A method and system for slot device scheduling control based on predictive resource reservation

Abstract

The application discloses a slot device scheduling control method and system based on predictive resource reservation, and relates to the field of semiconductor equipment control. In view of the scheduling conflict and capacity decline caused by resource competition, the method analyzes a time-space path map generated by a target basket formula; candidate reservation windows with safety margins are generated for key shared resources, and are compared with a time window reservation table; if there is a reservation conflict, a time translation amount is calculated to negotiate the window; the conflict-free window is written into the reservation table to determine the scheduling beat time and delay start; at the same time, actual data is collected during execution to update the beat prediction model and the safety margin parameter. The application changes passive avoidance to prior prediction and reservation, combines priority cooperation and closed-loop adaptive calibration, effectively eliminates the risk of deadlock, and significantly improves the equipment throughput and stability.

Description

Technical Field

[0001] This invention relates to the field of semiconductor automated manufacturing and equipment control technology, and more specifically, to a slot-type equipment scheduling control method and system based on predictive resource reservation. Background Technology

[0002] In semiconductor manufacturing processes, tank cleaning equipment is one of the key production machines. A typical semiconductor tank cleaning system usually includes multiple process tanks performing different chemical or physical treatments, a transfer station for basket transfer, and at least two robotic arms performing cross-area transport tasks. As semiconductor processes increasingly demand higher throughput and flexibility, tank cleaning systems need to support multiple baskets performing different process formulations in parallel across different tanks. This requires the equipment's control system to have efficient scheduling capabilities to coordinate multiple robotic arms to complete complex spatiotemporal motion logic.

[0003] In existing technologies, motion control and process execution in trough-type equipment are often relatively disconnected. Due to the limitations of traditional lower-level control systems in terms of logic processing capabilities, the equipment typically uses fixed feeding intervals to avoid potential collisions during operation. However, fixed feeding intervals cannot adapt to dynamic cycle time variations caused by different formulation combinations, often requiring extremely conservative delay intervals based on worst-case scenarios, resulting in significant waste of equipment throughput and capacity. To improve efficiency, some improved technologies introduce conflict detection and execution-level avoidance mechanisms. Specifically, during the actual operation of the robotic arm, when it detects that critical shared resources such as shared tracks or transfer stations are occupied, subsequent robotic arms are forced to perform a delay and wait in place or at a specific location.

[0004] This method, which relies on passive avoidance during the execution phase, still has many drawbacks. First, the transfer station and its surrounding area are bottleneck resources that multiple robotic arms compete for frequently. Relying solely on reactive avoidance can easily cause traffic congestion in the area, and in severe cases, lead to mutual waiting and deadlock among multiple robotic arms. Second, passive waiting can uncontrollably increase the exposure time of some baskets in non-designated slots or in the air, thereby affecting the process quality of semiconductor wafers. Finally, existing cycle time calculations and avoidance scheduling are mostly based on ideal theoretical time consumption, lacking adaptive feedback on the actual execution status of the equipment. In actual production, physical jitter such as speed reduction caused by robotic arm wear and valve opening and closing delays will continuously accumulate. Static scheduling models cannot detect and correct these errors, ultimately causing a serious deviation between the scheduling plan and the actual execution trajectory, forcing the system to frequently trigger emergency shutdowns or inefficient temporary avoidance operations. Summary of the Invention

[0005] To overcome the existing problems and shortcomings, this invention proposes a slot-type equipment scheduling and control method based on predictive resource reservation, applied to the equipment's control system, comprising the following steps:

[0006] The process formula of the target flower basket is analyzed to generate a step sequence containing movement steps and process steps, and the key shared resources required for the execution of each step are identified.

[0007] The basic execution time of the target flower basket is calculated based on the step sequence and the theoretical execution time of the equipment, and a spatiotemporal path map with theoretical time annotations is generated for each step.

