Intelligent equipment customization and production delivery method based on free module combination

Abstract

The invention discloses an intelligent equipment customization and production delivery method based on free module combination, and relates to the technical field of smart home, and the method comprises the steps: modular design: obtaining an intelligent equipment list and corresponding structure and function data; carrying out functional splitting on the intelligent equipment, determining a personalized composition and a fixed composition, and obtaining equipment modular data; production and intelligent analysis: acquiring room type data of a customer, and processing according to a preset point distribution recommendation process to generate point distribution data; sending the stationing data to the client, receiving modular design demand data and requests of the client, updating the stationing data, and forming order information; obtaining production data and inventory data of a factory; based on a preset production task, generating logic analysis order information, production data and inventory data, and completing task allocation; and acquiring execution process data after task allocation, tracking and performing dynamic adjustment when the task is abnormal. The method has the effect of reducing the stock pressure in production.

Description

Technical Field

[0001] The present application relates to the field of smart home technology, and in particular to a method for customizing and producing smart devices based on free combination of modules. Background Art

[0002] Existing smart device production and delivery methods generally adopt standardized and mass production.

[0003] Taking smart switches, lamps (such as downlights, ceiling lamps, etc.), sensors, sockets and other equipment as examples, the traditional production model is difficult to cope with the personalized customization needs of smart homes for different house types and buildings. The fixed production method leads to increased inventory pressure of equipment in supply chain management, and the delivery cycle is long. In recent years, many whole-house smart companies have gone from success to failure, mostly due to cash flow problems, with inventory control being the main reason. Therefore, this application proposes a new technical solution. Summary of the invention

[0004] In order to reduce inventory pressure in production, improve the fluency and efficiency of smart device customization, production and delivery, and meet the personalized needs of customers, this application provides a smart device customization and production delivery method based on free combination of modules.

[0005] This application provides a method for customization and production delivery of intelligent devices based on free combination of modules, which adopts the following technical solutions: A method for customizing and producing intelligent devices based on free combination of modules, comprising: Step 1: Modular design, which includes: Obtain a list of smart devices and their corresponding structure and function data; smart devices include switches, lamps, sensors, and sockets; Functionally split smart devices, determine individual components and fixed components, and obtain device modular data; Step 2: Production and intelligent analysis, which includes: Obtain the customer's room type data, and process it according to the preset recommended layout process to generate layout data; Send the layout data to the customer, receive the customer's modular design demand data and requests, update the layout data, and form order information; Obtain the factory's production and inventory data; Generate logic based on preset production tasks to analyze order information, production data and inventory data and complete task allocation; Obtain the execution process data after task assignment, track it and make dynamic adjustments when anomalies occur; Step 3: Packaging and installation deployment, which includes: Bind the output products and corresponding room type data one by one, and generate classification and packaging tasks; Send the layout data to the on-site installers.

[0006] Optionally, the site recommendation process includes: If the room type data includes drawing data, image recognition is performed to obtain the boundaries, dimensions and functional areas of each room in the drawing to form room layout data; According to the room layout data and the pre-stored functional data of the smart devices, the device type, quantity and installation location are allocated, and the room type and customer information are bound to generate a layout list as the layout data.

[0007] Optionally, the receiving of modular design requirement data and request from the customer and updating of the point distribution data includes: When generating a layout list, a layout diagram is generated based on the room type drawing, and the model icon of the corresponding smart device is called from the preset database to mark it in the layout diagram; If the customer's feedback data includes personalized demand data, the corresponding icon in the layout diagram will be adjusted according to the personalized demand data.

[0008] Optionally, the production task generation logic includes: Identify the location list in the location data and determine the equipment type; Decompose into several small order tasks according to the equipment type; Obtain order delivery time, factory production data and inventory data, and process them using task optimization rules to determine the optimal task allocation plan; Small order tasks are assigned to matching factories and production lines according to the optimal task allocation plan.

