Disclosure of Invention
In order to solve the problems of the scheme, the invention provides a material data management method and a material data management system for lithium battery diaphragm production.
The aim of the invention can be achieved by the following technical scheme:
A material data management method for lithium battery separator production, the method comprising:
step one, staff records data of all materials according to a preset material data input mode, and uploads the recorded material data;
further, the preset material input mode comprises:
establishing a recording end, and setting a recording template in the recording end, wherein the recording template comprises recording item grids and recording item statistics grids corresponding to the recording item grids;
And the staff records the material data through the recording template in the recording end, clicks the submitting button and submits the recorded material data.
Step two, building a storage model, identifying material data uploaded by each employee, and dynamically updating the storage model according to each material data, wherein the storage model comprises a material classification area and a material unit area corresponding to each material type;
further, the method for dynamically updating the warehouse model according to the material data comprises the following steps:
setting corresponding material attribute points according to the material data, and identifying storage positions and material types corresponding to the material attribute points;
The method comprises the steps of matching corresponding marking colors according to material types, identifying corresponding marking data in a storage model according to storage positions, wherein the marking data are material data corresponding to original material attribute points when corresponding storage positions in the storage model are not updated, adjusting the material data corresponding to the material attribute points according to the marking data to obtain new material data, adjusting the storage model according to the marking colors, the storage positions and the material attribute points, and recording corresponding adjustment records;
and identifying all material attribute points in the storage model in real time, and carrying out region merging according to all material attribute points to obtain all material classification areas and all material unit areas corresponding to all material classification areas.
Further, the method for carrying out region merging according to each material attribute point comprises the following steps:
Step SA1, setting each node area according to each material attribute point;
Step SA2, setting an initial area according to each node area;
step SA3, determining a region to be selected according to the initial region, carrying out combination evaluation on the initial region and the region to be selected, and judging whether the combination requirement is met or not;
when the combination requirement is judged to be met, combining the initial area with the area to be selected to obtain a new initial area;
When the combination requirement is judged not to be met, the combination is not carried out;
Step SA4, circulating the step SA3 until no area to be selected meeting the combination requirement exists, and marking the current initial area as a material unit area;
Step SA5, circulating the steps SA2 to SA4 until no initial area exists, and obtaining each material unit area;
And identifying the material types corresponding to each material unit area, and merging each material unit area according to each material type to obtain each material classification area.
Further, the method for carrying out the combined evaluation on the initial area and the area to be selected comprises the following steps:
Identifying the material types respectively corresponding to the initial area and the area to be selected;
when the material types are different, judging that the combination requirement is not met;
When the types of the materials are the same, identifying production time and warehousing time corresponding to the initial area and the area to be selected respectively, substituting the obtained production time and warehousing time into a preset classification value function, and obtaining an initial classification value and a classification value to be selected corresponding to the initial area and the area to be selected respectively;
the initial classification value is labeled CZi, where i=1, 2, &..once again, n is a positive integer; marking the classification value to be selected as DZ;
Calculating a corresponding combined value according to the formula HZ=max { CZi-DZ| }, wherein HZ is the combined value;
And when the merging value is larger than the threshold value X1, judging that the merging requirement is not met, and otherwise, judging that the merging requirement is met.
Step three, data arrangement is carried out on each material type according to a storage model, material summarized data corresponding to each material type are obtained, and the material summarized data comprise each unit value and classification values, wherein the unit values are the material quantity corresponding to corresponding material unit areas, and the classification values are the sum of the unit values in the material classification areas;
And fourthly, analyzing according to the material summarized data corresponding to each material type to obtain a corresponding material storage value, and carrying out material storage suggestion according to the obtained material storage value.
Further, the method for analyzing the material summary data corresponding to each material type comprises the following steps:
setting unit loss assessment values corresponding to the material unit areas, and matching corresponding loss assessment coefficients according to the obtained unit loss assessment values;
Each unit value is marked as DYj, j=1, 2, & gt, m is a positive integer;
According to the formulaCalculating a corresponding material storage value;
the formula is that PU is a material storage value, lambda is a cost adjustment value, namely, the cost of the material is set, delta is an invalid loss rate, namely, the invalid loss rate in the normal use process, and FY is a classification value.
