Mining instrument production line control system and method based on adaptive scheduling and multi-protocol fusion

Abstract

The invention relates to the technical field of production control, in particular to a mining instrument production line control system and method based on adaptive scheduling and multi-protocol fusion, and the method executed by the system comprises the steps: 1, triggering a production task according to an order; 2, analyzing a production task, disassembling the production task into a plurality of sub-tasks, distributing the sub-tasks to different stations to implement production, and monitoring the state of each station in real time; wherein in the production process, the production mode is adjusted in real time according to the order priority and the production state of each station. Through the adaptive task scheduling engine, the system can dynamically optimize the task allocation and execution sequence according to the real-time production state, and effectively cope with disturbances such as emergency order insertion and equipment faults.

Description

Control System and Method for Mining Instrument Production Line Based on Adaptive Scheduling and Multi-Protocol Fusion Technical Field

[0001] This application relates to the field of production control technology, and in particular to a control system and method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion. Background Technology

[0002] With the advancement of the action plan for the intelligent development of coal mines, the demand for intelligent equipment in the construction of intelligent mines continues to grow, while higher requirements are being placed on product stability, production efficiency and traceability.

[0003] Existing mining instrument production lines mostly adopt manual or semi-automated production methods, which have the following prominent problems: the production process is simple and lacks flexibility. When there are different emergency orders or equipment failures at individual workstations, the entire production line needs to be shut down and the production plan needs to be rearranged. The coordination between multiple workstations is poor: each workstation relies on manual transfer, the production rhythm is not coordinated, resulting in low overall production efficiency.

[0004] While some existing technologies have made improvements in areas such as production line scheduling, data traceability, or equipment integration, a comprehensive solution integrating order management, multi-station collaborative control, intelligent material scheduling, full-process quality closed-loop, and data traceability has not yet been formed, making it difficult to meet the actual needs of intelligent and automated production of mining instruments. Summary of the Invention

[0005] The technical problem that this invention aims to solve is that existing production scheduling and control systems have poor production flexibility.

[0006] Therefore, the present invention provides a control system and method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion.

[0007] The technical solution adopted by this invention to solve its technical problem is: a control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion, including step one, triggering a production task according to an order; step two, parsing the production task, breaking it down into multiple sub-tasks and assigning them to different workstations for production, and monitoring the status of each workstation in real time; wherein, during the production process, the production mode is adjusted in real time according to the order priority and the production status of each workstation.

[0008] Furthermore, in step one, the priority of each order is evaluated. In step two, regular production is carried out in normal mode. If a high-priority order is received, the system switches to immediate mode. After the high-priority order is completed, the system returns to normal mode.

[0009] Furthermore, when switching to Immediate mode, the system will immediately check all available workstations and prioritize the allocation of high-priority orders to idle workstations for production.

[0010] Furthermore, the triggering conditions for the Immediate mode also include: after equipment failure is resolved, production rhythm needs to be quickly restored; key materials are in place, and production needs to be started immediately; manual intervention is required to designate an emergency task; the system detects a risk of production delay and automatically upgrades to emergency mode.

[0011] Furthermore, in step two, during normal production in Normal mode, when a long queue or abnormal equipment efficiency is detected at a certain workstation, the system switches to Dynamic mode to dynamically adjust the subsequent task paths.

[0012] Furthermore, the Dynamic mode diverts tasks from workstations with excessively long queues to other available workstations, adjusts the task execution order, prioritizes upstream tasks of bottleneck workstations, dynamically adjusts AGV paths to avoid congested areas, and balances the load. In Dynamic mode, the system calculates the load of each workstation in real time and prioritizes assigning new tasks to workstations with lower loads.

[0013] Furthermore, in step two, the status of each workstation is monitored in real time. In Dynamic mode, once production efficiency is restored to normal and the workstation queuing problem is resolved, the system is restored to Normal mode.

[0014] Furthermore, in the production process, a quality inspection module is set up at each key work station to realize online quality inspection.

[0015] Furthermore, during the production process, the processing parameters and test results of each workstation are recorded in the order information and form a traceability code.

[0016] A mine instrument production line control system based on adaptive scheduling and multi-protocol fusion includes an interaction layer that provides a human-machine interface for operating the control system; a process control module that receives orders, decomposes the orders into production plans into atomic tasks, and adjusts the workstation instruction sequence and execution order in real time under Normal, Immediate, and Dynamic modes to implement production; a data processing module that monitors the production process and determines production quality; and an equipment driver module that connects to various production devices through different serial ports and converts equipment instructions and data of different protocols into an internally unified format.