[0008] Based on the spatiotemporal path map, a candidate reserved window with a safety margin is generated for the occupied interval of the target flower basket on the key shared resources;

[0009] The candidate reserved window is compared with the pre-established time window reservation table. If there is a reservation conflict with the confirmed reserved window in the time window reservation table, window negotiation is performed, and the candidate reserved window is offset from the confirmed reserved window by calculating the time shift amount.

[0010] After negotiating and eliminating conflicts, the candidate reserved window is written into the time window reserved table and marked as confirmed. The scheduling cycle time of the target flower basket is determined based on the base consumption time and the time shift amount.

[0011] The target flower basket is loaded with materials in a delayed manner according to the scheduled cycle time. During the execution, actual execution data is collected to update the cycle prediction model and the safety margin parameters of the corresponding key shared resources for the prediction and scheduling of the next flower basket.

[0012] Furthermore, the candidate reservation window with a safety margin is... ;

[0013] in, and Let be the theoretical start and end times of the k-th step of the target flower basket A, respectively. This refers to the safety margin parameter for resource r;

[0014] When satisfied At that time, determine the candidate reserved window and the confirmed reserved window of target basket A. There is a reservation conflict on resource r.

[0015] Furthermore, the step of calculating the time shift to offset the candidate reserved window from the confirmed reserved window specifically includes:

[0016] For each critical shared resource r where a conflict occurs, calculate the minimum feasible translation amount required to eliminate the conflict on that resource for the candidate reservation window of the target basket A in step k. ;

[0017] The maximum and minimum feasible shift among all conflicting resources and steps are selected as the global shift. And shift all candidate reserved windows for target basket A backward on the timeline. .

[0018] Furthermore, during window negotiation, if the calculated global translation amount... If the preset acceptance threshold is exceeded, an active path correction strategy is executed to regenerate the candidate reserved window;

[0019] The active path correction strategy includes: adjusting the running speed parameters of the non-critical track segments before the target basket reaches the critical shared resource, or adding temporary waiting positions before reaching the critical shared resource, to change the time when the target basket arrives at the critical shared resource so that it falls into an idle window.

[0020] Furthermore, during the delayed start-up feeding process of the target flower basket according to the aforementioned scheduling cycle time, a priority coordination and guarantee mechanism is also included:

[0021] Real-time data collection of the robot's position, task status, and the occupancy status of key shared resources;

[0022] When a priority collaborative control strategy is triggered when two or more robotic arms are detected to have a spatial overlap trend within the time window of entering the same critical shared resource, the priority collaborative control strategy is triggered.

[0023] Calculate the priority weight of each flower basket that shows an overlapping trend, and give priority to the robot arm corresponding to the flower basket with the highest priority weight, and guide the other robot arms to the safe waiting position; wherein, the priority weight is calculated based on the process time margin, the waiting time and the remaining path length of the corresponding flower basket.

[0024] Furthermore, the key shared resources include at least the transfer station and transfer station transfer area for cross-robot travel; after the robot corresponding to the flower basket with the highest priority weight completes the pick-up and put-down action at the transfer station, the robot is controlled to immediately return to the adjacent position or the starting position of the next task, and the transfer station and transfer station transfer area are released.

[0025] Furthermore, the process of collecting actual execution data to update the cycle prediction model and the corresponding safety margin parameters of the key shared resources specifically includes:

[0026] Record the actual execution time of the target flower basket, calculate the error value between it and the theoretically generated scheduling time, and use a smoothing algorithm to update the time correction amount used to correct the time annotation of the spatiotemporal path map of the next flower basket;

[0027] Record the arrival time deviation of the target flower basket into each key shared resource, and update the safety margin parameter of the corresponding key shared resource in an exponential smoothing manner so that the candidate reserved window generated next time matches the actual operating status of the device.

