CN109191030A - A kind of method promoting the quality of data and the method for improving warehouse operational paradigm - Google Patents
A kind of method promoting the quality of data and the method for improving warehouse operational paradigm Download PDFInfo
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Abstract
The present invention relates to technical field of data processing, and in particular to a kind of method for promoting the quality of data and the method for improving warehouse operational paradigm.By adding a label in data, the label is updated when may cause data inaccuracy event, the accuracy of the data is reflected by label；When needing to make movement using the data, the preferential highest data of reliability of choosing make movement.The present invention reflects the accuracy of data by the subsequent label of data in real time, the quality of data is improved, to promote operational paradigm；And the update track of the field label by the quality of data, targetedly backtracking is abnormal, promotes abnormal solution efficiency.When this method is applied to warehouse running field, outbound efficiency can not only be improved, moreover it is possible to improve the efficiency for managing and making an inventory in library, the effective operational paradigm for promoting warehouse and running are flexible.
Description
Technical field
The present invention relates to technical field of data processing, and in particular to a kind of method and raising warehouse fortune of the promotion quality of data
Make the method for efficiency.
Background technique
Quality of data label is a kind of means for being notified to the quality of data that information system uses to policymaker；Majority of case
Under, the data of information system are not 100% accurate.Under the premise of can not predict the accuracy rate of the quality of data, these are used
The data of existing defects will lead to policymaker and formulate the even catastrophic decision of mistake.
In fact, quality of data label is not yet successfully applied in information system, one of major reason is to safeguard this
Category information label is both expensive and time consuming；For example, the true property of prohibited data detection usually requires the true value of artificial observation data, but
The usual time and effort consuming of measurement process and error-prone, cannot achieve automation.With the growth of data volume, measurement in time and update letter
Data precision label in breath system is extremely difficult.
The solution of existing detection inexact data has following three classes: abnormal detection method, verifies analytic approach and makes
With alternate data source method.Only when following three conditions are set up, the inexact data in ability detection information system is to raw
Mark at accuracy data: 1, inexact data is " normal " data；2, inexact data can be analyzed by proof rule；3,
No suitable alternate data is for comparing.
1, inexact data is " normal " data
It observes whether data value meets desired value by executing integrity checking, does not meet normal, expected to find
Data pattern.Inspection has three classes abnormal: point is abnormal, and compared with other data, single data values are abnormal；Front and back is abnormal, data value
Front and back is abnormal in single environment；Collective is abnormal, and data value set and other data are comparably exception.It is not available abnormality detection
Carry out the true property of prohibited data detection, because are as follows: data noise may be obscured with data exception；Abnormal data in different application environment is not
It is identical to the greatest extent.
Accurate noise data may be mistakenly detected as inexact data.It is abnormal possible fine in certain fields
Ground indicates inaccuracy value, and in other fields, it extremely may be a very accurate value.Therefore, when abnormal data is not
When inexact data, that is, when inexact data is considered as " normal ", abnormality detection is not suitable for detecting its inaccuracy.
2, inexact data can be analyzed by proof rule
Proof rule method can be used for checking whether data are inaccurate.For example, inferring data not using individual data rule
Accuracy, for example, American society's security number must be made of nine bit digitals, if not nine bit digitals, then data are inaccurate.
Also may infer that inexact data using the rule that multiple related datas arrange, for example, verifying telephone number country code whether with
National title is identical.Proof rule may be more complicated, especially when inferring time inaccuracy, can pass through check data
Whether sequence is rationally and complete.But in reality, even if data still may inaccuracy by proof rule.Such as it is recorded in number
It may include nine bit digitals according to someone Social Security Number in library, and be not still his Social Security Number.
3, without suitable alternate data for comparing
In some cases, check that data can reduce the demand for checking real data using alternate data source, from
And the plenty of time is saved, but alternate data to what extent can accurate representation reality then worth discussion itself.Work as alternate data
When being not present and/or is incorrect in itself, i.e., when available without suitable Surrogate data source, alternate data cannot be used for detection data
Inaccuracy.
In conclusion there is presently no a kind of perfect solutions for detecting inexact data.
We are using the article in sorting physics warehouse as decision task, because it is similar to the spy in existing marker research
Determine event, it shows multiple freedom degrees, i.e., multiattribute decision task, and the existing method for detecting inaccurate row can not answer
With on warehouse sorts, i.e., it meets above three condition.
The advantages of warehouse management system (WMS), is that it is not influenced by decision-making, and the data for passing through article position
It automatically generates.Another advantage of this selection is the data used and reaches between the action that the result of decision is taken in the presence of straight
Relationship is connect, therefore is easy to measurement use information and marks whether that really reducing operation interrupts.
In warehouse sorting, various articles are usually stored in specific warehouse location with different number.Warehouse management system
The position for recording these articles is found when receiving new order sorting and sorts these articles.Storehouse management is usually noted article
Position, quantity and type of items.Following table shows an example, and position 5 is empty, therefore does not have type of items.Receiving object
When product order, warehouse management system uses this information, and finding which place includes sufficient amount of required article to meet order
Demand prints asset position information, and sorter is using the order segregating articles and gets ready the goods.
Position 1: type of goods: A, number of articles: 30；
Position 2: type of goods: A, number of articles: 20；
Position 3: type of goods: B, number of articles: 15；
Position 4: type of goods: B, number of articles: 4；
Position 5: type of goods :-, number of articles: 0.
There are multiple options, i.e. freedom degree from different location selection identical items, because the article of same type is commonly stored
In many different positions.Freedom degree/option over time may be different, because of the number of articles of warehouse location
It can update and change with order.Freedom degree had both been related to the Tactic selection of warehouse management system, was also related to the data note of warehouse location
Record.
Due to the inaccuracy of data, certain positions not actually exist the article indicated in warehouse management system.If picked
There is mistake when handling article in goods person, such as mistakenly places article or the position of mistake is picked up, then will appear inaccurate exact figures
According to.
If data are inaccurate, following interruption: D1 may cause, sorter is assigned to comprising very little article or is empty
Warehouse locations；D2, sorter are sent to the place comprising wrong type of items；D3, warehouse management system are assumed in warehouse
There is no enough articles, the order that refusal warehouse can fulfil；D4, warehouse management system assume there are enough articles in warehouse,
Receive the order that warehouse is unable to satisfy.It will lead to the low problem generation of the operational paradigm in warehouse in turn.
