50 results about "Manufacturing intelligence" patented technology

The invention discloses a dynamic real-time rendering method for a large-scale assembly scene based on three-dimensional Gaussian splashing, a three-dimensional Gaussian splashing model for real-time rendering of a dynamic scene is constructed through combination of a plurality of sensors, and the method can render any view angle of the assembly scene. The three-dimensional Gaussian splash model comprises sensor data alignment, initialization of the three-dimensional Gaussian splash model and prediction and updating of the three-dimensional Gaussian splash model, and a scene space point alignment and predictor is designed by combining the three-dimensional Gaussian splash model, so that the problems of redundancy of multi-sensor data information and difficulty in dynamic real-time rendering are solved; according to the method, the assembly safety and reliability are improved, the problems in the assembly process can be found and processed in time, rapid and high-quality development of industrial intelligent manufacturing is promoted, and therefore transformation of industrial manufacturing intelligence is promoted.

According to the mechanical arm control method based on multi-scale dynamic state estimation and error compensation, high-frequency and high-precision estimation of the state of a mechanical arm system is achieved through multi-sensor data fusion and an extended Kalman filtering algorithm, and the accuracy and reliability of state estimation are remarkably improved; on the basis, a multi-scale error analysis method combining a time domain and a frequency domain is provided, and an autoregressive moving average model is utilized to dynamically predict system errors, so that the sensing and pre-judging capability of the system on the errors is enhanced; a comprehensive control strategy including multiple links of feedforward, self-adaption and feedback is designed, a dynamic compensation and adjustment mechanism of errors is introduced, meanwhile, a real-time execution framework based on three-layer task scheduling is constructed, cooperative operation of all functional modules is coordinated, and the real-time performance and high efficiency of a control system are ensured. The method is suitable for multiple fields of industrial manufacturing, intelligent robots and the like, and provides technical support for precise control of mechanical arms in complex scenes.

The invention discloses a multi-agent asynchronous collaboration method and system under a centralized architecture, and is suitable for task scheduling and resource coordination of heterogeneous agents in an intelligent Internet of Things environment. According to the method, a main scheduling node centralized control mechanism is adopted, a scheduling priority function is calculated in combination with a multi-agent game model according to real-time state information of a plurality of heterogeneous agents, and asynchronous allocation and feedback control of tasks are achieved. Meanwhile, an asynchronous and synchronous window mechanism is introduced, the scheduling continuity and efficiency can still be kept under the condition of incomplete information, and fairness and robustness of task distribution are achieved through agent feedback delay modeling and revenue function design. The system throughput and the response speed are improved, the isomerism and the expandability are considered, and the method is suitable for multi-agent cooperation scenes such as disaster emergency, industrial manufacturing, smart home and intelligent traffic.

The invention relates to the technical field of electric power data analysis, in particular to an industrial manufacturing intelligent early warning method and system based on electric power data, and the method comprises the steps: obtaining industrial manufacturing electric power data, and carrying out the preprocessing of the industrial manufacturing electric power data, and obtaining electric power feature data; inputting the electric power characteristic data into a pre-trained electric power data prediction model to obtain an electric power data prediction value in a prediction time period; on the basis of the electric power data predicted value in the prediction time period, a health index function constructed in advance is used for calculation to obtain an industrial equipment health index; and comparing the health index of the industrial equipment with a preset health threshold value, and if the health index of the industrial equipment is lower than the health threshold value, sending an equipment fault alarm to a control terminal. According to the method, the dynamic mode and the long-term dependency relationship in the data are deeply mined, the health state of the equipment is comprehensively evaluated, accurate fault early warning is realized, and the accuracy and the reliability of fault early warning are greatly improved.

The invention provides a method for developing a tool function for an intelligent agent through computing power of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructures, and the method comprises the following steps: S1, a manufacturing intelligent agent receives task information provided by a user through an interactive interface and used for developing the tool function for a target intelligent agent; s2, the manufacturing agent determines development requirements of the tool function according to the task information, and the development requirements at least comprise function requirements of the tool function; and S3, the manufacturing agent automatically generates a code of the tool function of the target agent according to the development requirement of the tool function. In the invention, through the manufacturing agent running in the intelligent computing center, the process of communicating with the user, confirming the development demand, automatically completing the development of the tool function of the target agent and replacing the manual development of the tool function code can be realized, so that the development cost is effectively saved, the intelligent computing center can provide sufficient computing power resources, and the development efficiency is improved. And the development efficiency is greatly improved.