[0017] The beneficial effects of this invention are: (1) significantly improving production efficiency and resource utilization: through the adaptive task scheduling engine, the system can dynamically optimize task allocation and execution sequence according to the real-time production status (workstation load, equipment availability), effectively dealing with disturbances such as emergency order insertion and equipment failure. As shown in Figures 1 and 3, this dynamic scheduling reduces workstation waiting time, makes the production line cycle time more balanced, thereby increasing the overall production efficiency by about 40%, and significantly improving the overall equipment utilization rate (OEE).

[0018] (2) Achieving closed-loop quality control throughout the entire process and improving product consistency: By deeply integrating online visual inspection and electrical performance testing into each key workstation, and utilizing the algorithm of the data processing module for real-time automatic judgment, the system achieves an instantaneous closed loop of "inspection-judgment-diversion". Non-conforming products (NG) are immediately and automatically sorted to prevent defective products from flowing, while all quality data are completely recorded. This mechanism enables the product yield rate to be stably increased to over 98.5%.

[0019] (3) Building a refined, end-to-end data traceability capability: This invention innovatively establishes a multi-level associated data traceability model as shown in Figure 7. By binding barcode information to key production nodes (such as marking, assembly, and testing), the system structurally associates and persistently stores the order number, product unique SN code, core component code, process parameters (such as tightening torque), and all test results. As shown in Figure 12, this model supports reverse querying of the entire product lifecycle data through any unique code, achieving 100% traceability coverage and providing accurate and efficient data support for quality analysis, process optimization, and product recall.

[0020] (4) Significantly reduced reliance on manual labor and operating costs: The entire process, from order parsing, material scheduling, equipment coordination to quality judgment and data entry, is highly automated. The intelligent anti-duplication mechanism avoids errors in manual verification, and automatic material calling and AGV scheduling reduce the need for material handlers. These automation features significantly reduce the number of operators required for the production line, and according to implementation calculations, it can reduce related labor costs by about 60%, while also reducing quality losses caused by human error.

[0021] (5) Effectively solves the problems of equipment heterogeneity and "data silos": Faced with equipment (PLC, robot, camera, barcode scanner, etc.) with different brands, interfaces and communication protocols in the production line, this system uses the device driver module of the business logic layer to perform unified protocol encapsulation and adaptation. This multi-protocol converged communication technology enables different devices to be configured, monitored and driven in a unified manner, realizing seamless integration and data interoperability of heterogeneous devices, and completely breaking down "data silos".

[0022] (6) Excellent flexibility and scalability: Due to the adoption of a layered, modular software architecture and parameterized configuration, when producing different models and specifications of mining instruments, the scheduling strategy, process formula, and equipment parameters can be adjusted mainly through software to adapt to new requirements without the need for large-scale modifications to hardware wiring and mechanical structures. This enables the system to quickly respond to the production needs of multiple varieties and small batches, with wide adaptability and a long life cycle. Attached Figure Description

[0023] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] Figure 1 is a schematic diagram of the business process of the mine instrument production line control system based on adaptive scheduling and multi-protocol fusion in this invention.

[0025] Figure 2 is a hierarchical architecture diagram of the mine instrument production line control system based on adaptive scheduling and multi-protocol fusion in this invention.

[0026] Figure 3 is a schematic diagram of the order management interface of the host computer software in this invention.

[0027] Figure 4 is a schematic diagram of the MES dashboard interface of the host computer software in this invention.

[0028] Figure 5 is a schematic diagram of the data upload and code binding interface of the host computer software in this invention.

[0029] Figure 6 is a schematic diagram of the capacity statistics interface of the host computer software in this invention.

[0030] Figure 7 is a schematic diagram of the data query interface of the host computer software in this invention.

[0031] Figure 8 is a schematic diagram of the settings interface of the host computer software in this invention.

[0032] Figure 9 is a schematic diagram of the administrator login permissions of the host computer software in this invention.

[0033] Figure 10 is a flowchart of the system workflow based on state transition in this invention.

[0034] Figure 11 is a schematic diagram of hardware system integration and communication protocol fusion in this invention.

[0035] Figure 12 is a state machine implementation diagram of the adaptive task scheduling system in this invention.

[0036] Figure 13 is a flowchart of the intelligent anti-duplication mechanism in this invention.

[0037] Figure 14 is a diagram of the multi-level association full-process data traceability model in this invention. Detailed Implementation

[0038] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, illustrating only the basic structure of the invention, and therefore only show the components relevant to the invention.

[0039] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, features defined with "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0040] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0041] A mine instrument production line control system based on adaptive scheduling and multi-protocol fusion adopts a layered architecture design as shown in Figure 2. From top to bottom, it includes an interaction layer, a business logic layer, a data access layer, and a device layer. Each layer interacts with the others through standardized interfaces, achieving high cohesion and low coupling to support the entire business process from order to warehousing shown in Figure 1. The interaction layer, business logic layer, and data access layer are all housed in the host computer software.

