Visualization method for supervising warehouse operation condition for imported commodities

Abstract

The invention provides a visualization method for supervising warehouse operation conditions for imported commodities, and relates to the technical field of information visualization and visual analysis. The method comprises the steps of obtaining import commodity batch data from a warehouse logistics platform, wherein the import commodity batch data comprises detailed commodity batch data, warehouse-in data and warehouse-out data; performing data cleaning and data processing on the batch data of the imported commodities in sequence, and storing the data to a database; performing view design according to the batch data of the imported commodities subjected to data cleaning and data processing; and carrying out visual layout and implementation on view design results. According to the method, a complete analysis process of import commodities from entry, warehousing, delivery to supply and reception enterprises can be realized, the defect that an existing method focuses on local links is overcome, and the periodic operation condition of a specific warehouse can be comprehensively displayed.

Description

Technical Field

[0001] The present invention relates to the technical field of information visualization and visual analysis, and in particular to a visualization method for the operation of an import commodity supervision warehouse. Background Art

[0002] Compared with domestic goods, imported goods face stricter traceability management requirements to ensure that their sources and flows can be accurately tracked. Therefore, the supervision of imported goods needs to pay more attention to the detailed tracking and analysis of information such as import sources, warehouse operations, batch quantities, batch weights, etc. For imported goods, the supervision of warehouse operations is particularly critical.

[0003] Warehouse operation analysis often uses traditional data analysis methods to simply present existing data in numerical form. The rules and patterns hidden behind the data are often difficult to explore and cannot meet the actual needs of real-world scenarios. Visual analysis, as a science of analytical reasoning based on an interactive visualization interface, combines automated analysis technology with interactive visualization to effectively understand and reason on large and complex data sets.

[0004] At present, the existing visualization methods for warehouse operation analysis of imported goods usually involve logistics order analysis, warehouse operation and logistics monitoring in the process of warehouse operation, but usually only focus on a certain part of the warehouse logistics process, without covering the complete analysis process of warehouse operation, and ignoring the correlation between imported goods, storage warehouses, source provinces and cities, and supply and collection enterprises. At the same time, the view design is too simple, the interaction method is single, and it is difficult to fully present complex warehouse operation data, which is also a problem of existing visualization methods. In addition, the existing visualization methods lack the periodic analysis of warehouse operation and lack the ability to explore the periodic laws of warehouse operation. Summary of the invention

[0005] In order to solve the above technical problems existing in the prior art, the present invention provides a method for visualizing the operation status of an imported commodity supervision warehouse, which specifically includes the following steps:

[0006] Step S1: Obtaining imported commodity batch data from the warehousing and logistics platform, including detailed commodity batch data, warehouse entry data, and warehouse exit data;

[0007] Step S2: Clean and process the imported commodity batch data and store them in the database;

[0008] Step S3: Designing views based on the imported commodity batch data that has undergone data cleaning and data processing;

[0009] Step S4: Visualization layout and implementation of view design results.

[0010] Preferably, the detailed commodity batch data includes the commodity batch code, commodity name, commodity category, commodity country of origin, commodity entry port, commodity reporting province and city, commodity weight, commodity entry port province and city and entry date;

[0011] Warehouse entry data includes entry record code, commodity batch code, entry warehouse name, entry warehouse location, entry time, supplier company and the province and city where the supplier company is located;

[0012] Warehouse outbound data includes outbound record code, commodity batch code, inbound record code, outbound warehouse name, province and city where the outbound warehouse is located, outbound time, consignee company, and province and city where the consignee company is located.

[0013] Preferably, data cleaning includes:

[0014] The storage record creation time with a difference of no more than one minute replaces the storage time;

[0015] If there is no corresponding entry record for the outbound record, or the entry time is earlier than the entry time, or the outbound time is earlier than the entry time, the corresponding detailed commodity batch data, warehouse entry data and warehouse entry data will be cleared.

[0016] Preferably, the data processing includes:

[0017] Obtain the latitude and longitude coordinates of the corresponding locations according to the province and city where the warehouse is located and the port of entry is located;

[0018] For each warehouse, calculate the number of incoming batches, the number of outgoing batches, the weight of incoming goods, and the weight of outgoing goods every five minutes, and record the commodity batch codes of all incoming and outgoing goods during this period;

[0019] According to the commodity batch code, the detailed commodity batch data, warehouse entry data and warehouse exit data are integrated. For each batch of commodities, the entry residence time is calculated by the entry time and the entry time, and the entry residence time is calculated by the entry time and the exit time.

[0020] Preferably, the view design is specifically a warehouse operation analysis view design, including:

[0021] Two colors are used to encode outgoing and incoming batches respectively;

[0022] The bar graphs arranged in a ring shape along the inner and outer sides of the first loop line respectively represent the number of incoming batches and the number of outgoing batches every five minutes;

[0023] The average storage dwelling time of outgoing and incoming batches every five minutes is displayed through a line graph arranged along the second loop line;

[0024] Each of the N companies with the largest total batch number is represented by a circular glyph, and the total batch number is encoded with the radius of the circle; the total batch number includes the number of incoming batches and the number of outgoing batches, and the companies include the supplier companies and the consignee companies;

[0025] The outer circle of the circular glyph is divided according to the ratio of the number of incoming batches to the number of outgoing batches, and represented by different colors;

[0026] In the innermost circle of the circular glyphs corresponding to each enterprise, the average warehousing residence time is represented by a sector shape, and the ratio of the average warehousing residence time is encoded by the ratio of the arc angles; among them, the enterprise with the longest average warehousing residence time corresponds to a sector arc angle of 360°.

