CN115983901A - Equipment accessory demand prediction method, system and medium based on digital twin - Google Patents
Equipment accessory demand prediction method, system and medium based on digital twin Download PDFInfo
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Abstract
The application relates to the technical field of market accessory demand prediction, and discloses a method, a system and a medium for predicting demand of equipment accessories based on digital twins, wherein the method comprises the following steps: establishing a digital twin equipment model according to a product resource material accessory list; acquiring information of the equipment to be tested according to the digital twin equipment model; respectively acquiring the total quantity of the accessory requirements in the warranty period and the total quantity of the accessory requirements of the equipment protected in the annual region by using the information of the equipment to be tested; and predicting the annual regional accessory demand total according to the acquired quality guarantee period accessory demand total and the annual regional peripheral equipment accessory demand total. Therefore, the potential market demand of the after-sale service accessories of the equipment can be tracked and accurately predicted in real time, a manufacturer is helped to quickly master the change and the dynamic of the market customer demand, the inventory of the market accessories is adjusted and deployed in time, the turnover rate and the fund utilization rate of the accessories are improved, the cost input of the market accessories is reduced, and the effective supply of the market accessories is met.
Description
Technical Field
The invention relates to the technical field of market accessory demand prediction, in particular to a method, a system and a medium for predicting demand of equipment accessories based on digital twins.
Background
With the increase of post-market sales potential of equipment (such as excavators, loaders, rotary drilling rigs and the like), the importance of accurate analysis on post-market service and accessory requirements is more and more concerned and more emphasized. In order to meet the requirements of market service and accessories after equipment and ensure the satisfaction of customers, the instant and accurate supply of service accessories becomes an important foundation for supporting market operation after equipment is used.
However, there are some pain points in the inventory layout and efficient use of funds in the area market in the accessory operations business: due to the fact that the variety of material accessories of product resources is large, the equipment stock operating in different areas cannot be accurately mastered; the requirements for various maintenance accessories in each area cannot be accurately predicted; the fault occurrence condition of the operation equipment in each area cannot be accurately predicted, and the maintenance, distribution and replacement requirements caused by the fault occurrence condition cannot be accurately predicted; the construction time of the operation in each area cannot be mastered, so that the wearing condition of the wearing parts cannot be mastered in time, and the replacement frequency and the purchase demand of the wearing parts cannot be predicted. Therefore, establishing a method capable of realizing real-time monitoring of aftermarket accessory demand, and realizing real-time monitoring and accurate prediction of aftermarket maintenance accessory demand, service accessory demand and sales accessory demand becomes an important target of equipment manufacturers.
At present, the existing methods for predicting the market demand of accessories in the market are mainly divided into two methods, namely a method for allocating the sales volume of equipment; one is an annual sales trend referencing method. In the former method, a fixed assembly budget amount is set for equipment product resources, and the equipment is fixedly allocated according to the equipment sales volume of each region every year. By the method, market accessory requirements do not need to be subdivided and evaluated, accessory deployment is carried out in a quota planning mode, and the mode is simple and quick. However, due to the fact that market demands cannot be accurately positioned, long-term overstock of a large number of accessories is easily caused, capital cost investment is high due to the fact that long-term inventory cannot be timely digested, capital turnover rate is low, and the development requirements of rapid turnover of the existing accessory market cannot be met. The latter is to carry on the annual trend analysis through the sales volume of the fittings to historical year, calculate the sales coefficient of the fittings annual according to the analytical result, sell the coefficient and predict the sales volume of the fittings annual new year through the fittings annual sales coefficient of the fittings. However, this method needs to be calculated under the support of big data, and is suitable for prediction from a macroscopic view, and analysis and prediction from the area dimension and the equipment distribution dimension of area operation are prone to large deviation, which easily causes high and low component hit rate, and unstable component market capital investment and inventory deployment accuracy.
