CN105005677A - Equipment consumption rule analysis system based on consumption data - Google Patents
Equipment consumption rule analysis system based on consumption data Download PDFInfo
- Publication number
- CN105005677A CN105005677A CN201510555363.6A CN201510555363A CN105005677A CN 105005677 A CN105005677 A CN 105005677A CN 201510555363 A CN201510555363 A CN 201510555363A CN 105005677 A CN105005677 A CN 105005677A
- Authority
- CN
- China
- Prior art keywords
- equipment
- consumption
- data
- analysis module
- index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an equipment consumption rule analysis system based on consumption data, and solves the problems of aerial material fund waste and inaccurate ordering goods. The scheme is as follows: the system comprises an equipment using efficiency analysis module and a consumption rule analysis module, wherein the equipment using efficiency analysis module calculates the reliability index, the supportability index and the maintainability index of equipment through the logging of data, and analyzes the support capability of different units using the same equipment by utilizing the consumption data of organization units; the consumption rule analysis module analyzes the consumption rule of the equipment according to the method of an organization unit consumption rule, a single equipment consumption rule and consumption distribution of the equipment at different life stages. According to the equipment consumption rule analysis system based on the consumption data, provided by the invention, by utilizing the analysis on the equipment consumption data and the prediction for a subsequent ordering model, the aim of analyzing the equipment consumption rule is completed, and the deficiencies of large aerial material consumption and poor accuracy of ordering goods are remedied.
Description
Technical field
The present invention relates to the technical field of air materiel consumption data analysis statistical, particularly a kind of equipment consumption law-analysing system based on consumption data.
Background technology
At present, also exist to order goods in Air materiel support department and still exist with the situation of experience, empirical ordering method lacks theory support and simulating, verifying, easily causes the waste of boat aptitude gold, and on the other hand, air materiel consumption amount is very big, card No lacks again statistical study means to ensure the accuracy of ordering goods, and causes consumption law indefinite, the situation that consumption trend is not easily held, therefore, be necessary to develop the means of the consumption data of boat material being carried out to effective analytic statistics.
Summary of the invention
For above-mentioned situation, for overcoming the defect of prior art, the object of the present invention is to provide a kind of equipment consumption law-analysing system based on consumption data, efficiently solves the gold waste of boat aptitude and inaccurate problem of ordering goods.
Its technical scheme solved is, comprise equipment effective utilization analysis module and consumption law analysis module, described equipment effective utilization analysis module is by the typing of data, calculate the reliability index of equipment, protection index and Maintainability index, utilize the consumption data of organic unit simultaneously, the supportability of the not commensurate using equipment of the same race is analyzed;
The consumption law of method to equipment that described consumption law analysis module distributes in the consumption of different lifetime stage according to organic unit's consumption law, individual event equipment consumption rule and equipment is analyzed.
The present invention is based on the equipment consumption law-analysing system of consumption data, utilize the prediction of the analysis of equipment consumption data and follow-up bespeak model, complete the object that equipment consumption law is analyzed, compensate for air materiel consumption amount large, the deficiency of the poor accuracy of order.
Accompanying drawing explanation
Fig. 1 is the functional structure chart of equipment consumption law-analysing system of the present invention.
Fig. 2 is equipment effective utilization analytical procedure of the present invention.
Fig. 3 is the precise time data instance table in equipment effective utilization of the present invention.
Fig. 4 is the discrepancy database data sample table in equipment effective utilization of the present invention.
Fig. 5 is the corrective maintenance data instance table in equipment effective utilization of the present invention.
Fig. 6 is the preventative maintenance data instance table in equipment effective utilization of the present invention.
Fig. 7 is the supply data sample table in equipment effective utilization of the present invention.
Fig. 8 is the reorder data sample table in equipment effective utilization of the present invention.
Fig. 9 is the data entry form (1) of equipment effective utilization of the present invention.
Figure 10 is the data entry form (2) of equipment effective utilization of the present invention.
Figure 11 is the data entry form (3) of equipment effective utilization of the present invention.
Figure 12 is the fault data table of equipment effective utilization of the present invention.
Figure 13 is that the assessment result of equipment effective utilization of the present invention exports tables of data.
Figure 14 is the reliability images outputting of the assessment result of equipment effective utilization of the present invention.