[0009] Optionally, the tracking and dynamic adjustment in case of anomalies may include: Monitor the progress of each task; If the production dynamic information of a task meets the preset abnormal conditions, an alarm message is output; wherein the abnormal conditions include equipment failure and / or material shortage; Obtain the time consumed to eliminate the exception, and recalculate the task completion time based on the time consumed to eliminate the exception; If the production line or factory output is composed of equipment with production abnormalities, the associated task completion time will be corrected according to the new task completion time, and the task optimization rule processing results will be updated to generate a new optimal task allocation plan.

[0010] Optionally, the task optimization rules include: one or more of order urgency priority, high delivery efficiency priority, and parallel task optimization algorithm, and order urgency priority has a higher priority.

[0011] Optionally, also include: When the task is completed, the production cycle of the corresponding factory and production line is counted and the production efficiency is calculated; Determine whether there is overload and quality problems based on the actual load of the factory and production line during task execution; Optimize task generation and allocation based on production efficiency, whether there is overload, and whether there are quality problems.

[0012] Optionally, the production and intelligent analysis further includes: Get real-time production efficiency based on the execution process data analysis after task allocation; Estimate task completion time based on assigned tasks, current task progress and real-time production efficiency, and output; If the task completion time exceeds the planned time when the task was assigned, and the difference exceeds the preset warning threshold, a task overdue warning is output.

[0013] Optionally, the production and intelligent analysis further includes: The raw material input-output ratio is obtained based on the execution process data analysis after task allocation; Estimate the parameters of materials to be consumed based on the assigned tasks, current task progress and raw material input-output ratio; Compare the parameters of the materials to be consumed with the inventory data, and when the inventory data is insufficient, output procurement warning information; wherein the procurement warning information includes prompt information and material shortage parameters.

[0014] Optionally, a data analysis and processing center for the system / platform is established through distributed computing technology.

[0015] In summary, this application includes the following beneficial technical effects: 1) When designing the whole-house smart scene, this method can automatically generate the equipment distribution data, and apply modular design ideas to allow customers to flexibly adjust the equipment, which also reduces the problem of excessive inventory pressure of equipment in the supply chain caused by fixed production methods; 2) Orders are sent to the factory for modular production, during which the production process is dynamically optimized according to the actual production situation, thereby effectively improving production efficiency; 3) After the equipment is produced, it is matched one by one with the house type, and packaged in categories to ensure that the equipment corresponds to the house type; when installing the equipment, the layout data can be consulted to guide the on-site installation, thereby effectively improving the efficiency of equipment delivery and installation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the main process of this method. DETAILED DESCRIPTION

[0017] The following is combined with Figure 1This application is described in further detail.

[0018] The embodiment of the present application discloses a method for customizing and producing and delivering smart devices based on free combination of modules.

[0019] Reference Figure 1 , the intelligent equipment customization and production delivery methods based on free combination of modules include: Step 1: Modular design, which includes: S11, obtaining a list of smart devices and corresponding structure and function data; S12. Functionally split the smart device, determine the individual components and fixed components, and obtain device modular data.

[0020] This application is mainly aimed at smart homes, so the above-mentioned smart devices include switches, lamps, sensors and sockets; examples: 1) Disassemble the switch into modules such as relay box, PCBA board, front box, cover plate, etc.; the fixed component is the PCBA board, and the others are individual components; 2) Downlights, ceiling lights and other lamps are composed of intelligent drive modules and lamp bodies; the fixed component is the intelligent drive module, and the personalized component is the lamp body; 3) Temperature and humidity sensors, human body sensors, etc., are modularly designed through main control + transparent PCBA, shell, etc., and the shell is used as a personality component; 4) The socket has intelligent power control function, including PCBA and shell, and the shell is a personality component; The above examples have modular designs such as shell style and color to meet the needs of different room types.

