Intelligent management system for centralized meal distribution

Abstract

The invention discloses an intelligent management system for centralized meal delivery, and relates to the technical field of meal delivery management, and the main scheme is that meal order information data of a user side can be received and analyzed; kitchen workstations are selected according to analysis, a large number of orders are rapidly processed, automatic classification statistics is achieved, and manual operation time and error rate are reduced; calculating a food material purchase quantity according to order demands and inventory data, generating a list, and screening supplier transactions; operation data of cooking and kitchen equipment can be monitored in real time, cooking time is adjusted, and equipment abnormity is judged and early warning is performed; the distribution route can be planned according to the client address and the distribution requirement, and the time is estimated to determine the final route; customer feedback can be collected to generate reports, so that enterprises can improve services in time; data of the modules are mutually communicated and coordinated, resources are reasonably distributed, and waste is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of catering delivery management, and in particular to an intelligent management system for centralized dining delivery. Background Art

[0002] With the continuous development of society and the significantly accelerated pace of people's lives, the demand for centralized meal delivery is growing. In large enterprises, schools, hospitals and other places, centralized meal delivery has become a common solution to meet the needs of a large number of people dining at the same time.

[0003] However, the traditional meal distribution management system has a single management method and is unable to select the appropriate kitchen workstation according to the actual situation of the order, resulting in slow food delivery, long delivery distance, and low delivery efficiency; and lack of control over the quality and cost of ingredients, resulting in unstable food quality and unstable food prices and costs, chaotic order management, and unable to meet the growing demand for high-quality delivery. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent management system for centralized meal delivery. Through the collaborative work of multiple modules, a complete closed-loop management system is formed from order receipt to meal delivery and quality monitoring, which solves the problems of low delivery efficiency, difficulty in real-time monitoring of food quality, chaotic order management, and inability to meet the growing demand for high-quality delivery.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A centralized meal delivery intelligent management system, comprising: an order management module, for receiving meal order information data from a user terminal, analyzing the meal order information data, and selecting a kitchen workstation according to the analysis results;

[0008] The food procurement module calculates the purchase quantity of different ingredients based on the order demand data in the meal order information data and the inventory data of the kitchen workstation , generate a purchase list, and screen suppliers for docking and transactions;

[0009] The cooking monitoring module is used to monitor cooking data in real time and adjust cooking time; it also monitors the operating data of kitchen equipment, analyzes the operating data, determines whether there are any abnormalities in the kitchen equipment, and issues warning instructions when an abnormality occurs;

[0010] The delivery planning module plans the delivery route based on the customer address and delivery requirements in the meal order information data, estimates the delivery time T of different delivery routes, and determines the delivery route for this time based on the delivery time T;

[0011] The customer feedback module is used to collect customer feedback information and generate data analysis reports to improve service quality.

[0012] In the preferred solution of the centralized dining distribution intelligent management system, the method of selecting the kitchen workstation is:

[0013] Meal order information data includes at least: order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations ; By order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations Calculate the kitchen score index for each order corresponding to different kitchen workstations , the formula is as follows:

[0014] ;

[0015] in: is the urgency of the i-th order, with a value of 1 to 5; i is 1, 2, 3...k, k is the total number of orders, with a value of a positive integer; the number of orders received It refers to the number of orders received by the cth kitchen workstation, where c is 1, 2, 3...g, and g is the total number of kitchen workstations, which is a positive integer; It refers to the delivery distance between the dining location of the i-th order and the c-th kitchen workstation; The urgency of the order The weight coefficient ranges from 0.2 to 0.4. The number of orders received for different kitchen workstations The weight coefficient ranges from 0.3 to 0.4; The delivery distance between the dining location and different kitchen workstations The weight coefficient ranges from 0.2 to 0.3. , i is the order number, c is the kitchen number;

[0016] The kitchen scoring index of different kitchen workstations For comparison, select Kitchen Rating Index The kitchen workstation corresponding to the minimum value is used as the kitchen workstation for the current order.

[0017] In the preferred solution of the centralized dining distribution intelligent management system mentioned above: Calculate the purchase quantity of different ingredients for:

[0018] The order demand data at least includes the order demand of different ingredients and current inventory of different ingredients ; By order demand for different ingredients and current stock levels of different ingredients Calculate the purchase quantity of each ingredient , the formula is as follows:

[0019] ;

[0020] in: It is The purchase amount of food ingredients, Indicates the serial number of different ingredients, with values ​​of 1, 2, 3...n, where n is the number of ingredient types and is a positive integer.

