Visual production billboard system and use method thereof

Abstract

The invention discloses a visual production board system and a use method thereof, and relates to the field of management systems. According to the visual production billboard system, the system architecture comprises a hardware layer, an inner code layer, a machine interface instruction layer and an operating system layer, and the system is used through the following steps that firstly, engineering data are commonly connected in series; 2, the system monitors production; 3, unifying a system and a construction period standard; and step 4, enabling a real-time system board to be visible. According to the visual production billboard system, data of a previous project are integrated into a unified AS400 system, it is ensured that the data can be input and updated in real time, the whole production process is monitored through the system, the production progress and problem points are directly displayed in the system, the previous project and the next project are managed through the unified system, and a unified construction period standard is set; and the real-time system billboard is used for displaying the production progress and the inventory condition, so that the intermediate partition is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of management systems, and in particular to a visual production kanban system and a method for using the same. Background Art

[0002] Currently, there are multiple lines in the factory workshop, and the nodes between each line are different. The display screen corresponding to each equipment assembly line only displays the working signal of its own equipment.

[0003] Due to the large number of overall production processes, many items, and large fluctuations in planned quantities, the production plans and output times of each project are unclear, and the production information of each project cannot be interconnected in real time and effectively, resulting in: a large amount of inventory hanging between projects, a long production cycle, no fast feedback on quality, and failure to deliver on time and short-term production. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a visual production kanban system and a method for using the same, which solves the problems of large amounts of inventory hanging between projects, long production cycles, inability to quickly feedback on quality, and inability to deliver on time and produce in short lead times.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a visual production kanban system and a method for using the same, the system architecture comprising:

[0006] Hardware layer, the hardware layer includes the system main processor, memory, I / O bus and expansion components, supports multiple I / O buses, provides complete DMA function, and ensures efficient data transmission;

[0007] The inner code layer, which runs on the hardware layer, isolates the machine interface instruction layer and the operating system from the specific implementation details of the hardware;

[0008] The machine interface instruction layer includes high-level general instructions that are independent of the machine and supports operating systems, databases and other practical software;

[0009] The operating system layer adopts the AS / 400 system and is configured with the OS / 400 operating system, providing relational database management functions, flexible menu-driven operations, interactive and batch processing modes, and supporting multi-protocol communications and distributed processing network systems.

[0010] A method for using a visual production kanban system and a method for using the same, including a visual production kanban system and a method for using the same, the method for using the same comprising the following steps:

[0011] Step 1: Engineering data is connected in series. First, data is collected and sorted, and then the sorted data is integrated into the AS400 system. Real-time data input and update are achieved through the interface and API provided by the system, and then data verification and testing are performed;

[0012] Step 2: System monitoring production, configure the monitoring system, configure the monitoring system in the AS400 system, collect data in the production process in real time, and then display and analyze the data;

[0013] Step 3: Unify the system and construction period standards. First, integrate the system to unify the front-end and back-end engineering systems to ensure seamless data transfer and sharing. Then formulate construction period standards. According to production needs and resource conditions, formulate unified construction period standards and manage and monitor them through the AS400 system.

[0014] Step 4: Real-time system dashboard is visible.

[0015] Preferably, the data collection and collation specifically includes: firstly collecting the engineering data of the previous engineering, cleaning, collating and standardizing the data to ensure the consistency and accuracy of the data;

[0016] The data verification and testing specifically include: after the system integration is completed, data verification and testing are performed to ensure the correctness of the data and the stability of the system.

[0017] Preferably, the data display and analysis specifically include: displaying the production process and problem points in real time through the system interface, providing data analysis and reporting functions, and assisting management personnel to quickly locate problems and take corresponding measures.

[0018] Preferably, the real-time system dashboard visualization steps are specifically:

[0019] Design dashboard interface, design real-time system dashboard interface according to production needs and management requirements to display key indicators and data;

[0020] Data update and synchronization ensure that the data on the dashboard is updated and synchronized in real time to reflect the latest production status and problem points.

[0021] Preferably, the engineering data are commonly connected in series using a data integration and conversion algorithm to integrate engineering data of different formats and sources into the AS400 system and perform data format conversion and standardization processing.

[0022] Preferably, the system monitors production using a real-time monitoring algorithm for real-time collection and analysis of data during the production process, identification of abnormal situations and problem points, and provision of early warning and alarm functions.

[0023] Preferably, the unified system and construction period standard adopts data analysis and mining algorithms and optimized scheduling algorithms.