Summary of the invention
Mesh of the present invention provides a kind of method for promoting the quality of data and the method for improving warehouse operational paradigm, solves existing
The whether accurate problem of data cannot be grasped in real time by having in technology.
The technical scheme adopted by the invention is as follows:
A method of promoting the quality of data, comprising:
A label is added in data, being updated the label when may cause data inaccuracy event, being passed through mark
Sign the accuracy to reflect the data；
When needing to make movement using the data, the preferential highest data of reliability of choosing make movement.
As a preferred embodiment of the above technical solution, the label includes absolutely accurate data, relatively accurate data and absolutely not
Accurate data；The absolutely accurate data indicate that the data are entirely accurates, and the absolute inexact data indicates the data
It is complete inaccuracy, the relatively accurate data indicate that the reliability of the data is unknown.
As a preferred embodiment of the above technical solution, it is described cause data inaccuracy event occur before, preset an error probability
Value updates the label according to preset error probability value after causing data inaccuracy event to occur.
As a preferred embodiment of the above technical solution, the absolutely accurate data 0 are indicated with number in the label, it is described absolutely not
Accurate data indicates that the relatively accurate data use the digital representation between 0-1, numerical value in the label with number 1 in the label
Bigger, reliability is smaller.
As a preferred embodiment of the above technical solution, the initial value of the warehouse compartment label is 0, when warehouse compartment data are proved to be absolute
Tag update is 1 by inaccuracy, when causing data inaccuracy event to occur, updates label according to following formula:
Z=(X+Y)-(X*Y)
Wherein, after Z representative causes data inaccuracy event to occur, the value of label；X representative causes data inaccuracy event to be sent out
Before life, the value of label；Y represents preset error probability value.
As a preferred embodiment of the above technical solution, the reliability of the label can judge by the following method:
Assuming that A is the practical data acquisition system comprising causing accuracy by event, T is to be marked as inaccuracy data
Set event, | A | refer to the quantity of the practical inexact data in the data of recorded given event；
Situation one:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | T |, label is the warehouse compartment of false positive
Number is 0, and label is that the warehouse compartment number of true negative is | A |-| T |；
Situation two:
WhenAnd when A=T, then label is that the warehouse compartment number of true positives is | T |, label is false positive or true negative
Warehouse compartment number is 0；
Situation three:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A |, label is the warehouse compartment of false positive
Number is | T |-| A |, label is that the warehouse compartment number of true negative is 0；
Situation four:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A ∩ T |, label is false
Positive warehouse compartment number is Z=| T |-| A ∩ T |, label is that the warehouse compartment number of true negative is | A |-| A ∩ T |；
Situation five:
WhenAndWhen, if Z=0, label is that the warehouse compartment number of true positives is 0, and label is false positive
Warehouse compartment number is | T |, label is that the warehouse compartment number of true negative is | A |；
The true positives indicate that data label predicts that the data are wrong and practical and wrong；False positive indicates data mark
Label predict that the data are wrong but really pair；True negative indicates that data label predicts that the data are pair but really mistake
's.
A method of improving warehouse operational paradigm, comprising: the warehouse compartment data in warehouse add label, when generation causes to count
The label is updated when occurring according to inaccurate event, the accuracy of inventory data in each warehouse compartment is shown by label；When warehouse needs
When wanting quick shipment, sorter is preferentially assigned to data accuracy highest warehouse compartment and carries out sorting cargo.Warehouse compartment data include library
The item quantity placed in the description of goods and warehouse compartment placed in bit number, warehouse compartment.
As a preferred embodiment of the above technical solution, when the warehouse needs quick shipment, if sorter is in the mistake of sorting cargo
When finding that the cargo in cargo and inventory in warehouse compartment is not inconsistent in journey, the corresponding label of the warehouse compartment is modified；Due to needing
Quick shipment, so when sorter only the label of the warehouse compartment is modified, without warehouse compartment article clear up, to save sorter
The picking time.Sorter the other warehouse compartment for being placed with identical cargo is assigned to simultaneously to sort.
As a preferred embodiment of the above technical solution, when the warehouse does not need quick shipment, warehouse can by picking with make an inventory
It carries out together；That is, sorter, which is preferentially assigned to the minimum warehouse compartment of data accuracy, carries out sorting cargo, when in discovery warehouse compartment
When cargo in cargo and inventory is not inconsistent, the process that mistake occurs will be recalled according to the renewal process of the data label, to mention
The speed for correcting the exception is risen to update the label of corresponding warehouse compartment data after abnormal amendment, then proceed to picking.
As a preferred embodiment of the above technical solution, the warehouse arranged in library with when making an inventory, and the person of making an inventory will be according to accurate
The data of property from high to low are targetedly made an inventory successively to corresponding warehouse compartment；If finding the goods in warehouse compartment in inventory procedure
When cargo in object and system data is not inconsistent, the process that mistake occurs will be recalled according to the renewal process of the data label, thus
It promotes the speed for correcting the exception and updates the label of corresponding warehouse compartment data after abnormal amendment.
As a preferred embodiment of the above technical solution, described to lead to data inaccuracy event are as follows: sorter carries out a certain warehouse compartment
After goods sorting, warehouse compartment record once leads to data inaccuracy event.
As a preferred embodiment of the above technical solution, it is described cause data inaccuracy event occur after, the warehouse compartment of sorting and sorting
Warehouse compartment is adjacent and warehouse compartment in do not place the warehouse compartment of article, also record once leads to data inaccuracy event.Sorter is picking
After goods, it is easy to appear and kinds of goods is placed on inside adjacent empty warehouse compartment conveniently, therefore the adjacent warehouse compartment of warehouse compartment will be sorted and also record one
It is secondary to lead to data inaccuracy event.
As a preferred embodiment of the above technical solution, the label includes absolutely accurate data, relatively accurate data and absolutely not
Accurate data；The absolutely accurate data indicate that the data of the warehouse compartment are entirely accurates, and the absolute inexact data indicates
The data of the warehouse compartment are complete inaccuracy, and the relatively accurate data indicate that the accuracy of the data of the warehouse compartment is unknown.
As a preferred embodiment of the above technical solution, it is described cause data inaccuracy event occur before, preset an error probability
Value updates the label according to preset error probability value after causing data inaccuracy event to occur.
