LED production logistics automatic management system and management method

Abstract

The application relates to the technical field of logistics management, in particular to an LED production logistics automatic management system and a management method. The system comprises a business data acquisition unit, a logistics data acquisition unit, an intelligent allocation unit and an abnormality detection unit. The business data acquisition unit collects the production progress, quantity and in-out situation of different kinds of materials through corresponding acquisition modules. The logistics data acquisition unit collects the quantity of different kinds of materials to be carried, the data of carrying vehicles and the carrying situation data. The intelligent allocation unit intelligently generates corresponding carrying vehicle information and carrying time allocation information by a coefficient algorithm according to the production situation of different kinds of materials collected by the business data acquisition unit. When the carrying quantity and carrying time information of the carrying vehicle exceeds the allocation situation set by the intelligent allocation unit, the abnormality detection unit can timely alarm. The application can monitor the LED production situation and intelligently control the carrying vehicles.

Description

Technical Field

[0001] This invention relates to the field of logistics management technology, specifically to an automated management system and method for LED production logistics. Background Technology

[0002] Currently, in most electronics manufacturing industries, an increasing number of companies are choosing to use AGV (Automated Guided Vehicle) automated material handling. In the process of logistics automation, a combination of business systems and automated logistics systems is typically used. The business system records the type, quantity, and inbound / outbound status of materials, while the logistics system records the movement of materials on the shelves. However, existing logistics systems present fragmented information, requiring users to switch between multiple systems to obtain complete information. Furthermore, the training costs are high, and users need to master the use of two systems. In actual business operations, production personnel and warehouse managers focus on the business system, while maintenance personnel focus on the logistics system. It is difficult to achieve integrated management of all logistics information. Once a production or handling anomaly occurs, the system on the production or handling side cannot obtain data in time to judge the anomaly, resulting in overproduction of LED products or the dispatch of too much handling equipment for handling, leading to a waste of production and handling costs.

[0003] Based on the above problems, there is an urgent need for a management system and method that can automate the entire LED production logistics process and enable rapid and automatic reporting of faults. Summary of the Invention

[0004] In the current LED production logistics automation management system, each system is relatively independent. When a system malfunctions, it is difficult to deal with it in a timely manner, resulting in wasted production costs. This application provides an LED production logistics automation management system and management method to solve the above problems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: This application discloses an automated management system for LED production logistics, including: Business data acquisition unit: Collects data on the production progress, quantity, and inflow / outflow of different types of materials through corresponding acquisition modules; Logistics data acquisition unit: collects data on the quantity of different types of materials to be moved on the shelves, data on the handling vehicles, and data on the handling process; Intelligent dispatching unit: Real-time access to the production status of different types of materials collected by the business data acquisition unit, and intelligent generation of corresponding handling vehicle information and handling time dispatching information through coefficient algorithm; Anomaly detection unit: Monitors the quantity and time of transport by the transport vehicles in real time. When the quantity or time of transport by the transport vehicles exceeds the allocation conditions set by the intelligent dispatch unit, it can promptly issue an alarm.

[0006] By adopting the above technical solution: the solution can collect data on the production quantity and progress of different types of materials, the quantity of different types of materials to be transported on the shelves, the data on transport vehicles, and the transport status. The data collected by the above-mentioned collection module is transmitted to the intelligent allocation unit, which allocates transport vehicles and transport time through corresponding algorithm formulas. This can ensure the orderly progress of LED production logistics and prevent overproduction or over-allocation of transport vehicles from paralyzing the production logistics process.

[0007] Preferably, the business data acquisition unit includes: Product order number collection module: collects the creation time, update time, and production status of product orders. The production status includes: not started, in progress, completed, and abnormal.

[0008] Product production progress data acquisition module: It can collect the production quantity and inflow / outflow status of different types of materials at different time periods.

[0009] More preferably, the logistics data acquisition unit includes: Material to be transported acquisition module: used to collect the quantity of different types of materials to be transported on the shelf; The material handling information collection module collects data on material handling vehicles, material handling status, start time, end time, starting position, and target position. Vehicle information collection module: used to collect information such as vehicle location, whether it is carrying cargo, obstacle encounter information, and battery level.

