Automatic restaurant kitchen order management method and system

Abstract

The invention relates to the technical field of order processing, in particular to an automatic management method and system for restaurant kitchen orders, and the method comprises the steps: collecting dish process rhythm and post task data, analyzing task cycle deviation, generating rhythm coupling indexes in a standardized manner, dividing task priority partitions, constructing order configuration snapshots, and achieving automatic scheduling. According to the method and the device, the node task duration and the sorting index in the dish execution path are obtained, so that comprehensive quantification of dish processing rhythms can be formed, and the processing cycle of each dish has a rhythm characteristic before the task is released; and collecting the task numbers and the post identification codes of the posts during the operation period of the kitchen, and forming real-time expression of the current task bearing capacity and the response state of each post in combination with the task quantity and the frequency identifiers in unit time. And further extracting a cycle deviation combination and standardizing the cycle deviation combination by calling the average processing cycle of the same kind of dishes in different posts to form a rhythm coupling index between the posts and the dishes.

Description

Technical Field

[0001] The present invention relates to the technical field of order processing, and in particular to a method and system for automated management of restaurant kitchen orders. Background Art

[0002] The field of order processing technology encompasses systematic methods and devices for receiving, processing, and transmitting user-submitted order information. The core of this technology is the comprehensive management of order data, from front-end user input to back-end fulfillment responses. This encompasses order generation, data conversion, task allocation, status tracking, and execution feedback. Order processing technology is widely used in a variety of industries, including e-commerce, retail distribution, and restaurant management.

[0003] The automated restaurant kitchen order management method collects and analyzes customer order information, converts it into kitchen task information, and automatically issues instructions to relevant operations based on dish classification and production process requirements, while also synchronizing schedule information. This method addresses technical aspects such as order information processing, dish task assignment, task sequence control, completion status marking, and kitchen information synchronization. By establishing data mapping rules based on menu items and establishing corresponding relationships between the logical sequence of dish production and work nodes, it implements a multi-position collaboration mechanism within the kitchen, replacing manual communication and recording with electronic data push.

[0004] Existing automated restaurant kitchen order management methods rely solely on the collection and conversion of order information, failing to dynamically capture the processing cycles and cadence of tasks within each dish. This results in an inability to effectively represent the inter-task cadence. In scenarios where multiple tasks are running simultaneously, it's difficult to clearly identify the processing time differences between tasks and dishes, making it difficult to prioritize tasks properly. This can lead to concentrated resource allocation or repeated waiting. Task dispatching lacks a systematic integration of actual task duration and node ranking, resulting in information gaps between nodes during kitchen scheduling. This is particularly true when processing high-concurrency orders, where tasks frequently accumulate at specific tasks, causing operational stalls. Task status recording primarily relies on static tags, failing to provide a continuous representation of task activity levels and lacking data support for assessing differences in task processing cycles. For example, when multiple dishes require simultaneous frying, cutting, or plating, the order of task execution often misaligns with the dish cadence, reducing overall delivery efficiency and hindering collaborative processes. This can cause actual order fulfillment to deviate from control expectations, impacting service quality and kitchen efficiency. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a restaurant kitchen order automation management method and system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for automated management of restaurant kitchen orders, comprising the following steps:

[0007] S1: Obtain the process execution path of the dish in the current order of the restaurant kitchen, collect the duration of the node task and the node sorting index in the path, and obtain the dish node beat cycle;

[0008] S2: Obtain the task number record of each position during the kitchen operation, and generate a position task receiving list based on the position identification code;

[0009] S3: Based on the dish node beat cycle and the job task receiving list, call the average processing cycle time of similar dishes in each job task record, calculate the difference interval between the target cycle and the current dish node beat cycle, extract the task cycle deviation combination between each job and dish and perform normalization processing, use the normalized value as the rhythm coupling index of the job and dish, and obtain the job beat overlap coefficient;

[0010] S4: Divide the job beat overlap coefficient into multiple intervals, extract the partition attribution numbers of all tasks, and obtain a task priority partition number set;

[0011] S5: Construct a current order configuration distribution structure for the kitchen based on the assigned task numbers in the task priority partition number set, and mark the distribution state as a snapshot of the overall scheduling state under the current control conditions to obtain an automated order scheduling result.

[0012] The present invention has the following improvements: the dish node beat cycle specifically refers to the total duration of the path, the node sorting index structure, and the total rhythm of the dish process; the job task receiving list includes the job identification code, the number of tasks per unit time, and the active cycle frequency identifier; the job beat overlap coefficient includes the dish cycle deviation interval, the job rhythm response value, and the standardized matching index; the task priority partition number set specifically refers to the priority transfer area task number, the intermediate candidate area task number, and the scheduling buffer area task number; the order automation scheduling result includes the task partition proportion structure, the partition scheduling status identifier, and the kitchen order configuration distribution map.

[0013] The present invention has been improved in that the specific steps of obtaining the process execution path of the dishes in the current order of the restaurant kitchen, collecting the duration of the node tasks and the node sorting index in the path, and obtaining the dish node beat cycle are as follows:

[0014] S101: Obtain the process execution path of all dishes in the current order of the restaurant kitchen, collect the node task number corresponding to each dish in the path and the task duration of the target node, record the process node set of each dish by task number, and bind the node number as a sorting index to establish a node sequence structure for each dish, and generate a dish node index sequence;

[0015] S102: Extracting the task duration of each node at the position corresponding to the sorting index according to the dish node index sequence, sequentially connecting the task durations of each node according to the node sorting order, and integrating all durations to obtain the total dish processing cycle;

[0016] S103: Call the total processing cycle of the dish, calibrate the process path integrity identifier of each dish according to the node sorting structure, integrate the total processing cycle of each dish from the original feeding node to the terminal plating node, and obtain the dish node beat cycle.

[0017] The present invention has been improved in that the specific steps of obtaining the task number record of each position during the operation of the kitchen and generating a position task receiving list in combination with the position identification code are as follows:

[0018] S201: Obtain the task execution records of each position during the operation of the kitchen, collect the task number and the corresponding position number in each record, group and summarize all task numbers by position number, construct a task statistics list for each position, and filter out position records with zero task quantity to obtain the position task statistics result;

[0019] S202: Based on the job task statistics, call the start timestamp of the tasks in each job, set a specified time interval window, extract the number of task numbers within the window, calculate the number of task occurrences for each job in the time period, establish a time-frequency matching relationship corresponding to the job, and obtain the job time-task frequency;

[0020] S203: According to the job time task frequency, extract the identification code of each job, combine the frequency value with the corresponding job code, establish a mapping relationship between the number of job tasks and the job identifier, integrate the current active task reception status of all jobs, and obtain a job task reception list.