[0027] Furthermore, the view design also includes the interactive design of the warehouse operation analysis view, specifically:

[0028] Build a time selector and set up drag interaction in the time selector;

[0029] Build a control panel and set up click interactions on the control panel to view the corresponding imported commodity batch data during daily working hours and non-working hours;

[0030] For each circular glyph, set the click interaction:

[0031] Click to select, click again to cancel the selection, select at least one circular glyph at a time; not clicking means all are selected.

[0032] Preferably, step S4 specifically includes:

[0033] (1) Setting a control panel at the top of the warehouse operation analysis view; setting a bar chart, a time selector, a line chart and a circular glyph in the circular nested ring area in the middle of the warehouse operation analysis view from the outside to the inside;

[0034] (2) Time selector layout and implementation;

[0035] One rotation from the preset time direction represents twelve hours after the preset time. If the coordinates of the preset time are set to (0, 0), then

[0036]

[0037] In the formula, h represents hours, m represents minutes, (clockX h,m ,clockY h,m ) is the corresponding coordinate of the time interval [(h,m), (h,m+5)], baseRadius is the base radius of the line graph; where m=0,5,10,...,55;

[0038] (3) Calculation of histogram position;

[0039] Construct a linear scale cirBarScale(value) that maps the batch number to the bar chart height, replacing the base radius of the bar chart.

[0040] baseRadius(value)→baseRadius(value)+cirBarScale(value h,m );

[0041] or

[0042] baseRadius(value)→baseRadius(value)-cirBarScale(value h,m );

[0043] In the formula, “→” means replacement, value h,m is the number of outbound batches or inbound batches in the time interval [(h,m), (h,m+5)];

[0044] Based on the linear scale cirBarScale(value) and the base radius of the bar chart after replacement, calculate the coordinates of the far end of each bar chart;

[0045] (4) Calculation of line graph position;

[0046] Construct a linear scale cirLineScale(time) for the height of the inflection point in the average warehouse residence time mapping line graph, and replace the base radius of the line graph.

[0047] baseRadius(time)→baseRadius(time)+cirBarScale(time h,m );

[0048] In the formula, time h,m is the average storage time of the batch of goods in the time interval [(h,m), (h,m+5)]. Based on the linear scale cirLineScale(time) and the base radius of the replaced line graph, the coordinates of each line point are calculated.

[0049] (5) Layout and implementation of circular glyphs;

[0050] Circular glyph radius calculation:

[0051] glyphRadius=a×batchCount i +glyphRadius min ;

[0052]

[0053] In the formula, glyphRadius is the radius of the circular glyph, a is the calculation intermediate amount, i is the enterprise serial number, batchCount i is the total number of batches of the i-th enterprise, glyphRadius max 、glyphRadius min They are the maximum and minimum values ​​of the circular glyph radius respectively;

[0054] Outer ring ratio division:

[0055]

[0056] Where batchCount provider batchCount is the number of incoming batches for supplier companies only. consignee batchCount is the number of outbound batches for consignee companies only. both The number of incoming batches for both the supplier and consignee companies is converted to the sum of the number of outgoing batches; ω1 is batchCount provider The corresponding radian angle, ω2 is batchCount consignee The corresponding radian angle, ω3 is batchCount both The corresponding radian angle;

[0057] (6) Sector angle calculation;

[0058]

[0059] Where timeFanAngle is the angle of the fan, avgFreezerTime i represents the average storage residence time of the i-th enterprise;

[0060] (7) Circular font layout;

[0061] A force-directed layout is created between the circular glyphs corresponding to N enterprises according to the force simulation method, and the collision force between the circular glyphs is calculated according to the radius of the circular glyphs.

[0062] Preferably, the view design also includes warehouse space feature view design, specifically:

[0063] Each warehouse is coded by a hexagonal diagram, and the total weight, total number of batches, storage residence time, batch weight distribution and batch number distribution of the goods in the warehouse are coded by different colors, and seven sectors arranged in a circle from left to right represent Monday to Sunday;

[0064] The number of batches from Monday to Sunday is encoded by the height of the outermost sector of the hexagonal graph;

[0065] In each hexagonal diagram, the total weight and total number of batches of goods in the warehouse are represented by two second sectors in opposite directions;

[0066] The length of the rectangular diagram is used to encode the storage stay time;

[0067] The batch weight distribution of the goods is represented by a ring box plot, and the minimum value, lower quartile, median, upper quartile and maximum value of the batch weight are changed from left to right by the line segments of the ring box plot.

[0068] Furthermore, the view design also includes the interactive design of warehouse space feature views, specifically:

[0069] For each hexagon, set the click interaction:

[0070] Click on any hexagonal chart to display the import commodity batch data of the corresponding warehouse in the form of a bubble box;

[0071] Click to select, click again to cancel the selection, select at least one circular glyph at a time; not clicking means all are selected.

[0072] Preferably, step S4 specifically includes: (1) calculating the outer diameter of the sector;

[0073] weekRadius outer =b×batchPerDay+globalRadius×weekRadio inner ;

[0074]

[0075] Where weekRadius outer is the outer diameter of the fan segment, b is the intermediate calculation amount, batchPerDay is the number of batches per day, weekRadio inner is the ratio of the inner diameter of the sector to the radius of the hexagonal graph, weekRadio outer is the ratio of the maximum outer diameter of the fan segment to the radius of the hexagonal graph, k is the week number, batchPerDay k is the number of batches on the kth day of the week;

[0076] (2) Calculation of the second sector radius;

[0077]

[0078] Where fanRadius is the radius of the second fan, globalRadius is the radius of the hexagonal graph, fanRatio is the ratio of the radius of the second fan to the radius of the hexagonal graph, totalValue is the total number of batches or total weight, and batchValue is the current number of batches or weight;

