situation, and it is necessary to analyze the production speed and personnel mobilization of each product within the prescribed period in multiple dimensions, and formulate respective predetermined solutions for low, medium and high-end products, publish them through the early warning release module, and then automatically push the information to the production managers of low, medium and high-end products. The managers will allocate processing equipment and make timely arrangements for the staff. Mobilization to meet production needs, this multi-dimensional collaborative risk identification monitoring and early warning system can timely estimate the number of products required for the next cycle, and can produce the required number of products based on the estimated number of products required. It can also warn in advance whether the batch of products can be completed within the specified time. At the same time, it enables information exchange on the production status of low, medium and high-end products, and is more efficient in equipment usage and personnel mobilization, so that the number of products produced can adapt to meet the estimated number of products required, prevent the number of products from exceeding market demand, resulting in unsalable products and inventory backlogs, and also prevent the number of products from failing to meet market demand, resulting in product out-of-stock and customer loss.

[0101] Example 2: Please refer to Figures 1 to 6 , which is different from embodiment 1 in that the after-sales service data analysis unit includes a fault type analysis unit and an after-sales processing unit;

[0102] The fault type analysis unit includes an after-sales service recording unit, a product fault code recording unit, and a background service software fault recording unit;

[0103] After the after-sales service record unit completes the fault resolution through after-sales personnel, it records the product model, serial number, and fault code as a company record report;

[0104] The product fault code recording unit reports the product model, serial number, and fault code through the product management program downloaded on the customer's mobile phone and the mobile program downloaded by the area service personnel, and serves as a company record report;

[0105] The fault recording unit of the background service software records the product model, serial number, and fault code through the real-time updated data of the company's background, and uses it as a company record report.

[0106] The after-sales processing unit includes a telephone communication processing unit, a manual customer service connection unit, and an on-site service processing unit;

[0107] The telephone communication processing unit displays the alarm on the service personnel program based on the fault alarm information. The service personnel will independently contact the management personnel of the product in the area to resolve the fault alarm. The customer sees the fault alarm information and informs the service personnel or manual customer service by phone. The customer directly calls the manual customer service. The customer service informs the service personnel in the area of the customer's contact information and solves the customer's problem. Fault alarms that cannot be resolved by phone require on-site repair by service personnel in the area where the product is located.

[0108] In the present invention, a monitoring and early warning method based on multi-dimensional collaborative risk identification is provided. After-sales service personnel, customers who purchase products and customers of the company can download the product program APP on their mobile phones. The service personnel program displays an alarm, and the service personnel independently contact the management personnel of the product in the area. If the fault problem can be solved by phone, there is no need for on-site repair. When the fault alarm cannot be solved, the after-sales service personnel need to perform on-site repair to solve the fault alarm. After the after-sales service personnel completes the fault solution, the product model, serial number, and fault code need to be recorded as a company record report. The product fault code recording unit records the fault problem through the customer. The product management program downloaded on the mobile phone and the mobile phone program downloaded by the district service personnel can display the fault code in time, repair the product fault, and report the product model, serial number, fault code, and use it as a company record report. The background service software fault recording unit updates the data in real time through the company's background. The customer service records the product model, serial number, and fault code and uses it as a company record report, and informs the after-sales service personnel in the area to carry out repairs. The after-sales service personnel quickly solve the product failure problem, which improves the speed at which the after-sales service personnel solve product problems, thereby improving the service quality of the service personnel and retaining potential customers.

[0109] A monitoring and early warning method based on multi-dimensional collaborative risk identification, the steps of which are as follows:

[0110] S1: The acquisition module collects historical data and analyzes product sales volume, purchasing demographics, product lifecycles, and the current economic environment in each past cycle. This helps identify potential buyers and non-buyers, as well as the sales share of low-, mid-, and high-end products.

[0111] S2: Through the multi-dimensional data fusion module, the company's financial information, sales volume of low-, mid-, and high-end products, and market data for the current year are collected. Internal sales records are analyzed along with information on the years of use of consumer products collected through after-sales visits, questionnaires, and product registration information. This helps identify potential buyers and further analyzes the market share of low-, mid-, and high-end products.

[0112] S3: The data analysis module uses historical product sales data and the company's current year's market share of low-, medium-, and high-end products to analyze the number of products purchased by potential customers in real time and calculate the production volume of low-, medium-, and high-end products to be produced in the next cycle.

[0113] S4: Risk Assessment Module: This module assesses whether the production quantities of low-, medium-, and high-end products can meet market demand by the end of the cycle based on the company's current inventory quantities of low-, medium-, and high-end products, the quantities required by the low-, medium-, and high-end markets as analyzed by the data analysis module, and the current daily production efficiency of the production lines.