As a preferred embodiment of the above technical solution, the absolutely accurate data 0 are indicated with number in the label, it is described absolutely not
Accurate data indicates that the relatively accurate data use the digital representation between 0-1, numerical value in the label with number 1 in the label
Bigger, accuracy is smaller.
As a preferred embodiment of the above technical solution, the initial value of the warehouse compartment label is 0, when warehouse compartment data are proved to be absolute
Tag update is 1 by inaccuracy, when causing data inaccuracy event to occur, updates label according to following formula:
Z=(X+Y)-(X*Y)
Wherein, after Z representative causes data inaccuracy event to occur, the value of label；X representative causes data inaccuracy event to be sent out
Before life, the value of label；Y represents preset error probability value.
As a preferred embodiment of the above technical solution, the reliability of the label can judge by the following method:
Assuming that A is the practical data acquisition system comprising causing accuracy by event, T is to be marked as inaccuracy data
Set event, | A | refer to the quantity of the practical inexact data in the data of recorded given event；
Situation one:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | T |, label is the warehouse compartment of false positive
Number is 0, and label is that the warehouse compartment number of true negative is | A |-| T |；
Situation two:
WhenAnd when A=T, then label is that the warehouse compartment number of true positives is | T |, label is false positive or true negative
Warehouse compartment number is 0；
Situation three:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A |, label is the warehouse compartment of false positive
Number is | T |-| A |, label is that the warehouse compartment number of true negative is 0；
Situation four:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A ∩ T |, label is
The warehouse compartment number of false positive is Z=| T |-| A ∩ T |, label is that the warehouse compartment number of true negative is | A |-| A ∩ T |；
Situation five:
WhenAndWhen, if Z=0, label is that the warehouse compartment number of true positives is 0, and label is false positive
Warehouse compartment number is | T |, label is that the warehouse compartment number of true negative is | A |；
The true positives indicate that data label predicts that the data are wrong and practical and wrong；False positive indicates data mark
Label predict that the data are wrong but really pair；True negative indicates that data label predicts that the data are pair but really mistake
's.
The invention has the benefit that
The present invention reflects the accuracy of data by the subsequent label of data in real time, the quality of data is improved, to promote fortune
Make efficiency；And the update track of the field label by the quality of data, targetedly backtracking is abnormal, promotes abnormal solution effect
Rate.
In addition, adding label after the data of each warehouse compartment in the application in warehouse running field, reflecting the warehouse compartment in real time
The accuracy of data, when warehouse is busy needs to meet urgent shipment timeliness, warehouse system can be according to inventory data label
Sorter is preferentially assigned to the data precision highest warehouse compartment and carries out picking, sorter can be significantly reduced in this way and encounter warehouse compartment
The unmatched situation of article in data and practical warehouse compartment reduces the time for solving the exception, to improve outbound efficiency；When
When manage in library, warehouse system can preferentially be made an inventory the lower library of the data precision according to inventory data label in warehouse
Position can targetedly be found according to the update track of the quality of data label of the warehouse compartment data when an anomaly occurs and lose library
It deposits, closes exception rapidly, to improve the efficiency for managing and making an inventory in library, effectively improve the operational paradigm and fortune in warehouse
Make flexible.
Detailed description of the invention
Fig. 1 is architectural framework figure of the invention；
Fig. 2 is reliability judgement table of the invention；
Fig. 3 is that the label value of warehouse compartment after 10 pickings in the embodiment of the present invention 2 corresponds to table；
Fig. 4 is that the label value of warehouse compartment after 10 pickings in the embodiment of the present invention 1 corresponds to table；
Fig. 5 is made in experimental test that each combination in the embodiment of the present invention 2 for freedom degree and error rate executes
Hindering factor table.
Fig. 6 is the data markers sample table of warehouse item location information in the embodiment of the present invention 2；
Fig. 7 is that avoidance breakout operation is compared with the operation of normal warehouse management system in the embodiment of the present invention 2,200 sortings
The average interrupt number that task encounters；
Fig. 8 is that avoidance breakout operation is selected for 100 times compared with the operation of normal warehouse management system in the embodiment of the present invention 2
The average interrupt number encountered；
Fig. 9 be in the embodiment of the present invention 2 when attempting to find the inaccuracy compared with the operation of normal warehouse management system
It was found that 200 average error quantity selected；
Figure 10 be in the embodiment of the present invention 2 when attempt to find with the operation of normal warehouse management system compared to it is inaccurate when,
It was found that 100 average error quantity selected；
When Figure 11 is that sorting number is 200 times in the embodiment of the present invention 2, the inaccurate exact figures of potential problems data markers are found
The par of amount and the normal operation of warehouse management system；
Figure 12 is to sort number in the embodiment of the present invention 2 as 100 times to be, the inaccurate exact figures of discovery potential problems data markers
The par of amount and the normal operation of warehouse management system.
Specific embodiment
With reference to the accompanying drawing, the present invention is described in detail.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.The present invention being usually described and illustrated herein in the accompanying drawings is implemented
The component of example can be arranged and be designed with a variety of different configurations.
Therefore, the detailed description of the embodiment of the present invention provided in the accompanying drawings is not intended to limit below claimed
The scope of the present invention, but be merely representative of selected embodiment of the invention.Based on the embodiments of the present invention, this field is common
Technical staff's every other embodiment obtained without creative efforts belongs to the model that the present invention protects
It encloses.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need that it is further defined and explained in subsequent attached drawing.
In the description of the present invention, it should be noted that the orientation of the instructions such as term " on ", "vertical", "inner", "outside" or
Positional relationship be based on the orientation or positional relationship shown in the drawings or the invention product using when the orientation usually put or
The orientation or positional relationship that positional relationship or those skilled in the art usually understand is merely for convenience of the description present invention
It is described with simplifying, rather than the device or element of indication or suggestion meaning must have a particular orientation, with specific orientation structure
It makes and operates, therefore be not considered as limiting the invention.In addition, term " first ", " second " etc. are only used for distinguishing description,
It is not understood to indicate or imply relative importance.
In the description of the present invention, it is also necessary to which explanation is unless specifically defined or limited otherwise, term " setting ",
" installation ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or integrally connect
It connects；It can be mechanical connection, be also possible to be electrically connected；It can be directly connected, can also indirectly connected through an intermediary, it can
To be the connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood with concrete condition
Concrete meaning in the present invention.
