CN107688907A - A kind of goods and materials sampling observation method based on queue layered shaping mechanism - Google Patents

A kind of goods and materials sampling observation method based on queue layered shaping mechanism Download PDF

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Publication number
CN107688907A
CN107688907A CN201710788749.0A CN201710788749A CN107688907A CN 107688907 A CN107688907 A CN 107688907A CN 201710788749 A CN201710788749 A CN 201710788749A CN 107688907 A CN107688907 A CN 107688907A
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goods
materials
supplier
data
sampling observation
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CN107688907B (en
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冯曙明
祁建
胡天牧
凌绍伟
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State Grid Jiangsu Electric Power Co Ltd
Jiangsu Electric Power Information Technology Co Ltd
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State Grid Jiangsu Electric Power Co Ltd
Jiangsu Electric Power Information Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0633—Workflow analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/546—Message passing systems or structures, e.g. queues
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply

Abstract

The invention discloses providing a kind of goods and materials based on queue layered shaping mechanism to inspect method by random samples, based on queue layered shaping mechanism, it would be desirable to the batch sampling observation planning data layered shaping of multiple batches of processing；Carry out sizing screening processing and mark around 5 big balance rules, batch sampling observation data classified according to different identification, most meet the data generation sampling observation task of generation sampling observation task condition at last, by by high-volume data storage in the buffer；Hierarchical layered is handled respectively by autonomous channel, each level all refers to thread pool and multiple independent queue passage processing distribution data, triggered by self-timing, data automatic classification is lost respectively into corresponding queue, thread pool thread obtains queuing data and carries out logical calculated digestion automatically or carry out processing digestion again into next level.Present invention reduction interacts with database, improves the speed of stream compression, the efficiency and accuracy rate of lifting goods and materials sampling observation.

Description

A kind of goods and materials sampling observation method based on queue layered shaping mechanism
Technical field
It is specifically a kind of to be based on queue layered shaping machine the present invention relates to a kind of method inspected by random samples to Power Material The goods and materials sampling observation method of system.
Technical background
The goods and materials of Power Material department buying are related to thousands of kinds, and the sampling check for quality for goods and materials is indispensable process.Due to The species of sampling observation is more, and process is cumbersome, so when sampling observation is concentrated in the extensive supply of material, is brought very to inspection unit in the case of this kind Big pressure, then the shortage due to human resources, occurs work accumulation during sampling observation unavoidably, even using conventional letter The processing of breath system is also required to artificial many operations of doing, in addition during there is mistake.
The content of the invention
It is an object of the invention to provide a kind of goods and materials based on queue layered shaping mechanism to inspect method by random samples, for each level Open autonomous channel to handle respectively, so as to lift the efficiency and accuracy rate of goods and materials sampling observation.
The purpose of the present invention is achieved through the following technical solutions：
A kind of goods and materials sampling observation method based on queue layered shaping mechanism, it is characterised in that this method comprises the following steps：
1）Based on queue layered shaping mechanism, it would be desirable to the batch sampling observation planning data layered shaping of multiple batches of processing, place Reason rule includes following 5 big balance rules：New supplier's balance is regular, old supplier's balance is regular, for non-cancellation goods and materials Releveling, city's balance of company level, provincial company level balance；
2）Sizing screening processing and mark are carried out around 5 big balance rules, batch sampling observation data are classified according to different identification, most Meet at last generation sampling observation task condition data generation sampling observation task, by by high-volume data storage in the buffer；
3）Hierarchical layered is handled respectively by autonomous channel, and each level all refers to thread pool（TheadPool）It is and multiple only Vertical queue（Queue）Passage processing distribution data, are triggered by self-timing, data automatic classification lost respectively into corresponding team Row, thread pool thread acquisition queuing data carries out logical calculated digestion automatically or the next level of entrance carries out processing and disappeared again Change, reduction interacts with database, improves the speed of stream compression.
Further, comprise the following steps that：
Step 1：One layer of classification processing is done to the old and new supplier according to model algorithm
Disaggregated model is formulated as dimension using the batch that calls for bid, supplier, name of product, the sampling observation number that output is calculated according to model is made Judge the old and new supplier for foundation, it is regular as follows：
Model calculates output>=2, old supplier；Model calculates output<2, new supplier；
Step 2：Two layers of releveling processing
Releveling processing, judges non-cancellation goods and materials, then cancels the plan if " 01- applications are deleted " or " 02- applications are deleted "；
Judge non-cancellation goods and materials, during if non-reserved state, each goods and materials with the presence or absence of being captured in the sampling observation batch of first 3 months, If it is present cancel a plan.If it does not, detection goods and materials whether there is in " not possessing detection material table ", if it does, Cancel the plan.If there is no in " not possessing detection material table ", then " cable goods and materials " are determined whether, if it is, judging Whether length is less than 1KM or 100m, if it is cancels the plan；
Step 3：Three layers of processing are done to city-level using thread
Using thread city-level goods and materials are done with three layers of processing, it is first determined whether same districts and cities be present with supplier's multi-product, If it does not exist, then into step 4；
Judge same districts and cities with supplier with the plan entry of name of product " data source " whether be " prefecture-level company occupy with supply Plan ", contrasts same districts and cities with supplier and the purchase quantity with the goods and materials in name of product, if purchase quantity is different, retains The most goods and materials entry of purchase quantity；
Relatively more estimated to implement the time as purchase quantity is identical, if implemented, the time is different, takes implement the time the latest one, such as Implement time identical then random reservation one, if it is contrast purchase quantity in same name of product, if purchase quantity is different, Retain the most goods and materials entry of purchase quantity；It is relatively more estimated to implement the time if purchase quantity is identical, if implementing the time not Together, implement the time the latest one is taken, it is random if the implementation time is identical to retain one；
Step 4：Final process is done using queue
The situation with supplier with name of product across the entire province is judged, if there is no the property then retained under the product Money, and goods and materials are subjected to " remarks " field and retained for 03- applications；
If there is then and by goods and materials carry out " remarks " field for 04- application retain；
Step 5：Generate sampling observation task
It is what is retained by all data records, 03- applications retain, and remarks explanation does not complete plan for last month, and this month continues executing with, Apply retaining with 04-, remarks explanation is other, and for data according to districts and cities, supplier, the record with name of product carries out differential counting Statistics, and enter following judgement：
Judge same districts and cities, same to supplier, the statistical magnitude with name of product, take minimum districts and cities, if minimum districts and cities are unique, Then by corresponding plan generation task；If not unique, then the most ground of corresponding purchase quantity is selected in minimum districts and cities City, random if the districts and cities of most purchase quantities are not uniquely to retain one, other wholes cancel a plan；If purchase number Measure that most districts and cities are unique, then retain all goods and materials under the same name of product of the supplier under the districts and cities, and by corresponding meter Draw generation task；
It is intended to middle the planned data for not meeting generation sampling observation task condition to cancel a plan, cancels reason to be " final to reject Data ".
The present invention has the beneficial effect that：
Goods and materials sampling observation is efficiently managed based on queue layered shaping mechanism, autonomous channel is opened for each level and locates respectively Reason, interacted so as to reduce with database, improve the speed of stream compression, and then lift overall performance, increase the efficiency of flow, So as to lift the efficiency and accuracy rate of goods and materials sampling observation.
Brief description of the drawings
The flow chart of Fig. 1 present invention.
Embodiment
A kind of goods and materials sampling observation method based on queue layered shaping mechanism, based on queue layered shaping mechanism, it would be desirable to locate The batch sampling observation planning data layered shaping of multiple batches of reason, processing rule include following 5 big balance rules：New supplier puts down Weighing, regular, old supplier balances rule, releveling, city's balance of company level, provincial company level for non-cancellation goods and materials balance；Surround 5 big balance rules carry out sizing screening processing and mark, and batch sampling observation data are classified according to different identification, most meet life at last Into sampling observation task condition data generate sampling observation task, by by high-volume data storage in the buffer；Hierarchical layered passes through only Vertical passage is handled respectively, and each level all refers to thread pool（TheadPool）And multiple independent queues（Queue）At passage Reason distribution data, are triggered by self-timing, and data automatic classification is lost respectively and obtains team into corresponding queue, thread pool thread Column data carries out logical calculated digestion or carries out processing digestion again into next level automatically, reduces the friendship with database Mutually, the speed of stream compression is improved.
Timed task automatic start when inspecting librarian use information system by random samples, system are automatically loaded the plan after examination ＆ verification Temporal cache, then it is identified processing according to balance rule classification, subchannel respectively；Most specific identifier data are taken out at last Inspection task generates.
Step 1：One layer of classification processing is done to the old and new supplier according to model algorithm
Disaggregated model is formulated as dimension using the batch that calls for bid, supplier, name of product, model computation rule is as follows：
New supplier：If cable class, and length is less than 1KM or 1000M, then records this goods and materials and deleted for 02- applications （Other reasonses refer to remarks explanation）, while cancel this plan.Otherwise it is unique according to same supplier's unique Product title respectively The situation of material description, with supplier with whether there was only a kind of goods and materials in stock product, retouched with the material in product with supplier State whether be less than or equal to 3 kinds, contrast with supplier with the purchase quantities of the different goods and materials in product, contrast it is estimated implement the time this 5 rule-likes carry out processing digestion successively.
Old supplier：If cable class, and length is less than 1KM or 1000M, then records this goods and materials and apply for 02- Delete（Other reasonses refer to remarks explanation）, while cancel this plan.Otherwise respectively according to being in the batch of 3 months before judgement It is no underproof situation be present, according to supplier and name of product and material query history sampling observation batch with the presence or absence of not conforming to Lattice Examined, judge the unqualified material variety of history（With the same name of product of supplier）Whether it is more than 3, judges（Same supplier, With name of product dimension）This 4 rule-like of unqualified material description quantity digests successively.
The sampling observation number that output is calculated according to model is used as foundation to judge the old and new supplier, regular as follows.
Model calculates output>=2, old supplier；Model calculates output<2, new supplier
Step 2：Two layers of releveling processing
Releveling processing, judges non-cancellation goods and materials, if " 01- applications are deleted（Put plan on record）" or " 02- applications are deleted（Its His reason refers to remarks explanation）" then cancel the plan.
Non- cancellation goods and materials are judged, if non-reserved state（Memo field is sky）When, each goods and materials whether there is first 3 months Sampling observation batch in（According to supplier+name of product+material number）Crawl, if it is present canceling a plan.If it does not, Detect goods and materials to whether there is in " not possessing detection material table ", if it does, cancelling the plan.If there is no " not possessing inspection Survey material table " in, then " cable goods and materials " are determined whether, if it is, judging whether length is less than 1KM or 100m, if it is Cancel the plan.
Step 3：Three layers of processing are done to city-level using thread
Using thread city-level goods and materials are done with three layers of processing, it is first determined whether same districts and cities be present with supplier's multi-product, If it does not exist, then into step 4.
Judge same districts and cities with supplier with the plan entry of name of product " data source " whether be " prefecture-level company occupy matches somebody with somebody Supply plan ", purchase quantity of the same districts and cities with supplier with the goods and materials in same name of product is contrasted, if purchase quantity is different, Retain the most goods and materials entry of purchase quantity；
Relatively more estimated to implement the time as purchase quantity is identical, if implemented, the time is different, takes implement the time the latest one, such as Implement time identical then random reservation one, if it is contrast purchase quantity in same name of product, if purchase quantity is different, Retain the most goods and materials entry of purchase quantity；It is relatively more estimated to implement the time if purchase quantity is identical, if implementing the time not Together, implement the time the latest one is taken, it is random if the implementation time is identical to retain one
Step 4：Final process is done using queue
The situation with supplier with name of product across the entire province is judged, if there is no the property then retained under the product Money, and goods and materials are subjected to " remarks " field and retain (other) for 03- applications.
If there is then and by goods and materials carry out " remarks " field for 04- application retain (other).
Step 5：Generate sampling observation task
It is reservation by all data records（03- applications retain (last month does not complete plan, and this month continues executing with) and 04- applications Retain (other)）Data are according to districts and cities（Region affiliation）, supplier, with name of product record carry out differential counting statistics, and Judge into following：
Judge same districts and cities, same to supplier, the statistical magnitude with name of product, take minimum districts and cities, if minimum districts and cities are unique, Then by corresponding plan generation task；If not unique, then select corresponding purchase quantity most in minimum districts and cities（By production Product are that dimension carries out statistic of classification）Districts and cities, if the districts and cities of most purchase quantities be not it is unique if it is random retain one, its He all cancels a plan.If the most districts and cities of purchase quantity are unique, retain the same name of product of the supplier under the districts and cities Under all goods and materials, and by it is corresponding plan generation task；
It is intended to middle the planned data for not meeting generation sampling observation task condition to cancel a plan, cancels reason to be " final to reject Data ".

Claims (2)

  1. A kind of 1. goods and materials sampling observation method based on queue layered shaping mechanism, it is characterised in that this method comprises the following steps：
    1）Based on queue layered shaping mechanism, it would be desirable to the batch sampling observation planning data layered shaping of multiple batches of processing, place Reason rule includes following 5 big balance rules：New supplier's balance is regular, old supplier's balance is regular, for non-cancellation goods and materials Releveling, city's balance of company level, provincial company level balance；
    2）Sizing screening processing and mark are carried out around 5 big balance rules, batch sampling observation data are classified according to different identification, most Meet at last generation sampling observation task condition data generation sampling observation task, by by high-volume data storage in the buffer；
    3）Hierarchical layered is handled respectively by autonomous channel, and each level all refers to thread pool and multiple independent queue passages Processing distribution data, are triggered by self-timing, and data automatic classification is lost respectively and obtained into corresponding queue, thread pool thread Queuing data carries out logical calculated digestion or carries out processing digestion again into next level automatically, reduces the friendship with database Mutually, the speed of stream compression is improved.
  2. 2. the goods and materials sampling observation method according to claim 1 based on queue layered shaping mechanism, it is characterised in that specific step It is rapid as follows：
    Step 1：One layer of classification processing is done to the old and new supplier according to model algorithm
    Disaggregated model is formulated as dimension using the batch that calls for bid, supplier, name of product, the sampling observation number that output is calculated according to model is made Judge the old and new supplier for foundation, it is regular as follows：
    Model calculates output>=2, old supplier；Model calculates output<2, new supplier；
    Step 2：Two layers of releveling processing
    Releveling processing, judges non-cancellation goods and materials, then cancels the plan if " 01- applications are deleted " or " 02- applications are deleted "；
    Judge non-cancellation goods and materials, during if non-reserved state, each goods and materials with the presence or absence of being captured in the sampling observation batch of first 3 months, If it is present cancel a plan；
    If it does not, detection goods and materials whether there is in " not possessing detection material table ", if it does, cancelling the plan；
    If there is no in " not possessing detection material table ", then " cable goods and materials " are determined whether, if it is, whether judging length Less than 1KM or 100m, if it is cancel the plan；
    Step 3：Three layers of processing are done to city-level using thread
    Using thread city-level goods and materials are done with three layers of processing, it is first determined whether same districts and cities be present with supplier's multi-product, If it does not exist, then into step 4；
    Judge same districts and cities with supplier with the plan entry of name of product " data source " whether be " prefecture-level company occupy with supply Plan ", contrasts same districts and cities with supplier and the purchase quantity with the goods and materials in name of product, if purchase quantity is different, retains The most goods and materials entry of purchase quantity；
    Relatively more estimated to implement the time as purchase quantity is identical, if implemented, the time is different, takes implement the time the latest one, such as Implement time identical then random reservation one, if it is contrast purchase quantity in same name of product, if purchase quantity is different, Retain the most goods and materials entry of purchase quantity；It is relatively more estimated to implement the time if purchase quantity is identical, if implementing the time not Together, implement the time the latest one is taken, it is random if the implementation time is identical to retain one；
    Step 4：Final process is done using queue
    The situation with supplier with name of product across the entire province is judged, if there is no the property then retained under the product Money, and goods and materials are subjected to " remarks " field and retained for 03- applications；
    If there is then and by goods and materials carry out " remarks " field for 04- application retain；
    Step 5：Generate sampling observation task
    It is what is retained by all data records, 03- applications retain, and remarks explanation does not complete plan for last month, and this month continues executing with, Apply retaining with 04-, remarks explanation is other, and for data according to districts and cities, supplier, the record with name of product carries out differential counting Statistics, and enter following judgement：
    Judge same districts and cities, same to supplier, the statistical magnitude with name of product, take minimum districts and cities, if minimum districts and cities are unique, Then by corresponding plan generation task；If not unique, then the most ground of corresponding purchase quantity is selected in minimum districts and cities City, random if the districts and cities of most purchase quantities are not uniquely to retain one, other wholes cancel a plan；If purchase number Measure that most districts and cities are unique, then retain all goods and materials under the same name of product of the supplier under the districts and cities, and by corresponding meter Draw generation task；
    It is intended to middle the planned data for not meeting generation sampling observation task condition to cancel a plan, cancels reason to be " final to reject Data ".
CN201710788749.0A 2017-09-05 2017-09-05 Material sampling inspection method based on queue layering processing mechanism Active CN107688907B (en)

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