[0010] The above technical solution is adopted: The above solution subdivides the business data collection unit into various collection modules, including product order number collection and product production progress collection, which can realize the collection of product production order numbers and the production progress of products with different order numbers.

[0011] More preferably, the intelligent allocation unit includes: Information retrieval module: retrieves various data collected by the business data acquisition unit and the logistics data acquisition unit in real time; First data generation module: Calculates corresponding handling vehicle information through algorithm model based on various business data and logistics data collected by the information retrieval module; The second data generation module is used to generate vehicle handling time information based on the various business and logistics data collected by the information retrieval module and the handling vehicle information calculated by the first data generation module.

[0012] Output module: Used to output the transport vehicle information and vehicle transport time information generated by the first data generation module and the second data generation module.

[0013] The above technical solution is adopted as follows: The intelligent dispatching unit is subdivided into various modules to acquire the corresponding information, and the first data production module and the second data production module generate the corresponding information on the different transport vehicle models required, the quantity of each transport vehicle model, and the transport time required for each vehicle model.

[0014] More preferably, the algorithm formula set in the first data generation module is: , The algorithm formula set in the second data generation module is as follows: ; in, For the first Types of transport vehicles, For the first Types of transport vehicles, For the first The number of different types of transport vehicles For the inventory information of the i-th type of material on the shelf, For the material information of the i-th type on the shelf, Output material information for the i-th type of material on the shelf. Let be the material conversion coefficient of the i-th material on the shelf. There are m types of goods. To determine the quantity of material to produce for the i-th type of material, Let i be the material conversion coefficient for producing material i. For the first The time required for each type of transport vehicle to move goods. This is the conversion factor for transportation time.

[0015] The above technical solution provides algorithm formulas for the first data generation module and the second data production module, respectively. The two algorithm formulas can calculate the handling vehicle type, the quantity of the corresponding handling vehicle type, and the handling time information of the corresponding vehicle type based on the inventory quantity of the material and the production quantity of the material.

[0016] More preferably, the algorithm formula set in the first data generation module ultimately calculates the relationship between the number of transport vehicle models and the corresponding transport vehicle models, which can realize the adjustment of the corresponding vehicle models and the corresponding number of transport vehicle models according to the actual transport needs.

[0017] The above technical solution is used to calculate the final result of the algorithm formula, which is the operational relationship between the transport vehicle model and the corresponding transport vehicle model. This allows for the allocation of different transport vehicle models and the number of transport vehicles based on the on-site working environment and other data.

[0018] More preferably, the algorithm formula set in the second data generation module ultimately calculates the transport vehicle model and the transport time corresponding to that transport vehicle model, which can adjust the corresponding transport vehicle model and the transport time corresponding to the transport vehicle model according to the actual transport needs.

[0019] The above technical solution calculates the final result of the algorithm formula, which is the relationship between the transport vehicle model and the transport time corresponding to the transport vehicle model. This allows for adjustments to the transport vehicle model and the transport time of the corresponding vehicle model based on the actual situation on site.

[0020] More preferably, the anomaly detection unit includes: Vehicle anomaly proactive reporting module: When the corresponding data detection system on the transport vehicle detects an anomaly, it can proactively report the anomaly. Task execution timeout module: After the designated transport vehicle receives tasks assigned by the intelligent dispatch unit within different time periods, the corresponding detection system can detect and alarm when the task execution times out. Task waiting timeout module: When a designated transport vehicle receives a task assigned by the intelligent dispatch unit within a different time period, and the waiting time exceeds the set time, the corresponding detection system can detect it and issue an alarm.

[0021] The above technical solution refines the anomaly detection unit into a vehicle anomaly active reporting module, a task execution timeout module, and a task waiting timeout module. This enables the collection of specific vehicle data and vehicle operation time information. When a corresponding vehicle malfunctions or its execution time information becomes abnormal, the solution can promptly report the error and take appropriate action.