[0028] Furthermore, the time window reservation table is configured with a reservation expiration and dynamic recycling mechanism:

[0029] When a serious timeout failure is detected in the upstream step of the target basket, which prevents it from reaching the corresponding critical shared resource before the start time of the confirmed reserved window, the control system automatically marks the reserved window as invalid and releases and reclaims it for other parallel baskets to apply for reservation.

[0030] A slotted equipment scheduling and control system based on predictive resource reservation includes:

[0031] The recipe management module is used to parse the process recipe of the target flower basket and generate a sequence of steps;

[0032] The scheduling module is used to generate a spatiotemporal path map with theoretical time annotations based on the step sequence, and generate candidate reservation windows with safety margins for key shared resources on the time window reservation table; when there is a reservation conflict, it performs window negotiation to calculate the time shift, writes the conflict-free candidate reservation windows into the time window reservation table and outputs the scheduling cycle time; and continuously and adaptively updates the cycle prediction model and safety margin parameters using actual execution data.

[0033] The execution control module is used to control the delayed start of the target flower basket according to the scheduling cycle time, and to perform right-of-way avoidance and collaborative scheduling between robotic arms by calculating priority weights during the execution process.

[0034] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the slot device scheduling and control method based on predictive resource reservation as described in any of the preceding claims.

[0035] The present invention has the following beneficial effects:

[0036] This invention introduces a time window reservation table, shifting the resolution of resource conflicts during the parallel execution of multiple baskets from passive avoidance in the execution phase to proactive reservation in the scheduling phase. Before basket loading, the system can pre-simulate the entire process based on a spatiotemporal path map, reserving time windows with safety margins for critical shared resources such as transfer stations. When a reservation conflict is detected, a global time shift or proactive path correction mechanism is used to stagger resource occupation periods in advance. This mechanism fundamentally avoids irreconcilable competition for bottleneck resources by multiple robotic arms during the execution phase, eliminating the risk of deadlock. This allows the equipment to operate with a more compact and safer optimal loading interval, thereby significantly improving the overall utilization and throughput of the trough-type equipment.

[0037] This invention innovatively constructs a closed-loop adaptive scheduling architecture based on historical data feedback. Traditional static scheduling is prone to cumulative errors due to equipment physical jitter and component aging. This invention collects the deviation between the actual cycle time and arrival time in real time during execution and uses a smoothing algorithm to continuously update the cycle prediction model and the safety margin parameters of key resources. This incremental machine learning mechanism enables the scheduling system to have self-calibration capabilities. The reserved window can dynamically fit the real operating trajectory as the physical state of the equipment changes, greatly reducing the frequency of repeated negotiations and frequent bottom-level avoidance caused by inaccurate predictions, and ensuring the long-term stability of equipment operation.

[0038] This invention designs a priority coordination and protection mechanism at the execution layer that matches predictive reservation. During actual robotic handling, when minor execution jitter causes the preset window to overlap, the system can calculate priority weights based on dynamic parameters such as process time margin, waiting penalty, and remaining path, granting right-of-way to high-priority actions and guiding low-priority actions into safe waiting positions. This multi-dimensional priority allocation and proactive degradation recovery mechanism not only ensures the execution quality of critical process formulations, preventing wafer overexposure or process timeouts, but also ensures that core shared resources are not ineffectively occupied for extended periods, achieving an optimal balance between equipment coordination efficiency and process safety. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 A flowchart illustrating a slotted equipment scheduling and control method based on predictive resource reservation, provided in an embodiment of the present invention;

[0041] Figure 2This is a structural block diagram of a slot-type equipment scheduling and control system based on predictive resource reservation, provided as an embodiment of the present invention. Detailed Implementation

[0042] The present application will be described below with reference to specific embodiments:

[0043] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] Example 1:

[0045] This embodiment applies to the cluster control of a semiconductor tank cleaning equipment. The equipment includes multiple process tanks, loading and unloading ports, at least one transfer station, and at least two robotic arms. Each robotic arm has a defined travel range, and baskets are transferred across these ranges via the transfer station. During operation, multiple baskets execute different recipes concurrently. Resource competition exists between baskets at the transfer station, handover points, and shared track areas. Existing methods often handle conflicts during execution by waiting or yielding, leading to conservative loading interval values, reduced throughput, and predictive errors when load changes or execution jitter occur. This embodiment provides a method for motion logic control of tank cleaning equipment and calculation of loading interval time. It forms a closed loop by integrating recipe analysis and spatiotemporal path pre-planning, time window reservation based on key resources, dynamic cycle time calculation, execution layer priority coordination, and cycle prediction calibration based on historical data. This transforms the loading interval from passive yielding to predictive resource reservation driving, and continuously corrects model parameters through feedback, thereby improving feasibility and stability.

[0046] like Figure 1 As shown, the method flow of this embodiment can be summarized as follows: steps S1 to S6. The control system executes this process cyclically for each new basket loading request: S1. Formula analysis and generation of step sequence; S2. Generation of spatiotemporal path map based on step sequence; S3. Calculation of scheduling cycle time and determination of start time based on basic consumption time and key resource time window reservation table; S4. Execution of active path correction and re-reservation when reservation conflict cannot be eliminated or cost exceeds threshold; S5. Delayed start according to scheduling cycle time and priority collaborative control during execution to ensure reservation window; S6. Collection of theoretical cycle time and actual execution data and updating of cycle time prediction model and safety margin parameters for use in cycle time estimation and reservation window generation of the next basket.

[0047] In S1, the control system receives the recipe sent by user A to basket A and parses it to obtain the process step sequence and the movement step sequence. The process step sequence includes the slot number, process duration, and process sequence; the movement step sequence includes the pick-up / placement point, target point, robot arm identifier, and motion constraints. The system decomposes the recipe into a set of steps arranged chronologically.

[0048]

[0049] Each step This refers to a movement step or a process step. For a movement step, record the starting node. End point Execution robot 1. Desired speed parameters; 2. For each process step, record the slot position. With process time The system also determines which steps will consume critical shared resources based on equipment structure and travel limitations.

[0050]

[0051] Key shared resources include at least transfer station resources and their connecting area resources, and may also include shared rail segment resources.

[0052] In S2, the system generates a spatiotemporal path map for flower basket A. The spatiotemporal path map is used to represent the location and resources occupied by the flower basket within the time interval corresponding to each step. The system first provides theoretical time annotations without considering conflicts, assuming the planned start time of flower basket A is... Then, for each movement step, the sum of the theoretical movement time and the pick-up / placement time is given, denoted as .

[0053]

[0054] For each process step, directly take the formula specified. Therefore, the base time for basket A under conflict-free conditions can be obtained.

[0055]

[0056] in For the set of movement steps, This is a set of process steps. The system accumulates the theoretical start and end times of each step based on their sequential relationships.

[0057]

[0058] in The theoretical duration of the step is taken as the number of moves. Process steps The system further binds a resource consumption set to each step. This forms a path map representation consisting of several resource-occupying intervals.

[0059]

[0060] Each element describes the flower basket A in the... Steps for resources The time interval occupied.

[0061] In S3, the system introduces a time window reservation table to enable predictive reservation of critical shared resources. The time window reservation table is indexed by the resource and denoted as .

[0062]

[0063] in For resources The set of confirmed reserved windows, each reserved window is The system generates candidate reservation windows for each critical resource's candidate occupancy interval for basket A. To improve execution robustness, a safety margin is introduced into the candidate reservation windows. ,form

[0064]

[0065] When a candidate reserved window overlaps with any confirmed window, that is, when the condition is met.

[0066]

[0067] Then determine the resources There are reserved conflicts. The system checks all critical resources for conflicts one by one and resolves them through window negotiation. The preferred method for window negotiation is to perform a complete translation of the startup time of basket A, with a translation amount of . Then all candidate windows of flower basket A become...