[0079] (3) Calculation of rectangular diagram length;

[0080]

[0081] Where timeRectLength is the length of the rectangular graph, max(Length) is the maximum length of the rectangular graph, j is the warehouse number, and avgFreezerTime is j is the average storage residence time of the jth warehouse, and M is the number of warehouses;

[0082] (4) Calculation of the position of the ring box plot;

[0083] Get the weight distribution information of each batch of goods, including the lower quartile, median, upper quartile, minimum and maximum values;

[0084]

[0085] Where posAngle is the clockwise offset angle of the annular box diagram relative to the starting angle, boxGlobalAngle is the maximum angle of the annular box diagram, weightMax j is the maximum weight of the goods in the jth warehouse, and boxValue is the statistical value of the batch weight distribution;

[0086] (5) Layout and implementation of hexagonal graphs;

[0087]

[0088] In the formula, (hexCenterX l,e , hexCenterY l,e ) is the center coordinate of the hexagonal graph in the lth row and the eth column, (view left ,view top ) is the starting point coordinate of the warehouse space feature view, hexRadius is the radius of the hexagonal graph;

[0089] After determining the center coordinates of each hexagon, draw the warehouse space feature view.

[0090] The technical solution provided by the present invention is aimed at imported goods. The warehouse operation analysis process is incomplete, the view design elements are simple, and it is difficult to present the rich warehouse operation data characteristics. Through the visualization of periodic and comprehensive data, the complete analysis process of imported goods from entry, warehousing, and delivery to supply and collection enterprises can be realized, which makes up for the defects of existing methods focusing on local links and can comprehensively display the periodic operation status of specific warehouses. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 It is a schematic diagram of the overall process framework visualized in the present invention.

[0092] Figure 2 It is a schematic diagram of the visual encoding and visualization layout of the warehouse space feature view in the present invention.

[0093] Figure 3 It is a schematic diagram of the visual coding and visualization layout of the warehouse operation analysis view in the present invention.

[0094] Figure 4 Schematic diagram of the interaction mode of the warehouse operation analysis view in the present invention; wherein (a) is a prompt interaction diagram, and (b) is a click interaction diagram.

[0095] Figure 5 It is a schematic diagram of warehouse statistics glyphs of the warehouse space feature view in the present invention.

[0096] Figure 6 It is a schematic diagram of the implementation effect and overall layout of the present invention. DETAILED DESCRIPTION

[0097] Hereinafter, the technical solution provided by the present invention will be further elaborated in detail with reference to the accompanying drawings.

[0098] The present invention realizes a warehouse operation status visualization method for import commodity supervision through information visualization and visual analysis methods, combined with multi-view linkage methods and rich interactive means. Figure 1 As shown, it specifically includes: data acquisition and cleaning, data processing and storage, visualization view design, visualization layout and implementation. The specific technical solution is as follows:

[0099] Step 1: Data acquisition and cleaning

[0100] Data acquisition:

[0101] The present invention obtains the imported goods batch data from the warehousing and logistics platform, which contains three csv files, namely detailed goods batch data, warehouse entry data and warehouse outbound data. Among them, the detailed goods batch data include: goods batch code, goods name, goods category, goods country of origin, goods entry port, goods reporting province and city, goods weight, goods entry port province and city (i.e. source province and city), entry date; warehouse entry data include: entry record code, goods batch code, entry warehouse name, entry warehouse location, entry time, supplier enterprise, supplier enterprise province and city; warehouse outbound data include: outbound record code, goods batch code, corresponding entry record code, outbound warehouse name, outbound warehouse province and city, outbound time, consignee enterprise, consignee enterprise province and city.

[0102] Data cleaning:

[0103] The present invention performs preprocessing operations of data cleaning and completion based on the above database tables. When performing joint table matching on the warehouse inbound data table and the warehouse outbound data table, there are a small number of outbound records that do not match the corresponding inbound records. Such outbound records need to be cleaned, and their corresponding detailed commodity batch data also need to be included in the cleaning process. At the same time, there are logical problems in the time series fields such as "entry date", "entry time" and "outbound time" in some records. For example, the entry time of some commodity batches is later than the outbound time, which violates the actual execution order. Such data will have a negative impact on subsequent analysis and therefore need to be cleaned. In the detailed commodity batch data table, about 2% of the records have errors or omissions in the "commodity category" field. For these records, a large language model is used to perform semantic recognition on the "commodity name" field and classify it into the existing commodity category. In addition, about 5% of the records in the warehouse inbound data table are missing in the "entry time" field, which will affect the subsequent calculation of the "entry stay time" and "entry stay time" fields. The present invention uses a "warehouse entry record creation time" with a difference of no more than one minute as a substitute. This time point represents the time when the recorder starts to enter the warehouse entry record and is automatically generated by the warehousing logistics system.

[0104] Step 2: Data processing and storage

[0105] Data processing:

[0106] In order to better analyze the overview of warehouse space characteristics, the present invention processes each commodity batch record, and converts the latitude and longitude coordinate fields of the corresponding location according to the fields of "warehouse location" and "province and city where the entry port is located" to facilitate the implementation of spatial mapping in the subsequent visualization view. At the same time, for each value of the "warehouse name" and "province and city where the entry port is located" fields, the relevant data characteristics are calculated. For each warehouse, the present invention calculates the "number of inbound events", "number of outbound events", "inbound commodity weight" and "outbound commodity weight" fields every five minutes, and records the codes of all commodity batches that perform inbound and outbound operations during this time period. The fields in the three data tables are integrated according to the "commodity batch code" field, and the "entry time" and "entry time" fields are used to calculate the "entry stay time" field of each commodity batch record, and the "entry time" and "outbound time" are used to calculate its "entry stay time" field.