A ship pipe fitting recognition system based on multi-source data enhancement and intelligent recommendation comprises a multi-source data enhancement module, a model training module, a recommendation decision module, a federated learning platform and a block chain evidence storage module, the system is of a'cloud + side 'double-layer architecture, the cloud is used for intelligent evolution, distributed knowledge is integrated through federated learning, and the block chain evidence storage module is used for storing the distributed knowledge. The global model is continuously updated and optimized, the edge end is used for edge real-time response, and efficient pipe fitting feature detection and pipe fitting number recommendation are carried out at the equipment end. According to the method, the detection precision and the non-standard pipe fitting recognition capability in complex illumination and shielding scenes can be remarkably improved, and the misjudgment rate is reduced; the decision-making problem of similar part hybrid scenes is solved, and the assembly efficiency and accuracy are improved; meanwhile, the data privacy security is ensured; the technical blank in the aspects of data diversity, algorithm robustness and industrial adaptability in the field of ship pipe fitting recognition is filled, the efficient requirement of a ship assembly scene is met, and technical support is provided for ship manufacturing intelligence.

The invention provides a discrete manufacturing intelligent scheduling method based on a graph theory. The discrete manufacturing intelligent scheduling method comprises the steps of 1, constructing a heterogeneous graph model of scheduling elements; step 2, static scheduling optimization based on a critical path method; step 3, resource allocation optimization based on a multi-resource bipartite graph matching method; and 4, dynamic response and rescheduling are carried out. Based on a graph theory method, a complex'process-resource-constraint 'relationship is converted into a visual heterogeneous graph model, and a systematic scheduling solution based on the graph theory is constructed, so that the scheduling solution is suitable for a discrete manufacturing scene with multi-process, multi-equipment, multi-constraint and dynamic disturbance characteristics; the method is used for realizing static planning of production plan scheduling, resource optimization distribution and dynamic adjustment full-process optimization.

The invention relates to the technical field of intelligent manufacturing of elevators, and particularly discloses an intelligent scheduling and collaborative operation platform for intelligent manufacturing of elevators. A structured event acquisition module overcomes the problems of data acquisition and transmission delay and information isolated island by receiving monitoring data streams in real time and performing anomaly detection and structured packaging; and a dispatching center can master accurate event details and influence ranges in real time. And the report generation module processes structured event information and real-time production data by utilizing an intelligent analysis engine, so that the problem of low efficiency of complex event chain reaction assessment is solved. The scheme generation module generates an alternative rescheduling scheme in combination with an event influence analysis report and a production global snapshot, and after the scheme approval module checks, the execution instruction pushing module decomposes a confirmation scheme and directionally pushes the confirmation scheme to a related execution level and a collaborative party, so that the problem of scheduling plan transmission and execution deviation is avoided, and the scheduling efficiency is improved. The real-time performance and the cooperation efficiency of production scheduling are improved, and elevator manufacturing enterprises can better adapt to market requirements.

The invention provides an intelligent detection method and system for battery manufacturing and a medium, and belongs to the technical field of artificial intelligence and big data. The method comprises the following steps: acquiring battery raw material attribute information and manufacturing equipment basic information, constructing a battery manufacturing digital twin body, carrying out simulation manufacturing to obtain battery manufacturing tracking information, extracting positive and negative pole piece proportioning pulping information, coating piece making information and winding lamination information, the method comprises the following steps: respectively processing raw material quality data, coating effect evaluation data and preparation forming quality data to obtain raw material quality data, coating effect evaluation data and preparation forming quality data, carrying out evaluation processing to obtain a battery manufacturing reliability index, and correcting according to inter-batch manufacturing information and intra-batch manufacturing information to obtain a battery manufacturing reliability correction index. By constructing the battery manufacturing digital twinborn body, the manufacturing process can be predicted and optimized, battery raw materials and the manufacturing process are monitored and analyzed item by item, and all-around intelligent evaluation and visual representation of the whole battery manufacturing process are achieved.