[0022] An automated management method for LED production logistics, applied to an automated management system for LED production logistics as described in any one of the above, comprising: S1: The business data acquisition unit collects the production progress, quantity, and inbound / outbound status of different types of materials through the corresponding acquisition modules; S2: The logistics data acquisition unit collects data on the quantity of different types of materials to be transported on the shelves, the data of the transport vehicles, and the transport status. S3: The intelligent allocation unit retrieves the production status of different types of materials collected by the business data acquisition unit in real time, and intelligently generates corresponding handling vehicle information and handling time allocation information through system algorithms. S4: The anomaly detection unit monitors the quantity and time information of the transport vehicles in real time. When the quantity and time information of the transport vehicles exceed the allocation conditions set by the intelligent allocation unit, an alarm will be triggered in time.

[0023] The above technical solution provides a method that can collect LED production logistics information through a corresponding process and transmit the corresponding data to an intelligent dispatching unit, which then analyzes the corresponding handling vehicle type, number of handling vehicles, and handling time information of the corresponding handling vehicles.

[0024] More preferably, S3 includes: S31: The information retrieval module retrieves various data collected by the business data acquisition unit and the logistics data acquisition unit in real time; S32: The first data generation module calculates the corresponding handling vehicle information through an algorithm model based on the various business data and logistics data collected by the information retrieval module; S33: The second data generation module generates vehicle handling time information based on the various business data and logistics data collected by the information retrieval module and the handling vehicle information calculated by the first data generation module. S34: The output module outputs the transport vehicle information and vehicle transport time information generated by the first data production module and the second data production module.

[0025] The above technical solution refines the workflow of the intelligent dispatching unit, enabling the collection of logistics business data, and generating corresponding information on the types of handling vehicles, the number of different types of handling vehicles, and the handling time corresponding to the handling vehicles by the first data production module and the second data production module. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a connection block diagram of the LED production logistics automation management system of this application; Figure 2 This is a flowchart of the management method for this application; Figure 3 For this application Figure 2 Flowchart for step S3.

[0028] In the picture: 1. Business Data Acquisition Unit; 2. Logistics Data Acquisition Unit; 3. Intelligent Allocation Unit; 4. Anomaly Detection Unit; 5. Product Order Number Acquisition Module; 6. Product Production Progress Acquisition Module; 7. Materials to be Handled Acquisition Module; 8. Handling Information Acquisition Module; 9. Vehicle Information Acquisition Module; 10. Information Retrieval Module; 11. First Data Production Module; 12. Second Data Production Module; 13. Output Module; 14. Vehicle Anomaly Active Reporting Module; 15. Task Execution Timeout Module; 16. Task Waiting Timeout Module. Detailed Implementation

[0029] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0030] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0031] Please see Figures 1-3 Existing LED production logistics systems, such as those for LED production, lack corresponding data monitoring and vehicle dispatching systems. This can easily lead to overproduction or uneven distribution of transport vehicles, causing production process paralysis and economic losses. To address these issues, this application discloses an automated management system for LED production logistics, comprising: Business Data Acquisition Unit 1: Collects data on the production progress, quantity, and inflow / outflow of different types of materials through corresponding acquisition modules; Logistics data acquisition unit 2: Collects data on the quantity of different types of materials to be transported on the shelves, data on transport vehicles, and data on transport status; Intelligent dispatching unit 3: Real-time access to the production status of different types of materials collected by business data acquisition unit 1, and intelligent generation of corresponding handling vehicle information and handling time dispatching information through coefficient algorithm; Anomaly detection unit 4: Monitors the quantity and time information of the transport vehicles in real time. When the quantity and time information of the transport vehicles exceed the allocation conditions set by the intelligent allocation unit 3, it can promptly issue an alarm.

[0032] It is worth mentioning that the above solution can collect data on the production quantity and progress of different types of materials, the quantity of different types of materials to be transported on the shelves, the data on the handling vehicles, and the handling status. The data collected by the above-mentioned collection module is transmitted to the intelligent allocation unit 3. The intelligent allocation unit 3 allocates handling vehicles and handling time through corresponding algorithm formulas, which can ensure the orderly progress of LED production logistics and prevent overproduction or over-allocation of handling vehicles from paralyzing the production logistics process.

[0033] The business data acquisition unit 1 includes: Product Order Number Collection Module 5: Collects the creation time, update time, and production status of product orders. The production status includes: not started, in progress, completed, and abnormal.