[0042] The interaction layer is built on a graphical user interface framework (such as Windows Forms) and provides a series of human-computer interaction interfaces as shown in Figures 3 to 8. These interfaces include the order management interface (Figure 3), the MES dashboard monitoring interface (Figure 4), the data upload and code binding interface (Figure 5), the capacity statistics interface (Figure 6), the data query interface (Figure 7), and the system settings interface (Figure 8), which are used to display the production status of the entire production line, equipment data, alarm information in real time, and to receive control commands and parameter configurations from operators.

[0043] Business Logic Layer: As the core of the control system, it includes the following collaborative modules: Process Control Module: Integrates an adaptive task scheduling engine based on a finite state machine (its state transition logic is shown in Figure 12). This engine dynamically decomposes the production plan into atomic tasks based on received production orders (managed through the interface in Figure 3) and real-time production status (including workstation availability, material readiness, and equipment status) as shown in Figure 10. It also adjusts the workstation instruction sequence and execution order in real-time under three modes: Normal, Immediate, and Dynamic, to respond to order changes, equipment malfunctions, or production bottlenecks.

[0044] Data processing module: Integrates core algorithms, including: a barcode matching and anti-duplicate algorithm for the process shown in Figure 13, ensuring that the product's unique code is not repeated during circulation; a real-time material requirement calculation algorithm based on BOM, providing support for accurate material requisition; and a quality data classification algorithm for online quality judgment, which performs real-time monitoring, instant analysis, and OK / NG judgment on production data such as images captured by industrial cameras or data uploaded by testing equipment (as shown in the right branch of Figure 10).

[0045] Device driver module: This module encapsulates a multi-protocol communication driver library, enabling unified abstract access to heterogeneous devices as shown in Figure 11. It integrates adaptation and parsing of Modbus TCP / RTU (for PLCs and test benches), TCP / IP Socket (for robots and marking machines), RS-232 / 485 serial ports (used with a converter for barcode scanners), and custom serial protocols, converting device commands and data from different protocols into a unified internal format.

[0046] Business service module: Provides functions such as order lifecycle management, user access control, and process recipe management, and encapsulates standard interfaces such as RESTful API to achieve stable data interaction with the upper-level manufacturing execution system (MES) (as shown in the "Data Reporting and MES Integration" section at the bottom of Figure 10).

[0047] Data Access Layer: Employing the Data Access Object (DAO) design pattern, this layer connects to a lightweight relational database (such as SQLite). It is responsible for efficiently storing and retrieving production data throughout the entire process, particularly supporting the structured and unstructured data required for the multi-level correlation traceability model shown in Figure 14, which includes "order number - product SN code - key component code - process parameters - test results".

[0048] The equipment layer includes various industrial devices as shown in the network topology of Figure 11, such as control devices (PLCs), identification devices (barcode scanners, industrial cameras), processing devices (laser marking machines, robots), testing devices (performance testing benches), and material handling equipment (AGVs). These devices are connected via physical links such as industrial Ethernet and serial buses, and, with the help of multi-protocol converged communication technology in the business logic layer, they are subject to unified scheduling to achieve intelligent collaborative operation.

[0049] The system's operation is based on state transitions as its core logic (as shown in the main process in Figure 10 and the state machine in Figure 12), driving the production line to complete an automated control loop from order initialization, multi-station collaborative production, online quality judgment and automatic diversion (as shown in the NG diversion path in Figure 10), to end-to-end data binding and traceability (as shown in Figures 14, 5, and 7). Through the above-mentioned layered and decoupled architecture and modular design, this invention achieves flexible and traceable intelligent production of mining instruments.

[0050] A control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion includes the following steps: Step 1: System login permissions, data initialization, and hardware integration configuration are shown in Figure 9. Different system permissions are assigned to operators, managers, and maintenance personnel. Managers (prefixed with AD) have permissions to modify parameters and export reports. Operators (prefixed with OP) only have permissions to view production status and report anomalies. Maintenance personnel (prefixed with MR) mainly have permissions to perform maintenance tasks, such as viewing work orders, updating maintenance status, and recording working hours and parts usage.

[0051] Data initialization includes database initialization, creation of material information tables, order information tables, production process data tables, quality inspection tables, etc. Data backup is set to automatic daily backup upon completion of tasks. Before daily production, operators perform equipment self-checks through the application-layer monitoring system, checking sensor accuracy, communication link stability, and PLC operating status. Weekly cleaning and calibration of sensing layer equipment, monthly firmware updates for transmission layer gateways and switches, and quarterly hardware inspections of edge computing nodes and servers are conducted. When a communication link fails, the system automatically switches to a redundant link to ensure uninterrupted data transmission. If an edge computing node fails, a backup node (configured identically to the primary node) is immediately activated, with a switchover time of ≤3 seconds, ensuring no production data loss. An operation and maintenance log is established to record the time, cause, handling process, and results of equipment failures, providing valuable data for subsequent optimization.