[0068]

[0069] The system is minimal As candidate solutions, the candidate windows for basket A across all critical resources should not overlap with existing confirmed windows. For ease of implementation, the resource allocation for each candidate window can be calculated. Minimum feasible translation on

[0070]

[0071] And take the global translation as

[0072]

[0073] The system is based on Update the time markers on the path map of Flower Basket A. If conflicts still exist after the update, continue iterating until the reservation feasibility is met or the preset iteration limit is reached. After completing the feasibility negotiation, the system writes the reservation window for Flower Basket A on key resources. It is then marked as confirmed. The system also outputs the scheduling cycle time of flower basket A.

[0074]

[0075] In this embodiment, the scheduling tick time can be used to characterize the delayed start time of basket A, and also to update the global conflict-free start schedule.

[0076] In S4, if the system calculates the result in S3... Exceeding the threshold The threshold is used to characterize the unacceptable efficiency loss caused by simply delaying the start-up. The system then performs proactive path correction and re-reserves the path. The goal of proactive path correction is to change the arrival time of basket A at the critical resource, ensuring it falls within a reservable idle window, without altering the duration of the process steps, by adding temporary waiting positions before the critical resource or adjusting the speed curve of non-critical track segments. For ease of implementation, the system will determine the arrival time of basket A at a specific critical resource. The moment is represented as a function consisting of the sum of the durations of several non-critical movement segments.

[0077]

[0078] in This is the distance of the movement segment. For the reason The speed of decision This refers to the time required for pick-up, drop-off, or positioning operations. The system adjusts this time within upper and lower speed limits. This ensures that the arrival time at the critical resource falls within the target's idle window, thereby reducing... Or prevent it from exceeding the threshold. If speed adjustment still cannot meet the reservation requirements, the system sets a temporary wait bit before critical resources. The waiting bit is considered an additional step that occupies non-critical resources, and its duration is a controllable waiting time. And correct the arrival time of critical resources to

[0079]

[0080] This creates staggered traffic flow. After completing the active path correction, the system returns to S3 to regenerate candidate reserved windows and complete the table writing.

[0081] In S5, the system delays the start of basket A by scheduling the cycle time at the execution control layer, and coordinates in real time to address potential conflicts at critical resources during execution. The execution control layer collects real-time data on the robot's position and status, the transfer station's occupancy status, and the basket's running status, and predicts resource occupancy within a short future time window based on the path map. If an overlap is detected between two robots in a critical resource area, a priority coordination strategy is activated to ensure the confirmed reserved window is secured. Priority calculation follows the time margin and waiting penalty concepts from the briefing materials; let the time margin of basket X be...

[0082]

[0083] in Estimate the remaining processing time for the flower basket. This refers to the remaining process time or target time for this formulation standard. Priority weight is defined as follows:

[0084]

[0085] in To prevent extremely small positive numbers with a denominator of zero, For the waiting time, Standard waiting time This represents the remaining path length or the number of remaining movement segments. This is a configurable coefficient. The system grants the right-of-way to the robotic arm corresponding to the basket with the higher weight, while the other robotic arm moves to a safe waiting position to avoid actual collisions or interlocking at the transfer station handover point. To meet the constraint that robotic arms cannot remain in the transfer station for extended periods, after completing the pick-up and put-down at the transfer station, the execution control layer returns the robotic arm to an adjacent position or the starting position of the next task based on the path map of its next task, and updates the global state for subsequent scheduling.

[0086] In S6, the system records the result of each execution and uses it for adaptive updates of the cycle time prediction model and safety margin parameters. The system records the theoretical scheduling cycle time. Actual beat or actual critical step time The system calculates the cycle time error for this operation, taking into account the location and type of the conflicting resources, the actual time taken to avoid it, and physical events such as gate delays and pick-up / placement delays.