[0034] Product production progress data acquisition module 6: It can collect the production quantity and inflow / outflow status of different types of materials at different time periods.

[0035] The logistics data acquisition unit 2 includes: Material to be transported module 7: Used to collect the quantity of different types of materials to be transported on the shelf; Module 8 for collecting transport information: This module collects transport vehicle data, transport status data, transport start time, end time, start position, and target position. Vehicle Information Collection Module 9: Used to collect information on vehicle location, whether it is carrying cargo, obstacle encounter information, and battery level.

[0036] It is worth mentioning that the above solution subdivides the business data collection unit 1 into various collection modules, including product order number collection and product production progress collection, which can collect the product's production order number and the production progress of products with different order numbers.

[0037] The intelligent allocation unit 3 includes: Information retrieval module 10: retrieves various data collected by business data acquisition unit 1 and logistics data acquisition unit 2 in real time; First data generation module: Calculates corresponding handling vehicle information through algorithm model based on various business data and logistics data collected by information retrieval module 10; The second data generation module is used to generate vehicle handling time information based on the various business data and logistics data collected by the information retrieval module 10 and the handling vehicle information calculated by the first data generation module.

[0038] Output module 13: Used to output the transport vehicle information and vehicle transport time information generated by the first data generation module and the second data generation module.

[0039] It is worth mentioning that the above solution subdivides the intelligent dispatching unit 3 into various modules, acquires the corresponding collected information, and generates the corresponding required different transport vehicle models and the quantity information corresponding to different transport vehicle models, as well as the transport time required for different vehicle models, through the first data production module 11 and the second data production module 12.

[0040] More preferably, the algorithm formula set in the first data generation module is: , The algorithm formula set in the second data generation module is as follows: , in, For the first Types of transport vehicles, For the first Types of transport vehicles, For the first The number of different types of transport vehicles For the inventory information of the i-th type of material on the shelf, For the material information of the i-th type on the shelf, Output material information for the i-th type of material on the shelf. Let be the material conversion coefficient of the i-th material on the shelf. There are m types of goods. To determine the quantity of material to produce for the i-th type of material, Let i be the material conversion coefficient for producing material i. For the first The time required for each type of transport vehicle to move goods. This is the conversion factor for transportation time.

[0041] The above solution, by setting corresponding algorithm formulas, only needs to collect inventory information and material entry and exit information of different types of materials on the shelf to generate the corresponding handling vehicle type, the quantity of handling vehicle type, and the handling time of handling vehicle type. The material conversion coefficient, production material conversion coefficient, and handling time conversion coefficient mentioned above are conversion coefficient data calculated by autonomously dispatching vehicles multiple times based on actual work scenarios.

[0042] The above scheme provides the algorithm formulas corresponding to the first data generation module and the second data production module 12, respectively. The two algorithm formulas can calculate the handling vehicle type, the quantity of the corresponding handling vehicle type, and the handling time information of the corresponding vehicle type based on the inventory quantity of the material and the production quantity of the material, respectively.

[0043] The algorithm formula set in the first data generation module ultimately calculates the quantity relationship between transport vehicle models and transport vehicle models, which can realize the adjustment of the corresponding vehicle models and the corresponding quantity of transport vehicle models according to actual transport needs.

[0044] The algorithm formula in the above scheme ultimately calculates the relationship between the transport vehicle model and the corresponding transport vehicle model, which enables the allocation of different transport vehicle models and the number of transport vehicles based on the on-site working environment and other data information.

[0045] The algorithm formula set in the second data generation module ultimately calculates the transport vehicle model and the corresponding transport time, which can be adjusted according to actual transport needs.

[0046] The algorithm formula in the above scheme calculates the relationship between the transport vehicle model and the transport time corresponding to the transport vehicle model, which can adjust the transport vehicle model and the transport time of the corresponding vehicle model according to the actual situation on site.

[0047] The anomaly detection unit 4 includes: Vehicle anomaly proactive reporting module 14: When the corresponding data detection system on the transport vehicle detects an anomaly in the transport vehicle, it can proactively report the anomaly. Task execution timeout module 15: After the designated transport vehicle receives the tasks assigned by the intelligent dispatch unit 3 within different time periods, when the task execution timeout occurs, the corresponding detection system can detect and alarm. Task waiting timeout module 16: When a designated transport vehicle receives a task assigned by the intelligent dispatch unit 3 within a different time period, and the waiting time exceeds the set time, the corresponding detection system can detect and issue an alarm.