[0021] Step 2: Production and intelligent analysis, which includes: S21. Acquire the customer's room type data, and process it according to the preset distribution recommendation process to generate distribution data; Send the layout data to the customer, receive the customer's modular design demand data and requests, update the layout data, and form order information; S22. Obtain the factory's production data and inventory data (through, for example, docking with the factory's ERP system); the production data includes production line load, available resources for the production line, and real-time productivity; the inventory data includes the quantity and status of components such as lamp driver modules.

[0022] Generate logic based on preset production tasks to analyze order information, production data and inventory data and complete task allocation; Obtain the execution process data after task assignment, track it, and make dynamic adjustments when exceptions occur.

[0023] Step 3: Packaging and installation deployment, which includes: S31, binding the output products and corresponding room type data one by one, and generating classification and packaging tasks; S32. Sending the point distribution data to the on-site installation personnel.

[0024] Based on the above settings: 1) When designing the whole-house smart scene, this method can automatically generate the equipment distribution data, and apply modular design ideas to allow customers to flexibly adjust the equipment, which also reduces the problem of excessive inventory pressure of equipment in the supply chain caused by fixed production methods; 2) Orders are sent to the factory for modular production, during which the production process is dynamically optimized according to the actual production situation, thereby effectively improving production efficiency; 3) After the equipment is produced, it is matched one by one with the house type, and packaged in categories to ensure that the equipment corresponds to the house type; when installing the equipment, the layout data can be consulted to guide the on-site installation, thereby effectively improving the efficiency of equipment delivery and installation.

[0025] In one embodiment of the method, the site recommendation process includes: If the room type data includes drawing data, image recognition is performed to obtain the boundaries, dimensions and functional areas of each room in the drawing to form room layout data; According to the room layout data and the pre-stored functional data of the smart devices, the device type, quantity and installation location are allocated, and the room type and customer information are bound to generate a layout list as the layout data.

[0026] It is understandable that the functional data of each smart device can determine its applicable scenarios and scope. For example: lamp A is the main lamp in the living room, lamp B is a small lamp and the guided layout interval is 30cm. If a room has a living room and a rectangle with a length and width of 800*600c, then one lamp A is allocated, 26 lamps B are allocated for the length, and 20 lamps C are allocated for the width.

[0027] Regarding the above-mentioned receiving of customer's modular design demand data and requests, updating the layout data, which also includes: When generating a layout list, a layout map is generated based on the room drawing, and the model icons of the corresponding smart devices are called from the preset database to mark them in the layout map. The layout map serves as the composition of the layout data; that is, the equipment layout is visualized, and the color and style of the equipment are marked in the layout map, so that customers can intuitively determine the layout effect.

[0028] If the customer's feedback data includes personalized demand data (i.e., modular design change requirements), the corresponding icons in the layout diagram will be adjusted according to the personalized demand data; for example: if the customer requests to change the color of switch A to gray, all switches A in the layout diagram will be adjusted to gray.

[0029] According to the above settings, this method can enable customers to relatively intuitively understand the equipment layout effect.

[0030] In an embodiment of the present application, the above production task generation logic includes: Identify the layout list in the layout data and determine the equipment type; Decompose according to the equipment type to form several small order tasks; Example: Switches and lamps form small orders respectively, because different factories and production lines can complete different tasks, and after decomposition and distribution to different factories and production lines, multiple tasks can be carried out in parallel, greatly shortening the task delivery time.

[0031] Obtain the delivery time of the order (required by customers, designers, and construction parties), the production data and inventory data of the factory, and process them according to the task optimization rules to determine the optimal task allocation plan; Allocate small order tasks to the matching factories and production lines according to the optimal task allocation plan.

[0032] According to the above settings, this method can generate optimal production tasks according to different equipment types and quantities, combined with the inventory status of the factory.

[0033] In this embodiment, the task optimization rules include: order urgency priority, high delivery efficiency priority, and the order urgency priority level is higher; At this time, processing according to the task optimization rules means: If the order urgencies are the same, then according to the first-come-first-served method, determine the delivery time of each production line according to the production line load, real-time production capacity in the production data and the corresponding small order tasks, and select the one with the shortest delivery time.