[0087]

[0088] The beat correction is updated accordingly. When using exponential smoothing, the system maintains the correction item. Updated to

[0089]

[0090] in The smoothing coefficient is used. The beat rate of the next flower basket can be estimated using...

[0091]

[0092] in This refers to the shift amount negotiated based on the reservation table or the waiting amount resulting from proactive path correction. To ensure the reservation window safety margin matches device status, the system can also allocate resources based on criticality. Maintain margin parameters separately The update is based on avoiding time-consuming or actual arrival deviations, for example, by updating using exponential smoothing.

[0093]

[0094] in For the actual entry of flower baskets into resources The difference between the time of entry and the predicted entry time from the path map. To update the coefficients. By... and With continuous updates, the system can still make the reserved window closer to the actual occupied range when the load changes, the robot wears out, or the execution jitter occurs, thereby reducing repeated negotiations and temporary avoidance at the execution layer caused by estimation errors.

[0095] The following describes the specific operation process of this embodiment using a typical scenario from the disclosure materials, with transfer station Z as the main point of conflict. In the equipment, flower baskets B and C are in operation. Flower basket B needs to reach transfer station Z via robotic arm Arm2 within a certain time period to perform the handover, while flower basket A requests loading. In S1, the system analyzes the formula of flower basket A and obtains the set of steps; in S2, it calculates the basic time consumption. The system generates a path map within seconds. In S3, the system uses the path map to generate a candidate reserved window for basket A at transfer station Z, and queries the time window reserved table to find that it overlaps with the confirmed reserved window for basket B at resource Z. The system calculates the global minimum translation amount to obtain... The timer is then set to 1 second, and the entire reserved window for basket A is moved to the next position. After the feasible reservation is completed, it is written into the reservation table to obtain the scheduling cycle time. In S5, the system starts basket A with a 32-second delay. When Arm1, carrying basket A, approaches transfer station Z, the execution control layer detects that Arm2, carrying basket B, is likely to enter the vicinity of Z prematurely due to jitter. After calculating the priority weight, the system determines that Arm1 can pass, while Arm2 enters the safe waiting position. After Arm1 completes placing basket A into the transfer station and leaves the critical area, Arm2 enters to complete the subsequent actions of basket B. In S6, the system records that the actual avoidance time of Arm2 is 2.05 seconds, updates the clock correction term and the margin parameters of resource Z, so that the generation of the reserved window for the next similar scenario is closer to the actual execution, thereby reducing the probability of the execution layer triggering avoidance again.

[0096] Through the above steps, this embodiment can predictively reserve key resources such as transfer stations through a time window reservation table during the scheduling phase, thereby advancing and calculable conflict resolution. At the same time, during the execution phase, priority coordination ensures the reservation window is implemented, and cycle prediction and margin adaptation are achieved through historical data updates, thereby improving throughput and stability under the parallel conditions of multiple robotic arms and multiple flower baskets.

[0097] Example 2:

[0098] Based on the same inventive concept as in Embodiment 1 above, this embodiment provides a slot-type equipment scheduling and control system based on predictive resource reservation. Please refer to [reference needed]. Figure 2 , Figure 2 This is a structural block diagram of the trough-type equipment scheduling and control system provided in an embodiment of the present invention. The system can run on the host computer controller of the trough-type cleaning equipment or an industrial control computer, and specifically includes a recipe management module, a scheduling module, and an execution control module.

[0099] The recipe management module is primarily used to parse the process recipe of the target flower basket. This module can read externally input process files, verify their integrity, and break them down into a sequence of steps including movement steps and process steps. During this process, the recipe management module also identifies key shared resources such as transfer stations and transfer station handover areas required for each step, providing basic data for subsequent reservation and scheduling.