Embodiment 1:
A kind of method for improving warehouse operational paradigm is present embodiments provided, as shown in Figure 1 to Figure 2.
A method of warehouse operational paradigm is improved, a field is added in each warehouse compartment data in warehouse, as
The label of the quality of data reflects the reliabilities of the data in real time, and update when may cause data inaccuracy event should
Label shows the accuracy of inventory data in each warehouse compartment by label；When warehouse needs quick shipment, preferentially by sorter
It is assigned to data accuracy highest warehouse compartment and carries out sorting cargo.Warehouse compartment data include warehouse compartment number, the interior kinds of goods name placed of warehouse compartment
The item quantity for claiming and being placed in warehouse compartment.
When the warehouse does not need quick shipment, warehouse can carry out picking with making an inventory together.That is, preferentially by sorter
It is assigned to the minimum warehouse compartment of data accuracy and carries out sorting cargo, when the cargo in the cargo and inventory in discovery warehouse compartment is not inconsistent
When, the process that mistake occurs will be recalled according to the renewal process of the data label, to promote the speed for correcting the exception.It is abnormal
After amendment, the label for updating corresponding warehouse compartment data is 0.Then proceed to picking.
When the warehouse arrange and make an inventory in library, the person of making an inventory by according to accuracy data from high to low successively to phase
Warehouse compartment is answered, is targetedly made an inventory.When finding that the cargo in cargo and system data in warehouse compartment is not inconsistent in the process, by root
According to the process that the renewal process backtracking mistake of the data label occurs, to promote the speed for correcting the exception.After abnormal amendment,
The label for updating corresponding warehouse compartment data is 0.
The label includes absolutely accurate data, relatively accurate data and absolute inexact data；The absolutely accurate number
It is entirely accurate according to the data for indicating the warehouse compartment, the absolute inexact data indicates that the data of the warehouse compartment are complete inaccuracy
, the relatively accurate data indicate that the accuracy of the data of the warehouse compartment is unknown.
It is described cause data inaccuracy event to occur before, an error probability value is preset, when leading to data inaccuracy event
After generation, the label is updated according to preset error probability value.The absolutely accurate data 0 indicate with number in the label, institute
Stating absolute inexact data indicates that the relatively accurate data use the digital table between 0-1 in the label with number 1 in the label
Show, numerical value is bigger, and accuracy is smaller.
The initial value of the warehouse compartment label is 0, is absolutely not accurately to be when warehouse compartment data are proved to be by tag update
1, when causing data inaccuracy event to occur, label is updated according to following formula:
Z=(X+Y)-(X*Y)
Wherein, after Z representative causes data inaccuracy event to occur, the value of label；X representative causes data inaccuracy event to be sent out
Before life, the value of label；Y represents preset error probability value.
If the label value that Y is arranged to warehouse compartment after 0.1,10 pickings is corresponding as shown in Figure 4.
Embodiment 2:
A kind of method for improving warehouse operational paradigm is present embodiments provided, as shown in Figures 1 to 12.
A method of warehouse operational paradigm being improved, the warehouse compartment data in warehouse add label, when generation leads to data not
Accurate event updates the label when occurring, and the accuracy of inventory data in each warehouse compartment is shown by label；When warehouse needs fastly
When fast shipment, sorter is preferentially assigned to data accuracy highest warehouse compartment and carries out sorting cargo.Warehouse compartment data include that warehouse compartment is compiled
Number, the item quantity placed in the description of goods and warehouse compartment placed in warehouse compartment.
When the warehouse needs quick shipment, if sorter find during sort cargo cargo in warehouse compartment with clearly
When cargo in list is not inconsistent, the corresponding label of the warehouse compartment is modified；Due to needing quick shipment, so when sorter only will
The label of the warehouse compartment is modified, and is cleared up without warehouse compartment article, to save sorter's picking time.Sorter is distributed simultaneously
It is sorted to the other warehouse compartment for being placed with identical cargo.
When the warehouse does not need quick shipment, warehouse can carry out picking with making an inventory together.That is, preferentially by sorter
It is assigned to the minimum warehouse compartment of data accuracy and carries out sorting cargo, when the cargo in the cargo and inventory in discovery warehouse compartment is not inconsistent
When, the process that mistake occurs will be recalled according to the renewal process of the data label, to promote the speed for correcting the exception.It is abnormal
After amendment, the label for updating corresponding warehouse compartment data is 0.Then proceed to picking.
When the warehouse arrange and make an inventory in library, the person of making an inventory by according to accuracy data from high to low successively to phase
Warehouse compartment is answered, is targetedly made an inventory.When finding that the cargo in cargo and system data in warehouse compartment is not inconsistent in the process, by root
According to the process that the renewal process backtracking mistake of the data label occurs, to promote the speed for correcting the exception.After abnormal amendment,
The label for updating corresponding warehouse compartment data is 0.
It is described to lead to data inaccuracy event are as follows: after sorter carries out goods sorting to a certain warehouse compartment, warehouse compartment record one
It is secondary to lead to data inaccuracy event.
It is described cause data inaccuracy event to occur after, the warehouse compartment of sorting and the warehouse compartment of sorting is adjacent and warehouse compartment in do not place
The warehouse compartment of article, also record once leads to data inaccuracy event.Sorter is easy to appear after picking and conveniently puts kinds of goods
It sets inside adjacent empty warehouse compartment, therefore will sort the adjacent warehouse compartment of warehouse compartment and also record once leads to data inaccuracy event.
The label includes absolutely accurate data, relatively accurate data and absolute inexact data；The absolutely accurate number
It is entirely accurate according to the data for indicating the warehouse compartment, the absolute inexact data indicates that the data of the warehouse compartment are complete inaccuracy
, the relatively accurate data indicate that the accuracy of the data of the warehouse compartment is unknown.
It is described cause data inaccuracy event to occur before, an error probability value is preset, when leading to data inaccuracy event
After generation, the label is updated according to preset error probability value.
The absolutely accurate data indicate that the absolute inexact data uses number 1 in the label with number 0 in the label
It indicates, the relatively accurate data use the digital representation between 0-1 in the label, and numerical value is bigger, and accuracy is smaller.