[0034] In another embodiment of the present application, the above step 2, tracking in production and intelligent analysis and making dynamic adjustments when there are abnormalities, includes: Monitor the progress of each task (through the factory's ERP / MES system); If the production dynamic information of a certain task meets the preset abnormal conditions, output an alarm message (to the order placer, project management party); Among them, the abnormal conditions include equipment failure and / or material shortage; Obtain the time-consuming for troubleshooting (actively uploaded by the factory staff), and recalculate the task completion time according to the time-consuming for troubleshooting; If the production line or factory with production abnormalities produces equipment components (for example: the drive module of a lamp), then correct the completion time of the associated task (such as: the task of manufacturing a lamp) according to the new task completion time, and update the task optimization rule processing result to generate a new optimal task allocation plan.

[0035] According to the above settings, this method can promptly notify relevant staff when a task is abnormal, and provide a reference for task adjustment to ensure that the equipment production task can be completed in the best way.

[0036] In another embodiment of the present application, the task optimization rule also includes: a parallel task optimization algorithm, specifically: maximizing the number of parallel processing tasks by the delivery time of different factories and reducing the waiting time.

[0037] In another embodiment of the present application, the method further comprises: When the task is completed, the production cycle of the corresponding factory and production line is counted and the production efficiency is calculated; Determine whether there is overload and quality problems based on the actual load of the factory and production line during task execution; Optimize task generation and allocation based on production efficiency, overload, and quality issues. Example: Determine the assigned tasks based on the number of quality issues that occur in the tasks. The fewer the issues, the fewer tasks are assigned or other factories and production lines are given priority. Update the production line load corresponding to the factory and production line based on the overload situation. The higher the production efficiency, the more tasks are assigned.

[0038] In another embodiment of the method, the above step 2, production and intelligent analysis, further comprises: Get real-time production efficiency (e.g. average daily output) based on the execution process data analysis after task allocation; Estimate the task completion time based on the assigned tasks, current task progress and real-time production efficiency, and output it; Example: Calculate the remaining task amount based on the task amount and current task progress, calculate the estimated time based on the remaining task amount and production efficiency, and calculate the estimated time based on the current time and the estimated time to get the estimated task completion time; If the task completion time exceeds the planned time when the task was assigned, and the difference exceeds the preset warning threshold (for example: 2 days), a task overdue warning will be output (to the factory management).

[0039] According to the above content, this method can also monitor the task execution process, analyze and predict the task completion time, and issue early warnings in case of long overdue periods, so that factory managers can adjust the production process in time to avoid losses caused by the subsequent tasks being reallocated.

[0040] Furthermore, the above production and intelligent analysis also includes: The raw material input-output ratio is obtained based on the execution process data analysis after task allocation; Estimate the parameters of materials to be consumed based on the assigned tasks, current task progress and raw material input-output ratio; Compare the parameters of the materials to be consumed with the inventory data, and output procurement warning information when the inventory data is insufficient.

[0041] According to the above settings, this method can analyze whether the inventory materials are sufficient in combination with the actual production situation, rather than just analyzing the inventory based on the fixed parameters set in the past. Because different production environments, scenarios, etc. will lead to different material loss rates, the analysis of this method is more accurate, and it can give relevant staff procurement reminders in advance to prevent production delays due to insufficient raw materials. The above-mentioned procurement warning information includes prompt information and material shortage parameters. The prompt information is such as: "Insufficient inventory", and the material shortage parameters are such as: "XX material is out of stock, and the estimated shortage is XXX". In another embodiment of the present application, the method establishes a data analysis and processing center for the system / platform through distributed computing technology.