[0107] Data Storage:

[0108] The fields included in the processed detailed commodity batch data table are commodity batch code, commodity name, commodity category, commodity country of origin, commodity entry port, commodity reporting province and city, commodity weight, province and city where the commodity entry port is located (i.e. source province and city), and entry date; the warehouse entry data includes: entry record code, commodity batch code, entry warehouse name, entry warehouse location, entry time, supplier enterprise, province and city where the supplier enterprise is located, number of entry events within five minutes, number of entry commodity batches within five minutes, entry stay time, and entry stay time; the warehouse outbound data includes: outbound record code, commodity batch code, corresponding entry record code, outbound warehouse name, province and city where the outbound warehouse is located, outbound time, consignee enterprise, province and city where the consignee enterprise is located, number of outbound events within five minutes, and number of outbound commodity batches within five minutes.

[0109] Step 3: View Design

[0110] Warehouse space feature view design: Figure 2 As shown, the present invention provides an overview view of the characteristics of commodity batches in different warehouses. The method maps the province and city of origin fields of the imported commodity batch data into regular hexagons of different sizes and colors, and calculates the data characteristics and distribution based on each hexagon. It uses visualization techniques such as hexagonal mapping that keeps the relative position unchanged and custom nested glyphs to present the characteristics of commodity batches in different warehouses. At the same time, the method supports an overview of the data characteristics of different warehouses and source provinces and cities. Warehouse supervisors can quickly locate warehouses and source provinces and cities of interest, and can conduct further analysis through interactive operations.

[0111] (1) Visual encoding

[0112] Color: The present invention selects blue, cyan, and purple as the basic color system. In order to maintain the consistency of visual effects, each warehouse is coded with the same light blue hexagon. Customized glyphs that characterize the characteristics of warehouse commodity batches are embedded in each hexagon. Gray-blue and gray-green are selected in the glyphs to encode the total weight of the goods and the total batch of goods respectively; blue with different saturations is selected to encode the storage residence time and batch weight distribution; purple is selected to encode the distribution of the number of commodity batches.

[0113] Area: The present invention uses an upward gray-blue sector to represent the total weight of the current warehouse, and a downward gray-green sector to represent the total number of batches in the current warehouse. The area of ​​the sector encodes the total weight or total number of batches of the goods. The larger the area of ​​the sector, the larger the total weight or total number of batches of the goods in the current warehouse.

[0114] Length: The present invention uses the length of a light blue horizontal rectangle to encode the average storage residence time of the current warehouse goods. The longer the rectangle length is, the longer the average storage residence time of the current warehouse goods is.

[0115] Height: The present invention uses 7 sector segments to represent Monday to Sunday from left to right. The sector height encodes the number of commodity batches in the current warehouse from Monday to Sunday. The larger the height, the more commodity batches in the current warehouse.

[0116] Position: The present invention uses a circular box plot to represent the weight statistical distribution of the commodity batches in the current warehouse. The position of the box encodes the weight distribution of the commodity. The position of the box plot line segments from left to right encodes the minimum value, lower quartile, median, upper quartile and maximum value respectively.

[0117] (2) Interaction Design

[0118] Tips: Tip interaction can display data details in the form of a transparent bubble prompt box when the mouse hovers over a specific visual element. If warehouse supervisors have difficulty observing the glyphs in the warehouse hexagon and the source province and city hexagon, or want to know the specific values ​​of the warehouse statistics glyph view, they can use the tip interaction to hover the mouse over the warehouse statistics glyph, warehouse hexagon or source province and city hexagon to view the data details for accurate comparison and analysis.

[0119] Selection of multi-view linkage: Selection interaction can help warehouse supervisors select warehouses of interest for further analysis. When a warehouse supervisor clicks on a warehouse hexagon or a source province hexagon, the border of the hexagon will turn dark blue to indicate selection, and clicking again will cancel the selection. When a warehouse supervisor selects a hexagon, the warehouse operation analysis view will be redrawn based on the commodity batch data belonging to the warehouse or the source province. It is allowed to select multiple warehouses at the same time, and not selecting is equivalent to selecting all. In addition, warehouse supervisors can directly select all warehouses belonging to a city or all source provinces and cities belonging to a province, municipality or autonomous region by clicking on the connecting edges between the hexagons.

[0120] Warehouse operation analysis view: Figure 3 As shown in the figure, the warehouse operation analysis view provides detailed operation status of commodities in each warehouse and the associated suppliers and recipients. This view adopts a warehouse operation analysis visualization method based on the clock metaphor, which divides the commodity in-and-out data and its in-and-out residence time into five-minute time periods according to their in-and-out time, and displays them in the form of clock metaphor visualization. At the same time, this method uses custom glyphs to visualize the associated enterprises of the in-and-out data of imported commodities, so that warehouse supervisors can find enterprises of interest and conduct further analysis by selecting operations.

[0121] Visual Encoding

[0122] Color: Green and blue are used as the basic colors. Green encodes outbound events, and blue encodes inbound events. To facilitate the association between views, the color coding is consistent.

[0123] Height: The present invention represents the number of outbound batches and incoming batches within every five minutes with circularly arranged columns. The height of the column at the radially corresponding position of each five-minute time interval encodes the number of outbound batches or incoming batches within the time interval. The greater the height, the more batches of imported goods there are in the time interval; the average inbound residence time of the outbound batches and incoming batches within every five minutes is displayed using a broken line view. The height of the broken line point at the radially corresponding position of each five-minute time interval encodes the average inbound residence time of the outbound batches or incoming batches within the time interval through a logarithmic scale.