[0021] The present invention has been improved in that, based on the dish node beat cycle and the job task receiving list, the average processing cycle time of similar dishes in each job task record is called, the target cycle and the current dish node beat cycle are calculated, the task cycle deviation combination between each job and dish is extracted and standardized, and the standardized value is used as the rhythm coupling index of the job and the dish. The specific steps of obtaining the job beat overlap coefficient are as follows:

[0022] S301: Based on the dish node beat cycle and the job task receiving list, call the processing time information of the matching dish category in each job task record, extract the total processing cycle of each type of dish in the corresponding job, and calculate the sample size and the average cycle of job dishes;

[0023] S302: Based on the average cycle of the position dishes, the overall execution time length and the number of tasks of all matching dishes in each position are extracted. After filtering out the position entries with insufficient number of tasks, the span information of the task completion time of similar dishes in the position is extracted, and the offset is identified with the processing period of the corresponding dish in the dish node beat cycle to obtain the position dish deviation combination;

[0024] S303: Based on the position-dish deviation combination, calibrate the positional relationship between each deviation and the corresponding position and dish number, construct a set of all deviation data intervals, classify the deviation values corresponding to each group of positions and dishes according to the interval set, establish a standardized rhythm correspondence table, use the standardized value as the rhythm coupling index of the position and the dish, and obtain the position beat overlap coefficient.

[0025] The present invention is improved in that the formula is used to calculate the job beat overlap coefficient:

[0026]

[0027] Among them, Γ θ,ψ is the beat overlap coefficient of the post θ and the dish ψ, θ is the post number, ψ is the dish number, is the offset value of the rth item executed by job θ about dish ψ, ρ θ,ψ is the number of task samples corresponding to dish ψ for position θ, P ψ is the standard beat cycle of dish ψ, which represents the ideal total processing time from the original feeding node to the terminal loading node, which is set by the dish process design specification.

[0028] The present invention is improved in that the job beat overlap coefficient is divided into multiple intervals, and the partition attribution numbers of all tasks are extracted to obtain the task priority partition number set. The specific steps are as follows:

[0029] S401: Obtain the coefficients corresponding to all tasks in the job beat overlap coefficient, set the upper limit interval, the lower limit interval and the middle buffer zone as the partition determination basis, compare and screen each task based on the overlap coefficient and the boundaries of the three intervals, identify the target segment to which each task should belong, and obtain the task partition affiliation type;

[0030] S402: Based on the task partition type, task numbers are matched and sorted with corresponding segment types. Task numbers belonging to the upper limit interval are extracted and grouped as priority transfer areas. Task numbers belonging to the lower limit interval are extracted and grouped as scheduling buffer areas. The remaining task numbers are marked as intermediate candidate areas to obtain a task partition number matching sequence.

[0031] S403: According to the task partition number matching sequence, all tasks and their partition numbers are integrated to form an index mapping structure, and the task quantity and identification structure corresponding to each partition is established to obtain a task priority partition number set.

[0032] The present invention has been improved in that the upper limit interval, the lower limit interval and the intermediate buffer zone are set as the partition determination basis, and the formula is adopted:

[0033] L=μ Γ -β·σ Γ , U=μ Γ +α·σ Γ ;

[0034] Calculate the lower limit interval boundary value L and the upper limit interval boundary value U, and number all tasks according to the corresponding Γ θ,ψ The value is filtered by interval matching to determine whether it is less than L, in the middle, or higher than U, and the partition is assigned a type label accordingly;

[0035] Among them, μ Γ For all Γ θ,ψ The average value, σ Γ For all Γ θ,ψ The standard deviation of , α and β are the coefficients for regulating the upper and lower sensitivity limits.

[0036] The present invention has been improved in that, according to the assigned task numbers in the task priority partition number set, a current order configuration distribution structure of the kitchen is constructed, and the distribution state is marked as a snapshot of the overall scheduling state under the current control conditions. The specific steps for obtaining the order automation scheduling result are as follows:

[0037] S501: extracting task numbers according to partition affiliation labels from task numbers assigned to the task priority partition number set, extracting sets of task numbers identified as priority transfer-in areas, intermediate candidate areas, and scheduling buffer areas, and grouping the numbers by category to obtain a task partition number list;

[0038] S502: Based on the task partition number list, count the number of tasks corresponding to each partition, extract the total number of all task numbers as the benchmark task amount, calculate the proportion of the number of tasks in each partition to the total number of tasks, and save the proportion value corresponding to each partition in the partition identification field to obtain the task partition proportion;

[0039] S503: Based on the task partition ratio, extract the partition ratio and task number distribution structure, combine the partition classification result and the kitchen control configuration identifier, establish a task structure mapping view of the order task in the current time period, and obtain the order automation scheduling result.

[0040] An automated restaurant kitchen order management system, comprising:

[0041] The dish beat collection module obtains the process execution path of the dishes in the current order of the restaurant kitchen, collects the duration of the node tasks and the node sorting index in the path, and obtains the dish node beat cycle;

[0042] The job frequency monitoring module obtains the task number record of each job during the operation of the kitchen, and generates a job task receiving list based on the job identification code;

[0043] The beat coupling identification module is based on the beat cycle of the dish node and the job task receiving list, calls the average processing cycle time of similar dishes in each job task record, calculates the difference interval between the target cycle and the current dish node beat cycle, extracts the task cycle deviation combination between each job and dish and performs normalization processing, uses the normalized value as the rhythm coupling index of the job and dish, and obtains the job beat overlap coefficient;

[0044] The task partitioning module divides the job beat overlap coefficient into multiple intervals, extracts the partition attribution numbers of all tasks, and obtains a task priority partition number set;

[0045] The order scheduling generation module constructs the current order configuration distribution structure of the kitchen according to the assigned task numbers in the task priority partition number set, and marks the distribution status as a snapshot of the overall scheduling status under the current control conditions to obtain the order automation scheduling result.