[0042] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for customization and production delivery of intelligent devices based on free combination of modules, characterized in that: include: Step 1: Modular design, which includes: Obtain a list of smart devices and their corresponding structure and function data; smart devices include switches, lamps, sensors, and sockets; Functionally split smart devices, determine individual components and fixed components, and obtain device modular data; Step 2: Production and intelligent analysis, which includes: Obtain the customer's room type data, and process it according to the preset recommended layout process to generate layout data; Send the layout data to the customer, receive the customer's modular design demand data and requests, update the layout data, and form order information; Obtain the factory's production and inventory data; Generate logic based on preset production tasks to analyze order information, production data and inventory data and complete task allocation; Obtain the execution process data after task assignment, track it and make dynamic adjustments when anomalies occur; Step 3: Packaging and installation deployment, which includes: Bind the output products and corresponding room type data one by one, and generate classification and packaging tasks; Send the layout data to the on-site installers.

2. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 1 is characterized in that: The site recommendation process includes: If the room type data includes drawing data, image recognition is performed to obtain the boundaries, dimensions and functional areas of each room in the drawing to form room layout data; According to the room layout data and the pre-stored functional data of the smart devices, the device type, quantity and installation location are allocated, and the room type and customer information are bound to generate a layout list as the layout data.

3. The method for customizing and producing intelligent devices based on free combination of modules according to claim 2 is characterized in that: The receiving of modular design requirement data and request from the customer and updating of the point distribution data includes: When generating a layout list, a layout diagram is generated based on the room type drawing, and the model icon of the corresponding smart device is called from the preset database to mark it in the layout diagram; If the customer's feedback data includes personalized demand data, the corresponding icon in the layout diagram will be adjusted according to the personalized demand data.

4. The method for customizing and producing intelligent devices based on free combination of modules according to claim 2, characterized in that: The production task generation logic includes: Identify the location list in the location data and determine the equipment type; Decompose into several small order tasks according to the equipment type; Obtain order delivery time, factory production data and inventory data, and process them using task optimization rules to determine the optimal task allocation plan; Small order tasks are assigned to matching factories and production lines according to the optimal task allocation plan.

5. The method for customizing and producing intelligent devices based on free combination of modules according to claim 1, characterized in that: The tracking and dynamic adjustment in case of abnormality include: Monitor the progress of each task; If the production dynamic information of a task meets the preset abnormal conditions, an alarm message is output; wherein the abnormal conditions include equipment failure and / or material shortage; Obtain the time consumed to eliminate the exception, and recalculate the task completion time based on the time consumed to eliminate the exception; If the production line or factory output is composed of equipment with production abnormalities, the associated task completion time will be corrected according to the new task completion time, and the task optimization rule processing results will be updated to generate a new optimal task allocation plan.

6. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 5 is characterized in that: The task optimization rules include: one or more of order urgency priority, high delivery efficiency priority, and parallel task optimization algorithm, and the order urgency priority level is higher.

7. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 5, characterized in that: Also includes: When the task is completed, the production cycle of the corresponding factory and production line is counted and the production efficiency is calculated; Determine whether there is overload and quality problems based on the actual load of the factory and production line during task execution; Optimize task generation and allocation based on production efficiency, whether there is overload, and whether there are quality problems.

8. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 5, characterized in that: The production and intelligent analysis also includes: Get real-time production efficiency based on the execution process data analysis after task allocation; Estimate task completion time based on assigned tasks, current task progress and real-time production efficiency, and output; If the task completion time exceeds the planned time when the task was assigned, and the difference exceeds the preset warning threshold, a task overdue warning is output.

9. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 8, characterized in that: The production and intelligent analysis also includes: The raw material input-output ratio is obtained based on the execution process data analysis after task allocation; Estimate the parameters of materials to be consumed based on the assigned tasks, current task progress and raw material input-output ratio; Compare the parameters of the materials to be consumed with the inventory data, and when the inventory data is insufficient, output procurement warning information; wherein the procurement warning information includes prompt information and material shortage parameters.

10. The method for customization and production delivery of intelligent devices based on free combination of modules according to claim 1, characterized in that: Establish the data analysis and processing center of the system / platform through distributed computing technology.

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