[0100] The scheduling module is the core prediction and planning hub of the entire system. Based on the aforementioned step sequence and the theoretical execution time of the equipment, this module generates a spatiotemporal path map with theoretical time annotations and creates candidate reservation windows with safety margins for each key shared resource on the time window reservation table. When the module detects an overlap or conflict between the current candidate reservation window and a confirmed time window in the reservation table, it automatically triggers a window negotiation mechanism to eliminate the conflict by calculating the minimum feasible shift. The scheduling module then formally writes the conflict-free window into the time window reservation table, thereby calculating the scheduling cycle time for the target basket. Furthermore, this module includes adaptive learning capabilities, enabling it to continuously and adaptively update the cycle prediction model and the safety margin parameters of key resources using subsequent actual execution data.

[0101] The execution control module interacts directly with the underlying drive components of the equipment. This module issues delayed start-up loading commands to the robotic arms according to the scheduling cycle time output by the scheduling module. During actual equipment operation, the execution control module collects the position information and task status of each robotic arm in real time. When physical execution jitter causes the actual windows entering the same resource to face the risk of overlap, it dynamically calculates the process time margin, waiting time, and remaining path length of each basket to determine the priority weight. Based on this, it assigns right-of-way to high-priority actions and guides low-priority actions to safe waiting positions, thereby ensuring deadlock-free execution of the overall scheduling scheme.

[0102] It should be noted that the system in this embodiment is a corresponding virtual device for executing the scheduling and control method in Embodiment 1 above. The specific implementation methods, logical judgment formulas, and technical effects achieved by each module in this system are exactly the same as those in Embodiment 1. To keep the specification concise, they will not be repeated here.

[0103] Example 3:

[0104] Based on the same inventive concept, this embodiment also provides an electronic device and a computer-readable storage medium for supporting the operation of the above embodiments 1 and 2.

[0105] The electronic device includes a processor, a memory, and a communication interface, all connected via a system bus. The memory stores computer program instructions for implementing the aforementioned slot-type equipment scheduling and control method based on predictive resource reservation, as well as data generated during operation, such as time window reservation tables and cycle prediction models. The processor calls the program instructions in the memory to implement the various control steps described in Embodiment 1. This electronic device can be an industrial PC (IPC) integrated into the slot-type equipment, a programmable logic controller (PLC), or a remote centralized scheduling server.

[0106] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the slot-based device scheduling and control method based on predictive resource reservation as described in Embodiment 1. The computer-readable storage medium can be a non-volatile storage medium, such as a disk, optical disk, read-only memory (ROM), or solid-state drive (SSD).

[0107] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for scheduling and controlling slotted equipment based on predictive resource reservation, characterized in that, A control system applied to equipment includes the following steps: The process formula of the target flower basket is analyzed to generate a step sequence containing movement steps and process steps, and the key shared resources required for the execution of each step are identified. The basic execution time of the target flower basket is calculated based on the step sequence and the theoretical execution time of the equipment, and a spatiotemporal path map with theoretical time annotations is generated for each step. Based on the spatiotemporal path map, a candidate reserved window with a safety margin is generated for the occupied interval of the target flower basket on the key shared resources; The candidate reserved window is compared with the pre-established time window reservation table. If there is a reservation conflict with the confirmed reserved window in the time window reservation table, window negotiation is performed, and the candidate reserved window is offset from the confirmed reserved window by calculating the time shift amount. After negotiating and eliminating conflicts, the candidate reserved window is written into the time window reserved table and marked as confirmed. The scheduling cycle time of the target flower basket is determined based on the base consumption time and the time shift amount. The target flower basket is loaded with materials in a delayed manner according to the scheduled cycle time. During the execution, actual execution data is collected to update the cycle prediction model and the safety margin parameters of the corresponding key shared resources for the prediction and scheduling of the next flower basket.

2. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 1, characterized in that, The candidate reservation window with safety margin is ; in, and Let be the theoretical start and end times of the k-th step of the target flower basket A, respectively. This refers to the safety margin parameter for resource r; When satisfied At that time, determine the candidate reserved window and the confirmed reserved window of target basket A. There is a reservation conflict on resource r.

3. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 1, characterized in that, The step of calculating a time shift to offset the candidate reserved window from the confirmed reserved window specifically includes: For each critical shared resource r where a conflict occurs, calculate the minimum feasible translation amount required to eliminate the conflict on that resource for the candidate reservation window of the target basket A in step k. ; The maximum and minimum feasible shift among all conflicting resources and steps are selected as the global shift. And shift all candidate reserved windows for target basket A backward on the timeline. .

4. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 3, characterized in that, During window negotiation, if the calculated global translation amount If the preset acceptance threshold is exceeded, an active path correction strategy is executed to regenerate the candidate reserved window; The active path correction strategy includes: adjusting the running speed parameters of the non-critical track segments before the target basket reaches the critical shared resource, or adding temporary waiting positions before reaching the critical shared resource, to change the time when the target basket arrives at the critical shared resource so that it falls into an idle window.

5. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 1, characterized in that, The process of performing delayed start feeding of the target flower basket according to the aforementioned scheduling cycle time also includes a priority coordination and guarantee mechanism: Real-time data collection of the robot's position, task status, and the occupancy status of key shared resources; When a priority collaborative control strategy is triggered when two or more robotic arms are detected to have a spatial overlap trend within the time window of entering the same critical shared resource, the priority collaborative control strategy is triggered. Calculate the priority weight of each flower basket that shows an overlapping trend, and give priority to the robot arm corresponding to the flower basket with the highest priority weight, and guide the other robot arms to the safe waiting position; wherein, the priority weight is calculated based on the process time margin, the waiting time and the remaining path length of the corresponding flower basket.

6. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 5, characterized in that, The key shared resources include at least the transfer station and the transfer station handover area for cross-robot arm strokes; after the robot arm corresponding to the flower basket with the highest priority weight completes the picking and placing action at the transfer station, the robot arm is controlled to immediately return to the adjacent position or the starting position of the next task, and the transfer station and the transfer station handover area are released.

7. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 1, characterized in that, The process of collecting actual execution data to update the beat prediction model and the corresponding safety margin parameters of the key shared resources specifically includes: Record the actual execution time of the target flower basket, calculate the error value between it and the theoretically generated scheduling time, and use a smoothing algorithm to update the time correction amount used to correct the time annotation of the spatiotemporal path map of the next flower basket; Record the arrival time deviation of the target flower basket into each key shared resource, and update the safety margin parameter of the corresponding key shared resource in an exponential smoothing manner so that the candidate reserved window generated next time matches the actual operating status of the device.

8. The slot-type equipment scheduling and control method based on predictive resource reservation according to claim 1, characterized in that, The time window reservation table is configured with a reservation expiration and dynamic recycling mechanism: When a serious timeout failure is detected in the upstream step of the target basket, which prevents it from reaching the corresponding critical shared resource before the start time of the confirmed reserved window, the control system automatically marks the reserved window as invalid and releases and reclaims it for other parallel baskets to apply for reservation.

9. A slot-type equipment scheduling and control system based on predictive resource reservation, characterized in that, include: The recipe management module is used to parse the process recipe of the target flower basket and generate a sequence of steps; The scheduling module is used to generate a spatiotemporal path map with theoretical time annotations based on the step sequence, and generate candidate reservation windows with safety margins for key shared resources on the time window reservation table; when there is a reservation conflict, it performs window negotiation to calculate the time shift, writes the conflict-free candidate reservation windows into the time window reservation table and outputs the scheduling cycle time. And continuously and adaptively update the beat prediction model and safety margin parameters using actual execution data; The execution control module is used to control the delayed start of the target flower basket according to the scheduling cycle time, and to perform right-of-way avoidance and collaborative scheduling between robotic arms by calculating priority weights during the execution process.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the slot-type equipment scheduling and control method based on predictive resource reservation as described in any one of claims 1 to 8.

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