[0024] Preferably, the data analysis and mining algorithm is used to conduct in-depth analysis and mining of production data, discover potential problems and improvement points, and provide support for optimizing production processes and improving production efficiency;

[0025] The optimization scheduling algorithm optimizes production scheduling according to production demand and resource conditions, reduces fluctuations in the construction period of previous and subsequent projects, and improves production efficiency and resource utilization.

[0026] The present invention discloses a visual production kanban system and a method for using the same, which have the following beneficial effects:

[0027] 1. The visual production kanban system and its usage method integrate the data of previous projects into a unified AS400 system, ensuring that data can be input and updated in real time, improving data accuracy and consistency, and reducing errors caused by inconsistent data. Real-time data updates help management make timely decisions, optimize production processes, promote information sharing and collaboration between different projects, and improve overall production efficiency.

[0028] 2. The visual production kanban system and its use method monitor the entire production process through the system, and directly display the production progress and problem points in the system, reducing the time and manpower waste of personnel's back-and-forth confirmation, improving production efficiency, timely discovering and solving problems in production, and reducing production delays and losses caused by failure to discover problems in time. Through system monitoring, the production progress can be controlled more accurately to ensure that products are delivered on time.

[0029] 3. The visual production kanban system and its usage method use a unified system to manage the front and back projects and set a unified construction period standard to reduce the construction period fluctuations between the front and back projects and improve the accuracy and feasibility of the production plan. The unified construction period standard helps to optimize the production process, reduce unnecessary waiting time and waste of resources, improve overall production efficiency and reduce production costs.

[0030] 4. The visual production kanban system and its use method use real-time system kanbans to display production progress and inventory status, thereby reducing intermediate hangs. Through visual display, management can more intuitively understand production progress and inventory status and make more reasonable decisions. Reducing intermediate hangs can reduce inventory costs, improve capital turnover, and shorten production cycles, which will help the company respond to market demands more quickly, improve market competitiveness, enhance the company's overall operational efficiency, and enhance market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 It is a schematic diagram of the system architecture of the present invention;

[0033] Figure 2 It is a flow chart of the steps of the system of the present invention;

[0034] Figure 3 A schematic diagram of the algorithm for using engineering data in common serial connection according to the present invention;

[0035] Figure 4 A schematic diagram of an algorithm used in monitoring production by the system of the present invention;

[0036] Figure 5 This is a schematic diagram of the algorithm used to unify the system and construction period standards of the present invention. DETAILED DESCRIPTION

[0037] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0038] The embodiment of the present invention discloses a visual production kanban system and a method for using the same. Figure 1-5 As shown, the system architecture includes:

[0039] Hardware layer: The hardware layer includes the system main processor, memory, I / O bus and expansion components, supports multiple I / O buses, provides complete DMA function, and ensures efficient data transmission;

[0040] The internal code layer and the internal code layer operate on the hardware layer, isolating the machine interface instruction layer and the operating system from the specific implementation details of the hardware;

[0041] The machine interface instruction layer contains high-level general instructions that are independent of the machine and support operating systems, databases, and other utility software;

[0042] The operating system layer and the operating system layer adopt the AS / 400 system and are equipped with the OS / 400 operating system, providing relational database management functions, flexible menu-driven operations, interactive and batch processing job modes, and supporting multi-protocol communications and distributed decentralized processing network systems;

[0043] A method for using a visual production kanban system and a method for using the same, including a visual production kanban system and a method for using the same, the method for using the same comprising the following steps:

[0044] Step 1: Common connection of engineering data;

[0045] Step 2: System monitoring production;

[0046] Step 3: Unify system and construction period standards;

[0047] Step 4: Real-time system dashboard is visible.

[0048] The common serial connection steps of engineering data are specially disclosed as follows:

[0049] Data collection and organization, first of all, collect the engineering data of the previous project, clean, organize and standardize it to ensure the consistency and accuracy of the data;

[0050] System integration: Integrate the sorted data into the AS400 system and implement real-time data input and update through the interfaces and APIs provided by the system;

[0051] Data verification and testing: After system integration is completed, data verification and testing are carried out to ensure the correctness of the data and the stability of the system.

[0052] Specifically disclosed, the system monitors the production steps as follows:

[0053] Configure the monitoring system in the AS400 system to collect data in the production process in real time, such as equipment status, production progress, and quality issues;

[0054] Data display and analysis: the system interface displays the production process and problem points in real time, provides data analysis and reporting functions, and assists managers to quickly locate problems and take corresponding measures.