The initial value of the warehouse compartment label is 0, is absolutely not accurately to be when warehouse compartment data are proved to be by tag update
1, when causing data inaccuracy event to occur, label is updated according to following formula:
Z=(X+Y)-(X*Y)
Wherein, after Z representative causes data inaccuracy event to occur, the value of label；X representative causes data inaccuracy event to be sent out
Before life, the value of label；Y represents preset error probability value.
If Y is arranged to 0.05, the label value of warehouse compartment is corresponding as shown in Figure 3 after n times picking.
The reliability of the label can judge by the following method:
Assuming that A is the practical data acquisition system comprising causing accuracy by event, T is to be marked as inaccuracy data
Set event, | A | refer to the quantity of the practical inexact data in the data of recorded given event；
Situation one:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | T |, label is the warehouse compartment of false positive
Number is 0, and label is that the warehouse compartment number of true negative is | A |-| T |；
Situation two:
WhenAnd when A=T, then label is that the warehouse compartment number of true positives is | T |, label is false positive or true negative
Warehouse compartment number is 0；
Situation three:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A |, label is the warehouse compartment of false positive
Number is | T |-| A |, label is that the warehouse compartment number of true negative is 0；
Situation four:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A ∩ T |, label is false
Positive warehouse compartment number is Z=| T |-| A ∩ T |, label is that the warehouse compartment number of true negative is | A |-| A ∩ T |；
Situation five:
WhenAndWhen, if Z=0, label is that the warehouse compartment number of true positives is 0, and label is false positive
Warehouse compartment number is | T |, label is that the warehouse compartment number of true negative is | A |；
The true positives indicate that data label predicts that the data are wrong and practical and wrong；False positive indicates data mark
Label predict that the data are wrong but really pair；True negative indicates that data label predicts that the data are pair but really mistake
's.
Experimental verification:
Sort operation is simulated by using Java and MySQL, is compared by two databases, a database representation warehouse
Management system, the practical warehouse situation of another database representation.The operation in warehouse management system and practical warehouse can be by looking into
The data modeling of two databases is ask and updates, to automaticly inspect data inaccuracy by comparing two databases.
When order reaches warehouse, warehouse management system selects different warehouse compartment sorting commodity to meet order demand；Pick up object
When product, sorter may bring faulty operation in warehouse management system into, therefore subsequent pick-up task may be because of data not
Accurately cause to interrupt.There are two types of the mistakes of sorter: 1, accidentally setting, sorter removes special article from the shelf of warehouse compartment
Afterwards, the article of volume residual is put back to the position of mistake；2, it accidentally picks, sorter picks up from the other positions different from order designated position
Picking object.Based on the above mistake, sorter is likely encountered following three kinds of interruptions: D1, the warehouse compartment lack article or the warehouse compartment for sky；
What D2, the warehouse compartment were stored is the article of mistake；The order that D3, warehouse management system refusal warehouse can execute；D4, warehouse are always
It can satisfy order needs, sorter will not interrupt.
500 repetitions that sorter A carries out 200 pickup tasks are tested, between the average for determining three kinds of interruption situations
Significant difference: 1, it is normal, i.e., warehouse compartment is allocated before sorter's picking without using this method；2, avoidance breakout, i.e.,
Sorter is preferentially assigned to the highest warehouse compartment of data accuracy before sorter's picking using this method；3, discovery is interrupted,
Sorter is preferentially assigned to the minimum warehouse compartment of data accuracy before sorter's picking using this method.Three kinds different
Error rate is respectively 1%, 5% and 20%, and three kinds of different freedom degrees are respectively 2,12 and 60 combination.Fig. 5 summarizes variable
And its parameter, each freedom degree show the difference of parametrization.The free angle value of selection 2 and 60,2 be that the minimum that warehouse configures can
It can be worth, 60 be the maximum value possible of warehouse configuration, and 12 freedom degrees represent the freedom degree actual average number between extreme value.These
All be average value because freedom degree according to order, type of items, quantity, History Order and specific pickup task dispatching factor and
It changes.
In order to reduce mistake, the hindering factor that we are configured and be erroneously inserted using warehouse, warehouse is configured using five kinds not
Same method inserting error, other factors in 20 experimental tests are random.
It is interrupted in an experiment by increasing every time and interrupting related counter to record, and records pickup mission number
When occur to allow to investigate to interrupt.When sorter is when some position faces interruption, system can find the position of inaccuracy.
It note that sorter may be picked up from an inaccurate position, and if there is enough articles are available,
It not can determine that accuracy then, to be not counted in error instance.
Investigation when encounter interruption and how many interrupt it is also critically important because potential problems data markers avoidance breakout and
Searching to interrupt will only interrupt in the pickup task being transferred to respectively later or earlier, and interrupts and itself do not eliminate.Therefore, false
If testing 1 to 100 pickup tasks and 1 to 200 pickup tasks and comparing.
Each setting of simulation has multiple freedom degrees, referring to Fig. 5, is then solved the problems, such as using potential problems data markers
First condition met, and other two conditions depend on potential problems data markers specific implementation.
To realize potential problems data markers, need to update label in the database, input marking more new procedures, selection is more
The event and condition newly marked, the event of selected marker, and filtering report result.
Quality of data label is the additional tags of storehouse management database, in simulations, ' EP ': the mark value of expected probability
It is arranged to 0.05, this is based on the random quantity observed practical warehouse.
Flag update program may be implemented in Java simulation, it uses the SQL query for being published to database according to the rule in table 1
Then change mark value.Flag update program assembly update mark has following three kinds of situations: 1) when sorter selects from warehouse
When article, label automatically updates signal inexact data and may be inserted into, and 2) all labels are set as zero after Stock Check, it indicates
All data are all accurate, 3) it interrupts and confirms that label is set as 1 there are after problem encountering warehouse.
Event and condition selection:
When occurring accidentally to set or accidentally pick, information system can easily record the mistake of order sorting.In fact, when printing
When order sorting, it can be given sorter, and sorter may accidentally set or accidentally pick article when physical location sorts article.By
In being difficult to accurately determine which event causes the problem of accidentally setting or accidentally picking, therefore solution misregistration always.Therefore, condition
It is set as " always ", later it is contemplated that more advanced prediction.