[0046] Compared with the prior art, the advantages and positive effects of the present invention are:

[0047] In the present invention, by obtaining the duration and sorting index of the node tasks in the dish execution path, a comprehensive quantification of the dish processing rhythm can be formed, so that the processing cycle of each dish has a rhythmic feature before the task is released; the task number and position identification code of each position during the operation of the kitchen are aggregated, and the number of tasks and frequency identifiers per unit time are combined to form a real-time expression of the current task carrying capacity and response status of each position. By calling the average processing cycle of similar dishes in different positions, the current node cycle of the target dish and the historical average are calculated, and the cycle deviation combination is further extracted and standardized to form a rhythm coupling index between the position and the dish. The interval division mechanism of the rhythm coupling index is used to realize the attribution determination and priority number division of all tasks, so that tasks can be accurately matched to different priority processing areas according to their own degree of adaptation in the position load and the dish rhythm. Finally, a scheduling snapshot of the current order structure is constructed, so that the distribution status of the entire kitchen task can be mapped and updated in real time. The above-mentioned execution actions bring about significant improvements in the accuracy of scheduling results, the rhythm coordination of task advancement, and the real-time transparency of control distribution through the collection of dish beat cycles, the standardization of task cycle differences, and the calculation mechanism of task partition attribution. It effectively alleviates the problems of resource waste and process blockage caused by information asymmetry or task rhythm conflicts in multi-position collaboration. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of the method of the present invention;

[0049] Figure 2 This is a detailed flow chart of step S1 of the present invention;

[0050] Figure 3 This is a detailed flow chart of step S2 of the present invention;

[0051] Figure 4 This is a detailed flow chart of step S3 of the present invention;

[0052] Figure 5 This is a detailed flow chart of step S4 of the present invention;

[0053] Figure 6 This is a schematic diagram of a detailed process of step S5 of the present invention;

[0054] Figure 7 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0056] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the devices or elements referred to must have a specific direction, be constructed and operate in a specific direction, and therefore should not be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0057] See also Figure 1 The present invention provides a technical solution: a method for automated management of restaurant kitchen orders, comprising the following steps:

[0058] S1: Obtain the process execution path of the dishes in the current order of the restaurant kitchen, collect the duration of the node tasks and the node sorting index in the path, integrate the duration according to the node execution order, and construct the overall execution time sequence of each dish from the initial feeding to the terminal plating, and obtain the dish node beat cycle;

[0059] S2: Obtain the task number records for each position during kitchen operation, collect the number of task occurrences within a specified time interval for each position, exclude data samples in a static state without tasks, extract the frequency sequence of task reception for each position in the active state within the current time period, and generate a position task reception list based on the position identification code;

[0060] S3: Based on the dish node beat cycle and the job task receiving list, call the average processing cycle time of similar dishes in each job task record, calculate the difference interval between the target cycle and the current dish node beat cycle, and extract the task cycle deviation combination between each job and dish after comparison. The matching deviation of each combination item is integrated and standardized. The standardized value is used as the rhythm coupling indicator of the job and dish to obtain the job beat overlap coefficient;

[0061] S4: Set the upper and lower limits of the job beat overlap coefficient and the intermediate buffer as the partition determination criteria, determine whether the overlap coefficient corresponding to each task falls within the upper limit, divide the task into a priority transfer area, a scheduling buffer area, and an intermediate candidate area, extract the partition affiliation numbers of all tasks, and obtain the task priority partition number set;

[0062] S5: Based on the assigned task numbers in the task priority partition number set, extract all task numbers by partition affiliation type, count the number of tasks in the priority transfer zone, the number of tasks in the intermediate candidate zone, and the number of tasks in the scheduling buffer zone, calculate the proportion of tasks in each zone, construct the current order configuration distribution structure of the kitchen, and mark the distribution status as a snapshot of the overall scheduling status under the current control conditions, thereby obtaining the order automation scheduling result;

[0063] The dish node beat cycle specifically includes the total duration of the path, the node sorting index structure, and the total rhythm of the dish process. The job task receiving list includes the job identification code, the number of tasks per unit time, and the active cycle frequency identifier. The job beat overlap coefficient includes the dish cycle deviation interval, the job rhythm response value, and the standardized matching index. The task priority partition number set specifically refers to the priority transfer area task number, the intermediate candidate area task number, and the scheduling buffer task number. The order automation scheduling results include the task partition ratio structure, the partition scheduling status identifier, and the kitchen order configuration distribution map.

[0064] See also Figure 2 , obtain the process execution path of the dish in the current order of the restaurant kitchen, collect the duration of the node task and the node sorting index in the path, and obtain the specific steps of the dish node beat cycle as follows:

[0065] S101: Obtain the process execution path of all dishes in the current order of the restaurant kitchen, collect the node task number corresponding to each dish in the path and the task duration of the target node, record the process node set of each dish by task number, and bind the node number as a sorting index to establish a node sequence structure for each dish, and generate a dish node index sequence;

[0066] First, the order data received in real time in the kitchen order management system should be retrieved and analyzed, and the types and quantity information of dishes involved in the order should be extracted item by item. The standard process path corresponding to each dish should be matched through the menu database. Each path includes multiple nodes such as raw material preparation, preliminary processing, cooking, intermediate plating and finished product plating. These nodes are numbered, and task numbers are assigned to each node according to the execution process of the kitchen automation system or manual operation. For example, the process path of scrambled eggs with tomatoes is node A1 (beating eggs), A2 (cutting tomatoes), A3 (frying), and A4 (plating). Assuming that the task numbers are T101, T102, T103, and T104, and the task duration is 3 minutes, 2 minutes, 5 minutes, and 1 minute, the system binds the nodes to the task numbers to construct an ordered node structure. The process path of scrambled eggs with tomatoes is sorted according to the node number to obtain the node index sequence T101→T102→T103→T104. The same steps are performed for each dish to collect the path and assign tasks. The node number sorting adopts ascending logic to ensure the consistency of the node order. For example, for Kung Pao Chicken, it may be T201→T202→T203→T204→T205, where each node may be cutting chicken, preparing sauce, stir-frying, adding ingredients, and plating. If the task duration is 4 minutes, 2 minutes, 6 minutes, 2 minutes, and 1 minute respectively, the node structure is bound to the node set {T201, T202, T203, T204, T205}, where T201 is ranked first and T205 is ranked last, forming the index structure of the dish processing order.