[0021] In the preferred solution of the centralized meal distribution intelligent management system, the method for selecting suppliers is:

[0022] Obtain historical supply data from different suppliers; automatically select suitable suppliers based on factors such as supplier reputation, product quality and price.

[0023] The historical supply data at least includes: the number of on-time deliveries K and the total number of deliveries U. The on-time delivery rate M is calculated by the number of on-time deliveries K and the total number of deliveries U. The formula is as follows:

[0024] ;

[0025] in:

[0026] Preset delivery on-time rate threshold ; Compare the delivery on-time rate M of different suppliers with the preset delivery on-time rate threshold For comparison, if the delivery on-time rate , then the supplier meets the delivery standards; then, For comparison, if , the supplier has met the qualified standards in terms of on-time delivery rate;

[0027] Obtain the number of qualified samples of different ingredients from the delivery standard supplier's supply data And the total number of samples H, the number of qualified samples The formula for calculating the qualified rate F of food quality by comparing it with the total number of samples H is as follows:

[0028] ;

[0029] Preset sampling pass threshold , calculate the actual value F of the food quality sampling pass rate according to the formula, and then compare F with For comparison, if , then the supplier meets the qualified standard in terms of the qualified rate of food quality random inspection; then the supplier meets the random inspection standard;

[0030] Price volatility: The average price W of the current period and the average price E of the previous period. The price volatility R is calculated by the average price W of the current period and the average price E of the previous period. The formula is as follows:

[0031] ;

[0032] The threshold for price fluctuation is set as First, calculate the actual value R of price volatility according to the formula, and then compare R with If the positive and negative ranges are compared, , then the supplier meets the price volatility standard; then the supplier meets the price volatility standard;

[0033] The supply stability index CN of different suppliers is calculated based on their delivery on-time rate M, sampling qualified rate F and price fluctuation rate R. The formula is as follows:

[0034] ;

[0035] in: is the weight coefficient of the on-time delivery rate M, ranging from 0.2 to 0.3. is the weight coefficient of the sampling qualified rate F, ranging from 0.3 to 0.4. is the weight coefficient of price volatility R, ranging from 0.3 to 0.5. ;

[0036] The supply stability indexes CN of different suppliers are compared, and the supplier corresponding to the maximum supply stability index CN is selected as the current supplier.

[0037] In the preferred solution of the centralized meal distribution intelligent management system, the method for adjusting the cooking time is:

[0038] Calculating cooking time includes at least: the ideal processing time for different dishes and allowable deviation time , by the ideal processing time for different dishes and allowable deviation time Calculate standard processing time , the formula is as follows:

[0039] ;

[0040] Here's how to adjust cooking time based on temperature changes:

[0041] Adjusting cooking time according to temperature changes includes at least: the ideal temperature of different dishes , cooking time and the current actual temperature , through the ideal temperature of different dishes , cooking time is and the current actual temperature Calculate the adjusted cooking time for different dishes , the formula is as follows:

[0042] ;

[0043] in: It is the cooking index of dishes.

[0044] In the preferred solution of the centralized dining distribution intelligent management system, the method for determining whether there is an abnormality in the kitchen equipment is as follows:

[0045] Calculation of kitchen equipment failure warning indicators at least includes: current operating parameters and normal operating parameters , through the current operating parameters and normal operating parameters Calculate the fault warning index , the formula is as follows:

[0046] ;

[0047] in: is the tth monitoring value of the rth kitchen equipment in the current operating state, r is the serial number of the kitchen equipment, the value range of r is 1, 2, 3...h, h is the total number of kitchen equipment, and the value is a positive integer; t is the serial number of different monitoring values, the value range of t is 1, 2, 3...f, f is the total number of monitoring values, and the value is a positive integer; is the tth monitoring value of the rth kitchen equipment under normal operating conditions;

[0048] Preset the fault warning threshold L, and compare the kitchen equipment fault warning threshold L with the fault warning index For comparison, if , an early warning instruction will be issued.

[0049] In the preferred solution of the centralized meal delivery intelligent management system, the method for planning the delivery route is:

[0050] The delivery data at least includes the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The evaluation index value S of different routes is calculated based on the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The formula is as follows:

[0051] ;

[0052] in: is the weight coefficient of the delivery distance D, ranging from 0.2 to 0.3. is the weight coefficient of the average delivery speed V, ranging from 0.3 to 0.4, is the weight coefficient of the number of traffic nodes N, ranging from 0.3 to 0.4. ;

[0053] Preset the evaluation index value threshold A; compare the evaluation index value S of different routes with the evaluation index value threshold A, The delivery routes are screened as qualified routes;

[0054] Delivery data includes at least: delay time , through the delivery distance D, average delivery speed V and delay time The formula for calculating the delivery time T is as follows:

[0055] ;

[0056] in: For the The delay time of different traffic nodes, Indicates the serial number of different traffic nodes, with values ​​of 1, 2, 3...e, where e is a positive integer;

[0057] The delivery times T of different delivery routes are compared, and the delivery route corresponding to the maximum delivery time T is selected as the current delivery route, and the remaining delivery routes are alternative routes.