Further, material storage analysis is carried out according to the storage model, a target planning mode is determined, and the target planning mode is recommended to a manager.
Further, the method for determining the target planning mode comprises the following steps:
establishing a judgment model, wherein the expression of the judgment model is thatWherein s is input data, and the output data is a judgment value 1 or 0;
Identifying the types of the corresponding materials in the storage model, analyzing the types of the materials through the judgment model to obtain judgment analysis result data, and analyzing the storage model according to the judgment analysis result data to obtain each planning mode to be selected;
Performing simulation evaluation on each to-be-selected planning mode to obtain a warehouse-in efficiency value and a scheduling efficiency value corresponding to each to-be-selected planning mode;
Calculating a corresponding combined value according to the formula qa=b1×rk+b2×dk;
wherein QA is a combined value, b1 and b2 are both proportionality coefficients, the value range is 0< b1 less than or equal to 1,0< b2 less than or equal to 1, RK is a warehouse-in efficiency value, DK is a scheduling efficiency value;
and marking the selected planning mode with the largest combination value as a target planning mode.
A material data management system for lithium battery diaphragm production comprises a data acquisition module, a display module and a data analysis module;
The data acquisition module is used for acquiring material data, a recording end is established, and staff performs data acquisition through the recording end to acquire all material data.
The display module is used for displaying the material data, establishing a storage model, identifying the material data and dynamically updating the storage model according to the material data.
The data analysis module is used for carrying out data analysis, carrying out data arrangement on each material type according to the storage model to obtain material summarized data corresponding to each material type, analyzing the material summarized data to obtain corresponding material storage values, and carrying out material storage suggestion according to the obtained material storage values.
Compared with the prior art, the invention has the beneficial effects that:
through setting up the storage model, realize the visual processing to material data, can demonstrate material data in the form of chart, image etc. for the enterprise can know material service condition and production situation more directly perceivedly. The method provides powerful data support for enterprise decision making, is favorable for enterprises to make more scientific and reasonable production plans and management strategies, performs intelligent analysis on material data based on a storage model, evaluates and analyzes the current material storage mode, and achieves the effect of assisting management personnel in optimizing material storage management in time.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a material data management method for lithium battery separator production, the method comprises:
Step one, a worker records data of each material according to a preset material data input mode, and uploads the recorded material data;
In one embodiment, the preset material data input mode may be a common recording mode of current material recording, for example, recording each material manually, then carrying out manual statistics, and uploading each material data after statistics is completed, however, applying the mode will cause a larger burden to staff.
In another embodiment, the preset material data entry mode is:
A recording end is set, and the recording end is an intelligent end in various forms such as mobile equipment, mobile phone software, small programs and the like for workers to record materials;
The method comprises the steps of identifying historical material record data, determining various corresponding record items of various materials, such as various corresponding data items of material types, quantity, specification, suppliers, prices, positions, warehouse-in time and the like according to the historical material record data, identifying a record range corresponding to each record item according to the historical material record data, namely counting various record data appearing in each record item according to the historical material record data, integrating the record range into the record range of the record item, establishing a corresponding data record template according to each record item and the corresponding record range, such as a first column for each record item and marking the record item as a record item grid, and a second column for blank grids corresponding to filling data of each record item and marking the record item as a record item statistical grid;
When the material changes, staff records the material in the recording template through the recording end without counting the staff, and the staff can directly record 3 materials, can record 1 in three times or can record 1 first and then record 2, so that the operation difficulty of the staff is reduced, and the staff can submit after the recording is finished.
Through setting up the record end and assisting the user to carry out the material record, the statistics efficiency of staff that will be very big improves for staff has great flexibility when carrying out statistics to the material, is convenient for reduce staff's statistics work load, reduces staff's burden, improves work efficiency.