[0067] S102: Extract the task duration of each node at the position corresponding to the sorting index according to the dish node index sequence, connect the task duration of each node in sequence according to the node sorting order, and integrate all the durations to obtain the total dish processing cycle;

[0068] To extract the task duration of each node at the corresponding position of the sorted index, it is necessary to traverse the node index of each dish. During the traversal process, the corresponding duration parameters are extracted according to the node number sequence. For example, the node sequence of scrambled eggs with tomatoes is T101→T102→T103→T104, and the task durations are 3, 2, 5, and 1 minutes respectively. These time values are connected in sequence to form a processing time chain of 3+2+5+1=11 minutes, where 3 represents the egg beating time, 2 represents the tomato cutting time, 5 represents the frying time, and 1 represents the plating time. After integration, the total processing cycle of scrambled eggs with tomatoes is 11 minutes. For example, if the node sequence of another dish, Kung Pao Chicken, is T201→T202→T203→T204→T205, and the task duration is 4, 2, 6, 2, and 1 minutes, the total processing cycle is 4+2+6+2+1=15 minutes. The duration of each dish is integrated according to its node structure. In the system, it can be mapped and stored through data structures such as lists or dictionaries. The traversal and connection process can be implemented through programs. In programming languages such as Python, the sum() function can be used to integrate the duration elements of each node in the list, and finally the total processing cycle of each dish is obtained as the basis for subsequent scheduling.

[0069] S103: Call the total processing cycle of the dish, calibrate the process path integrity flag of each dish according to the node sorting structure, integrate the total processing cycle of each dish from the original material feeding node to the terminal plate loading node, and obtain the dish node beat cycle;

[0070] The process path integrity mark of each dish is calibrated according to the node sorting structure. In actual operation, the path integrity can be identified by judging whether the task duration of each dish from the starting node to the terminal node is all effectively marked. For example, if there is a node task duration of 0 or a null value in the Kung Pao Chicken node sequence T201 to T205, it is considered that the process path is incomplete. The system sets the integrity threshold as the node task duration is greater than 1 minute and is considered complete when there is no missing. The reference source for setting the threshold is the standard process specification of the dish, and the minimum task node duration is 1 minute. If a node is shorter than this duration or missing, it is considered an abnormality. After the path is complete, the system integrates the duration of all tasks, and the sum of the overall task sequence time from the starting node (such as cutting raw materials) to the terminal node (such as plating) is used as the dish node beat cycle. Assuming that the duration of each node of scrambled eggs with tomatoes is 3, 2, 5, and 1 minutes, the total beat cycle is 11 minutes. The beat cycle represents the sum of the task rhythms of the dish at all process nodes. This value will be used in subsequent process allocation and scheduling analysis. It does not involve the purpose function description and is only recorded as the sum of the processing flow time. If actual restaurant data is used, 5 dishes in the current order can be sampled, and the cycle statistical process can be executed for each dish to output the beat value as the result.

[0071] See also Figure 3The specific steps to obtain the task number record of each position during kitchen operation and generate the position task receiving list based on the position identification code are as follows:

[0072] S201: Obtain the task execution records of each position during the operation of the kitchen, collect the task number and the corresponding position number in each record, group and summarize all task numbers by position number, construct a task statistics list for each position, and filter out position records with zero task quantity to obtain the position task statistics result;

[0073] First, extract the task execution log table from the kitchen management database. The table fields include: task number (TaskID), station number (StationID), task start time, task duration, task status, etc. The system traverses each record and establishes a mapping relationship between TaskID and the corresponding StationID to form a key-value pair set such as: {T101: ST01, T102: ST02, T103: ST01}. All task numbers are grouped and counted based on the station number as the index. For example, the task number set under ST01 is {T101, T103}, and that under ST02 is {T102}. Use Python example

[0074] grouped=df.groupby('StationID')['TaskID'].apply(list). After grouping, calculate the number of tasks for each station. The statistical method is to apply the len() function to the task number list of each group to get the total number of tasks. For example, the number of tasks under ST01 is 2, ST02 is 1, and ST03 is 0. Set the screening threshold to task number N>0. According to the actual kitchen standards, this threshold is derived from the operation effectiveness screening benchmark to ensure that only stations with actual tasks are counted. If a position has no tasks in the current statistical period, it will not be included in the analysis scope. Execute the judgment statement iflen(task_list)>0 to eliminate invalid data, such as: position task statistics = {ST01:[T101,T103],ST02:[T102]}. In an actual kitchen, if the "cold dish area" is set to ST01, the "hot stir-fry area" is ST02, and the "snack area" is ST03, if the number of ST03 tasks is 0 in a certain period, it will be eliminated, and only ST01 and ST02 data will be retained to obtain the position task statistics results.

[0075] S202: Based on the job task statistics, call the start timestamp of the tasks in each job, set a specified time interval window, extract the number of task numbers within the window, calculate the number of task occurrences for each job in the time period, establish a time-frequency matching relationship corresponding to the job, and obtain the job time-task frequency;

[0076] Retrieve the start time field of each task and set the statistical window interval to 10 minutes, that is, the window width is Δt = 600 seconds. This value is set with reference to the "Kitchen Peak Operation Beat Specification" to ensure that the operation-intensive time period is reasonably divided. The system assigns the task timestamp data to the corresponding time window. For example, task T101 with a start time of 08:01:30 belongs to window 1 (08:00:00-08:10:00). The task number is counted into each window using a sliding window method. Statistics are performed for each position. Position ST01 has T101 and T103 in window 1, the number is 2, and there is no task in window 2, the number is 0. The task frequency is calculated using the following formula: Among them, f i,j Indicates the task frequency of position i in window j (in tasks / second), n i,j is the number of tasks in the window, Δt = 600 seconds is the window width, and the example values are: If the number of tasks for position ST02 in window 1 is 1, then its frequency is 0.0017. The structure of the position frequency table is as follows: Frequency Match =

[0077] {ST01:{[08:00:00,08:10:00]:0.0033},ST02:{[08:00:00,08:10:00]:0.0017}}, this frequency value matrix is used to reflect the occurrence density of tasks in each position and provide data support for subsequent position status identification.

[0078] S203: Extract the identification code of each position based on the position time task frequency, combine the frequency value with the corresponding position code, establish a mapping relationship between the number of position tasks and the position identifier, integrate the current active task reception status of all positions, and obtain a position task reception list;

[0079] According to the job time task frequency, first extract the unique identification code of each job in the kitchen system, such as ST01 for "cold dish area" and ST02 for "hot stir-fry area", and convert the frequency value f i,j Paired with the corresponding job code i and time window number j, for example: (ST01, 0.0033), (ST02, 0.0017), for each job number i, extract the task frequency set {f i,1 ,f i,2 ,…,f i,k}, and calculate the average frequency The formula is as follows: Where: i represents the position number, for example, ST01 represents the cold dish area position; j represents the time window number, for example, the first window represents 08:00–08:10; f i,jrepresents the task frequency of position i in the jth time window (in tasks / second); k represents the total number of time windows (for example, the morning peak period is from 08:00 to 10:00, with a total of 12 10-minute windows); taking the ST01 position as an example, its frequency data in the first four time windows are: f ST01,1 =0.0033, f ST01,2 =0.0025,f ST01,3 =0.0041,f ST01,4 =0.0037, and substituting it into the average frequency calculation formula, we get: According to the active identification benchmark for job tasks set in the Kitchen Operation Capability Assessment Manual, each job should complete at least one task every 5 minutes. The lower limit of the task frequency is: To ensure reasonable coverage of job volatility, the system sets the active identification threshold to f th =0.0020 (unit task number / second), all positions It is identified as the currently active position. If the ST01 frequency is 0.0034≥0.0020, it is included in the task reception list. Conversely, if the ST03 average frequency is 0, it is excluded. Finally, the system constructs the position task reception list for the current time period as follows: Task reception position list = [ST01, ST02]. The list mapping structure forms a static binding between the position number and the task activity status.