[0058] In the preferred solution of the centralized dining delivery intelligent management system, a delivery path correction module is also included, and the operation method is as follows:

[0059] Get the historical delivery time data of different delivery routes; the historical delivery time data is the historical delivery time of different delivery routes ;

[0060] Historical delivery times via different delivery routes Calculate the historical average delivery time for different routes , the formula is as follows:

[0061] ;

[0062] in, is the delivery time of the Nth delivery, where N is 1, 2, 3...X, and X is the total number of historical deliveries;

[0063] Compare the historical average delivery times for different delivery routes The delivery time T of this delivery route;

[0064] like , no route adjustment is required;

[0065] like , then reselect this route as the delivery route this time.

[0066] In the preferred solution of the centralized meal distribution intelligent management system, the method for generating a data analysis report is:

[0067] Feedback information data at least includes the scores of different evaluation indicators , through the scores of different evaluation indicators The formula for calculating customer satisfaction CS is as follows:

[0068] ;

[0069] in: It refers to The scores of the evaluation indicators, It refers to The weight of each evaluation indicator; Indicates the serial number of the evaluation index, ranging from 1 to 4;

[0070] Produce data analysis report based on dining order information data and corresponding customer satisfaction CS.

[0071] In the preferred solution of the centralized meal distribution intelligent management system, a quality inspection module is also included, and the operation method is: used to calculate the comprehensive inspection score of food quality and determine whether it meets the relevant quality standards, specifically:

[0072] The comprehensive test score of food quality is calculated as follows:

[0073] Get food testing scores by testing food after it’s purchased, cooked, and before it’s delivered , cooking test score and delivery detection score , scored through food testing , cooking test score and delivery detection score The comprehensive test score Y of food quality is calculated as follows:

[0074] ;

[0075] in: Score food testing Inspection scores for food purchases The weight coefficient ranges from 0.3 to 0.4. Score the cooking test The weight coefficient ranges from 0.2 to 0.3. Score delivery inspection The weight coefficient ranges from 0.3 to 0.5. ;

[0076] Preset quality detection standard threshold ;

[0077] The comprehensive detection score Y and the quality detection standard threshold For comparison, When the food is tested, it is judged to meet the relevant quality standards.

[0078] (III) Beneficial effects

[0079] The present invention provides an intelligent management system for centralized meal distribution, which has the following beneficial effects:

[0080] (1) Improved delivery efficiency: The order management module can quickly process a large number of orders, automatically classify and count them, and reduce the time and errors of manual operations; the delivery planning module can plan the optimal route based on a variety of factors, improve delivery efficiency, and reduce transportation time and costs;

[0081] (2) Ensure food quality: The cooking monitoring module monitors key parameters in the cooking process in real time to ensure food quality and safety; the food procurement module can accurately purchase according to order requirements and inventory status to ensure the freshness and quality of ingredients;

[0082] (3) Improve customer satisfaction: The customer feedback module can collect customer opinions and suggestions in a timely manner, so that companies can improve services and meet customer needs accordingly;

[0083] (4) Optimize resource allocation: Data interoperability and collaborative work among modules enable rational allocation of resources and avoid waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 The present invention is a schematic diagram of the working steps of a centralized meal delivery intelligent management system. DETAILED DESCRIPTION

[0085] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0086] See also Figure 1 The present invention provides a centralized meal distribution intelligent management system, comprising:

[0087] An order management module is used to receive meal order information data from a user terminal, analyze the meal order information data, and select a kitchen workstation according to the analysis results;

[0088] The method of selecting a kitchen workstation is:

[0089] Meal order information data includes at least: order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations ; By order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations Calculate the kitchen score index for each order corresponding to different kitchen workstations , the formula is as follows:

[0090] ;

[0091] Order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations These three factors are used to evaluate the suitability of each kitchen workstation for a specific order. The more urgent the order, the faster the order needs to be processed; the shorter the delivery distance, the shorter the delivery time and cost; the fewer orders the kitchen workstation has received, which means that its ability to process new orders is relatively strong. By assigning different weights to these three factors and summing them up, the kitchen scoring index is obtained. The weight setting is determined according to the company's emphasis on each factor and the actual operation strategy, and the sum of the three weights is 1, so that the scoring index is between 0 and 1. The larger the value, the more suitable the kitchen workstation is for the current order.