Disclosure of Invention
In view of the above, the present invention provides a demand forecasting method, system and medium for equipment parts based on digital twin, which can track and accurately forecast the potential demand of after-sale service parts market in real time, and help manufacturers to quickly master the demand change dynamics of market customers. The specific scheme is as follows:
a demand forecasting method for equipment accessories based on digital twinning comprises the following steps:
establishing a digital twin equipment model according to a product resource material accessory list;
acquiring information of the equipment to be tested according to the digital twin equipment model;
respectively acquiring the total quantity of the accessory requirements in the warranty period and the total quantity of the accessory requirements of the equipment protected in the annual region by using the information of the equipment to be tested;
and predicting the annual regional accessory demand total according to the acquired quality guarantee period accessory demand total and the annual regional external equipment accessory demand total.
Preferably, in the method for predicting demand for equipment accessories provided in the embodiment of the present invention, the method further includes:
and performing assignment display on the predicted annual area part demand total amount on a GIS map according to the area coordinates.
Preferably, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, obtaining a total demand for parts in warranty by using the information of the equipment to be tested includes:
calculating the demand of regional maintenance parts, the quantity of parts in a set time period and the annual part replacement rate according to the information of the equipment to be tested;
and acquiring the total quantity of the annual regional warranty period accessories according to the required quantity of the regional maintenance accessories, the quantity of the accessories in the set time period and the annual accessory replacement rate.
Preferably, in the method for predicting demand for equipment parts according to the embodiment of the present invention, calculating demand for area maintenance parts according to the information of the equipment to be tested includes:
obtaining equipment material assembling accessory information, equipment holding capacity, equipment positioning data, a regular maintenance template, equipment maintenance records and equipment working hours from the to-be-tested equipment information;
obtaining the area market holding capacity and the area storage holding capacity of the equipment in each region in the year according to the equipment holding capacity and the equipment positioning data;
calculating the total amount of the equipment regular maintenance according to the area protection inventory, the regular maintenance template, the equipment maintenance record and the working hours of the equipment;
and calculating the demand of the regional maintenance part according to the regional market holding quantity, the periodic maintenance total quantity of the equipment and the information of the equipment material assembling part.
Preferably, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, calculating the quantity of parts in a set time period according to the information of the equipment to be tested includes:
acquiring annual fault equipment working hours, fault accessories and fault accessory replacement quantity from the to-be-tested equipment information;
obtaining the fault occurrence amount of a region in a set time period according to the working hours of the fault equipment, the fault accessories and the replacement amount of the fault accessories in the year;
calculating the failure rate of the accessories according to the occurrence quantity of the regional failures in the set time period and the market reserve quantity of the region;
predicting the working hours of the equipment kept in the current year according to the area keeping quantity and the working hours of the equipment;
and calculating the quantity of the accessories in a set time period according to the accessory failure rate, the failed accessories, the replacement quantity of the failed accessories and the working hours of the equipment kept in the current year.
Preferably, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, acquiring a total demand for equipment parts reserved in an annual area by using the information of the equipment to be tested includes:
obtaining the fault accessory consumption, the area accessory sales volume and the area outside protection equipment growth coefficient of the area outside protection equipment according to the information of the equipment to be tested;
and acquiring the total quantity of the requirements of the annual region external equipment according to the fault accessory consumption of the region external equipment, the annual accessory replacement rate, the region accessory sales volume and the region external equipment growth coefficient.
Preferably, in the method for predicting demand for equipment accessories provided in the embodiment of the present invention, obtaining the usage amount of faulty accessories of the area outside protection equipment according to the information of the equipment to be tested includes:
obtaining fault accessories and fault accessory replacement amount in the fault report of the equipment protected from the previous year from the information of the equipment to be tested;
and according to the fault accessories and the fault accessory replacement quantity in the fault report of the equipment outside the regional protection equipment, counting the fault accessory consumption of the equipment outside the regional protection equipment according to the BOM version of the product resource.
Preferably, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, obtaining, according to the information of the device to be tested, a sales volume of area parts and an increase coefficient of area peripheral equipment, includes:
obtaining part sales orders, annual external storage quantity and distribution conditions of external storage equipment in each area in the previous year from the information of the equipment to be tested;
obtaining the sales volume of the regional accessories according to the sales orders of the regional accessories in the previous year;
and obtaining a region outside protection equipment growth coefficient according to the previous year outside protection holding capacity, the year outside protection holding capacity and the distribution condition of the outside protection equipment in each region.