[0052] The hardware system is centered around a central industrial control computer (host computer), as shown in Figure 11. It connects to devices at each layer via an industrial Ethernet switch, forming a star topology network. Specific connections and protocol configurations are as follows: Control devices: The production line main control PLC (Siemens S7-1200 series) and each workstation substation PLC (Inovance H3U series) are connected to the switch via Ethernet modules. The device driver module of the host computer's business logic layer is configured with the Modbus TCP protocol. The IP address of the main station PLC is set to 192.168.1.10, and the port is 502.

[0053] Identification devices: As shown in Figure 8 (order management interface), the fixed industrial barcode scanner (Keyence SR-1000) and the handheld PDA barcode scanner are connected via a serial port server (MOXA NPort 5150) that converts the data to TCP / IP signals. The fixed industrial barcode scanner (Keyence SR-1000) has an IP address of 192.168.1.67 and a port of 2002, while the handheld PDA barcode scanner has an IP address of 192.168.1.68 and a port of 2002. The visual positioning camera (Hikvision MV-CE series) is directly connected to the host computer via the GigE interface. Custom serial port protocols (baud rate 115200, 8-N-1) and GigE Vision protocols are configured for each device in the device driver module.

[0054] Processing and execution equipment: The six-axis assembly robot (FANUC series) and laser marking machine (Han's Laser) are connected via their built-in Ethernet ports. The host computer communicates with them through a TCP Socket client encapsulated in the device driver module. The robot controller's IP is 192.168.1.20, port 3000; the marking machine's IP is 192.168.1.21, port 8000.

[0055] Testing and Material Equipment: The comprehensive performance test bench is connected via RS-485 bus, using the Modbus RTU protocol, with address 01. The AGV scheduling system interacts with the host computer's business service module through a WebService API interface. After configuration, enter the aforementioned IP address, port, and protocol parameters into the system through the settings interface shown in Figure 8, and test the communication link status of all devices to ensure the "device layer" is ready.

[0056] Step 2: Order Import and Production Plan Generation (Refer to Figures 1 and 3) The production process begins with order placement. As shown in Figure 3 (Order Management Interface), operators can import orders in two ways: the MES system automatically imports orders and they can be imported manually.

[0057] Orders are automatically imported via the MES system: The business service module receives production orders from the MES system via a RESTful API, automatically parsing the order number, product model, quantity, priority, and delivery date. Order information is then manually entered in the "Order Settings" area of ​​the interface.

[0058] Once an order enters the system, it triggers the adaptive scheduling engine in the process control module. As shown in Figure 1, the scheduling engine first accesses the "Component Library" to check the inventory status of materials such as housings, sensors, PCBs, and back covers. Combining the Bill of Materials (BOM) and current capacity, the engine dynamically decomposes the order and generates an executable production plan. The plan is based on "batches," specifying the sequence, quantity, and required process formula for each batch of housings (as shown in the "Current Order Details" area of ​​Figure 3). After the plan is generated, the status is updated to "Scheduled" in the "All Order Information" list area.

[0059] Importing orders manually: As shown in Figure 3, select the order number to import next to the "Restore Orders" button, and fill in the order information according to the corresponding format.

[0060] Step 3: Adaptive Task Scheduling and Multi-Workstation Collaborative Execution (Refer to Figures 1, 10, and 12) After the batch plan is issued, the system enters the multi-workstation collaborative production stage centered on state transition. Figures 10 and 12 together depict this process: Task parsing and state monitoring: The scheduling engine's "task parsing layer" breaks down the batch plan into atomic tasks (such as "grab shell - workstation A" and "scan barcode - workstation B"). At the same time, the "state management layer" monitors the status of each workstation in real time (running, idle, faulty, blocked), forming a global state matrix.

[0061] Event-driven and dynamic scheduling: The system adopts an event-driven architecture. For example, when "shell preparation" is completed (event), the status of workstation A changes to "idle" (state), triggering the "execution scheduling layer" of the scheduling engine to assign the "shell grabbing and conveying" task to that workstation. As shown in Figure 12, scheduling supports three modes: Normal mode: regular production, tasks are executed in queue order.

[0062] Immediate mode: Used for high-priority orders or urgent tasks after equipment recovery, prioritizing resource allocation.

[0063] Dynamic mode: When a long queue or abnormal equipment efficiency is detected at a workstation, the subsequent task path is dynamically adjusted.