[0124] Font: In order to help warehouse supervisors screen and analyze the distribution of supply and receipt companies of commodity batches within the time interval of interest, the present invention provides a circular font of the Top N supply and receipt companies. The radius of the circular font maps the number of times the company serves as a supplier and consignee of a batch of imported goods. The larger the radius, the more times. The angle range occupied by the two-color rings on the outer circle of the font encodes the proportion of the company as a supplier or consignee. The angle occupied by a gray arc drawn clockwise and counterclockwise from the twelve o'clock direction encodes the proportion of the company as both a supplier and a consignee of a batch of imported goods. The larger the angle occupied, the greater the proportion. In particular, the maximum of the above two angle ranges is 360 degrees, indicating a 100% share. The angle occupied by the innermost blue sector of the font encodes the average warehousing residence time of the batch of the company as a supply and receipt company. The larger the angle occupied, the greater the average warehousing residence time. Among them, the maximum angle of 360 degrees (i.e., a complete circle) represents the maximum average warehousing residence time among the Top N companies.

[0125] Interaction Design

[0126] hint: Figure 4 As shown in (a), in order to accurately know the original data value, the present invention adds prompt interaction. If the warehouse supervisor wants to know the specific values ​​of the number of outbound batches, the number of inbound batches, the average inbound residence time of outbound batches and the average inbound residence time of inbound batches within a certain time interval, or wants to know the number of times a certain enterprise serves as a consignee and the specific values ​​of the average inbound residence time of the corresponding batches, then the prompt interaction can be used to hover the mouse over the outer area or the enterprise font to view the data details.

[0127] Drag: To facilitate warehouse supervisors to filter and analyze the supply and receiving companies of imported commodity batches within a specific time period, this article adds drag interaction on the clock scale and time selector. Warehouse supervisors can drag the dark blue rectangles at both ends of the time selector, and the supply and receiving company glyphs will be redrawn with the commodity batch data within the specified time period to view the imported commodity batch data within the specified time period every day.

[0128] Control panel interaction: The present invention divides the twenty-four hours of a day into two parts at 7 o'clock and 19 o'clock, of which 7 o'clock to 19 o'clock is recorded as "Day", indicating daytime, and the other part is recorded as "Night", indicating nighttime. Among them, the time interval of "Day" roughly corresponds to the working hours of the warehouse. When the warehouse supervisor clicks "Day" or "Night", all views of the warehouse operation analysis visualization method will be redrawn using the commodity batch data in the corresponding time interval. Among them, the time period division can be carried out according to the specific needs of the display.

[0129] Selection of multi-view linkage: Figure 4 As shown in (b), you can click on the supply and collection enterprise glyph to select it. The border of the glyph will turn dark blue to indicate selection. Click again to cancel the selection. When a supply and collection enterprise glyph is selected, the warehouse space feature view will be redrawn according to the commodity batch data of the supplier or consignee for the enterprise. In addition, the selection interaction allows multiple selections at the same time, and not selecting is equivalent to selecting all.

[0130] Step 4: Visualization layout and implementation

[0131] Visual layout and implementation of warehouse space feature views:

[0132] The warehouse space feature view mainly consists of three parts: the warehouse statistics glyph view used to display the data features of the warehouse and some numerical mapping legends; the warehouse hexagonal view used to display the data features of each warehouse and compare them; and the source province and city hexagonal view used to display the data features of each source province and city and compare them.

[0133] (1) Warehouse statistics font layout and implementation

[0134] like Figure 5 As shown, the warehouse statistics glyph layout involves the calculation of the radius of the fan chart, the length of the rectangular chart, the position of the box chart, and the outer diameter of the batch number distribution chart.

[0135] Calculation of the fan radius: The area of ​​the innermost fan of the glyph encodes the number or weight of the product batch, batchValue. Then, the calculation formula for the fan radius fanRadius is:

[0136]

[0137] Where: totalValue represents the total quantity or total weight of the product batch; globalRadius represents the radius of the entire font; fanRatio represents the ratio of the maximum radius of the fan to the radius of the entire font.

[0138] Rectangle length calculation: The length of the rectangle at the bottom of the glyph timeRectLength encodes the average storage time avgFreezerTime of the commodity batch. The specific calculation formula is:

[0139]

[0140] Where: maxLength represents the maximum length of the rectangle; avgFreezerTime i It represents the average storage time of commodity batches in each warehouse; n represents the number of warehouses.

[0141] Box plot position calculation: Before drawing the circular box plot, it is necessary to obtain the weight distribution information of each batch of goods, including the lower quartile Q1, median Median, upper quartile Q3, minimum value Min and maximum value Max of the batch weight distribution. Then use the angle mapping scale to obtain the clockwise offset angle posAngle of each statistical value boxValue in the circular box plot relative to the starting angle. The specific calculation formula is:

[0142]

[0143] Where: boxGlobalAngle represents the maximum angle occupied by the ring box diagram; weightMax i Represents the maximum value of the weight of each batch of goods in each warehouse within the valid range; n represents the number of warehouses.

[0144] Distribution map outer diameter calculation: The height of the sector of the outermost circle of the glyph is the number of batches from Monday to Sunday, batchPerDay, then the sector outer diameter weekRadius outer The calculation formula is:

[0145] weekRadius outer =b×batchPerDay+globalRadius×weekRadio inner ;

[0146]

[0147] Where b is the intermediate calculation amount, weekRadio outer Represents the ratio of the maximum outer diameter of the distribution graph to the entire glyph radius; weekRadio inner Represents the ratio of the inner diameter of the distribution map to the radius of the entire glyph; batchPerDay i Represents the distribution of product batches from Monday to Sunday.