The invention discloses a wine cabinet and an automatic wine mixing method thereof. The automatic wine mixing method comprises the following steps: acquiring a wine mixing instruction, extracting a stock solution proportion of a corresponding proportion according to a wine mixing scheme in the wine mixing instruction, adding ice blocks into a container through an ice maker, controlling the container to carry out wine mixing and filtering operations, carrying out self-cleaning after wine mixing is finished, and carrying out automatic wine mixing through an image recognition algorithm. Whether the user is adult or not is verified before the drink mixing function is started, the situation that children touch juveniles by mistake for drinking is avoided, drink mixing convenience is improved, and product intelligence and user experience are improved.

The utility model provides a control cabinet of a platform household elevator. The control cabinet comprises a main control cabinet and a battery box, the main control cabinet is detachably assembled with the battery box through a connecting assembly; the main control cabinet and the battery box are mounted on a shaft or a wall surface of an elevator hall; the main control cabinet comprises a cabinet door and a cabinet body; the cabinet door and the cabinet body are integrally formed; a first buckle is arranged on the cabinet door; a first clamping groove is formed in the cabinet body; the first buckle is clamped into the first clamping groove; the battery box comprises a cover plate and a box body; a second buckle is arranged on the cover plate; a second clamping groove is formed in the box body; the second buckle is clamped into the second clamping groove; according to the utility model, the number of parts is small, the product cost is reduced, the product cost performance and the market competitiveness are improved, the structure is firm, the installation is flexible, the integration degree is high, the compatibility is good, the product intelligence degree is improved, and the user experience is improved.

The present invention discloses a large-size intelligent touch device, comprising a host control module (1) and a device body (2) connected to each other, wherein the device body (2) is an interactive electronic whiteboard, a projection television or an LCD all-in-one machine, and the host control module (1) comprises a charger power supply or a PC adapter (11) and a PC mainboard (13), wherein the output end of the PC mainboard (13) is connected to an infrared touch module (3), and the charger power supply or the PC adapter (11) is connected to the input end of the PC mainboard (13) via a rechargeable battery (12). The device can improve the intelligence of products and the flexibility of matching, avoid product system damage and file loss due to sudden power failure of products, reduce maintenance costs and transformation costs, and benefit more people.

The present disclosure provides a method for predicting the trend of black industry attacks, which can be applied to the field of information security technology. The method includes obtaining information published in at least one black industry trading platform to obtain M original black industry intelligence; processing the original black industry intelligence into structured black industry intelligence to be analyzed, wherein the M original black industry intelligence corresponds to the M black industry intelligence to be analyzed; classifying the M black industry intelligence to be analyzed based on predetermined rules to obtain at least one black industry intelligence category; sorting the at least one black industry intelligence category according to the number of black industry intelligence to be analyzed contained in each black industry intelligence category, so as to predict the attack trend of the black industry according to the sorting result. The present disclosure also provides a device, equipment, storage medium and program product for predicting the trend of black industry attacks.

The application relates to the field of spring manufacturing intelligent control, and discloses a spring horizontal processing and single heat treatment coordinated intelligent regulation and control system, which comprises the following steps: a disturbance characteristic online coding module, which is used for online acquisition and coding of physical disturbance generated by each spring in horizontal processing procedures such as coiling and welding, and generates a unique disturbance characteristic spectrum; an online control law dynamic calibration module, which receives the disturbance characteristic spectrum and inversely solves a compensatory individualized heat treatment instruction sequence for the spring; an individualized heat treatment execution module, which executes accurate single heat treatment on a single spring according to the instruction sequence; and a quality feedback and model self-optimization module, which optimizes a control model in a long period according to the final measured performance of the spring. Through construction of a direct mapping and feedback optimization closed loop from horizontal processing disturbance to single heat treatment control, the application realizes deep coordination between the two, effectively compensates for process fluctuation, and significantly improves the consistency of spring product quality.

The utility model relates to the technical field of data line production, in particular to full-automatic wire soldering production equipment. Comprising a machine table, a wire feeding device arranged on the machine table, an outer layer peeling device used for peeling the outer layer of a wire, a core wire peeling device used for peeling the core wire of the wire, and a tin soldering device used for welding the wire into a finished product. The detection device is used for detecting the finished products; and the feeding manipulator is used for transferring the finished products. According to the utility model, automatic production and manufacturing of data lines are realized, the intelligent degree is high, the working efficiency and the working quality are improved, and the rapid production requirements of modern data lines are met.