[0064] Inter-station flow and anti-duplicate control: Materials (work-in-process) flow between workstations via conveyor lines or AGVs. Each flow node is equipped with a barcode scanning point. The intelligent anti-duplicate mechanism shown in Figure 13 takes effect here: When the product shell first arrives at the "Shell Recognition" workstation (Figure 1), the barcode scanner reads its unique code (such as a QR code). The barcode matching algorithm of the data processing module immediately verifies in memory whether the code already exists in the current production task set. If it is a duplicate code (such as due to reflow), the system immediately triggers a "Duplicate Code Warning" in the "Alarm Monitoring Display" area of ​​Figure 4 (MES Kanban interface) and suspends the flow of the material, awaiting manual handling. This mechanism is also applied to "Material Calling Anti-Duplicate" (preventing AGVs from repeatedly transporting the same material) and "PLC Command Anti-Duplicate" (verified through command serial number verification).

[0065] Specifically, Normal mode is the system's basic scheduling mode, applied to the execution of regular orders in a stable production environment, with no special priority requirements. Production plans are stable, material supply is sufficient, and there are no urgent delivery needs. This mode follows the "First-In, First-Out" (FIFO) principle, with tasks executed sequentially according to the batch plan's issuance order and the natural order of the workstation queues.

[0066] The Immediate mode inserts urgent orders during the Normal mode based on their urgency. It is used to handle urgent orders, urgent tasks after equipment recovery, or special production needs requiring rapid response. It is suitable for small-batch, rapid delivery tasks and allows urgent orders to prioritize the use of available resources on the production line. After the urgent order is completed, production resumes to Normal mode. The Dynamic mode is the system's intelligent scheduling mode. It dynamically adjusts task execution paths and resource allocation strategies by monitoring the production status in real time to cope with abnormal situations and efficiency fluctuations during the production process.

[0067] Specifically, in Normal mode, its core mechanisms are: 1) Task queue management: The system maintains a global task queue, adding atomic tasks (such as "grab shell - station A", "scan barcode - station B", "laser marking - station P30", etc.) after batch plan decomposition into the queue in sequence; 2) Station status matching: The scheduling engine monitors the status matrix of each station in real time. When the target station status is detected as "idle", the corresponding task is taken from the head of the queue and assigned to that station; 3) Sequential execution guarantee: Tasks are executed strictly in the order of the queue to ensure the predictability and traceability of the production process; 4) Balanced resource allocation: When multiple stations can execute the same type of task, the system allocates resources according to the load balancing principle to avoid overloading of a certain station.

[0068] The switching mechanism for Immediate mode is as follows: 1) Priority marking: The system sets priority markers for tasks. Immediate mode tasks have the highest priority (e.g., priority value = 100, Normal mode task priority value = 50). High-priority orders include VIP customer orders and emergency replenishment orders; 2) Resource preemption: When an order has a priority value greater than 50, an Immediate mode switching task is issued. The system will immediately check all idle workstations. Even if the workstation is waiting for a Normal mode task, it will be given priority to be assigned to an Immediate task. It should be noted that Immediate mode switching tasks will also be generated in the following situations: after equipment failure is recovered, production rhythm needs to be restored quickly; key materials are in place, production needs to be started immediately; manual intervention is required for designated emergency tasks; the system detects the risk of production delay and automatically upgrades to emergency mode; 3) Queue insertion: Immediate tasks do not enter the tail of the regular queue, but are inserted at the front of the queue at an idle workstation, or a separate emergency task queue is created; 4) Fast response: The system will skip the regular queue waiting time and directly trigger the task allocation process.

[0069] Dynamic mode is mainly used when bottleneck workstations occur in the production process, or when the material supply is unstable and dynamic adjustments are needed, or when multiple orders are produced in parallel and resource allocation needs to be optimized.

[0070] The core mechanisms of Dynamic mode are: 1) Real-time monitoring of the entire system: The system continuously monitors the status indicators of each workstation, including: workstation queue length (number of waiting tasks), workstation processing efficiency (number of tasks completed per unit time), workstation failure rate (number of failures / total running time), and material flow speed (time for work-in-process to flow between workstations); 2) Detection of abnormal system states: When the following situations are detected, the system automatically switches to Dynamic mode: the queue length of a workstation exceeds the threshold (e.g., >10 tasks), the workstation processing efficiency is more than 20% lower than the normal value, abnormal equipment efficiency is detected (e.g., sudden increase in processing time), and material flow is blocked; 3) Path optimization: Dynamic mode will recalculate the task execution path: divert tasks from workstations with excessively long queues to other available workstations, adjust the task execution order, prioritize the upstream tasks of bottleneck workstations, dynamically adjust AGV paths to avoid congested areas, and load balancing: the system will calculate the load of each workstation in real time and prioritize the allocation of new tasks to workstations with lower loads.

[0071] In this embodiment, the triggering conditions for Dynamic mode are: 1) The system automatically detects that the queue at the workstation is too long (the threshold is configurable, such as >8 tasks); 2) The equipment efficiency is abnormal (the processing time exceeds the normal value by 30%); 3) The material flow is blocked (the time that work-in-process stays at a certain workstation exceeds the threshold); 4) The load of multiple workstations is unbalanced (the load difference is >50%); 5) The dynamic adjustment command is manually triggered.