[0055] The specific steps for unifying the system and construction period standards are as follows:

[0056] System integration to unify front-end and back-end engineering systems and ensure seamless data flow and sharing;

[0057] Establish unified construction period standards based on production needs and resource conditions, and manage and monitor them through the AS400 system.

[0058] Specifically, the real-time system dashboard visual steps are:

[0059] Design dashboard interface, design real-time system dashboard interface according to production needs and management requirements to display key indicators and data;

[0060] Data update and synchronization ensure that the data on the dashboard is updated and synchronized in real time to reflect the latest production status and problem points.

[0061] Furthermore, the engineering data is commonly connected in series using data integration and conversion algorithms to integrate engineering data of different formats and sources into the AS400 system and perform data format conversion and standardization.

[0062] Data integration is the process of integrating data from different data sources to achieve data consistency and uniformity. Data conversion algorithms play a vital role in the data integration process. It is mainly responsible for converting data from one format to another to meet the needs of the AS400 system.

[0063] As an implementation method, in order to further improve the efficiency and accuracy of data integration and conversion, in order to cope with more complex and diverse engineering data, in this embodiment, an intelligent data identification and classification module based on natural language processing (NLP) and machine learning is introduced. This module automatically identifies the format, type and content of the data by performing semantic analysis and key information extraction on the engineering data, and classifies it into the corresponding data category according to predefined rules and algorithms. At the same time, a rule-based data quality detection and verification engine is introduced to perform automated quality inspection and error correction on the data. The quality detection rules can be flexibly defined and adjusted through the configuration file to adapt to different data characteristics and quality requirements. When the data integration and conversion algorithm is converted and loaded, the intelligent data identification and classification module and the data quality detection and verification engine are automatically called to ensure the accuracy and consistency of the data. By introducing an intelligent data processing mechanism, the efficiency and accuracy of data integration and conversion are improved, and manual intervention and error rate are reduced.

[0064] Furthermore, the system monitors production using a real-time monitoring algorithm that is used to collect and analyze data from the production process in real time, identify abnormal situations and problem points, and provide early warning and alarm functions.

[0065] The real-time monitoring algorithm is as follows:

[0066] Data collection: Real-time monitoring algorithms collect various data from the production process in real time through sensors and PLC devices.

[0067] Data analysis: The collected data is immediately analyzed by the real-time monitoring algorithm. The algorithm checks whether the data fluctuates within the normal range, whether there are outliers and trend changes. Through data analysis, the algorithm can promptly identify potential problems in the production process.

[0068] Abnormal identification and early warning: Once the algorithm detects an abnormal situation, it will immediately trigger the early warning mechanism. This usually includes sending alarm information to operators and displaying abnormal data and possible fault points on the monitoring interface.

[0069] As an implementation method, in order to realize intelligent management and predictive maintenance of production equipment and reduce the impact of equipment failure on production, in this embodiment, an intelligent monitoring and predictive maintenance system for equipment based on the Industrial Internet of Things (IIoT) is introduced. The system collects the operating parameters and status data of the equipment in real time by deploying various sensors such as temperature, vibration, current, etc. on key production equipment. The collected data is transmitted to the edge computing node or cloud platform via industrial Ethernet or wireless network for real-time analysis and processing. In the cloud, a prediction model for the health status of the equipment is established by using big data analysis and machine learning algorithms. By analyzing the historical operation data and real-time status data of the equipment, the potential failures and remaining service life of the equipment are predicted. The prediction results are displayed through a visual dashboard and integrated with the enterprise's maintenance management system to automatically generate maintenance work orders and spare parts demand plans. At the same time, the system also supports rule-based real-time early warning functions. When the key parameters of the equipment exceed the preset threshold, the alarm information is automatically triggered to notify relevant personnel to conduct inspection and maintenance. By introducing the intelligent monitoring and predictive maintenance system for equipment, real-time monitoring and fault prediction of equipment status are realized, the reliability and stability of the equipment are improved, and unexpected downtime and maintenance costs are reduced.

[0070] Furthermore, the unified system and duration standards adopt data analysis and mining algorithms and optimized scheduling algorithms.

[0071] Furthermore, data analysis and mining algorithms are used to conduct in-depth analysis and mining of production data, discover potential problems and improvement points, and provide support for optimizing production processes and improving production efficiency;

[0072] The data analysis and mining algorithms are as follows:

[0073] Data preprocessing: Before in-depth analysis, data analysis and mining algorithms will preprocess the collected data. This includes data cleaning (removing invalid and erroneous data), data integration (integrating data from different sources) and data conversion (converting data into a format suitable for analysis).