The application belongs to the field of precise manufacturing detection and industrial automation positioning technology in the new generation of information technology, and particularly relates to a three-degree-of-freedom optical measurement system and a use method thereof. In view of the technical problems of low integration and insufficient synchronous measurement accuracy in the three-degree-of-freedom measurement of objects in the existing precise manufacturing scene, the system comprises a point light source, a light splitting prism, a mirror with an included angle, an imaging optical system, a photoelectric detector and a data processing system, and through coupling calculation of the change of the reflected image information and the mirror included angle, integrated high-precision measurement of three-degree-of-freedom parameters is realized. The application relies on the fusion of optical imaging and data algorithm, breaks through the traditional measurement bottleneck, is suitable for high-precision positioning scenes such as semiconductor packaging detection, aerospace component assembly, industrial robot posture calibration and the like, and provides key technical support for the intelligent upgrading of the new generation of information technology supporting precise manufacturing.

The present invention discloses a controller and a control method for industrial embodied intelligent manufacturing, including: a sensing module for acquiring multi-modal sensing data during the execution of an industrial production task; a computing module for inferring the current attribute data of at least one target object in the industrial production task according to the multi-modal sensing data, and generating a corresponding control decision according to the current attribute data of each target object and the preset target attribute data corresponding to each target object at present; a control module for converting the control decision into a control signal for functionally controlling intelligent machine equipment; and a driving module for driving the intelligent machine equipment to perform corresponding operations in the industrial production task according to the control signal. The technical solution in the embodiment of the present invention realizes intelligent and efficient production in industrial manufacturing.

The invention discloses a working data acquisition and processing platform for numerical control equipment. The platform is composed of a data acquisition module, a data storage module, a data calling module, an equipment modeling module and a data visualization module. The platform realizes efficient and credible acquisition of multi-source heterogeneous data through a multi-protocol plug-in, edge computing and an event-driven mechanism; data association, anomaly recognition and real-time early warning are completed based on semantic modeling and a graph neural network; ledger management, alarm linkage and a unified data service interface are integrated, and multi-system butt joint and business expansion are supported; and the visualization module supports dynamic display of the equipment state, the processing process and the early warning information. According to the method, the problems of limited data acquisition dimension, weak intelligent analysis capability, poor system expansibility and the like of an existing acquisition platform are solved, the method is suitable for complex state monitoring and predictive maintenance of production equipment in industrial scenes of high-end equipment manufacturing, intelligent workshop management and the like, and the method has good universality and popularization value.

1. Name of the product of this design: Graphical user interface of intelligent torque assembly system for transformer assembly manufacturing of electronic equipment. 2. Purpose of this design product: for electronic equipment. 3. The key design point of this design product lies in the content displayed in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5.Omit other views. 6.Purpose of Graphical User Interface: Used for intelligent torque assembly interaction and control in transformer assembly and manufacturing process. 7. Description of the changing states of the graphical user interface: The main view is the interface after logging into the software. Click the "Torque System" button on the left side of the main view, and the interface will jump to the interface shown in Figure 1 of the interface changing state; click the "MES Order" button, and the interface will jump to the interface shown in Figure 2 of the interface changing state; click the "Process Task" button, and the interface will jump to the interface shown in Figure 3 of the interface changing state; click the "Completion Report" button, and the interface will jump to the interface shown in Figure 4 of the interface changing state; click the "Task Check and Report" button, and the interface will jump to the interface shown in Figure 5 of the interface changing state.

The invention discloses an intelligent wall and ground leveling electronic ruler which comprises a ruler body, a photoelectric sensor, a setting function key, a processor, an error data display screen, an error count-off loudspeaker, an electricity storage device and a switch. The bottom surface of the ruler body is a plane, the bottom surface of the ruler body is provided with a plurality of light sensing perforations which are distributed at intervals, and the positions of the photoelectric sensors are in one-to-one correspondence with the positions of the light sensing perforations; the processor is used for receiving the signal of the photoelectric sensor, determining the position and the size of the measured object, and comparing the position and the size with an internally set standard value to obtain an error index. The error data display screen is used for displaying error indexes, and the error count-off loudspeaker informs workers of the error indexes of measurement results through sounds. The photoelectric sensor is used for detecting the flatness and perpendicularity of an object, the measured error index is informed to a worker in real time in a display and sound mode, the worker can conduct correction treatment in time, meanwhile, the detection result accuracy is high, the product intelligence degree is high, and the building or construction quality is effectively guaranteed.