[0072] In this embodiment, several application examples from real-world production processes are used to further illustrate this section.

[0073] Case 1: Mode switching scenario description in normal production: A batch of orders (order number: PO-2024-001, quantity: 500 pieces) is placed normally, and the system enters Normal mode for production.

[0074] In the case study, the execution process of Normal mode is as follows: 1. Task parsing: The batch plan is broken down into an atomic task sequence: Task 1: Shell preparation - Station A (100 pieces) Task 2: Shell grabbing and conveying - Station A (100 pieces) Task 3: Barcode scanning and recognition - Station B (100 pieces) Task 4: Laser marking - Station P30 (100 pieces) ... (subsequent station tasks) 2. Status monitoring: The status management layer monitors in real time: Station A: Idle → Running → Idle (loop) Station B: Idle → Running → Idle (loop) Station P30: Idle → Running → Idle (loop) 3. Task allocation: When the status of Station A changes to "Idle", the scheduling engine retrieves the "Shell grabbing and conveying" task from the queue and allocates it to Station A.

[0075] 4. Normal execution: Tasks are executed sequentially according to the queue order, and 300 tasks have been completed.

[0076] Switch to Immediate mode: At this time, the system receives an urgent order (order number: PO-2024-002, quantity: 50 pieces, priority: high) that needs to be produced immediately.

[0077] The switching steps used in this case are as follows: First: Priority identification: The system identifies PO-2024-002 as a high-priority order and automatically switches to Immediate mode.

[0078] Second: Task insertion: Urgent orders are inserted at the front of the queue with a priority of 100.

[0079] Third: Resource preemption: When the P30 workstation completes the current Normal mode task, the system immediately assigns an Immediate mode task instead of continuing to process tasks in the Normal queue.

[0080] Fourth: Rapid execution: Urgent orders of 50 products are completed within 30 minutes, prioritizing the use of all available workstation resources.

[0081] Case switching back to Normal mode: After the emergency order is completed, the system automatically switches back to Normal mode and continues to execute the remaining 200 tasks of PO-2024-001.

[0082] Case 2: Mode switching scenario after equipment failure recovery: The system was operating normally in Normal mode when the P30 laser marking station suddenly malfunctioned.

[0083] Case 2 Handling Steps: When the status management layer detects that the status of workstation P30 changes from "Running" to "Fault," the scheduling engine suspends the tasks assigned to workstation P30 and adds them back to the queue to wait. Then, the system triggers a "P30 Workstation Fault" alarm on the MES dashboard interface.

[0084] Equipment Fault Recovery: Step 1: After maintenance is completed, the P30 workstation status will change from "Faulty" to "Idle". Step 2: When the system detects equipment recovery, it will automatically switch to Immediate mode to prioritize handling tasks backlogged due to the fault. Step 3: At this time, the P30 workstation will receive priority task assignment and quickly process the backlog queue (e.g., 15 tasks backlogged). Step 4: Once the backlog of tasks is reduced to a normal level (<5), the system switches back to Normal mode.

[0085] Case switching logic: After the equipment is restored, if the number of backlogged tasks is >10, it will be in Immediate mode; if the number of backlogged tasks is 5-10, it will be in Dynamic mode (dynamic adjustment to speed up processing); if the number of backlogged tasks is <5, it will be in Normal mode. Case 3: Dynamic adjustment in Dynamic mode. Case scenario description: The system is producing in Normal mode, and multiple workstations are processing tasks from different orders in parallel.

[0086] Initial state (Normal mode): Station A (shell grabbing): 3 tasks in queue, processing efficiency is normal; Station B (barcode scanning and recognition): 2 tasks in queue, processing efficiency is normal; Station P30 (laser marking): 8 tasks in queue, processing efficiency is normal; Station P31 (next process): 1 task in queue, processing efficiency is normal.

[0087] In Case 3, when the system detects an abnormal state, it will trigger Dynamic mode: First, the system monitors that the queue length of P30 workstation increases from 8 to 15 (exceeding the threshold of 10), and the processing efficiency decreases by 20%.

[0088] Second: The system automatically switches to Dynamic mode.

[0089] Third: Dynamic mode analysis revealed that if the processing speed of the upstream (B) station of P30 increases, it leads to an increase in input to P30 station and a slight decrease in the efficiency of the P30 station equipment (possibly due to equipment aging or environmental factors). In this case, Dynamic mode automatically adjusts its strategy: 1. Diverting some tasks from P30 station to a backup marking station (if one exists), adjusting the output rhythm of the upstream B station, and temporarily slowing down material delivery to P30 station; 2. Prioritizing the processing of the longest-waiting tasks in the P30 station queue (to prevent timeouts), temporarily buffering newly arriving tasks, and waiting for the P30 station queue to decrease; 3. Checking if other stations can share some of the work of P30 station, dynamically adjusting the AGV path, and prioritizing material delivery to P30 station. After 30 minutes of adjustment, the queue length at P30 station decreased to 6, the system detected that the queue length had returned to normal, and automatically switched back to Normal mode, restoring stable production cycle time.