[0092] The order management module can quickly process a large number of orders, automatically classify and count them, and reduce the time and errors of manual operations;

[0093] The food procurement module calculates the purchase quantity of different ingredients based on the order demand data in the meal order information data and the inventory data of the kitchen workstation , generate a purchase list, and screen suppliers for docking and transactions;

[0094] The order demand data at least includes the order demand of different ingredients and current inventory of different ingredients ; By order demand for different ingredients and current stock levels of different ingredients Calculate the purchase quantity of each ingredient , the formula is as follows:

[0095] ;

[0096] in: Current inventory of different ingredients The safety stock factor is determined based on the company's experience, risk tolerance and the importance of the ingredients. Obtained from the order management system, Real-time statistics through inventory management system;

[0097] First, the order demand minus the current inventory quantity is used to get the theoretical quantity that needs to be replenished. Then, the safety inventory is added to ensure that there are enough ingredients available to avoid stockouts in the face of unexpected situations, such as a sudden increase in orders and delays in supplier delivery. This way, while meeting order demand, a certain inventory buffer can be maintained to ensure the normal operation of the business.

[0098] The historical supply data at least includes: the number of on-time deliveries K and the total number of deliveries U. The on-time delivery rate M is calculated by the number of on-time deliveries K and the total number of deliveries U. The formula is as follows:

[0099] ;

[0100] Among them: M reflects the supplier's ability to deliver goods on time;

[0101] Obtain the number of qualified samples of different ingredients from the delivery standard supplier's supply data And the total number of samples H, the number of qualified samples The formula for calculating the qualified rate F of food quality by comparing it with the total number of samples H is as follows:

[0102] ;

[0103] Among them: F reflects the quality of the goods supplied by the supplier;

[0104] Price volatility: The average price W of the current period and the average price E of the previous period. The price volatility R is calculated by the average price W of the current period and the average price E of the previous period. The formula is as follows:

[0105] ;

[0106] Among them: R is a measure of the stability of the supplier's goods price. The smaller the value, the more stable the price;

[0107] The supply stability index CN of different suppliers is calculated based on their delivery on-time rate M, sampling qualified rate F and price fluctuation rate R. The formula is as follows:

[0108] ;

[0109] This formula comprehensively evaluates the supplier's supply stability by weighted summing the three key indicators of on-time delivery rate, sampling inspection pass rate and price volatility. On-time delivery rate and sampling inspection pass rate are directly related to the normal operation of the supply chain and the quality of goods, and are usually given higher weights. Price volatility reflects the stability of costs and is also of certain importance. The weight setting is determined according to the company's emphasis on each indicator and actual business needs, and can intuitively reflect the degree of supply stability. The larger the value, the higher the supplier's supply stability.

[0110] The food procurement module can accurately purchase according to order requirements and inventory conditions to ensure the freshness and quality of ingredients;

[0111] The cooking monitoring module is used to monitor cooking data in real time and adjust cooking time; it also monitors the operating data of kitchen equipment, analyzes the operating data, determines whether there are any abnormalities in the kitchen equipment, and issues warning instructions when an abnormality occurs;

[0112] Calculating cooking time includes at least: the ideal processing time for different dishes and allowable deviation time , by the ideal processing time for different dishes and allowable deviation time Calculate standard processing time , the formula is as follows:

[0113] ;

[0114] Among them: Ideal processing time for different dishes The value range is usually a positive real number, indicating time, and the unit can be minutes or hours, which is determined according to the process requirements of the dish, empirical data or experimental determination; the allowable deviation time Usually a positive real number, representing time, unit and ideal processing time for different dishes The same is determined based on actual production conditions, quality control requirements, equipment performance and other factors;

[0115] The principle of this formula is to determine the ideal processing time, take into account the uncertainty and acceptable fluctuation range in actual production, and obtain a time interval, namely the standard processing time, by adding or subtracting the allowable deviation time. This not only clarifies the ideal processing time for dish processing, but also provides a certain degree of flexibility and fault tolerance for actual operation. Completing the processing within this time range can not only ensure the stability of dish quality, but also adapt to a certain degree of production changes;

[0116] For example, if the ideal processing time for a dish is 30 minutes and the allowable deviation time is 5 minutes, then the standard processing time is between 25 minutes and 35 minutes;