[0148] (2) Hexagonal layout and implementation

[0149] Hexagon location calculation: The location calculation method of the warehouse hexagon is similar to that of the source province and city hexagon, except that the starting point coordinates (view left ,view top ) is different from the hexagon radius hexRadius. The center coordinates (hexCenterX i,j ,hexCenterY i,j ) is calculated as:

[0150]

[0151] Wherein: k represents an integer, 2k+1 is an odd number, and 2k is an even number.

[0152] After confirming the center coordinates of each hexagon, generate and draw the hexagonal path data with the center coordinates as the center point. Then draw the warehouse statistics glyph with these coordinates as the center point. It is worth noting that the fan-shaped graphs of the glyphs inside the two hexagons have a minimum area. At the same time, the rectangular graph length of the glyphs inside the source province and city hexagons encodes the average entry stay time and has no distribution map, so it is necessary to make slight adjustments based on the above glyph implementation.

[0153] Visual layout and implementation of warehouse operation analysis view

[0154] The layout of the warehouse operation analysis view mainly consists of five parts: a bar view of inbound and outbound events for displaying the distribution of goods inbound and outbound events over 24 hours a day; a clock scale and time selector for obtaining time information and filtering time intervals; a line view for displaying the average inbound residence time in each time period; a glyph group view of the supply and receipt enterprises of the associated enterprises of the filtered commodity batches; and a control panel for controlling whether to display data during the daytime working period or the night non-working period.

[0155] The layout is mainly divided into two areas, the top area and the middle nested ring area. The top area is the control panel. The middle nested ring area can be divided into four layers, from the outside of the ring to the center of the circle, they are recorded as the first layer, the second layer, the third layer and the fourth layer. The first layer area is the columnar view of in-and-out warehouse events, which has two circles of columns arranged in a ring. The second layer area is the clock scale and time selector, which simulates the clock layout and adds time labels, and draws a fan-shaped time selector with seven o'clock as the starting and end points. The third layer area is the average warehouse residence time line view, which has two color-filled radial line charts. The fourth layer area is the supply and collection enterprise glyph group view, which uses the force-guided algorithm to layout multiple circular custom glyphs representing supply and collection enterprises.

[0156] (1) Clock Metaphor Layout and Implementation

[0157] Clock position calculation: Starting from 7 o'clock, one circle is rotated clockwise, which represents the time range from 7 o'clock to 19 o'clock or 19 o'clock to 7 o'clock. Define the center of the clock as the coordinate (0,0), which represents the time interval from m minutes to m+5 minutes (m is a multiple of 5) at h o'clock. h,m ,clockY h,m )for:

[0158]

[0159] Where baseRadius represents the base radius, where the base radius of the annular bar chart and the annular line chart are different.

[0160] Calculation of the position of the circular bar chart: Construct a linear scale cirBarScale(value) that maps the batch number to the bar height, and then replace baseRadius with

[0161] baseRadius+cirBarScale(value h,m );

[0162] or

[0163] baseRadius-cirBarScale(value h,m );

[0164] Among them, value h,m The number of outbound batches or inbound batches from h:m:00 to h:m+5:00 can be used to obtain the top coordinates of each outbound column and the bottom coordinates of each inbound column, thereby completing the drawing of the circular bar chart.

[0165] Calculation of the position of the circular line graph: Construct a linear scale cirLineScale(time) that maps the height of the line points to the average storage residence time, and then replace the baseRadius in the formula for calculating the clock position with baseRadius+cirLineScale(time h,m ), where time h,m The average storage residence time of the commodity batches from h:m:00 to h:m+5:00 is the average storage residence time of the commodity batches from h:m:00 to h:m+5:00. The coordinates of each broken line point can be obtained, thereby completing the drawing of the circular broken line graph.

[0166] (2) Enterprise font layout and implementation

[0167] Glyph radius calculation: The glyph radius glyphRadius encodes the number of product batches of the enterprise batchCount. The specific calculation formula is:

[0168] glyphRadius=A×batchCount+glyphRadius min ;

[0169]

[0170] Where: glyphRadius max Indicates the maximum value of the enterprise glyph radius, in order to prevent glyph drawing overflow; glyphRadius min Indicates the minimum radius of the corporate font to ensure visual effects; batchCount iIndicates the number of product batches of each enterprise (among the TopN enterprises).

[0171] Calculation of supply-receipt ratio: First, count the batch count of the company as a supplier. provider , as the batch number batchCount of the consignee consignee , batchCount as both supplier and consignee both ;

[0172] Next, we use 2π×batchCount provider / batchCount gets the angle range of the blue supplier ring;

[0173] By 2π×batchCount consignee / batchCount gets the angle range of the green consignee ring;

[0174] By 2π×batchCount both / batchCount obtains the angle range of the gray self-supplying and self-retracting arc for subsequent drawing.

[0175] Fan angle calculation: The angle of the fan at the innermost part of the glyph, timeFanAngle, encodes the average storage residence time avgFreezerTime of the enterprise batch. The specific calculation formula is:

[0176]

[0177] Where: avgFreezerTime i It indicates the average storage residence time of product batches of each enterprise (among the Top N enterprises).

[0178] Enterprise glyph layout: Use forceSimulation method to create force-directed layout between top N enterprise glyphs. The collision force (i.e. repulsion) between glyphs is determined by their radius glyphRadius (i.e. batch number). Then, according to the calculation results of force-directed layout, draw the supply and collection enterprise glyph groups.

[0179] After completing the visualization layout and implementation of the above two views, the implementation effect and overall layout of the present invention are as follows: Figure 6 shown.

[0180] It should be noted that, in the above content, all the parts involving color construction, the colors used are all optional solutions. In other words, any replacement or change of color is an optional solution of the present invention.