[0080] See also Figure 4 Based on the dish node beat cycle and the job task receiving list, the average processing cycle time of similar dishes in each job task record is called, the difference interval between the target cycle and the current dish node beat cycle is calculated, the task cycle deviation combination between each job and dish is extracted and standardized, and the standardized value is used as the rhythm coupling index of the job and dish. The specific steps to obtain the job beat overlap coefficient are as follows:

[0081] S301: Based on the dish node beat cycle and the job task receiving list, call the processing time information of the matching dish category in each job task record, extract the total processing cycle of each dish category in the corresponding job, and calculate the sample size and the average cycle of the job dish;

[0082] First, extract the active post number list and its corresponding task execution data from the task database. Each task record contains fields such as dish number, post number, start and end time, etc. The system matches the dish number corresponding to the task with the node beat cycle structure to determine the dish category to which the task belongs. Active tasks are filtered by matching the post number with the post task receiving list, and all task records corresponding to the dish category processed by each post are extracted. The processing time information, that is, the time difference between the start and end of the task, is read in sequence. The processing time is T=T end -T start Based on the difference results, the system aggregates and counts the processing time according to the dish category, and accumulates all processing times of the same dish in the same position to form the total processing cycle. Then, the number of task samples of the dish category in the position is counted, and the total processing cycle is divided by the number of samples to obtain the average cycle of dishes in the position. The system performs this calculation for each dish-position combination to form a set of average processing cycles of dishes in the position. For example, if ST01 processes Kung Pao Chicken 5 times, the processing time each time is 300 seconds, 280 seconds, 310 seconds, 295 seconds, and 305 seconds respectively, the total processing cycle is 1490 seconds, and the average cycle is 298 seconds. The structure is stored as {(ST01, Kung Pao Chicken): 298}, and finally the average cycle statistical structure of all dishes in each position is completed.

[0083] S302: Based on the average cycle of dishes in each position, extract the overall execution time length and number of tasks for all matching dishes in each position. After filtering out positions with insufficient number of tasks, extract the span information of task completion time for similar dishes in the position. This information is offset with the processing period of the corresponding dish in the dish node beat cycle to obtain the position dish deviation combination.

[0084] Based on the average cycle of job dishes, the system extracts the start and end time fields of all matching dish tasks, calculates the total execution time of each job and dish combination, and records the total number of tasks N, to determine whether the number of tasks meets the minimum sample threshold N min =3. If the number is insufficient, the combined data will be eliminated. The threshold setting refers to Appendix 1 of the "Minimum Credible Sample Standard for Kitchen Process Tasks", which requires that each statistical item contains at least 3 independent task records. After screening, the combination with sufficient sample number is retained. The earliest start time and the latest end time in the extracted task are recorded as T respectively. start,min With T end,max , calculate the span of time for completing the task of the same type of dish in this position as ΔT = T end,max -T start,min , compare this time span with the standard processing period P of the corresponding dish in the dish node beat period table c Compare and calculate the time difference, that is, the offset value δ = ΔT-P cWhen the offset value is positive, it indicates that the job processing has timed out, and when the offset is negative, it indicates that it is completed ahead of schedule. The system records the offset value of each job-dish combination and constructs a job-dish deviation combination structure. The structure example is {(ST02, Kung Pao Chicken): 25}, which means that the processing cycle of the dish at this job exceeds the standard beat cycle by 25 seconds.

[0085] S303: Based on the position-dish deviation combination, the positional relationship between each deviation and the corresponding position and dish number is calibrated, and a set of all deviation data intervals is constructed. The deviation values corresponding to each group of positions and dishes are classified according to the interval set, and a standardized rhythm correspondence table is established. The standardized value is used as the rhythm coupling index of the position and dish, and the position beat overlap coefficient is obtained;

[0086] Based on the position-dish deviation combination, the system extracts the dish number c, position number i and deviation value δ of each offset data from the record in sequence c,i , combined into a triple (i, c, δ c,i ), all offset values ​​compose the deviation set {δ c,i}, and divide the offset value into sections according to the 7-level rhythm interval standard defined in the "Kitchen Beat Response Offset Benchmark Table V2.0", including: severe advance (δ≤-90), moderate advance (-90<δ≤-60), slight advance (-60<δ≤-30), normal fluctuation (-30<δ<30), slight delay (

[0087] 30≤δ<60), moderate delay (60≤δ<90), severe delay (δ≥90), all offset values are in seconds and are assigned a standardized level number λ by determining the interval in which they are located. c,i , then combine the job number and the dish number for structural mapping to form a standardized rhythm matching table, and finally perform the beat overlap coefficient γ for each combination of job i and dish c c,i The calculation is processed using the following formula:

[0088] Extract the job number θ, dish number ψ and offset value for each deviation data record The three constitute a set of combined relationship structures in It represents the offset value between the actual processing and the beat standard of the task corresponding to the dish ψ executed by the rth position θ, in seconds. The system forms a set of all offset values where ρ θ,ψ represents the total number of tasks corresponding to position θ under dish ψ, and then extracts the standard beat period P of dish ψ ψ , in seconds, the system calculates the job beat overlap coefficient according to the following formula:

[0089]

[0090] Among them, Γ θ,ψ is the beat overlap coefficient between the position θ and the dish ψ, with dimensionless units; θ is the position number, e.g. ST01 represents the cold dish section; ψ is the dish number, e.g. D03 represents Kung Pao Chicken; is the offset value of the rth item ψ executed by position θ, in seconds; ρ θ,ψ is the number of task samples (positive integer) corresponding to dish ψ for position θ; ψ is the standard cycle time of dish ψ, in seconds, which represents the ideal total processing time from the initial feeding point to the final loading point, as set by the dish process design specification;

[0091] Assume that the total number of tasks of job ST02 (θ=ST02) in processing dish D03 (ψ=D03, i.e. Kung Pao Chicken) in this round of production is ρ ST02,D03 = 4 times, and the offset value of each task from the standard beat cycle is as follows: The standard beat period is P D03 =300 seconds, substitute into the formula: Calculate each item: The final beat overlap coefficient is: Γ ST02,D03 =0.0808.