[0048] The above scheme further subdivides the anomaly detection unit 4 into a vehicle anomaly active reporting module 14, a task execution timeout module 15, and a task waiting timeout module 16. This enables the collection of specific data information of the vehicle and the vehicle's operation time information. When the corresponding vehicle malfunctions or the vehicle's execution time information is abnormal, it can promptly report the error and take appropriate action.

[0049] An automated management method for LED production logistics, applied to an automated management system for LED production logistics as described in any one of the above, comprising: S1: Business data acquisition unit 1 collects the production progress, quantity, and inbound / outbound status of different types of materials through the corresponding acquisition modules; S2: Logistics data acquisition unit 2 collects data on the quantity of different types of materials to be transported on the shelf, transport vehicle data, and transport status. S3: The intelligent allocation unit 3 retrieves the production status of different types of materials collected by the business data acquisition unit 1 in real time, and intelligently generates corresponding handling vehicle information and handling time allocation information through system algorithms. S4: The anomaly detection unit 4 monitors the quantity and time information of the transport vehicles in real time. When the quantity and time information of the transport vehicles exceed the allocation conditions set by the intelligent allocation unit 3, an alarm will be triggered in time.

[0050] The above solution provides a method that can collect LED production logistics information through a corresponding process and transmit the corresponding data to the intelligent dispatching unit 3. The intelligent dispatching unit 3 then analyzes the corresponding handling vehicle type, number of handling vehicles, and handling time information of the corresponding handling vehicles.

[0051] S3 includes: S31: The information retrieval module 10 retrieves various data collected by the business data acquisition unit 1 and the logistics data acquisition unit 2 in real time; S32: The first data generation module calculates the corresponding handling vehicle information through an algorithm model based on the various business data and logistics data collected by the information retrieval module 10. S33: The second data generation module generates vehicle handling time information based on the various business data and logistics data collected by the information retrieval module 10 and the handling vehicle information calculated by the first data generation module. S34: Output module 13 outputs the transport vehicle information and vehicle transport time information generated by the first data production module 11 and the second data production module 12.

[0052] The above scheme refines the workflow of the intelligent dispatching unit 3, enabling the collection of logistics business data, and the generation of corresponding handling vehicle types, quantities of different types of handling vehicles, and handling time information corresponding to the handling vehicles by the first data production module 11 and the second data production module 12.

[0053] Unless otherwise specified, the equipment components involved in the above embodiments are all conventional equipment components, and the connection methods and control methods involved are all conventional connection methods and control methods unless otherwise specified.

[0054] The present invention has been described in detail above with reference to the embodiments. However, those skilled in the art will understand that, without departing from the spirit of the present invention, various specific parameters in the above embodiments can be changed to form multiple specific embodiments, all of which are common variations of the present invention, and will not be described in detail here.

Claims

1. An automated management system for LED production logistics, characterized in that, include: Business data acquisition unit: Collects data on the production progress, quantity, and inflow / outflow of different types of materials through corresponding acquisition modules; Logistics data acquisition unit: collects data on the quantity of different types of materials to be moved on the shelves, data on the handling vehicles, and data on the handling process; Intelligent dispatching unit: Real-time access to the production status of different types of materials collected by the business data acquisition unit, and intelligent generation of corresponding handling vehicle information and handling time dispatching information through coefficient algorithm; Anomaly detection unit: Monitors the quantity and time of transport by the transport vehicles in real time. When the quantity or time of transport by the transport vehicles exceeds the allocation conditions set by the intelligent dispatch unit, it can promptly issue an alarm.

2. The LED production logistics automated management system according to claim 1, characterized in that, The business data acquisition unit includes: Product order number collection module: collects the creation time, update time, and production status of product orders. The production status includes: not started, in progress, completed, and abnormal. Product production progress data acquisition module: It can collect the production quantity and inflow / outflow status of different types of materials at different time periods.