Figure 15 is that the Maintainability index of the assessment result of equipment effective utilization of the present invention exports tables of data.
Figure 16 is that the protection index of the assessment result of equipment effective utilization of the present invention exports tables of data.
Figure 17 is organic unit's consumption law analytical table of consumption law analysis module of the present invention.
Figure 18 is the Output rusults schematic diagram that different phase consumption law of the present invention is analyzed.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
Shown in existing composition graphs 1 to Figure 18, a kind of equipment consumption law-analysing system based on consumption data of the present invention, comprise equipment effective utilization analysis module and consumption law analysis module, described equipment effective utilization analysis module is by the typing of data, calculate the reliability index of equipment, protection index and Maintainability index, utilize the consumption data of organic unit simultaneously, the supportability of the not commensurate using equipment of the same race is analyzed;
The consumption law of method to equipment that described consumption law analysis module distributes in the consumption of different lifetime stage according to organic unit's consumption law, individual event equipment consumption rule and equipment is analyzed.
Fig. 2 provides the analytical procedure of equipment effective utilization, first the fault data of reaction equipment consumption, database data, maintainability data and the supply guarantee data of coming in and going out are included in the category of calculating, recycling averaging method, the effective utilization of least square method Sum Maximum Likelihood Estimate method to equipment are analyzed, and draw equipment reliability index in actual use, Maintainability index and protection index.
Described equipment effective utilization data message comprises the data of three types: fault data, mantenance data and preventative maintenance data.
Described fault data has two seed categories: precise time data and between-failures data, the input of precise time data comprises: component coding, component names, affiliated model, affiliated unit and fault origination point, as shown in Figure 3, described fault-time is the concrete calendar time recording the generation of this fault to precise time data form; Failure, MTTF is time worked aboard before this unit failure; Typing people be this record fill in people; Affiliated unit is the parts of this record and the organic unit belonging to aircraft.
Described discrepancy database data input, comprise component coding, component names, affiliated model, unit, initial time, end time, outbound number of packages, this section of time inner part cumulative operation time, specifically as shown in Figure 4, described outbound number of packages is the number of components of adding up in " initial time " and outbound in " end time "; This time inner part cumulative operation time is the net cycle time pointing out all these parts of aircraft ensured in " initial time " and " end time ".
Database data example of coming in and going out shows, in 2014 years, communication module consumes 15, period has ensured 12 airplanes, each aircraft has 1 communication module, within 2014, all aircraft cumulative flight time are 2000 hours, and therefore this time inner part cumulative operation time is 2000 hours.
Described mantenance data is divided into corrective maintenance data and preventative maintenance data, maintainability mantenance data comprises: component coding, repair location, change part time and servicing time, as described in Figure 5, the repair location of described corrective maintenance data essential record parts and servicing time, maintenance time of origin refers to the calendar time that maintenance event occurs, refer to replacing construction and servicing time the time that maintenance event spends, comprise the time of turnover, management; Described preventive maintenance time comprises: component coding, repair location and servicing time, as shown in Figure 6, shown by preventative maintenance data instance data: communication module has done a preventative maintenance on August 2nd, 2013, before carrying out preventative maintenance, parts have worked 500h aboard, maintenance website is XX boat material stock, and keeping in repair turnover period is 48 hours.
Described guarantee data comprise supply data and reorder data, described supply data is when spare part abundance, to the time of getting spare part from subordinate's website application, content comprises component names, site name, higher level's site name, the haulage time from higher level to subordinate and the haulage time from subordinate to higher level, as shown in Figure 7, the haulage time of these charting parts, comprises various scheduling and is unified in administrative time in haulage time; Reorder data comprises: component coding, parts storage location and backlog time, and as shown in Figure 8, the backlog time of these charting parts, comprises various declaring and be placed in haulage time with unification administrative time reorder data.
The present invention adopts 3 Computational Methods: averaging method, least square method Sum Maximum Likelihood Estimate method, the present invention, for averaging method, calculates the average life of certain type equipment.
The computing method of averaging method:
In formula, the parameter of T-to be assessed; Ti-the i-th time record value; N-summary journal number of times.