The embodiment of the invention also provides a system for predicting the demand of equipment accessories, which comprises:
the model building module is used for building a digital twin equipment model according to a product resource material accessory list;
the information acquisition module is used for acquiring the information of the equipment to be tested according to the digital twin equipment model;
the data processing module is used for respectively acquiring the total quantity of the accessory requirements in the warranty period and the total quantity of the accessory requirements of the equipment reserved in the annual region by using the information of the equipment to be detected;
and the demand forecasting module is used for forecasting the demand total of the annual regional accessories according to the acquired demand total of the quality guarantee period accessories and the demand total of the annual regional peripheral equipment accessories.
Embodiments of the present invention further provide a computer-readable storage medium for storing a computer program, where the computer program, when executed by a processor, implements the above method for predicting demand for a device part based on a digital twin according to the embodiments of the present invention.
According to the technical scheme, the method for predicting the demand quantity of the equipment accessories based on the digital twin comprises the following steps: establishing a digital twin equipment model according to a product resource material accessory list; acquiring information of the equipment to be tested according to the digital twin equipment model; respectively acquiring the total quantity of the demand of the equipment accessories in the warranty period and the total quantity of the demand of the equipment accessories outside the annual region by using the information of the equipment to be tested; and predicting the annual regional accessory demand total according to the acquired quality guarantee period accessory demand total and the annual regional peripheral equipment accessory demand total.
According to the equipment part demand forecasting method provided by the invention, the part data is mined based on a digital twin technology, the total quantity of equipment part demands in a warranty period and the total quantity of equipment part demands outside a protection area of an annual area are respectively calculated, and the total quantity of the equipment part demands in the annual area is forecasted, so that the potential demand of the after-sale service accessory market of the equipment can be tracked and accurately forecasted in real time, a manufacturer is helped to quickly master the change dynamic of the market customer demands, the market part inventory is adjusted and deployed in time, the part turnover rate and the fund utilization rate are improved, the market part cost investment is reduced, and the effective supply of market parts is met.
In addition, the invention also provides a corresponding system and a computer readable storage medium for the device accessory demand forecasting method based on the digital twin, so that the method has higher practicability, and the system and the computer readable storage medium have corresponding advantages.
Drawings
In order to more clearly illustrate the embodiments of the present invention or technical solutions in related arts, the drawings used in the description of the embodiments or related arts will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a method for predicting demand for equipment accessories according to an embodiment of the present invention;
FIG. 2 is a block diagram of a method for predicting demand for equipment parts according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a system for predicting demand for equipment accessories according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a demand quantity forecasting method for equipment accessories based on digital twins, which comprises the following steps as shown in figure 1:
s101, establishing a digital twin equipment model according to a product resource material accessory list.
Specifically, the product resource PR refers to design versions of the BOM of the equipment products in different time periods, and in the invention, a material accessory list of the product resource of each version can be obtained, and a digital twin equipment model of each equipment can be established according to the material accessory list.
Because the product BOM only designs the product composition structure, and the specifications of specific accessories used in the actual production process are different according to the accessories of different models and different processes, procedures, generally, an enterprise refines the product BOM by using the product resource PR, namely, subdivides the product BOM into specific equipment combinations on the basis of the product BOM. The BOM structure of the product resource corresponds to actual equipment materials (accessory information) of equipment actually put on the market, and a digital twin equipment model is established according to the product resource material accessory list, so that mirror image mapping of a structure formed by the product resource material accessory list and real equipment can be guaranteed.
And S102, acquiring information of the equipment to be tested according to the digital twin equipment model.
It can be understood that the parameters related to the demand forecast of the accessories can be refined and decomposed according to the digital twin equipment model, and the method starts from multiple dimensions of product resources PR, market holding equipment MP (namely equipment which is confirmed to be sold to an end user), internal maintenance, internal service, external sales and the like, so that the information of the equipment to be tested of the required product resources can be clearly obtained, specific brand, specification, model and production area of the accessories can be accurately obtained in the future during maintenance and replacement, and the calculation result can be infinitely close to the real situation by taking the calculation basis when the demand of the accessories in the market is forecasted. In practical application, the information of the device to be tested may include BOM data of device production, market device holding amount, device material assembling accessory information, device maintenance service data, device positioning and monitoring data, and the like. The device Positioning and monitoring data may be fed back by a Global Positioning System (GPS) or a Beidou Navigation Satellite System (BDS), or may be fed back by other Positioning systems, which is not limited herein.