3. The LED production logistics automated management system according to claim 1, characterized in that, The logistics data acquisition unit includes: Material to be transported acquisition module: used to collect the quantity of different types of materials to be transported on the shelf; The material handling information collection module collects data on material handling vehicles, material handling status, start time, end time, starting position, and target position. Vehicle information collection module: used to collect information such as vehicle location, whether it is carrying cargo, obstacle encounter information, and battery level.

4. The LED production logistics automated management system according to claim 1, characterized in that, The intelligent allocation unit includes: Information retrieval module: retrieves various data collected by the business data acquisition unit and the logistics data acquisition unit in real time; First data generation module: Calculates corresponding handling vehicle information through algorithm model based on various business data and logistics data collected by the information retrieval module; The second data generation module is used to generate vehicle handling time information based on the various business data and logistics data collected by the information retrieval module and the handling vehicle information calculated by the first data generation module. Output module: Used to output the transport vehicle information and vehicle transport time information generated by the first data generation module and the second data generation module.

5. The LED production logistics automated management system according to claim 4, characterized in that, The algorithm formula set within the first data generation module is as follows: ， The algorithm formula set in the second data generation module is as follows: ； in, For the first Types of transport vehicles, For the first Types of transport vehicles, For the first The number of different types of transport vehicles For the inventory information of the i-th type of material on the shelf, For the material information of the i-th type on the shelf, Output material information for the i-th type of material on the shelf. Let be the material conversion coefficient of the i-th material on the shelf. There are m types of goods. To determine the quantity of material to produce for the i-th type of material, Let i be the material conversion coefficient for producing material i. For the first The time required for each type of transport vehicle to move goods. This is the conversion factor for transportation time.

6. The LED production logistics automated management system according to claim 5, characterized in that, The algorithm formula set in the first data generation module ultimately calculates the quantity relationship between transport vehicle models and transport vehicle models, which can realize the adjustment of the corresponding vehicle models and the corresponding quantity of transport vehicle models according to actual transport needs.

7. The LED production logistics automated management system according to claim 5, characterized in that, The algorithm formula set in the second data generation module ultimately calculates the transport vehicle model and the corresponding transport time, which can be adjusted according to actual transport needs.

8. The LED production logistics automated management system according to claim 1, characterized in that, The anomaly detection unit includes: Vehicle anomaly proactive reporting module: When the corresponding data detection system on the transport vehicle detects an anomaly, it can proactively report the anomaly. Task execution timeout module: After the designated transport vehicle receives tasks assigned by the intelligent dispatch unit within different time periods, the corresponding detection system can detect and alarm when the task execution times out. Task waiting timeout module: When a designated transport vehicle receives a task assigned by the intelligent dispatch unit within a different time period, and the waiting time exceeds the set time, the corresponding detection system can detect it and issue an alarm.

9. An automated management method for LED production logistics, applied to an automated management system for LED production logistics as described in any one of claims 1-8, characterized in that, include: S1: The business data acquisition unit collects the production progress, quantity, and inbound / outbound status of different types of materials through the corresponding acquisition modules; S2: The logistics data acquisition unit collects data on the quantity of different types of materials to be transported on the shelves, the data of the transport vehicles, and the transport status. S3: The intelligent allocation unit retrieves the production status of different types of materials collected by the business data acquisition unit in real time, and intelligently generates corresponding handling vehicle information and handling time allocation information through system algorithms. S4: The anomaly detection unit monitors the quantity and time information of the transport vehicles in real time. When the quantity and time information of the transport vehicles exceed the allocation conditions set by the intelligent allocation unit, an alarm will be triggered in time.

10. The LED production logistics automation management method according to claim 9, characterized in that, S3 includes: S31: The information retrieval module retrieves various data collected by the business data acquisition unit and the logistics data acquisition unit in real time; S32: The first data generation module calculates the corresponding handling vehicle information through an algorithm model based on the various business data and logistics data collected by the information retrieval module; S33: The second data generation module generates vehicle handling time information based on the various business data and logistics data collected by the information retrieval module and the handling vehicle information calculated by the first data generation module. S34: The output module outputs the transport vehicle information and vehicle transport time information generated by the first data production module and the second data production module.

Images