[0092] This value represents the normalized amplitude of rhythm fluctuation relative to the beat period during the ST02 task of preparing the Kung Pao Chicken dish. Larger values indicate more severe rhythm deviation.

[0093] See also Figure 5 , divide the job beat overlap coefficient into multiple intervals, extract the partition attribution numbers of all tasks, and obtain the task priority partition number set. The specific steps are as follows:

[0094] S401: Obtain the coefficients corresponding to all tasks in the job beat overlap coefficient, set the upper limit interval, lower limit interval and middle buffer zone as the partition determination basis, compare and screen each task based on the overlap coefficient and the boundaries of the three intervals, identify the target segment to which each task belongs, and obtain the task partition affiliation type;

[0095] First, extract the job number θ and dish number ψ to which each task belongs, and extract its beat overlap coefficient Γ from the job-dish relationship table θ,ψ , bind these coefficients to each task number one by one, that is, build a mapping structure {TaskID ω :Γ θ,ψ}, where all bindings follow the principle of cross-location between task execution positions and dish information, i.e., task ω is executed by position θ and processes dish ψ, and the system locates the beat overlap coefficient Γ of the position to which it belongs. θ,ψ ,Then set three rhythm intervals for screening, namely: lower limit interval (-∞,L], middle buffer zone (L,U), upper limit interval [U,+∞), the three interval boundary values L and U are set by standard deviation control, the formula is as follows: L = μ Γ -β·σ Γ , U=μ Γ +α·σ Γ , where μ Γ For all Γ θ,ψ The arithmetic mean of Γ is the standard deviation; α and β are the coefficients for regulating the upper and lower sensitivity limits, both of which are 1 by default; for example, if all the Γ θ,ψ In the sample, the average value is μ Γ =0.072, standard deviation σ Γ =0.015, then we get: L = 0.057, U = 0.087, the system will number all tasks according to their corresponding Γ θ,ψ The value is filtered by interval matching to determine whether it is less than L, in the middle, or higher than U, and the partition is assigned a type label accordingly.

[0096] S402: Based on the task partition type, the task numbers are matched and sorted with the corresponding segment types. Task numbers belonging to the upper limit interval are extracted and grouped as the priority transfer zone. Task numbers belonging to the lower limit interval are extracted and grouped as the scheduling buffer zone. The remaining task numbers are marked as intermediate candidate zones to obtain a task partition number matching sequence.

[0097] The system will overlap the task number with the job beat coefficient Γ θ,ψ The corresponding interval types are paired, and each task is constructed into a tuple (TaskID ω ,χ ω ), where χ ω Indicates the beat overlap partition to which it belongs, with the value of "priority transfer zone", "intermediate candidate zone" or "scheduling buffer zone". All task numbers are classified and archived according to this type field. For example, all Γ θ,ψ Task numbers ≥0.087 are classified That is, the task set is transferred in first; all Γ θ,ψ ≤0.057 is included That is, the scheduling buffer task set; the remaining task numbers falling into the middle buffer (0.057, 0.087) are classified That is, the set of intermediate candidate tasks. For example, the actual division results may be as follows: T001, T005, and T009 are located in T002 and T007 are located in T004, T006, T008, and T010 are located in The final output is the task partition number matching sequence, which is a systematic list of matching results between tasks and their beat overlapping intervals.

[0098] S403: According to the task partition number matching sequence, all tasks and their partition numbers are integrated to form an index mapping structure, and the task quantity and identification structure corresponding to each partition are established to obtain the task priority partition number set;

[0099] The system creates a TaskID for each task ω and its affiliated partition χ ω Mapping index structure Then the system counts the number of tasks by partition type and builds a task priority partition summary structure, including the total number of tasks N in the priority transfer zone. 优 , the total number of tasks in the intermediate candidate area N 中 , the total number of scheduling buffer tasks N 缓 , the statistics are based on the job beat overlap coefficient Γ corresponding to the task θ,ψ Not every task has an independent overlap value, but inherits the overlap strength of its position-dish combination. For example, if three tasks are bound to Γ ST01,D01 =0.092, which is higher than the upper limit, so all three tasks are included If the two tasks belong to Γ ST03,D05 =0.049, then classified The system finally constructs the following index statistics: {priority transfer-in area: 3, intermediate candidate area: 4, scheduling buffer: 2}, completing the generation of the task priority partition number set structure, which provides a quantitative index basis for the next stage of task scheduling sorting and transfer operations.

[0100] See also Figure 6 ,According to the assigned task numbers in the task priority partition number set, the current order configuration distribution structure of the kitchen is constructed, and the distribution status is marked as the overall scheduling status snapshot under the current control conditions. The specific steps to obtain the order automation scheduling result are as follows:

[0101] S501: Extract task numbers according to the partition affiliation labels from the assigned task numbers in the task priority partition number set, extract task number sets identified as priority transfer-in areas, intermediate candidate areas, and scheduling buffer areas, and group the task numbers by category to obtain a task partition number list;

[0102] According to the task number assigned to the task priority partition number set, the system reads the index structure TaskID ω represents the ωth task number, χ ω The priority segment label corresponding to the task. The label value is limited to three enumerated fields: "priority transfer zone", "intermediate candidate zone", and "scheduling buffer zone". The system scans all task number sets, classifies and groups them according to their label fields, and classifies task numbers with the same segment identifier into the same set, resulting in three number lists: in Indicates the set of task numbers with the highest degree of beat overlap and the ones that need to be allocated first. is a set of intermediate candidate task numbers whose beat offset is within a reasonable floating range. For the scheduling buffer set with low beat overlap coefficient and stable processing cycle tasks, the classification judgment process is completed by comparing the field values. For example, the Python statement iflabel== is used to prioritize the call-in area: list_

[0103] Append(task_id) performs judgment and append operations. Each number list is ultimately output and archived according to the classification structure, forming a three-segment task number list structure for subsequent statistics and partition structure visualization. This structure, combined with the execution capabilities of each process position in the kitchen, ensures the logical consistency of the classification structure and rhythm partitioning.