Identifying material data uploaded by each staff, identifying material types, storage positions and production time corresponding to the material data, matching corresponding marking colors for the material according to the identified material types, namely identifying various material types, setting a marking color for each material type, such as red, yellow, green and the like, and setting different material types without similar colors, such as red, light red, dark red and the like;
Setting corresponding material attribute points according to material data, namely taking the material data as a data point, wherein the corresponding material data can be identified according to the data point, marking the corresponding material attribute points in a storage model according to matched marking colors to carry out corresponding marking, automatically counting according to the original material data at the position in the marking process, such as increasing or decreasing, and recording corresponding counting records, specifically identifying the marking data at the corresponding position in the storage model, namely the condition of the existing material attribute points at the position, if the marking data are not available, the marking data are empty, and if the marking data are available, the marking data are the material data corresponding to the material attribute points, according to actual conditions, the materials at the same position are only the same material, adjusting the material data corresponding to the material attribute points according to the marking data to obtain new material data, recording corresponding adjustment records, and marking the material attribute points at the corresponding positions in the storage model according to the marking colors;
and identifying all material attribute points in the storage model in real time, and carrying out region merging according to all material attribute points to obtain all material classification areas and all material unit areas corresponding to all material classification areas.
The method for carrying out region merging according to each material attribute point comprises the following steps:
step SA1, setting each node area according to each material attribute point, namely a space area corresponding to the stored material;
step SA2, setting initial areas according to the node areas, selecting the node areas as the initial areas in an optional mode, and simultaneously selecting a plurality of initial areas;
Step SA3, marking a node area or an initial area adjacent to the initial area as a to-be-selected area, carrying out combination evaluation on the initial area and the to-be-selected area, judging whether the combination requirement is met, combining the initial area and the to-be-selected area when the combination requirement is judged to be met, and obtaining a new initial area;
Step SA4, circulating the step SA3 until no area to be selected meeting the combination requirement exists, and marking the current initial area as a material unit area;
And step SA5, namely, circulating the steps SA2 to SA4 until no initial area exists, obtaining each material unit area, merging according to the material types corresponding to each material unit area, and obtaining a material classification area, namely, merging the material unit areas belonging to the same material type, and marking each material unit area in the material classification area.
The method for carrying out combined evaluation on the initial area and the area to be selected comprises the following steps:
When the material types are different, the corresponding production time and the corresponding warehousing time of the initial area and the corresponding warehousing time of the area to be selected are identified, the corresponding initial classification value and the corresponding classification value to be selected are set according to the obtained production time and the obtained warehousing time, the value range of the classification value is [0,100], the classification value 100 indicates that the material in the production time and the warehousing time has no influence on the performance, the quality and the like of the material, and the classification value 0 indicates that the material in the production time and the warehousing time can not meet the use requirement;
When the initial area is composed of a plurality of node areas, a plurality of initial classification values are matched according to the production time and the warehousing time corresponding to each node area, wherein the initial classification values are marked as CZi, i=1, 2, and n is a positive integer;
calculating corresponding merging values according to the formula hz=max { | CZi-dz| };
And when the merging value is larger than the threshold value X1, judging that the merging requirement is not met, and otherwise, judging that the merging requirement is met.