The data entry form of equipment effective utilization of the present invention and fault data table as shown in Fig. 9, Figure 10, Figure 11 and Figure 12, from averaging method:
The mean lifetime of certain type equipment:
T
on average=(121+85+103+97+141+134+200*6)/12=156.75 (hour)
The assessment result display of described equipment effective utilization analysis module: effective utilization analysis module selects different organic units, analyze the analysis of Reliability of equipment, Maintainability index analysis and protection index analysis, carry out supportability analysis according to different regions or whole air force simultaneously.
The output-index of described analysis of Reliability is component life distribution function, Reliability Function, probability density function, crash rate λ and mean time between failures MTBF, as for exponential distribution, first its distribution parameter λ value is provided, then MTBF value is calculated, and export relational graph, export tables of data as shown in figure 13, reliability images outputting as shown in figure 14; Described Maintainability index exports as average preventative maintenance turnover period, average corrective maintenance turnover period, more careful for maintenance job being divided, such as by maintenance task analysis for dismantling, detect, send and repair and install, the averaging time that can export each sub-work item respectively carries out assessment Maintainability index, as shown in figure 15.
Described protection index exports as average order time and average supply time, and output formats as shown in figure 16.
Described consumption law analysis module, comprises the consumption law analysis and prediction of organic unit's consumption law analysis and prediction, individual event equipment consumption law-analysing, different phase.
Described organic unit's consumption law analysis and prediction, according to the classification of warehouse, the single military region, group, statistical study is carried out to consumption data with chart and spreadsheet format, consumption curve is provided according to the chronomere of year, the moon, according to the situation of the overall or single equipment amount of money, equipment consumption quantity, contrast the Expenditure Levels of different organic unit; There is provided the situation in the moon of organic unit, season, year, provide air force-wide Expenditure Levels by similar mechanism, now need to provide air force-wide basic data, calculate the equipment consumption rule next year, its output formats as shown in figure 17.
Described individual event equipment consumption law-analysing, it is the consumption law of research whole air force individual event equipment, individual event equipment consumption law-analysing needs the equipment reliability level considering whole air force, and consumption data in recent years carries out curve fitting, and obtains equipment consumption Trendline and quantity.
Individual event equipment consumption law-analysing, with chart and spreadsheet format, according to the classification of full air force or the military region, group, a certain equipment is carried out to the statistical study of consumption data, provide quantity consumed, consumption trend, the consumption amount information of individual event according to the chronomere of year, the moon.
The consumption law analysis and prediction of described different phase, according to the different phase residing for aircraft, analyze its consumption law, the component life distribution function that computing method are analyzed according to effective utilization, user calculates its probability occurring to lose efficacy according to the different aircraft stages, thus the consumption law of determining means, its Output rusults is as shown in figure 18.
The present invention utilizes consumption equipment, calculates the effective utilization of equipment, and the model of the Index Establishment equipment consumption analysis module of recycling equipment effective utilization, according to the analysis of consumption data and the prediction of follow-up bespeak model, completes the object that equipment consumption law is analyzed.
The present invention is based on the equipment consumption law-analysing system of consumption data, utilize the prediction of the analysis of equipment consumption data and follow-up bespeak model, complete the object that equipment consumption law is analyzed, compensate for air materiel consumption amount large, the deficiency of the poor accuracy of order.