[0104] S502: Based on the task partition number list, count the number of tasks corresponding to each partition, extract the total number of all task numbers as the benchmark task amount, calculate the proportion of the number of tasks in each partition to the total number of tasks, and save the proportion value corresponding to each partition in the partition identification field to obtain the task partition proportion;

[0105] The system performs the collection Perform element count operation by using the length function to calculate the length of the list, that is, Then sum the number of tasks in the three partitions to get the total number of tasks N 总 =N 优 +N 中 +N 缓 This value is used as the denominator benchmark value of the task distribution ratio. The system divides the number of tasks in each partition by the total number of tasks to obtain the proportion of the partition in the current order ρ x The proportion calculation formula is as follows: x∈

[0106] {Excellent, Medium, Slow}, using a specific example, if Then: N 总 =3+4+2=9, The above ratio values are all retained in the identification fields corresponding to the respective partitions. For example, the system record structure is: {Priority transfer zone

[0107] :33.3%, middle candidate area: 44.4%, scheduling buffer: 22.2%}, all proportion data are saved in the structure in floating-point format to achieve precision control in the subsequent order task structure visualization and regulation analysis process, ensuring that the proportion calculation is completely consistent with the original number list data structure.

[0108] S503: Based on the task partition ratio, the partition ratio and task number distribution structure are extracted. The partition classification results are combined with the kitchen control configuration identifier to establish a task structure mapping view of the order tasks in the current time period and obtain the order automation scheduling result.

[0109] First, read the percentage field and number list set corresponding to each partition type in the structured data record. Based on this structure, combined with the kitchen operation control strategy table The standard scheduling model template is extracted according to the task allocation configuration rules corresponding to the current system time period. The system performs the task allocation structure matching process according to the field constraints such as the upper limit of the priority task allocation ratio, the intermediate task retention benchmark ratio and the buffer task allocation delay period defined in the configuration table. The current statistical task distribution structure is compared with the scheduling recommendation structure in the control table at the field level, and all numbers are recorded in the scheduling mapping table. where χ ω Indicates the priority segment to which the task belongs, ρ ω Indicates the proportion of the segment corresponding to the task, τ t Indicates the timing beat position segment that the task is to be transferred into. The system maps all task numbers on the scheduling timeline and finally outputs a graphical view of the mapping structure. This view consists of a horizontal axis of task number and a vertical axis of task priority, allocation ratio, and time configuration, enabling time-controlled mapping output of task structure distribution. The system registers this structure as the automated scheduling result of the current order task.

[0110] See also Figure 7 , a restaurant kitchen order automation management system, the system includes:

[0111] The dish beat collection module obtains the process execution path of the dishes in the current order of the restaurant kitchen, collects the duration of the node tasks and the node sorting index in the path, and obtains the dish node beat cycle;

[0112] The job frequency monitoring module obtains the task number record of each job during the operation of the kitchen, and generates a job task receiving list based on the job identification code;

[0113] The beat coupling identification module is based on the beat cycle of the dish node and the job task receiving list. It calls the average processing cycle time of similar dishes in each job task record, calculates the difference interval between the target cycle and the current dish node beat cycle, extracts the task cycle deviation combination between each job and dish, and performs normalization processing. The normalized value is used as the rhythm coupling index of the job and dish to obtain the job beat overlap coefficient.

[0114] The task partitioning module divides the job beat overlap coefficient into multiple intervals, extracts the partition attribution numbers of all tasks, and obtains the task priority partition number set;

[0115] The order scheduling generation module constructs the current order configuration distribution structure of the kitchen according to the assigned task numbers in the task priority partition number set, and marks the distribution status as a snapshot of the overall scheduling status under the current control conditions to obtain the order automation scheduling result.

[0116] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A restaurant kitchen order automation management method, characterized in that: The following steps are involved: S1: Obtain the process execution path of the dish in the current order of the restaurant kitchen, collect the duration of the node task and the node sorting index in the path, and obtain the dish node beat cycle; S2: Obtain the task number record of each position during the kitchen operation, and generate a position task receiving list based on the position identification code; S3: Based on the dish node beat cycle and the job task receiving list, call the average processing cycle time of similar dishes in each job task record, calculate the difference interval between the target cycle and the current dish node beat cycle, extract the task cycle deviation combination between each job and dish and perform normalization processing, use the normalized value as the rhythm coupling index of the job and dish, and obtain the job beat overlap coefficient; S4: Divide the job beat overlap coefficient into multiple intervals, extract the partition attribution numbers of all tasks, and obtain a task priority partition number set; S5: Construct a current order configuration distribution structure for the kitchen based on the assigned task numbers in the task priority partition number set, and mark the distribution state as a snapshot of the overall scheduling state under the current control conditions to obtain an automated order scheduling result.

2. The restaurant kitchen order automation management method according to claim 1, characterized in that: The dish node beat cycle specifically includes the total duration of the path, the node sorting index structure, and the total rhythm of the dish process. The job task receiving list includes the job identification code, the number of tasks per unit time, and the active cycle frequency identifier. The job beat overlap coefficient includes the dish cycle deviation interval, the job rhythm response value, and the standardized matching index. The task priority partition number set specifically refers to the priority transfer area task number, the intermediate candidate area task number, and the scheduling buffer task number. The order automation scheduling result includes the task partition ratio structure, the partition scheduling status identifier, and the kitchen order configuration distribution map.

3. The restaurant kitchen order automation management method according to claim 1, characterized in that: The specific steps to obtain the process execution path of the dish in the current order of the restaurant kitchen, collect the duration of the node tasks and the node sorting index in the path, and obtain the dish node beat cycle are as follows: S101: Obtain the process execution path of all dishes in the current order of the restaurant kitchen, collect the node task number corresponding to each dish in the path and the task duration of the target node, record the process node set of each dish by task number, and bind the node number as a sorting index to establish a node sequence structure for each dish, and generate a dish node index sequence; S102: Extracting the task duration of each node at the position corresponding to the sorting index according to the dish node index sequence, sequentially connecting the task durations of each node according to the node sorting order, and integrating all durations to obtain the total dish processing cycle; S103: Call the total processing cycle of the dish, calibrate the process path integrity identifier of each dish according to the node sorting structure, integrate the total processing cycle of each dish from the original feeding node to the terminal plating node, and obtain the dish node beat cycle.