[0117] Adjusting cooking time according to temperature changes includes at least: the ideal temperature of different dishes , cooking time and the current actual temperature , through the ideal temperature of different dishes , cooking time is and the current actual temperature Calculate the adjusted cooking time for different dishes , the formula is as follows:

[0118] ;

[0119] Among them: Ideal temperature for different dishes Usually a positive number in degrees Celsius, determined according to the cooking requirements of the dish and experience, the current actual temperature It is usually a positive number in degrees Celsius and is measured in real time by a temperature sensor. k is usually a specific coefficient used to adjust the calculation of cooking time. It depends on the characteristics of the cooking process, the properties of the dish, and related cooking experience and experimental data. Its value is often determined through observation, analysis and summary of a large number of cooking practices to ensure that the calculated adjusted cooking time can meet the requirements for achieving the ideal cooking effect of the dish.

[0120] This formula is based on the principle of heat transfer and the influence of temperature on the cooking process. When the actual temperature is lower than the ideal temperature, the cooking time needs to be extended to achieve the same cooking effect. Conversely, when the actual temperature is higher than the ideal temperature, the cooking time needs to be shortened. The cooking time is adjusted by multiplying the ratio of the ideal temperature to the actual temperature by the initial cooking time to ensure that the ideal cooking effect can be achieved as much as possible under different actual temperature conditions.

[0121] Calculation of kitchen equipment failure warning indicators at least includes: current operating parameters and normal operating parameters , through the current operating parameters and normal operating parameters Calculate the fault warning index , the formula is as follows:

[0122] ;

[0123] in: It is The tth monitoring value of a kitchen device in the current operating state, r is the serial number of the kitchen device, the value range of r is 1, 2, 3...h, h is the total number of kitchen devices in the kitchen, and the value is a positive integer; t is the serial number of different monitoring values, the value range of t is 1, 2, 3...f, f is the total number of monitoring values, and the value is a positive integer; is the tth monitoring value of the rth kitchen appliance under normal operating conditions; the kitchen appliance may be an oven, an induction cooker, a steamer, etc., and the monitoring value may be current, voltage, power, etc.;

[0124] Preset the fault warning threshold L, and compare the kitchen equipment fault warning threshold L with the fault warning index For comparison, if , an early warning instruction will be issued.

[0125] It should be noted that the fault warning threshold L is set according to the critical values ​​of the working parameters of different devices in the normal state and the working parameters in the fault state, and is obtained by statistical calculation through historical experience data.

[0126] The principle of this formula is to comprehensively evaluate the system's failure risk level by comparing the difference between the current operating parameters and the normal operating parameters, and performing weighted summation based on the importance of each parameter. The difference value of each operating parameter, such as current operating parameters minus normal operating parameters, reflects the degree to which the parameter deviates from the normal state, and the weight reflects the relative importance of the parameter in the overall fault judgment.

[0127] The cooking monitoring module monitors key parameters of the cooking process in real time to ensure food quality and safety;

[0128] The delivery planning module plans the delivery route based on the customer address and delivery requirements in the meal order information data, estimates the delivery time T of different delivery routes, and determines the delivery route for this time based on the delivery time T;

[0129] The delivery data at least includes the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The evaluation index value S of different routes is calculated based on the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The formula is as follows:

[0130] ;

[0131] Among them: the number of traffic nodes N is the number of nodes such as traffic lights and intersections passed by the route, which is obtained through analysis and statistics of the route; the average delivery speed V is the average driving speed during delivery, which is a positive number, indicating that the speed unit can be kilometers per hour or meters per second, and is estimated based on historical delivery data statistics or real-time traffic information; the delivery distance D refers to the actual distance from the starting point to the end point, which is usually a positive number, indicating the distance, and the unit can be kilometers or meters;

[0132] The principle of this formula is to comprehensively consider the impact of delivery distance, average delivery speed and the number of traffic nodes on the delivery route. The delivery distance divided by the average delivery speed gives a basic estimate of the delivery time. The number of traffic nodes multiplied by the traffic node impact coefficient reflects the additional impact of traffic nodes on the delivery time. Adding these two parts together gives the evaluation index value of the route. The smaller the evaluation index value, the better the time efficiency of the route.

[0133] For example, if the delivery distance of a route is 10 km, the average delivery speed is 30 km / h, and the number of traffic nodes is 10, the weight coefficient of the number of traffic nodes is Assuming it is 0.5 minutes per time, the evaluation index value S = 10 / 30 + 0.5 × 10 = 3.33 hours.