Select the record to be marked:
Mistake, which may be placed, by warehouse item there are two record is influenced: 1) information of record sort positions, and 2) record
Article is placed or the mistake of take-off location.First record is the record of warehouse management system.But Article 2 record is unknown
, need deduction/conjecture.Therefore, we label first record.If occurring accidentally to set mistake really, illustrate first mark
Note is certainly inaccurate.Therefore, situation 1 of the solution suitable for Fig. 2, because it will generate a true positives and one true
It is negative.The second condition that can quality status stamp provide benefit is also met.Because of solution sentinel first record,
The last one condition is also met, and particular event is selected, and condition and label record are as shown in Figure 6.Printing sorting every time is ordered
Dan Shi, the label value list for picking all records in matching are automatically updated by flag update program assembly.
Realize report mechanism switching:
Switch in report mechanism picks the position in order for changing, and for giving order, WMS can automatically select packet
Containing required type of items and sufficient amount of storage position.In this case, system default be with required type of items and
Sufficient amount of position, and minimum mark value is returned to avoid interrupting or returning highest mark value to search and interrupt.Therefore it marks
Note value is not displayed to sorter forever.
Fig. 6 is shown using the example markup value occurred after this new mechanism label.The table shows open from Stock Check
Begin to the state of the WMS after the completion of 6 sorting tasks, i.e., all data are all accurate.Article sorts once from position 1,
Position 3 is sorted twice, and position 4 is sorted three times；Mark value reflects this point.Therefore, position 4 is most possibly comprising inaccuracy
Value, because a possibility that sorter makes a mistake in the position is maximum.Position 2 is the optimum position of segregating articles " A ", to avoid in
It is disconnected.
Experimental result:
This section introduce first execute simulation as a result, compared with the normal operating of WMS, avoidance breakout, then search interrupt/
Inaccuracy.Table in following section show it is preceding 200 sorting and first 100 sorting as a result, to determine solution
Performance whether over time and improve or reduce.The average of the interruption encountered as the result is shown and for all
The average of the inaccuracy of freedom degree and error rate.
Avoidance breakout:
Other than 1% error rate of 1% error rate of 2 freedom degrees and 12 freedom degrees, potential problems data markers with
Normal condition has significant difference, sees attached drawing 7 and attached drawing 8.Refuse null hypothesis in these cases, it is meant that with use WMS normal
It compares, it is less to avoid the interruption encountered when interrupting using potential problems data markers.In fact, in addition to 12 freedom degrees
Except 5% error rate, all situations are only significant under 95% confidence level.In 1% error rate and 12 freedom of 2 freedom degrees
In the case of 1% error rate of degree, null hypothesis can not be refused, it means that potential problems data markers in these cases will not band
Carry out any benefit.
Preceding 100 sortings are tested, see that attached drawing 8, all situations all may cause refusal null hypothesis, and avoidance breakout
Probability continues to decline over time.The average interrupt number of potential problems data markers and the positive reason in attached drawing 7
Condition and shows lesser difference in attached drawing 7 compared to showing larger difference.At its best, Estimating Confidence Interval with
Normal condition is compared, and experiment can be to avoid in 200 sorting tasks about 2 to nearly 4 interruptions.When only considering preceding 12 error rates
For preceding 100 sortings task of 12 and 60 freedom degrees, can be interrupted to avoid additional 3 to 4 times.
It searches and interrupts:
When searching interruption, as the result is shown in most instances, potential problems data markers and warehouse management system are just
Often operation has significant difference in 99.9% confidence level, sees attached drawing 9.Another situation, i.e. 1% mistake of 12% freedom degree
Rate, it is still critically important in 95% confidence level.First 100 are sorted, confidence level 99.9%, the 1% of 12 freedom degrees is wrong
Accidentally rate also has significant difference, sees attached drawing 10.Over time, the performance for searching interruption can also decline.This can also pass through
The average inaccuracy of potential problems data markers is observed, the larger difference between the normal condition in interruption and attached drawing 11 is searched
It is different, with the smaller difference in attached drawing 11.When searching interruption using potential problems data markers, all situations can all refuse former vacation
If.
Compared with the normal condition of 20% error rate of 60 freedom degrees, mostly 7 can be found in 200 sorting tasks and arrived
8 inaccuracy are interrupted.This be equivalent in 200 sorting tasks be inserted into data 40 mistakes in find 17.5% to 20% it
Between.For 20% error rate of 2 and 12 freedom degrees, this is about that 4 to 6 inaccuracy are interrupted.When only considering 2 freedom degrees
When preceding 100 sortings task of 20% error rate, the quantity for searching interruption falls to approximately 2.There are also the 60 of 20% error rate
A freedom degree can find 6 to 7 inaccuracy and interrupt.However, for 20% error rate of 12 freedom degrees, confidence interval itself from
(5.58,6.23) of preceding 100 sortings task increases to (4.54,6.55) of all 200 sortings tasks.
For avoiding and searching configuration, compared with normal condition, performance is improved with the increase of error rate.With mistake
The increase of rate, wrong report label because mistake there is no and cause replaced the real positive.Therefore, with the increasing of error rate
Add, label becomes more accurate.
This improve can also be with partial interpretation, because normal condition shows to obtain phase when wrong seldom when avoidance breakout
It is a good.This is because very possible avoidance breakout because there are many storage location can therefrom select article without will cause in
It is disconnected.For searching the less lookup situation of less mistake, situation is exactly the opposite, therefore searching configuration can also be with lower error rate
It executes.On the contrary, lowest error rate is worst performance when avoiding.Other than lower error rate, configuration pair is searched
Also showed well in higher error rate, and have a lot of reasons can explain why: search configuration in, ordered from different
Identical storage location is selected in list, until their quantity exhausts.Therefore, configuration is searched to tend to arrive erroneous packet
Small number of position, these positions have higher a possibility that including inaccuracy.Be not under normal circumstances in this way, its
Middle inaccuracy is more uniformly distributed between position.This phenomenon also makes have inaccuracy from previous picking task
Position be more likely to unexpectedly be again marked as with inaccuracy.Therefore, some real negatives become really actively
Factor, to improve performance.
About freedom degree, it is contemplated that performance can be improved as it increases, because this can be potential problems data
Label provides more chances to select the different storage locations of more or less possible inaccuracy.Keeping away for task is sorted for 100
Exempt from and search configure-ack this point, wherein confidence interval is increased monotonically with the increase of error rate and freedom degree.For
For 200 sorting tasks, same mode is it will be apparent that still there is some abnormal phenomenon such as 5%, 12 freedom
Degree does not follow the mode.It is as caused by changeability intrinsic in simulation that explanation most probable to exception, which is them,.