The invention relates to the technical field of industrial production management, and discloses an industrial manufacturing operation management method based on hybrid enhanced intelligence, and the method comprises the following steps: S1, constructing a multi-source knowledge base, and building a task matching initial model based on multiple dimensions; s2, performing autonomous task planning, task decomposition, task allocation and task release based on the task matching initial model, and updating a work allocation method knowledge base according to a real-time task execution condition; and S3, according to the updated work distribution method knowledge base and real-time feedback, cooperatively adjusting a management strategy so as to ensure that the knowledge base is synchronously updated with an actual demand, and optimizing a task distribution strategy. By constructing a knowledge-driven intelligent decision closed loop, efficient and collaborative operation, dynamic resource optimization, management cost reduction and continuous self-adaption of the system are realized, and the overall manufacturing intelligence level is remarkably improved.

The invention provides an intelligent scheduling method and device for product manufacturing, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: obtaining an original workpiece set and a new arrival workpiece set, enabling the original workpiece set to comprise original workpieces, enabling the new arrival workpiece set to comprise new arrival workpieces, and enabling the new arrival workpiece set to comprise new arrival workpieces; an initial optimal scheduling scheme is correspondingly provided; setting a selectable processing strategy for each newly arrived workpiece; the absolute value of the difference between the completion time of the original workpiece in the new scheduling scheme and the completion time of the original workpiece in the initial optimal scheduling scheme is limited not to exceed a preset threshold value, and the maximum completion time deviation constraint is obtained; constructing an objective function according to the weighted total completion time, the maximum completion time deviation cost, the compression cost and the rejection cost; and establishing a mixed integer programming model based on the target function and the maximum completion time deviation constraint, and realizing global optimization or approximate optimization of the total cost on the premise of guaranteeing the stability of the original plan while accepting a new order.

The intelligent sensor self-diagnosis optimization system comprises a laser interference unit and a temperature detection unit which are integrated in the sensor, the displacement phase difference of the sensor is obtained through laser interference measurement, and internal temperature data are combined to obtain the self-diagnosis optimization of the intelligent sensor. And the physical displacement is calculated in real time by a built-in artificial intelligence processor of the edge calculation unit. And the dynamic reference calibration unit is used for identifying reference workpiece characteristics in the production line based on the target detection neural network and generating a space error compensation matrix in combination with the physical displacement. And a compensation result is dynamically loaded by an FPGA register in the sensor compensation circuit unit, so that fine compensation of output signals of the sensor is realized. The method has high-precision dynamic error compensation, autonomous diagnosis optimization capability and good system integration, and is suitable for sensor adaptive control in scenes of high-precision manufacturing, intelligent factories and the like.

The present application relates to the technical field of intelligent management of ship manufacturing, and particularly relates to a method and system for ship pipeline design drawing stage management, which acquires and structurally processes production schedule and process specification data, constructs a standardized input set, uses a multi-objective optimization engine to resolve conflicts, optimize progress and cost, and generates a preliminary pipeline scheme in combination with a four-dimensional model, semantic verification and dynamic scheduling, and outputs construction drawings and animations after three-dimensional simulation verification, collects feedback in real time during construction, triggers secondary scheduling and optimization, realizes continuous iteration and accurate execution of design, and through intelligent decision-making of the multi-objective optimization engine, the design drawing efficiency can be improved by more than 40%, the design error rate is reduced by 90%, and the rework in the later stage is greatly reduced.

1. Name of the product of this design: Graphical user interface of torque workstation module of intelligent torque assembly system for transformer assembly manufacturing of electronic equipment. 2. Purpose of this design product: for electronic equipment. 3. The key design point of this design product lies in the content displayed in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5.Omit other views. 6.Purpose of the graphical user interface: This design interface is a computer software interface used for interaction and control of the torque workstation module during the transformer assembly and manufacturing process. 7. Description of the changing states of the graphical user interface: The main view is the interface after logging into the software. Click the "Process Task" button, and the interface will jump to the interface shown in Figure 1 of the interface changing state; click the "Add" button, and the interface will jump to the interface shown in Figure 2 of the interface changing state; click the "Select Task List" button, and the interface will jump to the interface shown in Figure 3 of the interface changing state.