[0134] Delivery data includes at least: delay time , through the delivery distance D, average delivery speed V and delay time The formula for calculating the delivery time T is as follows:

[0135] ;

[0136] Including: Delay time It is the extra time consumed during the delivery process due to various unexpected situations, such as traffic congestion, road construction, and weather. It is usually a positive number, representing time. The unit is the same as the delivery time, such as hours or minutes. It is estimated based on real-time traffic conditions, weather data, and historical experience.

[0137] This formula is based on the basic principle that time = distance ÷ speed. The delivery distance is divided by the average delivery speed to get the time required under ideal conditions without considering delays. The delay time is then added to comprehensively consider the impact of various unfavorable factors on delivery time, thereby more accurately estimating the actual delivery time.

[0138] For example, if the delivery distance is 50 km, the average delivery speed is 50 km / h, and the delay time is 0.5 hours, then the delivery time T = 50 / 50 + 0.5 = 1.5 hours;

[0139] The distribution planning module can plan the optimal route based on various factors, improve distribution efficiency, and reduce transportation time and costs;

[0140] The delivery route correction module obtains the historical delivery time data of different delivery routes; the historical delivery time data is the historical delivery time of different delivery routes ; Historical delivery times via different delivery routes Calculate the historical average delivery time for different routes , the formula is as follows:

[0141] ;

[0142] The principle of this formula is to sum up the historical delivery time of a certain delivery route and then divide it by the number of deliveries to get the average value of the historical delivery time of the route. The average value can reflect the general delivery time of this route in the past and help evaluate its delivery efficiency and stability.

[0143] For example, a delivery route has been delivered 5 times in history, with delivery times of 60 minutes, 50 minutes, 70 minutes, 55 minutes, and 65 minutes respectively. The average historical delivery time is =(60+50+70+55+65) / 5=60 minutes.

[0144] The customer feedback module is used to collect customer feedback information and generate data analysis reports to improve service quality, specifically:

[0145] Feedback information data at least includes the scores of different evaluation indicators , through the scores of different evaluation indicators The formula for calculating customer satisfaction CS is as follows:

[0146] ;

[0147] in: It refers to The scores of the evaluation indicators, The serial number of the evaluation index, ranging from 1 to 4, can be the satisfaction of the food, the satisfaction of the delivery speed, the service attitude of the delivery personnel, and the completeness of the delivery packaging; It refers to The weight of each evaluation indicator ranges from 0 to 1. The sum of the weights of all evaluation indicators is 1. yes The maximum value of

[0148] The principle of this formula is to calculate customer satisfaction by weighted average. Different evaluation indicators are given different weights according to their importance. Determined based on the specific content of customer feedback and company settings; the weight reflects the relative importance of each indicator in the overall satisfaction, and the score reflects the customer's specific evaluation of the indicator. In this way, multiple factors can be taken into account to measure the customer's satisfaction level more comprehensively and accurately;

[0149] The customer feedback module can collect customer opinions and suggestions in a timely manner, so that enterprises can improve services and meet customer needs;

[0150] The quality inspection module is used to conduct quality inspections during food procurement, cooking and before delivery to ensure that the food meets relevant quality standards. It may include chemical inspection and microbial inspection functions.

[0151] The calculation of the comprehensive test score of food quality includes at least: the test score of food procurement , cooking completion test score and pre-delivery inspection scores , through the detection score of food procurement , cooking completion test score and pre-delivery inspection scores The comprehensive test score Y of food quality is calculated as follows:

[0152] ;

[0153] The value range is from 0 to 100, and its specific value comes from the evaluation results of various specific testing indicators such as chemical testing, microbiological testing, etc. in each link; for example, whether a certain harmful substance exceeds the standard in chemical testing, whether the total number of bacteria in microbiological testing is within the allowable range, etc., and scores are given according to the test results and the corresponding standards.

[0154] This formula is based on the principle of weighted summation. Food quality is affected in the three stages of procurement, cooking, and distribution, and the test score at each stage reflects the quality level of that stage. By assigning corresponding weights to the test scores of each stage and performing weighted summation, a comprehensive test score is obtained to fully reflect the quality status of food throughout the entire process. The setting of weights reflects the relative importance of different stages in affecting the final food quality;

[0155] Data intercommunication and collaborative work among modules achieve rational allocation of resources and avoid waste.