[0114] S5: The results obtained after the risk assessment module's evaluation need to be analyzed in multiple dimensions to determine the production speed and personnel deployment of each product within the specified period, and to formulate respective predetermined solutions for low, medium and high-end products, which will be released through the early warning release module and then automatically pushed to the production managers of each of the low, medium and high-end products.

[0115] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0116] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the invention, and the scope of the invention will be limited.

Claims

1. A monitoring and early warning system based on multi-dimensional collaborative risk identification, characterized by: It includes acquisition module, multi-dimensional data fusion module, data analysis module, risk assessment module, warning release module, and information push module; The acquisition module collects historical data, analyzes the sales volume of products in each period of previous years, the purchasing intentions of the purchasing groups and the service life of the products, and determines the users who intend to purchase and those who do not; The multi-dimensional data fusion module collects the company's financial information, sales volume of low-, medium-, and high-end products, and market data for the current year, and determines the number of products that potential users will purchase based on internal sales records and the years of use of consumers' purchased products collected through after-sales visits, questionnaires, and product registration information. The data analysis module uses the sales data of previous products and the sales share of the company's low, medium and high-end products in the market this year to analyze the number of products purchased by potential customers in real time; The risk assessment module evaluates whether the production quantity of low, medium and high-end products can meet the market demand before the end of the cycle based on the current stock quantity of the company's low, medium and high-end products, the quantity required by the mid-to-high-end market analyzed by the data analysis module, and the current daily production efficiency of the production line.

2. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 1 is characterized by: The collection module includes a crowd collection unit, a season cycle unit, a usage cycle unit and an economic environment collection unit; The crowd collection unit uses internal data sources, social software and telephone consultation to count the number of purchasers in different time periods, different regions, different ages and genders, and determines the number of users who intend to purchase again among the historical purchasers; The seasonal cycle unit uses a time recorder to clearly record the sales quantity and sales data of products in each cycle by month, quarter and year, and to highlight the periods of historical hot sales of products; The usage cycle unit collects the time of historical product purchases and actual product usage through internal data sources, sorts out products that are about to reach their service life, and uses social software and telephone consultation to inquire whether the products need to be replaced; The economic environment collection unit monitors macroeconomic indicators, industry development trends, technology updates and annual indicators of key development projects in real time through network computers, and collects corporate stock price trends and industry average financial indicator market data from financial information websites, securities trading platforms and external data sources through web crawler technology.

3. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 1 is characterized by: The data multi-dimensional fusion module includes a financial data collection unit, a product grade ratio analysis unit, a market data collection unit and an internal management data unit; The financial data acquisition unit obtains the company's balance sheet, income statement, cash flow statement, financial statement data, and various financial indicator data through the internal database; The market data collection unit calculates the proportion of sales of low-, medium-, and high-quality products of an enterprise in a specific market to the total market sales, and measures the brand influence, market recognition, and market competitiveness of the enterprise through evaluation data from market research institutions and brand exposure on social media; Through the interaction between the financial data collection unit and the market data collection unit, the changes in product sales in the next cycle are estimated, and the data indicator curve chart is generated through the multi-dimensional data fusion module.

4. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 3 is characterized by: The product grade proportion analysis unit calculates the market share of low-end, medium-end and high-end products that have been sold through the interaction of data between the financial data collection unit and the market data collection unit; The internal management data unit also includes a sales data analysis unit, an after-sales service data analysis unit and a production data unit; The sales data analysis unit determines the sales records of the sales department for low-, medium-, and high-priced products through the internal resource record library; The after-sales service data analysis unit determines the handover service and after-sales service records of all sold products by the after-sales service department through the internal resource record library; The production data unit determines the production quantity of low-, medium- and high-end products and the normal daily output quantity of products by the production department through the internal resource record library.

5. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 1 is characterized by: The data analysis module centrally stores and manages the data from the acquisition module and the data multi-dimensional fusion module through the data warehouse system, provides a unified data view, obtains historical data and current data through analysis of the time period dimension and performs comparative analysis to derive the production quantities of low-, medium- and high-end products required.

6. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 5 is characterized by: The risk assessment module includes a risk type unit, a risk prevention unit, a production scheduling unit and a production monitoring unit; The risk type unit assesses the stability and reliability of raw material supply, as well as the supplier's reputation and delivery capabilities, and evaluates the technical difficulties and time delays in the application of new technologies that may be encountered in the production of low-, medium-, and high-end products; The risk prevention unit formulates reasonable inventory management strategies, safety stock quantities and order point settings, and through effective inventory management, copes with the uncertainty of market demand and ensures that production quantities are consistent with estimates; The production monitoring unit uses modern information technology to monitor production equipment in real time, collects production data and equipment working intensity, and promptly analyzes the number of products produced that day; The production scheduling unit rationally arranges production tasks based on real-time monitoring of equipment status, employee skill assessment levels, and production capacity to ensure that production quantities are consistent with estimates; The risk assessment module is based on the current stock quantities of the company's low, medium and high-end products and the quantities required by the low, medium and high-end markets analyzed by the data analysis module, as well as the current daily production efficiency of the production line.

7. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 6 is characterized by: The risk assessment module evaluation formula: Among them, α represents the production capacity utilization rate, M represents the actual output, which is the number of products actually completed within a specified time, and m represents the theoretical production capacity, which is the maximum output that the factory can achieve; Where T represents the time schedule compliance rate, T 实 Indicates the actual completion time, the actual time spent on completing the current production task, t 规 Indicates the time limit originally planned for completing the production task; in The difference between the estimated and actual products, S represents the number of estimated products, and P represents the actual number of completed products; Among them, ω represents the comprehensive evaluation index; According to the inventory quantity of the product, the comprehensive evaluation index range of the product production is set to [90%~94%]. When the ω value of the product is between [90%~94%], the quantity of product production plus the quantity of inventory products meet the estimated product demand, and the quantity of products produced is adapted to the estimated quantity of products required for production. When the ω value of the product is less than 90%, the quantity of product production plus the quantity of inventory products is lower than the estimated product quantity demand, and the output needs to be increased. When the ω value of the product is greater than 94%, the quantity of product production plus the quantity of inventory products is higher than the estimated product quantity demand, and the production quantity is in excess.

8. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 4 is characterized by: The after-sales service data analysis unit includes a fault type analysis unit and an after-sales processing unit; The fault type analysis unit includes an after-sales service recording unit, a product fault code recording unit and a background service software fault recording unit; The after-sales service recording unit records the product model, serial number, and fault code as a company record report after the after-sales personnel have resolved the fault; The product fault code recording unit reports the product model, serial number, and fault code through the product management program downloaded on the customer's mobile phone and the mobile phone program downloaded by the area service personnel, and serves as a company record report; The back-end service software fault recording unit records the product model, serial number, and fault code through the data updated in real time by the company's back-end, and uses it as a company record report.

9. The monitoring and early warning system based on multi-dimensional collaborative risk identification according to claim 8, characterized in that: The after-sales processing unit includes a telephone communication processing unit, a manual customer service connection unit and an on-site service processing unit; The telephone communication processing unit displays an alarm on the service personnel program based on the fault alarm information. The service personnel independently contacts the manager of the product in the area to resolve the fault alarm. The customer sees the fault alarm information and informs the service personnel or manual customer service by phone. The customer directly contacts the manual customer service by phone. The customer service informs the service personnel in the area of the customer's contact information and solves the customer's problem. Fault alarms that cannot be resolved by phone require on-site repair by service personnel in the area where the product is located.

10. A monitoring and early warning method based on multi-dimensional collaborative risk identification, referring to the monitoring and early warning system based on multi-dimensional collaborative risk identification according to any one of claims 1 to 9, comprising the following steps: S1: The acquisition module collects historical data and analyzes product sales volume, purchasing demographics, product lifecycles, and the current economic environment in each past cycle. This helps identify potential buyers and non-buyers, as well as the sales share of low-, mid-, and high-end products. S2: Through the multi-dimensional data fusion module, the company's financial information, sales volume of low-, mid-, and high-end products, and market data for the current year are collected. Internal sales records are analyzed along with information on the years of use of consumer products collected through after-sales visits, questionnaires, and product registration information. This helps identify potential buyers and further analyzes the market share of low-, mid-, and high-end products. S3: The data analysis module uses historical product sales data and the company's current year's market share of low-, medium-, and high-end products to analyze the number of products purchased by potential customers in real time and calculate the production volume of low-, medium-, and high-end products to be produced in the next cycle. S4: Risk Assessment Module: This module assesses whether the production quantities of low-, medium-, and high-end products can meet market demand by the end of the cycle based on the company's current inventory quantities of low-, medium-, and high-end products, the quantities required by the low-, medium-, and high-end markets as analyzed by the data analysis module, and the current daily production efficiency of the production lines. S5: The results obtained after the risk assessment module's evaluation need to be analyzed in multiple dimensions to determine the production speed and personnel deployment of each product within the specified period, and to formulate respective predetermined solutions for low, medium and high-end products, which will be released through the early warning release module and then automatically pushed to the production managers of each of the low, medium and high-end products.

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