[0074] Statistical analysis: The preprocessed data will be statistically analyzed. Statistical analysis can help us understand the distribution characteristics of data, trend changes, and the relationship between different variables. Through statistical analysis, potential problems and improvement points in the production process can be discovered.

[0075] Machine Learning: Machine learning algorithms are a core part of data analysis and mining. They can learn patterns and regularities from large amounts of data and use them to predict future trends and identify anomalies.

[0076] Visualization and reporting: Finally, data analysis and mining algorithms will present the analysis results in a visual way, such as charts and reports.

[0077] The optimization scheduling algorithm optimizes production scheduling according to production demand and resource conditions, reduces fluctuations in the construction period of previous and subsequent projects, and improves production efficiency and resource utilization.

[0078] The optimization scheduling algorithm is as follows:

[0079] Demand forecasting: The optimization scheduling algorithm will first predict future production needs based on historical data and market demand.

[0080] Resource optimization: Based on the predicted demand, the algorithm considers the utilization of existing resources and tries to find the best resource allocation solution.

[0081] Scheduling Optimization: Finally, the algorithm will generate the optimal production schedule based on demand forecast and resource optimization results.

[0082] Dynamic adjustment: In the actual production process, due to the influence of various factors, the production schedule may need to be adjusted dynamically. The optimization scheduling algorithm can make real-time adjustments according to the actual situation to ensure the smooth execution of the production plan.

[0083] Integrate the data of previous projects into a unified AS400 system to ensure that data can be input and updated in real time, improve data accuracy and consistency, and reduce errors caused by inconsistent data. Real-time data updates help management make timely decisions, optimize production processes, promote information sharing and collaboration between different projects, and improve overall production efficiency.

[0084] The system monitors the entire production process and directly displays the production progress and problem points in the system, reducing the time and manpower waste of personnel going back and forth to confirm, improving production efficiency, promptly discovering and solving problems in production, and reducing production delays and losses caused by failure to discover problems in time. Through system monitoring, the production progress can be controlled more accurately to ensure that products are delivered on time.

[0085] Use a unified system to manage front-end and back-end projects, and set unified construction period standards to reduce construction period fluctuations between front-end and back-end projects, improve the accuracy and feasibility of production plans, and unify construction period standards to help optimize production processes, reduce unnecessary waiting time and waste of resources, improve overall production efficiency, and reduce production costs.

[0086] Real-time system dashboards are used to display production progress and inventory status, thereby reducing intermediate hangs. Through visual display, management can more intuitively understand production progress and inventory status and make more reasonable decisions. Reducing intermediate hangs can reduce inventory costs, improve capital turnover, and shorten production cycles, which will help the company respond to market demand more quickly, improve market competitiveness, enhance the company's overall operational efficiency, and enhance market competitiveness.

[0087] As an implementation method, in order to realize intelligent scheduling and optimization of the production process and improve production efficiency and resource utilization, in this embodiment, on the basis of the original data analysis and mining algorithm and optimization scheduling algorithm, an intelligent scheduling system for the production process based on digital twins and intelligent optimization is introduced. The system constructs a digital twin model of the production process by three-dimensional modeling and simulation of the production workshop. By deploying various sensors and data acquisition equipment at the production site, various data in the production process, such as equipment status, material consumption, and man-hours, are collected in real time, and transmitted to the digital twin model to realize real-time mapping and synchronization of the production process. On this basis, intelligent optimization algorithms, such as genetic algorithms and particle swarm algorithms, are used to optimize production scheduling and resource allocation in real time to find the optimal production plan and scheduling scheme. The optimization target can be configured according to actual needs, such as minimizing the production cycle, maximizing equipment utilization, etc. The optimization results are presented through a visual interface and integrated with systems such as MES and ERP to automatically issue production instructions and scheduling tasks. At the same time, the system also supports real-time production monitoring and early warning functions. When abnormal deviations occur in the production process, early warning information is automatically triggered, and production plans and resource allocations are automatically adjusted according to preset rules and strategies to ensure smooth production. By introducing the production process intelligent scheduling system, real-time optimization and intelligent scheduling of the production process are achieved, production efficiency and resource utilization are improved, and production bottlenecks and waste are reduced.