S103, respectively acquiring the total quantity of the equipment requirements in the warranty period and the total quantity of the equipment requirements outside the annual region by using the information of the equipment to be tested.
And S104, predicting the annual regional accessory demand total according to the acquired quality guarantee period accessory demand total and the annual regional peripheral equipment accessory demand total.
Specifically, as shown in fig. 2, the total quantity of demand for the components in the warranty period and the total quantity of demand for the components in the equipment outside the annual area are summed up to obtain the total quantity of demand for the components in the annual area.
The "equipment" in the present invention may be engineering machinery equipment such as an excavator, a loader, a rotary drilling rig, or other equipment with a relatively large amount in the market. The "device" may be equipped with GPS or BDS components to acquire device location and monitoring data. The "year" in the invention can refer to the current year, and can also be any other year, and the calculation can be carried out according to the year time counted by specific needs in practical application.
In the method for predicting the demand of the equipment accessories, provided by the embodiment of the invention, the accessory data is mined based on a digital twin technology, the demand total of the accessories in the warranty period and the demand total of the equipment accessories outside the annual area are calculated respectively from two angles, and the demand total of the accessories in the annual area is predicted, so that the potential demand of the after-sale service accessory market of the equipment can be tracked and accurately predicted in real time, a manufacturer is helped to quickly master the demand change dynamic of market customers, the inventory of the market accessories is adjusted and deployed in time, the turnover rate and the fund utilization rate of the accessories are improved, the cost input of the market accessories is reduced, and the effective supply of the market accessories is met.
Further, in a specific implementation, in the method for predicting a demand amount of an equipment part according to the embodiment of the present invention, after the step S104 of predicting a total demand amount of an equipment part in an annual area is executed, the method may further include: and carrying out assignment display on the predicted annual regional accessory demand total amount on a GIS map according to the regional coordinates.
The steps are based on budget results obtained under the support of a digital twin technology, and the data results are assigned to the map on the GIS map according to market distribution of each area and are displayed to the user in a visual mode. Specifically, the distribution of accessory market demands, the modeling of deployment scenes and the data docking are assisted by a GIS map component of a digital twin platform, and the classifying, regional gathering and displaying of accessory demand subdivided markets according to the dimensions such as regions, products and time are achieved. In practical application, interactive display can be supported on display platforms such as a large screen end, a computer end and a mobile end in a visual mode.
In the following, reference will be made to the basic parameters, some of which are shown in fig. 2, the following meanings of which are explained for ease of understanding:
"device holding amount" refers to all the held devices sold in the statistical history, i.e., market holding amount MPT = ∑ (market holding device MP).
"in-store device" GP refers to a device that has been sold and is still within its warranty period.
"keep-alive device" OP refers to a device that has been sold and has exceeded its warranty period.
The "number of hours worked" WH refers to the current working time counted by each model device GPS or BDS.
The "guaranteed internal storage capacity" GPT refers to a capacity which is verified whether the operating hours of each model device are within the warranty period according to the statistics of the market capacity, and is in the state of the guaranteed internal device, that is, "guaranteed internal storage capacity" GPT = (guaranteed internal device GP).
The market reserve amount-the internal reserve amount is "external reserve amount" OPT = market reserve amount MPT-the internal reserve amount GPT.
The PMM of the equipment corresponding to each product resource comprises specified maintenance times MT, quality guarantee time GPWH, maintenance contents and the number MPT of maintenance accessories needing to be used. The maintenance time criteria may be calculated in terms of hours of operation of the equipment, typically by default.