[0156] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0157] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0158] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An intelligent management system for centralized meal distribution, characterized in that: include: An order management module is used to receive meal order information data from a user terminal, analyze the meal order information data, and select a kitchen workstation according to the analysis results; The food procurement module calculates the purchase quantity of different ingredients based on the order demand data in the meal order information data and the inventory data of the kitchen workstation , generate a purchase list, and screen suppliers for docking and transactions; Cooking monitoring module, used to monitor cooking data in real time and adjust cooking time; And monitor the operating data of kitchen equipment, analyze the operating data, determine whether there are any abnormalities in the kitchen equipment, and issue early warning instructions when abnormalities occur; The delivery planning module plans the delivery route based on the customer address and delivery requirements in the meal order information data, estimates the delivery time T of different delivery routes, and determines the delivery route for this time based on the delivery time T; The customer feedback module is used to collect customer feedback information and generate data analysis reports to improve service quality.

2. According to claim 1, a centralized meal distribution intelligent management system is characterized by: The method of selecting a kitchen workstation is: Meal order information data includes at least: order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations ; By order urgency , the delivery distance between dining locations and different kitchen workstations and the number of orders received by different kitchen workstations Calculate the kitchen score index for each order corresponding to different kitchen workstations , the formula is as follows: ; in: is the urgency of the i-th order, with a value of 1 to 5; i is 1, 2, 3...k, k is the total number of orders, with a value of a positive integer; It refers to the number of orders received by the cth kitchen workstation, where c is 1, 2, 3...g, and g is the total number of kitchen workstations, which is a positive integer; It refers to the delivery distance between the dining location of the i-th order and the c-th kitchen workstation; Order urgency The weight coefficient ranges from 0.2 to 0.

4. The number of orders received for different kitchen workstations The weight coefficient ranges from 0.3 to 0.4; The delivery distance between the dining location and different kitchen workstations The weight coefficient ranges from 0.2 to 0.

3. The sum is equal to 1, i is the order number, c is the kitchen number; The kitchen scoring index of different kitchen workstations For comparison, select Kitchen Rating Index The kitchen workstation corresponding to the minimum value is used as the kitchen workstation for the current order.

3. According to claim 2, a centralized meal distribution intelligent management system is characterized by: Calculate the purchase amount of different ingredients for: The order demand data at least includes the order demand of different ingredients and current inventory of different ingredients ; By order demand for different ingredients and current stock levels of different ingredients Calculate the purchase quantity of each ingredient , the formula is as follows: ; in: It is The purchase amount of food ingredients, Indicates the serial number of different ingredients, with values ​​of 1, 2, 3...n, where n is the number of ingredient types and is a positive integer.

4. The centralized meal distribution intelligent management system according to claim 3 is characterized by: The method for screening suppliers is: Obtain historical supply data from different suppliers; automatically select suitable suppliers based on factors such as supplier reputation, product quality and price. The historical supply data at least includes: the number of on-time deliveries K and the total number of deliveries U. The on-time delivery rate M is calculated by the number of on-time deliveries K and the total number of deliveries U. The formula is as follows: ; in: Preset delivery on-time rate threshold ; Compare the delivery on-time rate M of different suppliers with the preset delivery on-time rate threshold Compare, if the delivery on-time rate M ≥ the delivery on-time rate threshold , then the supplier meets the delivery standards; then, compare M with For comparison, if , the supplier has met the qualified standards in terms of on-time delivery rate; Obtain the number of qualified samples of different ingredients from the delivery standard supplier's supply data And the total number of samples H, the number of qualified samples The formula for calculating the qualified rate F of food quality by comparing it with the total number of samples H is as follows: ; Preset sampling pass threshold , calculate the actual value of the food quality sampling pass rate according to the formula , then, F and For comparison, if , then the supplier meets the qualified standard in terms of the qualified rate of food quality random inspection; then the supplier meets the random inspection standard; Price volatility: The average price W of the current period and the average price E of the previous period. The price volatility R is calculated by the average price W of the current period and the average price E of the previous period. The formula is as follows: ; The threshold for price fluctuation is set as First, calculate the actual value R of price volatility according to the formula, and then compare R with If the positive and negative ranges are compared, , then the supplier meets the price volatility standard; then the supplier meets the price volatility standard; The supply stability index CN of different suppliers is calculated based on their delivery on-time rate M, sampling qualified rate F and price fluctuation rate R. The formula is as follows: ; in: is the weight coefficient of the on-time delivery rate M, ranging from 0.2 to 0.

3. is the weight coefficient of the sampling qualified rate F, ranging from 0.3 to 0.

4. is the weight coefficient of price volatility R, ranging from 0.3 to 0.

5. Add up to 1; The supply stability indexes CN of different suppliers are compared, and the supplier corresponding to the maximum supply stability index CN is selected as the current supplier.