In one embodiment, the positions of all the material attribute points are analyzed to determine whether the storage positions are reasonable, and an optimal storage mode is recommended for the user, and the specific modes are as follows:
Obtaining various material types possibly used in lithium battery diaphragm production, evaluating whether the material types can be mutually contacted and adjacent in the storage process, obtaining corresponding evaluation results, and establishing a corresponding judgment model according to the data of the evaluation results, wherein the judgment model is used for judging whether the two material types can be stored in adjacent positions, and the expression is thatWherein s is input data, namely corresponding data of two material types, the output data is a judgment value of 1 or 0, and the fact that the two material types are not stored adjacently is not met;
The method comprises the steps of identifying each material type corresponding to a storage model, analyzing each material type through a judgment model to obtain judgment analysis result data, judging whether the analysis result data, namely, judging data which can be stored adjacently for every two material types, analyzing the storage model according to the judgment analysis result data, determining the distribution mode of each material unit area which can be provided on the premise of meeting the judgment analysis result data, marking as a planning mode to be selected, namely, determining the planning mode to be selected by utilizing the existing mathematical statistical method and storage common knowledge under the condition of determining the material quantity, storable area and each material unit area of each material type;
performing simulation evaluation on each planning mode to be selected, namely performing simulation by using historical background conditions, such as scheduling, warehousing and the like, determining warehousing efficiency values and scheduling efficiency values corresponding to each planning mode to be selected, comparing the warehousing efficiency values and the scheduling efficiency values with the current conditions, marking the corresponding ratio as corresponding warehousing efficiency values or scheduling efficiency values, comparing the warehousing efficiency values with the warehousing speed of purchased materials, and comparing the scheduling efficiency with the using speed of scheduled stored materials;
calculating a corresponding combined value according to a formula QA=b1×RK+b2×DK, wherein QA is the combined value, b1 and b2 are both proportional coefficients, the value range is 0< b1 less than or equal to 1,0< b2 less than or equal to 1, RK is a warehouse-in efficiency value, and DK is a scheduling efficiency value;
and marking the selected planning mode with the largest combination value as a target planning mode, and recommending the target planning mode to a manager.
Step three, data arrangement is carried out on various material types according to the storage model, material summarized data corresponding to the various material types are obtained, the material summarized data comprise material quantity corresponding to each material unit area and material quantity corresponding to the material classification area, and the material summarized data are respectively marked as a unit value and a classification value;
And fourthly, analyzing according to the material summarized data corresponding to each material type to obtain a corresponding material storage value, and carrying out material storage suggestion according to the obtained material storage value. The method comprises the steps of determining whether storage management adjustment of the material type is needed according to a material storage value, if not, not suggesting, if so, prompting a manager to conduct corresponding storage volume planning adjustment, specifically adjusting according to actual requirements of a user, and if so, suggesting when the material storage value is larger than a preset value.
The method for analyzing the material summary data corresponding to each material type comprises the following steps:
The method comprises the steps of identifying each classification value corresponding to each material unit area, calculating a corresponding average value, marking the average value as a unit loss assessment value, matching the corresponding loss assessment coefficient according to the obtained unit loss assessment value, determining the material loss condition of the material type under the condition of the unit loss assessment value according to actual historical storage loss data, taking the average value as a representative value of a material standard quantity, calculating the proportion of the representative value and the corresponding material standard quantity, marking the proportion as the loss assessment coefficient, carrying out corresponding summarization and arrangement, and then matching according to the unit loss assessment value;
Each unit value is marked as DYj, j=1, 2, & gt, m is a positive integer;
According to the formulaCalculating a corresponding material storage value;
the formula is that PU is a material storage value, lambda is a cost adjustment value, namely, the cost of the material is set, delta is an invalid loss rate, namely, the invalid loss rate in the normal use process, and FY is a classification value.
Through setting up the storage model, realize the visual processing to material data, can demonstrate material data in the form of chart, image etc. for the enterprise can know material service condition and production situation more directly perceivedly. The method provides powerful data support for enterprise decision making, is favorable for enterprises to make more scientific and reasonable production plans and management strategies, performs intelligent analysis on material data based on a storage model, evaluates and analyzes the current material storage mode, and achieves the effect of assisting management personnel in optimizing material storage management in time.
A material data management system for lithium battery diaphragm production comprises a data acquisition module, a display module and a data analysis module;
The data acquisition module is used for acquiring material data, a recording end is established, and staff performs data acquisition through the recording end to acquire all material data.
The display module is used for displaying the material data, establishing a storage model, identifying the material data and dynamically updating the storage model according to the material data.
The data analysis module is used for carrying out data analysis, carrying out data arrangement on each material type according to the storage model to obtain material summarized data corresponding to each material type, analyzing the material summarized data to obtain corresponding material storage values, and carrying out material storage suggestion according to the obtained material storage values.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.