[0090] Case 4: Multi-mode collaborative application scenario description: The system processes multiple orders simultaneously, requiring three modes to work together.

[0091] Case production environment: Order 1 (PO-001): Regular order, 500 pieces, Normal mode; Order 2 (PO-002): Urgent order, 50 pieces, Immediate mode; Order 3 (PO-003): Regular order, 300 pieces, Normal mode.

[0092] Initial state of the case: All order tasks enter a unified task queue, but with different priority markers: PO-002 task: priority 100 (Immediate); PO-001 task: priority 50 (Normal); PO-003 task: priority 50 (Normal).

[0093] Case execution process: First: Immediate mode priority: All tasks of PO-002 are executed first, quickly occupying available workstation resources.

[0094] Second: Normal mode parallel execution: PO-001 and PO-003 tasks are executed in FIFO order, but PO-002 task can be interrupted at any time.

[0095] Third: Dynamic mode intervention: When it is detected that the queue of workstation A (shell grabbing) is too long (12 tasks): The hypothetical analysis of the case found that if the urgent task of PO-002 occupies a lot of workstation A resources, the Dynamic mode will adjust: temporarily cache some tasks of PO-001 and PO-003, prioritize the completion of PO-002, and optimize the AGV path to speed up the material flow.

[0096] Based on the analysis results, the system executed the following timeline: T0-T30 minutes: Normal mode (PO-001 and PO-003 executed normally); T30 minutes: Urgent order PO-002 arrived → switch to Immediate mode; T30-T60 minutes: Immediate mode (PO-002 executed first); T45 minutes: Long queue detected at workstation A → Dynamic mode was enabled for optimization; T60 minutes: PO-002 completed → switch back to Normal mode; T60-T120 minutes: Normal mode (PO-001 and PO-003 continued to execute).

[0097] In this embodiment, through intelligent switching and collaborative work of three modes, the system can maintain efficient and stable operation in various production scenarios, achieving true adaptive task scheduling and multi-workstation collaborative execution.

[0098] Step 4: Online Quality Inspection and Full-Process Traceability (Refer to Figures 1 and 10) Quality inspection is deeply embedded in each key assembly and testing station, and can be traced and queried throughout the entire process, forming a closed loop, as shown in the "Online Quality Inspection" branch on the right side of Figures 1 and 10: Assembly Process Inspection: At the "Shell Component Assembly" station, an industrial camera captures the assembly results. The data processing module's quality data classification algorithm (based on OpenCV edge detection and template matching) analyzes the images to determine whether sensors, PCB boards, etc., are installed correctly. The results are fed back to the process control module in real time.

[0099] Performance Testing and Automated Sorting: The assembled semi-finished products enter the "Performance Testing" station. The testing equipment sequentially performs "Rotation Test," "Pressure Resistance Test," and "Performance Test" (see Figure 10). The results of each test (pass / fail and specific parameters) are collected and uploaded in real time by the equipment driver module.

[0100] Judgment and Diversion: The central control unit makes immediate judgments based on preset standards (e.g., withstand voltage ≥1500V). Qualified products flow into the next process, "laser marking." Unqualified products (NG) immediately trigger a diversion command: the process control module modifies the product's status and instructs the PLC to control cylinders or baffles to physically push it into the NG return line. The defect type, occurrence station, and timestamp of all NG products are recorded.

[0101] Full-process traceability query: During the production process, the processing parameters of each workstation (including the material's entry time, exit time, and process parameters at that workstation) and the test results are recorded in the order information and form a traceability code.

[0102] Managers can use the application-layer traceability system to input product traceability codes or order numbers to query the entire lifecycle data of a product, from material warehousing, processing parameters at each workstation, test results, operators, to the time of shipment. The traceability data is retained for no less than 3 years. When a quality complaint occurs, the problematic process and responsible personnel can be located within 5 minutes through the traceability code, supporting quality improvement.

[0103] Step 5: Data Binding, Traceability, and Finished Product Warehousing (Refer to Figures 1, 14, and 5) Laser Marking and Data Binding: Qualified products arrive at the laser marking station, where the marking machine engraves a unique product serial number (SN) on their casing. Simultaneously, the system performs the core data association operation. The multi-level association traceability model shown in Figure 14 is constructed here: the data management module logically associates the order number, the newly generated product SN, the casing code used for the product, the batch code of core components (such as sensors), and the process parameters (such as tightening torque) and test results of each station, and stores them in the database. This binding process ensures a complete and tamper-proof data chain.