Claims (1)
1. the equipment consumption law-analysing system based on consumption data, it is characterized in that, comprise equipment effective utilization analysis module and consumption law analysis module, described equipment effective utilization analysis module is by the typing of data, calculate the reliability index of equipment, protection index and Maintainability index, utilize the consumption data of organic unit simultaneously, the supportability of the not commensurate using equipment of the same race is analyzed;
The consumption law of method to equipment that described consumption law analysis module distributes in the consumption of different lifetime stage according to organic unit's consumption law, individual event equipment consumption rule and equipment is analyzed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510555363.6A CN105005677B (en) | 2015-09-02 | 2015-09-02 | A kind of equipment consumption law-analysing system based on consumption data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510555363.6A CN105005677B (en) | 2015-09-02 | 2015-09-02 | A kind of equipment consumption law-analysing system based on consumption data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105005677A true CN105005677A (en) | 2015-10-28 |
| CN105005677B CN105005677B (en) | 2018-01-19 |
Family
ID=54378350
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510555363.6A Active CN105005677B (en) | 2015-09-02 | 2015-09-02 | A kind of equipment consumption law-analysing system based on consumption data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105005677B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111275248A (en) * | 2020-01-15 | 2020-06-12 | 中国人民解放军陆军军事交通学院镇江校区 | Ship equipment consumption law analysis system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040148216A1 (en) * | 2003-01-23 | 2004-07-29 | Accenture Global Services Gmbh | Calculating the benefit of an investment in training |
| CN102156924A (en) * | 2011-04-25 | 2011-08-17 | 北京航空航天大学 | Method for forecasting equipment guarantee expense in development stage |
| CN102339419A (en) * | 2010-07-21 | 2012-02-01 | 北京汽车研究总院有限公司 | Method and device for realizing reliability, maintainability and supportability (RMS) of military vehicle product |
-
2015
- 2015-09-02 CN CN201510555363.6A patent/CN105005677B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040148216A1 (en) * | 2003-01-23 | 2004-07-29 | Accenture Global Services Gmbh | Calculating the benefit of an investment in training |
| CN102339419A (en) * | 2010-07-21 | 2012-02-01 | 北京汽车研究总院有限公司 | Method and device for realizing reliability, maintainability and supportability (RMS) of military vehicle product |
| CN102156924A (en) * | 2011-04-25 | 2011-08-17 | 北京航空航天大学 | Method for forecasting equipment guarantee expense in development stage |
Non-Patent Citations (3)
| Title |
|---|
| 王亮 等: "军用车辆器材消耗规律初探", 《汽车运用》 * |
| 王海燕等: "装备维修保障计划评估信息系统的设计与实现", 《装备学院学报》 * |
| 董鑫 等: "器材消耗预测方法综述", 《四川兵工学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111275248A (en) * | 2020-01-15 | 2020-06-12 | 中国人民解放军陆军军事交通学院镇江校区 | Ship equipment consumption law analysis system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105005677B (en) | 2018-01-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Baker et al. | Regional aviation and economic growth: cointegration and causality analysis in Australia | |
| Banker et al. | Employment protection legislation, adjustment costs and cross-country differences in cost behavior | |
| Rødseth et al. | Deep digital maintenance | |
| Ahi et al. | Energy-related performance measures employed in sustainable supply chains: A bibliometric analysis | |
| CN102567807A (en) | Method for predicating gas card customer churn | |
| Yan et al. | Cash transportation vehicle routing and scheduling under stochastic travel times | |
| Chen et al. | Vulnerability modeling, assessment, and improvement in urban metro systems: A probabilistic system dynamics approach | |
| Vorobyov et al. | Bases of the methodology of monitoring the impact of the human factor on the reliability of the railway infrastructure | |
| Jiang et al. | Transportation system evaluation model based on DEA | |
| Graham et al. | Design of a single pilot cockpit for airline operations | |
| CN111340536A (en) | Model training method, passenger seat rate progress prediction method, system, device and medium | |
| Rogers et al. | Big data-driven decision-making processes, real-time advanced analytics, and cyber-physical production networks in industry 4.0-based manufacturing systems | |
| Durán et al. | Analysis of long-term impact of maintenance policy on maintenance capacity using a time-driven activity-based life-cycle costing | |
| CN111915100A (en) | High-precision freight prediction method and freight prediction system | |
| Suleykin et al. | Designing data-intensive application system for production plans data processing and near real-time analytics | |
| Lamb et al. | Research and development target‐setting difficulties addressed through the emergent method: technology forecasting using data envelopment analysis | |
| CN105005677A (en) | Equipment consumption rule analysis system based on consumption data | |
| Barnum et al. | DEA efficiency analysis involving multiple production processes | |
| Sun et al. | An ordering decision-making approach on spare parts for civil aircraft based on a one-sample prediction | |
| CN104392326B (en) | Iron-contained solid waste circulation utilization monitoring method for iron and steel enterprise | |
| Keys et al. | Gaining effective organizational control with RCA.(Cost Management). | |
| Pipe | Practical prognostics for condition based maintenance | |
| CN114781855A (en) | DEA model-based logistics transmission efficiency analysis method, device, equipment and medium | |
| Maslak et al. | Anti-crisis approach in the industrial enterprise management: methodological tools of preventive regulation | |
| Sohn et al. | Dynamic preventive maintenance scheduling of the modules of fighter aircraft based on random effects regression model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |