CN111105129B - Detection task intelligent distribution method based on detection mechanism evaluation - Google Patents
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Abstract
The invention relates to an intelligent distribution method of detection tasks based on detection mechanism evaluation, which comprises the following steps: 1. inputting a detection plan; 2. screening by a detection mechanism for detecting the types of materials in the plan and the detection requirements of the current-stage national network distribution materials; 3. acquiring the service quality of each detection mechanism, and acquiring data of the real-time bearing capacity of the detection mechanism and the real-time bearing capacity of the logistics; 4. calculating a detection task allocation model by using three indexes; 5. outputting a sampling inspection strategy; the invention is suitable for distribution material detection task provincial level and nationwide detection task distribution. Compared with the traditional manual distribution method based on experience, the method has the advantages of intelligent planning, science and stability, and is more efficient and controllable in management of detection tasks and utilization of detection resources.
Description
Technical Field
The invention belongs to the field of dynamic planning of resources, and particularly relates to a novel intelligent distribution method and system of detection tasks based on evaluation of detection mechanisms, which are mainly used for distribution of detection tasks and optimization of distribution strategies of national power grid electric power material quality detection.
Background
The national power grid company continuously increases the power of the power grid material spot check, the management range of the material spot check is continuously enlarged, and the management and control power is continuously enhanced. Throughout the inspection process, the determination of inspection tasks and their allocation is an important task. However, the detection mechanism and the detection resource are lack to be shared at the present stage, and the detection task is distributed by manpower and lacks scientific guidance, so that the phenomenon of low detection efficiency and high cost at the present stage is caused. The staff is liberated from the heavy planning task, the intellectualization and automation of the distribution of the material detection task are realized, the distribution efficiency of the inspection and delivery and the timeliness of the detection task can be effectively improved, and the resource utilization rate of the detection base can be improved.
The method comprehensively considers the characteristics of detection task allocation under a national grid company provincial and urban two-stage detection center system, designs the intelligent detection task allocation method and system based on detection mechanism evaluation, and realizes high benefit, high efficiency and high reliability of detection task allocation.
Disclosure of Invention
With the construction of a two-stage detection center system of a national power grid in each province in recent years, the task amount of detection work of distribution materials is more and more increased. The traditional mode of manually distributing detection tasks to each detection center according to an empirical mode shows the problems of low efficiency, poor scientificity and poor reliability. The intelligent distribution of the detection tasks mainly refers to the distribution of the detection tasks based on the historical data accumulated by each detection mechanism and the informatization system and the state data shared by the detection mechanisms in real time, and the traditional manual distribution to the scientific intelligent distribution are realized, so that the high benefit, the high efficiency and the high reliability of the detection process are realized.
The invention provides an intelligent distribution method and an intelligent distribution system for detection tasks based on detection mechanism evaluation.
The invention adopts the following technical scheme: an intelligent distribution method of detection tasks based on detection mechanism evaluation comprises the following steps:
s1: inputting a detection plan including a material type, a material model, a supplier, a winning batch, a arriving batch, a sample number, a storage position and a detection grade;
s2: screening by a detection mechanism for detecting the types of materials in the plan and the detection requirements of the current-stage national network distribution materials;
s3: for the detection mechanisms screened in S2, acquiring the service quality of each detection mechanism, and acquiring data of the real-time bearing capacity of the detection mechanism and the real-time bearing capacity of the logistics;
s4: performing detection task allocation model calculation on the three indexes calculated in the step S3;
s5: and finally, outputting the sampling inspection strategy by the calculation result of the step S4.
The analysis of the spot check plan in the S1 comprises the steps of obtaining the detection energy levels of the material types, the material models, the suppliers, the winning batches, the arrival batches, the sample numbers, the storage positions and the related requirements in the spot check plan.
S2, analyzing the material types and detection requirements, wherein the method comprises the following steps of:
(1) Obtaining detection material types and detection grades in a detection plan;
(2) Converting the detection grade in the step (1) into a corresponding experimental detection item;
(3) Screening all detection mechanisms with the materials and corresponding experimental projects;
(4) And selecting the detection mechanism with the 4 detection mechanisms before the completion time of the detection mechanism according to the predicted completion time, and outputting the detection mechanism.
In S3, the calculation and analysis of the service quality, the real-time bearing capacity and the real-time bearing capacity of the logistics of the detection mechanism include:
(1) The method for obtaining the service quality of the detection mechanism mainly comprises the detection mechanism and the service quality Q Clothes with a pair of wearing articles ；
(2) Acquiring detection efficiency P of detection mechanism Inspection and detection And waiting time T Etc ；
(3) Acquiring the fastest delivery time T of a detection mechanism Matching with 。
The calculation analysis of the detection task allocation model in S4 includes:
(1) Detection efficiency P using detection center Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection ；
(2) Single test sample distribution, calculation of T of each test mechanism Inspection and detection Detecting time, selecting the shortest detecting time detecting mechanism O i Then recalculate the waiting time T of the detection mechanism i ；
(3) Cycling (2) until all the samples are distributed, and obtaining the quantity D of the samples distributed by each detection mechanism i ；
(4) Removing the detection mechanism with small sample number from the detection mechanisms, and distributing the detection mechanism to other detection mechanisms;
(5) The total number of samples for all dispensing detection mechanisms and the expected start detection time and expected completion time are calculated.
The sampling inspection strategy output in the S5 comprises the type of the delivered materials, the type of the materials, the storage position, the distribution detection mechanism, the expected starting detection time and the expected finishing time.
The method for acquiring the detection material types and the detection grades in the detection plan and converting the detection grades into corresponding experimental detection items comprises the following steps:
(1) The acquired detection demand level J and the material category M;
(2) Searching a material M in a network material quality detection capability standard library, and executing (3) if the material exists; if the material category does not exist, directly returning to the material category does not exist, and ending the distribution calculation;
(3) And searching all corresponding detection items G in the material quality detection capability standard library through the material type M and the detection requirement level J.
The detection mechanism completion time is calculated by using the waiting time and the detection time, and the method comprises the following steps:
(1) Obtaining the detection efficiency P of the detection center Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection The calculation method is as follows:
T inspection and detection ＝D Inspection and detection ×P Inspection and detection +T Etc
(2) Detection completion time T of each detection mechanism h The calculation method is as follows:
(3)T etc For waiting time, T Matching with For delivery time, T Inspection and detection Time required for detection
Calculating by using the planned expected completion time and the actual completion time to obtain the service quality Q service corresponding to the detection mechanism;
calculating the maximum delivery time T by adding the delivery time calculated by the delivery efficiency and the distance and the actual delivery waiting time Matching with 。
Further, when the detection mechanism redistributes the samples of the removed detection mechanism, the removed detection mechanism is removed and distributed on the basis of the distribution, and the method comprises the following steps:
(1) Removing the removed detection mechanism from the screened detection to generate a residual detection mechanism combination;
(2) Calculating various weights and parameters of the distributed samples;
(3) And re-distributing according to the calculation method of the intelligent distribution model of the detection task.
The invention has the positive effects that: the invention is suitable for distribution material detection task provincial level and nationwide detection task distribution. Compared with the traditional manual distribution method based on experience, the method has the advantages of intelligent planning, science and stability, and is more efficient and controllable in management of detection tasks and utilization of detection resources.
Drawings
FIG. 1 is a workflow diagram of an intelligent distribution method of detection tasks based on detection mechanism evaluation according to the present invention;
FIG. 2 is a design diagram of a detection task intelligent distribution method model based on detection mechanism evaluation;
FIG. 3 is a schematic diagram of the time difference calculation weights according to the present invention.
Detailed Description
The present invention will be described in detail with reference to examples and drawings. The scope of the invention is not limited to the examples, and any modifications within the scope of the claims are within the scope of the invention.
As shown in fig. 1 and 2, the invention comprises the following steps:
s1: inputting a detection plan mainly comprising a material type, a material model, a supplier, a winning batch, a arriving batch, a sample number, a storage position and a detection grade;
s2: screening by a detection mechanism for detecting the types of materials in the plan and the detection requirements of the current-stage national network distribution materials;
s3: for the detection mechanisms screened in S2, acquiring the service quality of each detection mechanism, and acquiring data of the real-time bearing capacity of the detection mechanism and the real-time bearing capacity of the logistics;
s4: performing detection task allocation model calculation on the three indexes calculated in the step S3;
s5: finally S4, outputting the sampling inspection strategy by the calculation result
And (3) analyzing the spot check plan in the step (S1) to obtain the detection energy levels of the material types, the material models, the suppliers, the winning batches, the arrival batches, the sample numbers, the storage positions and the related requirements in the spot check plan.
Analyzing the material types and the detection requirements in the step S2, specifically comprising the following steps:
s21: acquiring detection material types and detection grades in the detection plan in the step S1;
s22: converting the detection grade in the step S1 into a corresponding experimental detection item;
s22: screening all detection mechanisms with the materials and corresponding experimental projects;
s23: according to the detection completion time T of each detection mechanism h The calculation method is as follows:
T etc Waiting time, T Matching with Delivery time, T Inspection and detection Time required for detection
S24: and selecting the detection mechanism with the 4 detection mechanisms before the completion time of the detection mechanism, and outputting the detection mechanism.
In step S3, the calculation and analysis of the service quality, the real-time bearing capacity and the real-time bearing capacity of the logistics of the detection mechanism include:
s31: the method for obtaining the service quality of the detection mechanism mainly comprises the detection mechanism and the service quality Q Clothes with a pair of wearing articles ；
S32: acquiring detection efficiency P of detection mechanism Inspection and detection And waiting time T Etc ；
S33: acquiring the fastest delivery time T of a detection mechanism Matching with 。
The calculation and analysis of the intelligent allocation model of the detection task in the step S4 comprise the following steps:
s41: using the detection efficiency P of the detection center obtained in S3 Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection The calculation method is as follows:
T inspection and detection ＝D Inspection and detection ×P Inspection and detection +T Etc
T Etc For waiting time, T Matching with For delivery time, T Inspection and detection For detecting the required time, D Inspection and detection To detect the amount of supplies;
s42: single test sample distribution, calculation of T of each test mechanism Inspection and detection Detecting time, selecting the shortest detecting time detecting mechanism Oi, and then recalculating the waiting time Ti of the detecting mechanism;
s43: and S42, circulating until all the samples are distributed, and acquiring the quantity Di of the samples distributed by each detection mechanism.
S44: and removing the detection mechanism with small sample quantity from the detection mechanisms, and distributing the detection mechanism to other detection mechanisms. Less than 5 and less than one-fourth of the total number of dispensed samples were counted, labeled as reject detection mechanism.
S45: the total number of samples for all dispensing detection mechanisms and the expected start detection time and expected completion time are calculated.
In step S5, the sampling inspection policy is generated by using the calculation result in step S4, and the sampling inspection policy mainly includes the distribution material type, the material model, the storage location, the distribution detection mechanism, the expected start detection time and the expected completion time.
The step of converting the detection level into a corresponding experimental detection item in step S22 includes:
s221, acquiring the detection demand level J and the material category M acquired in the step S21;
s222, searching a material M in a network material quality detection capability standard library, and executing S223 if the material exists; if the material category does not exist, directly returning to the material category does not exist, and ending the distribution calculation;
s223: and searching all corresponding detection items G in the material quality detection capability standard library through the material type M and the detection requirement level J.
The detection mechanism completion time is calculated by using the waiting time and the detection time, and the method comprises the following steps:
(1) Obtaining the detection efficiency P of the detection center Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection The calculation method is as follows:
T inspection and detection ＝D Inspection and detection ×P Inspection and detection +T Etc
(2) Detection completion time T of each detection mechanism h The calculation method is as follows:
(3)T etc Waiting time, T Matching with Delivery time, T Inspection and detection The time required for detection.
Calculating by using the planned expected completion time and the actual completion time to obtain the service quality Q corresponding to the detection mechanism Clothes with a pair of wearing articles ；
Calculating the maximum delivery time T by adding the delivery time calculated by the delivery efficiency and the distance and the actual delivery waiting time Matching with 。
When the detection mechanism redistributes the samples of the rejecting mechanism, the rejecting mechanism is removed and the samples are distributed on the basis of the distributed samples, and the method is as follows:
(1) Removing the removing detection mechanism from the detection selected by the screening to generate a residual detection mechanism combination;
(2) Calculating various weights and parameters of the distributed samples;
(3) And re-distributing according to the calculation method of the intelligent distribution model of the detection task.
The invention mainly adopts big data analysis technology, decision tree technology and dynamic programming technology to realize scientific and effective analysis of historical detection mechanism data, detection mechanism detection capability and detection mechanism bearing capability, extracts the internal association relationship of the data and the association relationship between the data and results, evaluates the service quality of the detection mechanism, and utilizes the sampling inspection strategy to sample the types and the quantity of the materials and test items required to be carried out to match with the real-time detection capability and the detection bearing capability of the detection mechanism at the present stage. And determining a detection mechanism meeting the requirements, and finally determining the task allocation of the detection mechanism through the sample storage position and the service quality of the detection mechanism.
Detection mechanism matching calculation: the detection mechanism matching calculation mainly aims at searching a detection mechanism meeting detection requirements from the sampling inspection scheme, and the main calculation process is as follows:
input data: the spot check plans (mainly including material names, material models, manufacturers, winning batches, arrival batches and sample amounts) are as follows:
detection mechanism data: the device mainly comprises a detection mechanism and a level which corresponds to a detection material institute and can carry out detection test.
| Sequence number | Detection | Detection level | |
| 1 | | B | |
| 2 | XXXX2 | B | |
| 3 | XXXX3 | A | |
| 4 | XXXX4 | C | |
| … | … | … |
And (3) data output: the total of the secondary spot inspection is 220KV transformer 90, and the 90 detection mechanisms are divided into 4 companies and 6 batches. Basic detection requirement data can be obtained according to the requirements of 10% for A-level detection, 80% for B-level detection and 10% for C-level detection. And the attached data table is as follows:
namely, the sampling inspection materials need 13A-stage detection devices, 64B-stage detection devices and 13C-stage detection devices.
Mechanism meeting the demand: the matching of the detection mechanism is as follows for the generated detection requirements and the detection capability of the detection mechanism.
| Sequence number | Detection mechanism | Class A | Class | Class C | |
| 1 | XXXX1 | 64 | 13 | ||
| 2 | XXXX2 | 64 | 13 | ||
| 3 | XXXX3 | 13 | 64 | 13 | |
| 4 | XXXX4 | 13 | |||
| … | … | … | … | … |
Detecting task allocation efficiency calculation: the detection task allocation high-efficiency calculation mainly takes the sample collection time as the principle when the detection task is allocated, namely the high-efficiency of the detection task completion is ensured. And the real-time data of the detection mechanism is subjected to task simulation distribution according to the carrying capacity and the detection efficiency by the real-time data of the detection mechanism and the spot check strategy, and the sample collection efficiency of the detection mechanism is calculated, so that the calculation is performed in a high-efficiency principle. The main calculation process is as follows:
input data: mainly comprises a material name, a material model, a manufacturer, a winning batch, a receiving batch and a sample number. The following table:
detection mechanism data:
first, considering a detection item with relatively deficient detection resources, such as a class A detection item, 13 devices in 90 devices to be detected directly need to be distributed to XXXX3 for detection. The real-time bearer capability after delivery is as follows:
then, considering the items with a relatively small number of tests, such as class C test items, class C test items are 13 in total, and according to the fastest efficiency calculation, XXXX1 needs to be completed after 25 days, XXXX2 needs to be completed after 9 days, XXXX3 needs to be completed after 10 days, and XXXX4 needs to be completed after 2 days. The 12-day distribution transformer that needed the class C test item is dispatched to XXXX4. The real-time bearing capacity of the detection mechanism at this time is as follows:
the last 64 distribution transformers need to be subjected to B-stage detection items, and XXXX1, XXXX2 and XXXX3 can be carried out on the B-stage detection items. And distributing the 64 distribution transformers by adopting a dynamic programming calculation method. The process is as follows:
the detection amount of each detection mechanism is calculated by taking the detection mechanism with the largest waiting days as a criterion. As shown, calculated on a XXXX1 day 22 basis:
| sequence number | Detection mechanism | Calculation | Measurement amount | |
| 1 | XXXX1 | (22-22)*4 | 0 table | |
| 2 | XXXX2 | (22-8)*5 | 70 tables | |
| 3 | XXXX3 | (22-7)*6 | 90 tables | |
| … | … | … |
Then, the sum of the detection amounts of the detection mechanisms is judged to be larger than the demand. If the inspection volume is greater than the demand, no inspection sub-package of XXXX1 is required. Otherwise the detection mechanism is required to be added to the task allocation. Due to this calculation
(75+90)＞64
Then there is no need for XXXX1 to be added to the task allocation this time. Thus, two detection mechanisms XXXX2 and XXXX3 are left, the above operation is repeated again, the total detection amount of the two detection mechanisms is 6, and if the total detection amount is less than 6, the task allocation is carried out by the two detection mechanisms.
Task allocation process: firstly, the excess is discharged, namely, after 8 XXXX3 is allocated, the waiting time of XXXX2 and XXXX3 is the same, and then, the daily full allocation is carried out on the two detection mechanisms, namely, the sample collection time of the two detection mechanisms is calculated at the same time.
Sample collection time (day) = (64-6)/(5+6) =5.3 (day)
Namely, the maximum sample collection time is 5.3 days, the detection mechanism distributes the B-level detection amount as follows:
XXXX2 allocation = 5 x 5.3 = 27 stations
The B-stage detection of XXXX3 is: (6+1) 5.3=37 (table)
And (3) data output: the total of the secondary spot inspection is 220KV transformer 90, and the 90 detection mechanisms are divided into 4 companies and 6 batches. Basic detection requirement data can be obtained according to the requirements of 10% for A-level detection, 80% for B-level detection and 10% for C-level detection. The workload is mainly borne by XXXX2, XXXX3 and XXXX4, and the final sample collection time is 14 working days. The results are as follows:
calculating distribution cost: in the delivery process, the delivery time is also an important factor affecting the sample collection efficiency, so that the delivery problem of the detection mechanism and the warehouse quality inspection is fully considered, when the detection mechanism is selected, the closer the detection mechanism is to the storage place, the higher the selected priority is, the closer the principle is the main principle of reducing the logistics period and the logistics cost, the maximum reliability and the lowest cost of logistics are ensured, and the reliability of the detection process is ensured to a certain extent.
Input data: the detection plan and the storage condition thereof mainly comprise a material name, a material model, a manufacturer, a winning batch, a arriving batch and a storage position, and the data are as follows:
logistics distribution real-time condition of each detection mechanism and storage quality inspection
The calculation process comprises the following steps: this time, taking the distribution of 64 distribution transformers as a sample, the XXXX2 distributes 64 distribution transformers to different detection mechanisms, and the distribution time is calculated as follows:
delivery time= (total delivery/single delivery) delivery cycle + waiting time
The result center library of data output delivers the materials to different detection centers for the required delivery time length, which is shown as follows:
service optimization principle calculation: the service optimal calculation is to perform data analysis on the historical detection data of the detection equipment aiming at different detection institutions so as to evaluate the detection service quality of the products by the different detection institutions. The principle of distributing detection tasks by considering detection services and detection quality provided by different detection mechanisms is that detection mechanisms with good service quality of the detection mechanisms are selected to distribute the detection tasks as far as possible under the allowable condition. The service quality evaluation of different detection institutions is formed mainly through the detection data of the detection institution history by utilizing a data analysis principle, and analysis is carried out through an evaluation result.
Input data: the historical test results mainly comprise the estimated completion time, the actual completion time and the like of the spot check plan.
The calculation process comprises the following steps: the historical detection plan data are obtained, and the task completion time difference Q of each time is calculated by the following calculation method:
m is the predicted completion time, N is the actual completion time
The closer the calculation is to the present time, the higher the weight, the weighted time difference is calculated, and the weight is removed as shown in fig. 3.
The total quality of service F is then calculated as follows:
outputting information
Quality of service of the detection mechanism: mainly comprises the evaluation of the service quality of a detection mechanism. The results are as follows:
calculating a distribution strategy: the distribution strategy is mainly calculated by fully considering the efficiency, the distribution cost and the service quality on the basis of distribution matching. The main idea is to add the service quality factor into the time period in a certain proportion based on the principle of fastest sample receiving period, and finally find the optimal time efficiency.
Inputting information: basic delivery strategy
Delivery cost:
quality of service:
the calculation process comprises the following steps: the efficiency cycle refers to the cycle required for assignment of tasks to the detection mechanism and the reflection of one comprehensive effect of the detection quality of the detection mechanism. The system mainly comprises the sum of a detection period and a distribution period, is influenced by the service quality of a detection mechanism, and has the advantages of higher detection service quality, smaller efficiency period, poorer detection service quality and larger efficiency period. The calculation mode is as follows:
efficiency period= (detection period + delivery period) ×quality of service/100
Quality of service/100+delivery period =quality of service/100
Firstly, dividing the service quality measuring period into a detecting period and a distributing period, and the result is as follows:
the weighted delivery cycle is calculated as follows:
calculating the total difference between the logistics waiting time and the distribution waiting time to obtain the waiting time, wherein the calculating mode is as follows:
if the detection waiting time is greater than the logistics waiting time, the detection waiting time is the logistics waiting time, otherwise, the detection waiting time is unchanged. The new detection latency is obtained as follows:
the average sample collection time of each distribution transformer, i.e., sample collection efficiency=detection weighting efficiency+distribution weighting efficiency, is calculated. The results were as follows:
and then calculating a detection task allocation strategy of availability through detection task allocation high efficiency.
The post-condition of the distributed A-level detection task is as follows:
after the C-stage detection task is distributed, the following steps are performed:
after the B-stage detection task is distributed, the following steps are performed:
outputting data: and outputting data as a final distribution strategy and a sample receiving period.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. The intelligent distribution method for the detection tasks based on the detection mechanism evaluation is characterized by comprising the following steps of:
s1: inputting a detection plan including a material type, a material model, a supplier, a winning batch, a arriving batch, a sample number, a storage position and a detection grade;
s2: screening by a detection mechanism for detecting the types of materials in the plan and the detection requirements of the current-stage national network distribution materials;
s3: for the detection mechanisms screened in S2, acquiring the service quality of each detection mechanism, and acquiring data of the real-time bearing capacity of the detection mechanism and the real-time bearing capacity of the logistics;
in S3, the calculation and analysis of the service quality, the real-time bearing capacity and the real-time bearing capacity of the logistics of the detection mechanism include:
(1) Acquiring quality of service of detection mechanism, including detection mechanism and quality of service Q Clothes with a pair of wearing articles ；
(2) Acquiring detection efficiency P of detection mechanism Inspection and detection And waiting time T Etc ；
(3) Acquiring the fastest delivery time T of a detection mechanism Matching with ；
S4: performing detection task allocation model calculation on the three indexes calculated in the step S3;
the calculation analysis of the detection task allocation model in S4 includes:
(1) By detecting efficiency P of the detecting mechanism Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection ；
(2) Single test sample distribution, calculation of T of each test mechanism Inspection and detection Detecting time, selecting the shortest detecting time detecting mechanism O i Then recalculate the waiting time T of the detection mechanism i ；
(3) Cycling (2) until all the samples are distributed, and obtaining the quantity D of the samples distributed by each detection mechanism i ；
(4) Removing the detection mechanism with small sample number from the detection mechanisms, and distributing the detection mechanism to other detection mechanisms;
(5) Calculating the total number of samples of all the dispensing detection mechanisms, and an expected start detection time and an expected completion time;
s5: and finally, outputting the sampling inspection strategy by the calculation result of the step S4.
2. The intelligent distribution method for detection tasks based on detection mechanism evaluation according to claim 1, wherein the analysis of the detection plan in S1 includes obtaining detection levels of the material category, the material model, the supplier, the winning lot, the arrival lot, the sample number, the storage location and the related requirements in the detection plan.
3. The intelligent distribution method of detection tasks based on detection mechanism evaluation according to claim 1, wherein the analysis of the material types and the detection requirements in S2 comprises the following steps:
(1) Obtaining detection material types and detection grades in a detection plan;
(2) Converting the detection grade in the step (1) into a corresponding experimental detection item;
(3) Screening all detection mechanisms with the materials and corresponding experimental projects;
(4) And selecting the detection mechanism with the 4 detection mechanisms before the completion time of the detection mechanism according to the predicted completion time, and outputting the detection mechanism.
4. The intelligent distribution method for detection tasks based on detection mechanism evaluation according to claim 1, wherein the sampling inspection strategy output in S5 comprises distribution material type, material model, storage location, distribution detection mechanism, expected start detection time and expected completion time.
5. The intelligent distribution method for detection tasks based on detection mechanism evaluation according to claim 3, wherein the steps of obtaining the detection material types and the detection grades in the detection plan and converting the detection grades into corresponding experimental detection items comprise the following steps:
(1) The acquired detection demand level J and the material category M;
(2) Searching a material M in a national net material quality detection capability standard library, and executing the step (3) if the material exists; if the material category does not exist, directly returning to the material category does not exist, and ending the distribution calculation;
(3) And searching all corresponding detection items G in the material quality detection capability standard library through the material type M and the detection requirement level J.
6. A method for intelligently distributing detection tasks based on detection mechanism evaluation according to claim 3, wherein the detection mechanism completion time is calculated by using the waiting time and the detection time, and the steps comprise:
(1) Acquiring detection efficiency P of detection mechanism Inspection and detection Waiting time T Etc Calculating the detection time T Inspection and detection The calculation method is as follows:
T inspection and detection ＝D Inspection and detection ×P Inspection and detection +T Etc
D Inspection and detection To detect the amount of supplies;
(2) Detection completion time T of each detection mechanism h The calculation method is as follows:
T etc For waiting time, T Matching with For delivery time, T Inspection and detection Time required for detection.
7. The intelligent distribution method for detection tasks based on detection mechanism evaluation according to claim 1, wherein the service quality Q corresponding to the detection mechanism is obtained by calculating the planned expected completion time and the actual completion time Clothes with a pair of wearing articles The method comprises the steps of carrying out a first treatment on the surface of the Calculating the maximum delivery time T by adding the delivery time calculated by the delivery efficiency and the distance and the actual delivery waiting time Matching with 。
8. The intelligent distribution method for detection tasks based on detection mechanism evaluation according to claim 7, wherein when the detection mechanism distributes the samples of the removed detection mechanism again, the removed detection mechanism is removed on the basis of the distribution, and the distribution is performed, the method is as follows:
(1) Removing the removed detection mechanism from the screened detection to generate a residual detection mechanism combination;
(2) Calculating various weights and parameters of the distributed samples;
(3) And re-distributing according to the calculation method of the intelligent distribution model of the detection task.
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