The present invention discloses a dynamic real-time rendering method for a large assembly scene based on three-dimensional Gaussian splashing. By combining multiple sensors, a three-dimensional Gaussian splashing model for real-time rendering of dynamic scenes is constructed. The method can render any viewing angle of the assembly scene. The three-dimensional Gaussian splashing model includes sensor data alignment, initialization of the three-dimensional Gaussian splashing model, prediction and update of the three-dimensional Gaussian splashing model. In combination with the three-dimensional Gaussian splashing model, a scene space point alignment and predictor are designed to solve the problems of multi-sensor data information redundancy and dynamic real-time rendering difficulties. This method improves the safety and reliability of assembly, can timely discover and handle problems in the assembly process, and helps to promote the rapid and high-quality development of industrial intelligent manufacturing, thereby promoting the transformation of industrial manufacturing intelligence.

The invention discloses a modular plug-in connection structure and method for a transformer winding lead and a sleeve, and relates to the technical field of power transformer manufacturing. Comprising a plug module, a socket module and a winding lead, and the plug module is fixedly connected to the tail end of the winding lead; the plug module comprises a plug base and a male conductive contact arranged on the plug base, and the socket module comprises a socket base and a female conductive contact arranged on the socket base; a first guide part and a first locking part are arranged on the plug base; the socket base is provided with a second guide part matched with the first guide part and a second locking part matched with the first locking part; an inner cavity of the female conductive contact is internally provided with an elastic contact member which is in crimping cooperation with the male conductive contact. According to the invention, the assembly and maintenance time is greatly shortened, the connection consistency and safety are improved, and the manufacturing intelligence and operation and maintenance efficiency of the transformer are supported.

1. Name of the product of this design: Graphical user interface of process manufacturing model of intelligent torque assembly system for transformer assembly manufacturing of electronic equipment. 2. Purpose of this design product: for electronic equipment. 3. The key design point of this design product lies in the content displayed in the graphical user interface. 4. The picture or photo that best illustrates the key points of the design: main view. 5.Omit other views. 6. Purpose of the graphical user interface: This design interface is a computer software interface used for three-dimensional visualization of the product during the transformer assembly and manufacturing process. 7. Other situations that need explanation are explained in the reference figures: The main view is the interface after software login. Click any one of the buttons "Stacking Boards", "Plug-in Boards", "Leads" and "Device Body" on the left side of the main view, and the interface will jump to the interface shown in Figure 1 of the interface change state; click the "Rear View" button at the top, and the interface will jump to the interface shown in Figure 2 of the interface change state; click the "Up View" button at the top, and the interface will jump to the interface shown in Figure 3 of the interface change state; click the "Left View" button at the top, and the interface will jump to the interface shown in Figure 4 of the interface change state; click the "Right View" button at the top, and the interface will jump to the interface shown in Figure 5 of the interface change state.

The application provides a product manufacturing intelligent scheduling method and device, and relates to the technical field of intelligent manufacturing. The method comprises the following steps: acquiring an original workpiece set and a newly-arrived workpiece set, wherein the original workpiece set comprises original workpieces, the newly-arrived workpiece set comprises newly-arrived workpieces, and there is an initial optimal scheduling scheme corresponding to the original workpiece set; setting an optional processing strategy for each newly-arrived workpiece; limiting the absolute value of the difference between the completion time of the original workpiece in a new scheduling scheme and the completion time of the original workpiece in the initial optimal scheduling scheme to be not more than a preset threshold value, and obtaining a maximum completion time deviation constraint; constructing a target function according to a weighted total completion time, a maximum completion time deviation cost, a compression cost and a rejection cost; and based on the target function and the maximum completion time deviation constraint, a mixed integer programming model is established, so that the global optimal or approximate optimal total cost is realized while the new order is accepted and the stability of the original plan is ensured.

The invention discloses a controller and a control method for intelligent manufacturing of an industrial tool, and the controller comprises a sensing module which is used for obtaining multi-modal sensing data in the execution process of an industrial production task; the calculation module is used for reasoning current attribute data of at least one target object in the industrial production task according to the multi-modal sensing data, and generating a corresponding control decision according to the current attribute data of each target object and preset target attribute data corresponding to each target object at present; the control module is used for converting the control decision into a control signal for performing function control on the intelligent machine equipment; and the driving module is used for driving the intelligent machine equipment to execute corresponding operation in the industrial production task according to the control signal. According to the technical scheme in the embodiment of the invention, intelligent and efficient production of industrial manufacturing is realized.