[0104] Data Upload and Code Binding: All production data (including binding relationships) is not uploaded to MES in real time, but is temporarily stored locally. Operators can manage this data through the interface shown in Figure 5: They can view products that have been produced but not yet synchronized in the "Products Awaiting Upload List". Using the "Data Upload Control" button, operators can manually or automatically package and upload a batch of data to the MES server. If the system detects that a product's part code is missing (e.g., scanning failed), the product will appear in the "Missing Products List", and operators can use the "Code Binding Control" function to manually add and associate it.

[0105] Finished Product Warehousing and Process Completion: After data binding is completed and the qualified finished products undergo a final visual inspection, they are transported by AGV to the designated storage location in the automated warehouse. The system updates the batch status to "Completed," as shown in Figure 1, the end point of the process.

[0106] Step 6: Production monitoring, statistics and query (refer to Figures 4, 6 and 7) Throughout the production process, managers can conduct comprehensive monitoring and analysis through the software interface: Real-time monitoring: As shown in Figure 4 (MES dashboard interface), the status of each workstation ("Production Line Monitoring" area), the working status of the laser marking machine, real-time alarm information and the current scanning process progress can be viewed in real time.

[0107] Production Capacity Statistics: As shown in Figure 6, after selecting the date and shift, the system automatically calculates and displays key indicators such as total output, number of good products, number of defective products, first-pass yield, and OEE (Overall Equipment Effectiveness). The "Product Details" section allows users to drill down to view the production time for each product.

[0108] Data Traceability Query: As shown in Figure 7, the interface provides powerful traceability capabilities. Enter any code (order number, product SN code, shell code) in the "Unique Identifier Code Recognition" box and click "Query." The complete production history of the product will be displayed below, including all associated material information, process parameters, test data, and operation records. The query results can be exported as reports.

[0109] In summary, this specific implementation method, through the aforementioned six steps, details the entire process from hardware networking and order import to intelligent scheduling, collaborative production, quality control, data traceability, and finally, finished product warehousing. The implementation details of each step are closely integrated with the corresponding diagrams, providing a clear and operable technical solution that ensures the system's efficient, stable, and reliable operation.

[0110] Based on the above-described preferred embodiments of the present invention, and through the foregoing description, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined by the scope of the claims.

Claims

1. A control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion, characterized in that, The process includes: Step 1, triggering production tasks based on orders; Step 2, parsing production tasks, breaking them down into multiple sub-tasks and assigning them to different workstations for production, and monitoring the status of each workstation in real time; and during the production process, adjusting the production mode in real time based on order priority and the production status of each workstation.

2. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 1, characterized in that, In step one, the priority of each order is evaluated. In step two, regular production is carried out in normal mode. If a high-priority order is received, the system switches to immediate mode. After the high-priority order is completed, the system returns to normal mode.

3. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 2, characterized in that, When switching to Immediate mode, the system will immediately check all available workstations and prioritize the allocation of high-priority orders to idle workstations for production.

4. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 2, characterized in that, The triggering conditions for the Immediate mode also include: after equipment failure is resolved, production rhythm needs to be restored quickly; critical materials are in place, and production needs to be started immediately; manual intervention is required for designated emergency tasks; and the system detects a risk of production delay and automatically upgrades to emergency mode.

5. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 2, characterized in that, In step two, during normal production in Normal mode, if a long queue or abnormal equipment efficiency is detected at a certain workstation, the system switches to Dynamic mode to dynamically adjust the subsequent task paths.

6. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 5, characterized in that, The Dynamic mode diverts tasks from workstations with long queues to other available workstations, adjusts the task execution order, prioritizes upstream tasks of bottleneck workstations, dynamically adjusts AGV paths to avoid congested areas, and balances the load. In Dynamic mode, the system calculates the load of each workstation in real time and prioritizes assigning new tasks to workstations with lower loads.

7. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 5, characterized in that, In step two, the status of each workstation is monitored in real time. In Dynamic mode, once production efficiency is restored to normal and the workstation queuing problem is resolved, the system is switched back to Normal mode.

8. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 1, characterized in that, In the production process, a quality inspection module is set up at each key work station to realize online quality inspection.

9. The control method for a mining instrument production line based on adaptive scheduling and multi-protocol fusion according to claim 1, characterized in that, During the production process, the processing parameters and test results of each workstation are recorded in the order information and form a traceability code.

10. A control system for a mining instrument production line based on adaptive scheduling and multi-protocol fusion, characterized in that, The system includes an interaction layer that provides a human-machine interface for operating the control system; a process control module that receives orders, breaks them down into production plans, and adjusts the workstation instruction sequence and execution order in real time under Normal, Immediate, and Dynamic modes to implement production; a data processing module that monitors the production process and determines production quality; and a device driver module that connects to various production devices via different serial ports and converts device instructions and data from different protocols into an internally unified format.

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