Avoid setting more preferable than preceding 100 sorting tasks, rather than complete 200 tasks, because this realization will not
It eliminates and interrupts, but avoid them.Therefore, with the increase for sorting quantity, the inaccuracy ratio of remaining position is higher.Cause
This more likely faces interruption even if being avoided being arranged using potential problems data markers in later selection.
Potential problems data markers avoid and search the improvement for being arranged and all showing to normal condition, and with mistake
The increase of rate and freedom degree and increasingly optimize.This makes the concept of data markers closer to adopting in actual information system
With because this method reduces the time and efforts cost of data markers maintenance since its is increasingly automated.
One advantage of potential problems data markers is dynamically to avoid and search free switching between configuration.?
In warehouse case, label can be completed in any point between picking task.Therefore, it preferably controls when to encounter and have
The data of inaccuracy, and when want to avoid the influence of bad data.This switching capability has caused about when executing
The problem of data quality checking/correction program Best Times, flexibly in the case where being likely to encounter a large amount of inexact datas
Switching, then may make data more efficient use；Simultaneously can also deliberately execute this operation when data are set, so as to detect/
Correction.
Embodiment 3:
A kind of method for improving warehouse operational paradigm is present embodiments provided, as shown in Figures 1 to 12.
A method of improving warehouse operational paradigm, comprising: the warehouse compartment data in warehouse add label, when generation causes to count
The label is updated when occurring according to inaccurate event, the accuracy of inventory data in each warehouse compartment is shown by label；When warehouse needs
When wanting quick shipment, sorter is preferentially assigned to data accuracy highest warehouse compartment and carries out sorting cargo.Warehouse compartment data include library
The item quantity placed in the description of goods and warehouse compartment placed in bit number, warehouse compartment.
When the warehouse does not need quick shipment, warehouse can carry out picking with making an inventory together.That is, preferentially by sorter
It is assigned to the minimum warehouse compartment of data accuracy and carries out sorting cargo, when the cargo in the cargo and inventory in discovery warehouse compartment is not inconsistent
When, the process that mistake occurs will be recalled according to the renewal process of the data label, to promote the speed for correcting the exception.It is abnormal
After amendment, the label for updating corresponding warehouse compartment data is 0.Then proceed to picking.When the warehouse needs quick shipment, if sorter
When finding that the cargo in cargo and inventory in warehouse compartment is not inconsistent during sorting cargo, the corresponding label of the warehouse compartment is carried out
Modification；Due to needing quick shipment, so when sorter only the label of the warehouse compartment is modified, it is clear without warehouse compartment article
Reason, to save sorter's picking time.Sorter the other warehouse compartment for being placed with identical cargo is assigned to simultaneously to sort.
When the warehouse arrange and make an inventory in library, the person of making an inventory by according to accuracy data from high to low successively to phase
Warehouse compartment is answered, is targetedly made an inventory.When finding that the cargo in cargo and system data in warehouse compartment is not inconsistent in the process, by root
According to the process that the renewal process backtracking mistake of the data label occurs, to promote the speed for correcting the exception.After abnormal amendment,
The label for updating corresponding warehouse compartment data is 0.
The reliability of the label can judge by the following method:
Assuming that A is the practical data acquisition system comprising causing accuracy by event, T is to be marked as inaccuracy data
Set event, | A | refer to the quantity of the practical inexact data in the data of recorded given event；
Situation one:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | T |, label is the warehouse compartment of false positive
Number is 0, and label is that the warehouse compartment number of true negative is | A |-| T |；
Situation two:
WhenAnd when A=T, then label is that the warehouse compartment number of true positives is | T |, label is false positive or true negative
Warehouse compartment number is 0；
Situation three:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A |, label is the warehouse compartment of false positive
Number is | T |-| A |, label is that the warehouse compartment number of true negative is 0；
Situation four:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A ∩ T |, label is false
Positive warehouse compartment number is Z=| T |-| A ∩ T |, label is that the warehouse compartment number of true negative is | A |-| A ∩ T |；
Situation five:
WhenAndWhen, if Z=0, label is that the warehouse compartment number of true positives is 0, and label is false positive
Warehouse compartment number is | T |, label is that the warehouse compartment number of true negative is | A |；
The true positives indicate that data label predicts that the data are wrong and practical and wrong；False positive indicates data mark
Label predict that the data are wrong but really pair；True negative indicates that data label predicts that the data are pair but really mistake
's.
By the number of labels of true positives, false positive or true negative, flag data label when event occurs can be tracked
The value of accuracy, the method for optimizing flag data label.As shown in Figure 2.
Such as in actual operation, there are 100 warehouse compartments, wherein the numerical value of 5 warehouse compartments is wrong, A=(warehouse compartment 1, warehouse compartment 2, library
Position 3, warehouse compartment 4, warehouse compartment 5), | A |=5.
In systems, also record has 100 warehouse compartment data to show data in systems by the method for label record
Group T=(warehouse compartment 1, warehouse compartment 2, warehouse compartment 3, warehouse compartment 4, warehouse compartment 5), | T |=5.Then such case is exactly the second situation in Fig. 2,
That is A=T.
If A=(warehouse compartment 1, warehouse compartment 2, warehouse compartment 3, warehouse compartment 4, warehouse compartment 5), | A |=5；However T=(warehouse compartment 1, warehouse compartment 2, library
Position 3), | T |=3, here it is the first situations in Fig. 2.So in this case, the warehouse compartment numbers of true positives=| T |=3；It is false
Positive warehouse compartment number=0；The warehouse compartment number of true negative=| A |-| T |=5-3=2.Its excess-three kind situation and so on.
For example, there are 10 cargos from warehouse compartment a, require to sort out from the inside now to come 5, remaining 5 will put back to Yuan Ku
Position.Assuming that this former warehouse compartment is in the 4th layer of shelf, then warehouse compartment b, c, d, e of surrounding (up and down) are vacancy, so this
In the case of, the movement for putting back to former warehouse compartment may malfunction, and may put any one of this four warehouse compartments into.So such
In the case of, if we mark bcde warehouse compartment to be likely to malfunction, T > A is exactly the third situation in Fig. 2；If I
Know the general warehouse compartment that can only misplace the left side or the right of this sorter, then we only can one warehouse compartment of label can go out
Mistake, then being possible to is second in Fig. 2 or the 5th kind of situation.By this optimization method, label can not only be judged
Reliability, additionally it is possible to the accuracy rate of data label is continuously improved.
The present invention is not limited to above-mentioned optional embodiment, anyone can show that other are each under the inspiration of the present invention
The product of kind form.Above-mentioned specific embodiment should not be understood the limitation of pairs of protection scope of the present invention, protection of the invention
Range should be subject to be defined in claims, and specification can be used for interpreting the claims.
Claims (10)
1. a kind of method for promoting the quality of data characterized by comprising
In data add a label, update the label when may cause data inaccuracy event, by label come
Reflect the accuracy of the data；
When needing to make movement using the data, the preferential highest data of reliability of choosing make movement.
2. the method according to claim 1 for promoting the quality of data, it is characterised in that: the label includes absolutely accurate number
According to, relatively accurate data and absolute inexact data；The absolutely accurate data indicate that the data are entirely accurates, described exhausted
Inaccurate data indicate that the data are complete inaccuracy, and the relatively accurate data indicate that the reliability of the data is unknown.
3. the method according to claim 2 for promoting the quality of data, it is characterised in that: described to lead to data inaccuracy event
Before generation, an error probability value is preset, after causing data inaccuracy event to occur, is updated according to preset error probability value
The label.
4. the method according to claim 3 for promoting the quality of data, it is characterised in that: the absolutely accurate data are in label
Middle to be indicated with number 0, the absolute inexact data indicates that the relatively accurate data are in the label with number 1 in the label
With the digital representation between 0-1, numerical value is bigger, and reliability is smaller.
5. the method according to claim 4 for promoting the quality of data, it is characterised in that: the initial value of the warehouse compartment label is
0, being absolutely not accurately when warehouse compartment data are proved to be is 1 by tag update, when causing data inaccuracy event to occur,
Label is updated according to following formula:
Z=(X+Y)-(X*Y)
Wherein, after Z representative causes data inaccuracy event to occur, the value of label；X representative causes data inaccuracy event that it occurs
Before, the value of label；Y represents preset error probability value.
6. the method according to claim 4 for promoting the quality of data, which is characterized in that the reliability of the label can pass through
Following methods judgement:
Assuming that A is the practical data acquisition system comprising causing accuracy by event, T is the set for being marked as inaccuracy data
Event, | A | refer to the quantity of the practical inexact data in the data of recorded given event；
Situation one:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | T |, label is that the warehouse compartment number of false positive is 0,
Label is that the warehouse compartment number of true negative is | A |-| T |；
Situation two:
WhenAnd when A=T, then label is that the warehouse compartment number of true positives is | T |, label is the warehouse compartment of false positive or true negative
Number is 0；
Situation three:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A |, label is that the warehouse compartment number of false positive is |
T |-| A |, label is that the warehouse compartment number of true negative is 0；
Situation four:
WhenAndWhen, then label is that the warehouse compartment number of true positives is | A ∩ T |, label is false positive
Warehouse compartment number be Z=| T |-| A ∩ T |, label is that the warehouse compartment number of true negative is | A |-| A ∩ T |；
Situation five:
WhenAndWhen, if Z=0, label is that the warehouse compartment number of true positives is 0, and label is the warehouse compartment of false positive
Number is | T |, label is that the warehouse compartment number of true negative is | A |；
The true positives indicate that data label predicts that the data are wrong and practical and wrong；False positive indicates that data label is pre-
It is wrong but really pair for surveying the data；True negative indicates that data label predicts that the data are pair but really mistake.
7. a kind of method for improving warehouse operational paradigm characterized by comprising
Label is added, the warehouse compartment data in warehouse add label, when generation causes data inaccuracy event to update the mark when occurring
Label, the accuracy of inventory data in each warehouse compartment is shown by label；
When warehouse needs quick shipment, sorter is preferentially assigned to data accuracy highest warehouse compartment and carries out sorting cargo.
8. the method according to claim 7 for improving warehouse operational paradigm, which is characterized in that the warehouse does not need quickly
When shipment, warehouse can carry out picking with making an inventory together；That is, sorter is preferentially assigned to the minimum warehouse compartment of data accuracy
Sorting cargo is carried out, it, will be according to the updated of the data label when finding that the cargo in cargo and inventory in warehouse compartment is not inconsistent
The process that journey backtracking mistake occurs after abnormal amendment, updates the mark of corresponding warehouse compartment data to promote the speed for correcting the exception
Label, then proceed to picking.
9. the method according to claim 7 for improving warehouse operational paradigm, which is characterized in that the warehouse carries out whole in library
When managing and making an inventory, the person of making an inventory, successively to corresponding warehouse compartment, will targetedly make an inventory according to accuracy data from high to low；
It, will be according to the updated of the data label if find that the cargo in cargo and system data in warehouse compartment is not inconsistent in inventory procedure
The process that journey backtracking mistake occurs after abnormal amendment, updates the mark of corresponding warehouse compartment data to promote the speed for correcting the exception
Label.
10. the method according to claim 7 for improving warehouse operational paradigm, it is characterised in that: described to cause data inaccurate
True event are as follows: after sorter carries out goods sorting to a certain warehouse compartment, warehouse compartment record once leads to data inaccuracy event；It is described
After causing data inaccuracy event to occur, the warehouse compartment of sorting and the warehouse compartment of sorting is adjacent and warehouse compartment in do not place the warehouse compartment of article,
Also record once leads to data inaccuracy event.
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| US20080243646A1 (en) * | 2007-03-30 | 2008-10-02 | Andrew Christopher Stein | Methods for proactively reconciling bin denials in inventory management environments |
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Address after: 510000 No. 1109, main tower of shipping center, No. 59, Linhai Avenue, Qianhai Shenzhen Hong Kong cooperation zone, Shenzhen, Guangdong Applicant after: Shenzhen Yuehai Global Supply Chain Co.,Ltd. Address before: 510000 No. 1109, main tower of shipping center, No. 59, Linhai Avenue, Qianhai Shenzhen Hong Kong cooperation zone, Shenzhen, Guangdong Applicant before: SHENZHEN YH GLOBAL SUPPLY CHAIN Co.,Ltd. |
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