4. The restaurant kitchen order automation management method according to claim 3, characterized in that: The specific steps to obtain the task number record of each position during kitchen operation and generate a position task receiving list based on the position identification code are as follows: S201: Obtain the task execution records of each position during the operation of the kitchen, collect the task number and the corresponding position number in each record, group and summarize all task numbers by position number, construct a task statistics list for each position, and filter out position records with zero task quantity to obtain the position task statistics result; S202: Based on the job task statistics, call the start timestamp of the tasks in each job, set a specified time interval window, extract the number of task numbers within the window, calculate the number of task occurrences for each job in the time period, establish a time-frequency matching relationship corresponding to the job, and obtain the job time-task frequency; S203: According to the job time task frequency, extract the identification code of each job, combine the frequency value with the corresponding job code, establish a mapping relationship between the number of job tasks and the job identifier, integrate the current active task reception status of all jobs, and obtain a job task reception list.

5. The restaurant kitchen order automation management method according to claim 4, characterized in that: Based on the dish node beat cycle and the job task receiving list, the average processing cycle time of similar dishes in each job task record is called, the difference interval between the target cycle and the current dish node beat cycle is calculated, the task cycle deviation combination between each job and dish is extracted and standardized, and the standardized value is used as the rhythm coupling index of the job and the dish. The specific steps for obtaining the job beat overlap coefficient are as follows: S301: Based on the dish node beat cycle and the job task receiving list, call the processing time information of the matching dish category in each job task record, extract the total processing cycle of each type of dish in the corresponding job, and calculate the sample size and the average cycle of job dishes; S302: Based on the average cycle of the position dishes, the overall execution time length and the number of tasks of all matching dishes in each position are extracted. After filtering out the position entries with insufficient number of tasks, the span information of the task completion time of similar dishes in the position is extracted, and the offset is identified with the processing period of the corresponding dish in the dish node beat cycle to obtain the position dish deviation combination; S303: Based on the position-dish deviation combination, calibrate the positional relationship between each deviation and the corresponding position and dish number, construct a set of all deviation data intervals, classify the deviation values corresponding to each group of positions and dishes according to the interval set, establish a standardized rhythm correspondence table, use the standardized value as the rhythm coupling index of the position and the dish, and obtain the position beat overlap coefficient.

6. The restaurant kitchen order automation management method according to claim 5, characterized in that: To calculate the job beat overlap coefficient, the formula is used: Among them, Γ θ,ψ is the beat overlap coefficient between the job θ and the dish ψ, which is used to measure the degree of match between the timing of a job's execution when processing a dish and the dish's standard beat, that is, the ideal processing time from start to finish. θ is the job number, ψ is the dish number, is the offset value of the rth item executed by job θ about dish ψ, ρ θ,ψ is the number of task samples corresponding to dish ψ for position θ, P ψ is the standard beat cycle of dish ψ, which represents the ideal total processing time from the original feeding node to the terminal loading node, which is set by the dish process design specification.

7. The restaurant kitchen order automation management method according to claim 5, characterized in that: The specific steps of dividing the job beat overlap coefficient into multiple intervals, extracting the partition attribution numbers of all tasks, and obtaining the task priority partition number set are as follows: S401: Obtain the coefficients corresponding to all tasks in the job beat overlap coefficient, set the upper limit interval, the lower limit interval and the middle buffer zone as the partition determination basis, compare and screen each task based on the overlap coefficient and the boundaries of the three intervals, identify the target segment to which each task should belong, and obtain the task partition affiliation type; S402: Based on the task partition type, task numbers are matched and sorted with corresponding segment types. Task numbers belonging to the upper limit interval are extracted and grouped as priority transfer areas. Task numbers belonging to the lower limit interval are extracted and grouped as scheduling buffer areas. The remaining task numbers are marked as intermediate candidate areas to obtain a task partition number matching sequence. S403: According to the task partition number matching sequence, all tasks and their partition numbers are integrated to form an index mapping structure, and the task quantity and identification structure corresponding to each partition is established to obtain a task priority partition number set.

8. The restaurant kitchen order automation management method according to claim 7, characterized in that: For setting the upper limit interval, lower limit interval and middle buffer zone as the partition determination basis, the formula is used: L=μ Γ -b·s Γ ,U=μ Γ +a·s Γ ; Calculate the lower limit interval boundary value L and the upper limit interval boundary value U, and number all tasks according to the corresponding Γ θ,ψ The value is filtered by interval matching to determine whether it is less than L, in the middle, or higher than U, and the partition is assigned a type label accordingly; Among them, μ Γ For all Γ θ,ψ The average value, σ Γ For all Γ θ,ψ The standard deviation of , α and β are the coefficients for regulating the upper and lower sensitivity limits.

9. The restaurant kitchen order automation management method according to claim 7, characterized in that: Based on the assigned task numbers in the task priority partition number set, the current order configuration distribution structure of the kitchen is constructed, and the distribution status is marked as a snapshot of the overall scheduling status under the current control conditions. The specific steps for obtaining the order automation scheduling result are as follows: S501: extracting task numbers according to partition affiliation labels from task numbers assigned to the task priority partition number set, extracting sets of task numbers identified as priority transfer-in areas, intermediate candidate areas, and scheduling buffer areas, and grouping the numbers by category to obtain a task partition number list; S502: Based on the task partition number list, count the number of tasks corresponding to each partition, extract the total number of all task numbers as the benchmark task amount, calculate the proportion of the number of tasks in each partition to the total number of tasks, and save the proportion value corresponding to each partition in the partition identification field to obtain the task partition proportion; S503: Based on the task partition ratio, extract the partition ratio and task number distribution structure, combine the partition classification result and the kitchen control configuration identifier, establish a task structure mapping view of the order task in the current time period, and obtain the order automation scheduling result.

10. A restaurant kitchen order automation management system, characterized in that: The restaurant kitchen order automation management method according to any one of claims 1 to 9 is implemented, wherein the system comprises: The dish beat collection module obtains the process execution path of the dishes in the current order of the restaurant kitchen, collects the duration of the node tasks and the node sorting index in the path, and obtains the dish node beat cycle; The job frequency monitoring module obtains the task number record of each job during the operation of the kitchen, and generates a job task receiving list based on the job identification code; The beat coupling identification module is based on the beat cycle of the dish node and the job task receiving list, calls the average processing cycle time of similar dishes in each job task record, calculates the difference interval between the target cycle and the current dish node beat cycle, extracts the task cycle deviation combination between each job and dish and performs normalization processing, uses the normalized value as the rhythm coupling index of the job and dish, and obtains the job beat overlap coefficient; The task partitioning module divides the job beat overlap coefficient into multiple intervals, extracts the partition attribution numbers of all tasks, and obtains a task priority partition number set; The order scheduling generation module constructs the current order configuration distribution structure of the kitchen according to the assigned task numbers in the task priority partition number set, and marks the distribution status as a snapshot of the overall scheduling status under the current control conditions to obtain the order automation scheduling result.

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