[0181] The present invention makes up for the shortcomings of the existing methods for imported goods, such as incomplete warehouse operation analysis process, simple view design elements, and difficulty in presenting rich warehouse operation data features. The present invention proposes a warehouse operation visualization method for imported goods, designs a warehouse space feature view, provides an overview of the spatial features of the commodity warehouse and the source province and city, uses hexagonal design to encode the commodity warehouse or the source province and city, embeds custom feature fonts in the hexagon, and uses a variety of visual elements such as fan charts, rectangular charts, and box charts to encode and present warehouse commodity features. Design a warehouse operation analysis view to provide specific warehouse operation information under each warehouse. Based on the clock metaphor, the warehouse operation status within a day is visualized, and the number of commodity batches and the in-and-out storage stay time are respectively encoded using annular bar charts and annular line charts to present their relationship over time. The method supports interactive modes such as prompts, selections, and dragging to achieve linkage between multiple views and assist warehouse supervisors in completing the analysis process. The interactive linkage of the two views can realize the complete analysis process of imported goods from entry, storage, out-of-stock to supply and collection enterprises, making up for the defect that the existing methods focus on local links.

[0182] The present invention makes up for the shortcomings of existing methods in mining the analysis of periodic warehouse operation rules. For each warehouse, the present invention uses one day as the analysis period and divides the time range according to the working hours, allowing analysts to drag the time axis to select time periods, showing the distribution of the number of inbound and outbound events in each time period and the average inbound residence time statistics, which can comprehensively display and analyze the periodic warehouse operation of specific warehouses.

[0183] To summarize, in short, the technical solution provided by the present invention is aimed at imported goods, but the warehouse operation analysis process is incomplete, the view design elements are simple, and it is difficult to present the rich warehouse operation data characteristics; through the visualization of periodic and comprehensive data, a complete analysis process of imported goods from entry, warehousing, and delivery to supply and collection enterprises is realized, which makes up for the defect of existing methods focusing on local links, and can comprehensively display the periodic operation of specific warehouses.

Claims

1. A method for visualizing the operation of an import commodity supervision warehouse, characterized in that: The following steps are involved: Step S1: Obtaining imported commodity batch data from the warehousing and logistics platform, including detailed commodity batch data, warehouse entry data, and warehouse exit data; Step S2: Clean and process the imported commodity batch data and store them in a database; Step S3: Designing views based on the imported commodity batch data that has undergone data cleaning and data processing; Step S4: Visualization layout and implementation of view design results.

2. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 1, characterized in that: The detailed commodity batch data includes the commodity batch code, commodity name, commodity category, commodity country of origin, commodity entry port, commodity reporting province and city, commodity weight, commodity entry port province and city and entry date; The warehouse entry data includes the entry record code, commodity batch code, entry warehouse name, entry warehouse location, entry time, supplier company and the province and city where the supplier company is located; The warehouse outbound data includes the outbound record code, commodity batch code, incoming record code, outbound warehouse name, the province and city where the outbound warehouse is located, outbound time, consignee company, and the province and city where the consignee company is located.

3. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 2, characterized in that: The data cleaning includes: The storage record creation time with a difference of no more than one minute replaces the storage time; If there is no corresponding entry record for the outbound record, or the entry time is earlier than the entry time, or the outbound time is earlier than the entry time, the corresponding detailed commodity batch data, warehouse entry data and warehouse entry data will be cleared.

4. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 2, characterized in that: The data processing includes: Obtain the latitude and longitude coordinates of the corresponding locations according to the province and city where the warehouse is located and the port of entry is located; For each warehouse, calculate the number of incoming batches, the number of outgoing batches, the weight of incoming goods, and the weight of outgoing goods every five minutes, and record the commodity batch codes of all incoming and outgoing goods during this period; According to the commodity batch code, the detailed commodity batch data, warehouse entry data and warehouse exit data are integrated. For each batch of commodities, the entry residence time is calculated by the entry time and the entry time, and the entry residence time is calculated by the entry time and the exit time.

5. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 2, characterized in that: The view design is specifically a warehouse operation analysis view design, including: Two colors are used to encode outgoing and incoming batches respectively; The bar graphs arranged in a ring shape along the inner and outer sides of the first loop line respectively represent the number of incoming batches and the number of outgoing batches every five minutes; The average storage dwelling time of outgoing and incoming batches every five minutes is displayed through a line graph arranged along the second loop line; Each of the top N companies with the largest total batch number is represented by a circular glyph, and the total batch number is encoded with the radius of the circle; the total batch number includes the number of incoming batches and the number of outgoing batches, and the companies include supplier companies and consignee companies; The outer circle of the circular glyph is divided according to the ratio of the number of incoming batches to the number of outgoing batches, and represented by different colors; In the innermost circle of the circular glyphs corresponding to each enterprise, the average warehousing residence time is represented by a sector shape, and the ratio of the average warehousing residence time is encoded by the ratio of the arc angles; among them, the enterprise with the longest average warehousing residence time corresponds to a sector arc angle of 360°.

6. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 5, characterized in that: It also includes the interactive design of the warehouse operation analysis view, specifically: Build a time selector and set up drag interaction in the time selector; Build a control panel and set up click interactions on the control panel to view the corresponding imported commodity batch data during daily working hours and non-working hours; For each circular glyph, set the click interaction: Click to select, click again to cancel the selection, select at least one circular glyph at a time; not clicking means all are selected.

7. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 6, characterized in that: Step S4 specifically includes: (1) Setting a control panel at the top of the warehouse operation analysis view; setting a bar chart, a time selector, a line chart and a circular glyph in the circular nested ring area in the middle of the warehouse operation analysis view from the outside to the inside; (2) Layout and implementation of the time selector; One rotation from the preset time direction represents twelve hours after the preset time. If the coordinates of the preset time are set to (0, 0), then In the formula, h represents hours, m represents minutes, (clockX h,m ,clockY h,m ) is the corresponding coordinate of the time interval [(h,m), (h,m+5)], baseRadius is the base radius of the line graph; where m=0,5,10,55; (3) Calculation of histogram position; Construct a linear scale cirBarScale(value) that maps the batch number to the bar chart height, replacing the base radius of the bar chart. baseRadius(value)→baseRadius(value)+cirBarScale(value h,m ); or baseRadius(value)→baseRadius(value)-cirBarScale(value h,m ); In the formula, "→" means replacement, value h,m is the number of outbound batches or inbound batches in the time interval [(h,m), (h,m+5)]; Based on the linear scale cirBarScale(value) and the base radius of the bar chart after replacement, calculate the coordinates of the far end of each bar chart; (4) Line graph position calculation; Construct a linear scale cirLineScale(time) for the height of the inflection point in the average warehouse residence time mapping line graph, and replace the base radius of the line graph. baseRadius(time)→baseRadius(time)+cirBarScale(time h,m ); In the formula, time h,m is the average storage time of the batch of goods in the time interval [(h,m), (h,m+5)]. Based on the linear scale cirLineScale(time) and the base radius of the replaced line graph, the coordinates of each line point are calculated. (5) Layout and implementation of circular glyphs; Circular glyph radius calculation: glyphRadius=a×batchCount i +glyphRadius min ; In the formula, glyphRadius is the radius of the circular glyph, a is the calculation intermediate quantity, i is the enterprise serial number, batchCount i is the total number of batches of the i-th enterprise, glyphRadius max 、glyphRadius min They are the maximum and minimum values ​​of the circular glyph radius respectively; Outer ring ratio division: Where batchCount provider batchCount is the number of incoming batches for supplier companies only. consignee batchCount is the number of outbound batches for the consignee company only. both The number of incoming batches for both the supplier and consignee companies is converted to the sum of the number of outgoing batches; ω1 is batchCount provider The corresponding radian angle, ω2 is batchCount consignee The corresponding radian angle, ω3 is batchCount both The corresponding radian angle; (6) Sector angle calculation; Where timeFanAngle is the angle of the fan, avgFreezerTime i represents the average storage residence time of the i-th enterprise; (7) Circular font layout; A force-directed layout is created between the circular glyphs corresponding to N enterprises according to the force simulation method, and the collision force between the circular glyphs is calculated according to the radius of the circular glyphs.

8. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 2, characterized in that: The view design also includes warehouse space feature view design, specifically: Each warehouse is coded by a hexagonal diagram, and the total weight, total number of batches, storage residence time, batch weight distribution and batch number distribution of the goods in the warehouse are coded by different colors, and seven sectors arranged in a circle from left to right represent Monday to Sunday; The number of batches from Monday to Sunday is encoded by the height of the outermost sector of the hexagonal graph; In each hexagonal diagram, the total weight and total number of batches of goods in the warehouse are represented by two second sectors in opposite directions; The length of the rectangular diagram is used to encode the storage stay time; The batch weight distribution of the goods is represented by a ring box plot, and the minimum value, lower quartile, median, upper quartile and maximum value of the batch weight are changed from left to right by the line segments of the ring box plot.

9. A method for visualizing the operation of an import commodity supervision warehouse as claimed in claim 8, characterized in that: It also includes the interactive design of warehouse space feature views, specifically: For each hexagon, set up click interaction: Click on any hexagonal chart to display the import commodity batch data of the corresponding warehouse in the form of a bubble box; Click to select, click again to cancel the selection, select at least one circular glyph at a time; not clicking means all are selected.

10. A method for visualizing the operation of an import commodity supervision warehouse according to claim 8, characterized in that: Step S4 specifically includes: (1) Calculation of the outer diameter of the fan segment; weekRadius outer =b×batchPerDay+globalRadius×weekRadio inner ; Where weekRadius outer is the outer diameter of the fan segment, b is the intermediate calculation amount, batchPerDay is the number of batches per day, weekRadio inner is the ratio of the inner diameter of the sector to the radius of the hexagonal graph, weekRadio outer is the ratio of the maximum outer diameter of the fan segment to the radius of the hexagonal graph, k is the week number, batchPerDay k is the number of batches on the kth day of the week; (2) Calculation of the second sector radius; Where fanRadius is the radius of the second fan, globalRadius is the radius of the hexagonal graph, fanRatio is the ratio of the radius of the second fan to the radius of the hexagonal graph, totalValue is the total number of batches or total weight, and batchValue is the current number of batches or weight; (3) Calculation of rectangular diagram length; 0≤j≤M Where timeRectLength is the length of the rectangular graph, max(Length) is the maximum length of the rectangular graph, j is the warehouse number, and avgFreezerTime is j is the average storage residence time of the jth warehouse, and M is the number of warehouses; (4) Calculation of the position of the ring box plot; Get the weight distribution information of each batch of goods, including the lower quartile, median, upper quartile, minimum and maximum values; Where posAngle is the clockwise offset angle of the annular box diagram relative to the starting angle, boxGlobalAngle is the maximum angle of the annular box diagram, weightMax j is the maximum weight of the goods in the jth warehouse, and boxValue is the statistical value of the batch weight distribution; (5) Hexagonal graph layout and implementation; In the formula, (hexCenterX l,e , hexCenterY l,e ) is the center coordinate of the hexagonal graph in the lth row and the eth column, view left ,view top ) is the starting point coordinate of the warehouse space feature view, hexRadius is the radius of the hexagonal graph; After determining the center coordinates of each hexagon, draw the warehouse space feature view.

Images