[0088] As an implementation method, in order to achieve collaborative optimization and risk management of the supply chain and improve the agility and resilience of the supply chain, in this embodiment, on the basis of the original AS400 system, a supply chain collaborative optimization and risk management platform based on blockchain and machine learning is introduced. The platform uses blockchain technology to build distributed ledgers and smart contracts between all parties involved in the supply chain to achieve secure sharing of supply chain data and business collaboration. By deploying data collection equipment and sensors in various links of the supply chain, real-time collection of supply chain operation data, such as order information, inventory levels, logistics status, etc., and uploading them to the blockchain network, the transparency and traceability of supply chain data are achieved. On this basis, machine learning algorithms, such as time series prediction and demand prediction, are used to predict and analyze key indicators of the supply chain in real time, such as demand forecasting, inventory optimization, production planning, etc., and the corresponding business processes and tasks are automatically triggered through smart contracts to achieve collaborative optimization of the supply chain. At the same time, the platform also integrates risk prediction and simulation models, identifies and quantifies risk factors in various links of the supply chain, predicts potential risks and impacts of the supply chain, and automatically generates risk response strategies and plans according to risk levels, such as alternative suppliers, safety stocks, etc., to improve the risk resistance of the supply chain. By introducing the supply chain collaborative optimization and risk management platform, transparent, collaborative and intelligent management of the supply chain is achieved, the agility and resilience of the supply chain are improved, and the supply chain risks and costs are reduced.

[0089] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A visual production kanban system, characterized in that: The system architecture includes: Hardware layer, the hardware layer includes the system main processor, memory, I / O bus and expansion components; The inner code layer, which runs on the hardware layer, isolates the machine interface instruction layer and the operating system from the specific implementation details of the hardware; The machine interface instruction layer includes high-level general instructions that are independent of the machine and supports operating systems, databases and other practical software; The operating system layer adopts the AS / 400 system and is configured with the OS / 400 operating system, providing relational database management functions, flexible menu-driven operations, interactive and batch processing modes, and supporting multi-protocol communications and distributed processing network systems.

2. A method for using a visual production kanban system, comprising the visual production kanban system according to claim 1, characterized in that: The method of use comprises the following steps: Step 1: Engineering data is connected in series. First, data is collected and sorted, and then the sorted data is integrated into the AS400 system. Real-time data input and update are achieved through the interface and API provided by the system, and then data verification and testing are performed; Step 2: System monitoring production, configure the monitoring system, configure the monitoring system in the AS400 system, collect data in the production process in real time, and then display and analyze the data; Step 3: Unify the system and construction period standards. First, integrate the system to unify the front-end and back-end engineering systems to ensure seamless data transfer and sharing. Then formulate construction period standards. According to production needs and resource conditions, formulate unified construction period standards and manage and monitor them through the AS400 system. Step 4: Real-time system dashboard is visible.

3. The method for using a visual production kanban system according to claim 2, characterized in that: The data collection and collation are specifically as follows: firstly, the engineering data of the previous project is collected, and then cleaned, collated and standardized to ensure the consistency and accuracy of the data; The data verification and testing specifically include: after the system integration is completed, data verification and testing are performed to ensure the correctness of the data and the stability of the system.

4. The method for using a visual production kanban system according to claim 2, characterized in that: The data display and analysis specifically include: displaying the production process and problem points in real time through the system interface, providing data analysis and reporting functions, and assisting management personnel to quickly locate problems and take corresponding measures.

5. The method for using a visual production kanban system according to claim 2, characterized in that: The real-time system dashboard visual steps are as follows: Design dashboard interface, design real-time system dashboard interface according to production needs and management requirements to display key indicators and data; Data update and synchronization ensure that the data on the dashboard is updated and synchronized in real time to reflect the latest production status and problem points.

6. The method for using a visual production kanban system according to claim 2, characterized in that: The engineering data are commonly connected in series using a data integration and conversion algorithm to integrate engineering data of different formats and sources into the AS400 system and perform data format conversion and standardization processing.

7. The method for using a visual production kanban system according to claim 2, characterized in that: The system monitors production using a real-time monitoring algorithm for real-time collection and analysis of data during the production process, identifying abnormal situations and problem points, and providing early warning and alarm functions.

8. The method for using a visual production kanban system according to claim 2, characterized in that: The unified system and construction period standard adopts data analysis and mining algorithms and optimized scheduling algorithms.

9. The method for using a visual production kanban system according to claim 8, characterized in that: The data analysis and mining algorithm is used to conduct in-depth analysis and mining of production data, discover potential problems and improvement points, and provide support for optimizing production processes and improving production efficiency; The optimization scheduling algorithm optimizes production scheduling according to production demand and resource conditions, reduces fluctuations in the construction period of previous and subsequent projects, and improves production efficiency and resource utilization.

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