5. The centralized meal distribution intelligent management system according to claim 4 is characterized by: To adjust the cooking time: Calculating cooking time includes at least: the ideal processing time for different dishes and allowable deviation time , by the ideal processing time for different dishes and allowable deviation time Calculate standard processing time , the formula is as follows: ; Here's how to adjust cooking time based on temperature changes: Adjusting cooking time according to temperature changes includes at least: the ideal temperature of different dishes , cooking time and the current actual temperature , through the ideal temperature of different dishes , cooking time is and the current actual temperature Calculate the adjusted cooking time for different dishes , the formula is as follows: ; Where: k is the cooking index of the dish.

6. The centralized dining distribution intelligent management system according to claim 4 is characterized in that The methods for judging whether there are abnormalities in kitchen equipment are as follows: Calculation of kitchen equipment failure warning indicators at least includes: current operating parameters and normal operating parameters , through the current operating parameters and normal operating parameters Calculate the fault warning index , the formula is as follows: ; in: is the tth monitoring value of the rth kitchen equipment in the current operating state, r is the serial number of the kitchen equipment, the value range of r is 1, 2, 3...h, h is a positive integer; t is the serial number of different monitoring values, the value range of t is 1, 2, 3...f, f is a positive integer; is the tth monitoring value of the rth kitchen equipment under normal operating conditions; Preset the fault warning threshold L, and compare the kitchen equipment fault warning threshold L with the fault warning index For comparison, if , an early warning instruction will be issued.

7. The centralized meal distribution intelligent management system according to claim 6 is characterized by: The method for planning delivery routes is: The delivery data at least includes the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The evaluation index value S of different routes is calculated based on the delivery distance D, the average delivery speed V, and the number of traffic nodes N. The formula is as follows: ; in: is the weight coefficient of the delivery distance D, ranging from 0.2 to 0.

3. Average delivery speed The weight coefficient ranges from 0.3 to 0.

4. is the weight coefficient of the number of traffic nodes N, ranging from 0.3 to 0.

4. ; Preset the evaluation index value threshold A; compare the evaluation index value S of different routes with the evaluation index value threshold A, and the evaluation index value The delivery routes with the evaluation index value threshold A are screened as qualified routes; Delivery data includes at least: delay time , through the delivery distance D, average delivery speed V and delay time The formula for calculating the delivery time T is as follows: ; in: For the The delay time of different traffic nodes, Indicates the serial number of different traffic nodes, with values ​​of 1, 2, 3...e, where e is a positive integer; The delivery times T of different delivery routes are compared, and the delivery route corresponding to the maximum delivery time T is selected as the current delivery route, and the remaining delivery routes are alternative routes.

8. The centralized meal distribution intelligent management system according to claim 7 is characterized by: It also includes a delivery path correction module, which is run as follows: Get the historical delivery time data of different delivery routes; the historical delivery time data is the historical delivery time of different delivery routes ; Historical delivery times via different delivery routes Calculate the historical average delivery time for different routes , the formula is as follows: ; in, is the delivery time of the Nth delivery, where N is 1, 2, 3...X, and X is the total number of historical deliveries; Compare the historical average delivery times for different delivery routes The delivery time T of this delivery route; like , no route adjustment is required; like , then reselect this route as the delivery route this time.

9. The centralized meal distribution intelligent management system according to claim 8, characterized in that: The method to generate data analysis report is: Feedback information data at least includes the scores of different evaluation indicators , through the scores of different evaluation indicators The formula for calculating customer satisfaction CS is as follows: ; in: It refers to The scores of the evaluation indicators, It refers to The weight of each evaluation indicator; Indicates the serial number of the evaluation index, ranging from 1 to 4; Produce data analysis report based on dining order information data and corresponding customer satisfaction CS.

10. The centralized meal distribution intelligent management system according to claim 9, characterized in that: It also includes a quality inspection module, which is used to calculate the comprehensive inspection score of food quality and determine whether it meets the relevant quality standards, specifically: The comprehensive test score of food quality is calculated as follows: Get food testing scores by testing food after it’s purchased, cooked, and before it’s delivered , cooking test score and delivery detection score , scored through food testing , cooking test score and delivery detection score Calculate the comprehensive test score of food quality , the formula is as follows: ; in: Score food testing Inspection scores for food purchases The weight coefficient ranges from 0.3 to 0.

4. Score the cooking test The weight coefficient ranges from 0.2 to 0.

3. Score delivery inspection The weight coefficient ranges from 0.3 to 0.

5. ; Preset quality detection standard threshold ; The comprehensive test score Quality detection threshold For comparison, When the food is tested, it is judged to meet the relevant quality standards.

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