In this year, various types of maintenance are completed according to a regular maintenance template, equipment with the working hours close to but not exceeding the warranty time is 'temporary guarantee equipment' TOP, and the total number of the temporary guarantee equipment is counted as 'temporary guarantee quantity' TOPT = ∑ (temporary guarantee equipment TOP).
The 'failure report' BMR records equipment failure maintenance information, including the working hours BWH recorded by a GPS or BDS when a failure occurs, a failed accessory BP and a failed accessory replacement BPRT.
Newly adding a sale excavator device in the year as a sale device SM, and counting the total number of the sale devices as a total sale quantity SMT = ∑ (sale device SM).
In specific implementation, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, the step S103 obtains the total demand for equipment parts in warranty period by using the information of the equipment to be tested, which may specifically include:
step one, calculating the demand of regional maintenance parts, the quantity of parts in a set time period and the annual part replacement rate according to the information of the equipment to be tested.
In specific implementation, calculating the demand of the area maintenance part according to the information of the device to be tested may specifically include: firstly, obtaining equipment material assembling accessory information, equipment holding capacity MPT, equipment positioning data, a regular maintenance template, equipment maintenance records and equipment working hours from equipment information to be tested; then, according to the equipment storage capacity MPT and the equipment positioning data, obtaining the area market storage capacity PRA _ MPT and the area storage capacity PRA _ GPT of the equipment in each region in the year; then, calculating the equipment regular maintenance total amount PRA _ MT according to the area maintenance retention amount PRA _ GPT, the regular maintenance template, the equipment maintenance record and the equipment working hours; and finally, calculating the required quantity PRA _ MTPC of the area maintenance part according to the MPT of the area market holding quantity, the PRA _ MT of the equipment regular maintenance total quantity and the equipment material assembly part information.
The steps are that the number of the used pieces of the equipment in the insurance space in each area to be maintained regularly is calculated according to the regular maintenance template. The device positioning data can confirm that each device on the market is in the regions, and the number, the amount of the reserved devices in each region and the amount of the reserved devices outside the region are counted according to the regions. Area reserved volume PRA _ GPT = area market reserved volume PRA _ MPT-the area is expecting reserved volume PRA _ TOPT + total area sales PRA _ SMT. According to the year, the designated area, the area maintenance amount, the regular maintenance template, the equipment maintenance record and the working hour information of each piece of equipment, the regular maintenance total amount PRA _ MT = sigma (maintenance times MT) of each piece of equipment which is to be completed in the area in the current year is calculated in a statistical manner, and the area maintenance part demand amount PRA _ MTPC = sigma (the regular maintenance total amount PRA _ MT multiplied by the market maintenance amount MPT) which is to be replaced or used corresponding to each type of regular maintenance template is calculated.
In specific implementation, the calculating of the number of accessories in a set time period according to the information of the device to be tested may specifically include: acquiring annual fault equipment working hours BWH, fault accessories BP and fault accessory replacement BPRT from equipment information to be tested; obtaining a failure occurrence amount PR _ BMT of a set time period area according to the working hours BWH of annual failure equipment, a failure accessory BP and a failure accessory replacement amount BPRT; calculating the failure rate BPFT of the accessories according to the area failure occurrence amount PR _ BMT and the area market retention amount PRA _ MPT in a set time period; predicting the working hours PRA _ GPWH of the equipment kept in the current year according to the area keeping quantity PRA _ GPT and the working hours WH of the equipment; and calculating the component quantity PRA _ GPBPRT in the set period according to the component failure rate BPFT, the failed component BP, the failed component replacement quantity BPRT and the working hours PRA _ GPWH of the equipment kept in the current year.
The steps are from calculating the accessory quantity caused by the faults possibly generated by the equipment in the storage in each area to obtaining the accessory quantity PRA _ GPBPR in the set time period. In practical applications, the GPS or BDS records the working data by hours when the device is used, and the reliability, the service life or the depreciation of the device are generally evaluated by the working hours in the industry. The failure occurrence probability can be calculated once according to a set time period (for example, every 50 hours, 100 hours or 200 hours is set as a statistical time period) for counting the number of times that devices of different resource types (or models) fail in each set time period.
In specific implementation, according to the information of the device to be tested, the annual component replacement rate is calculated, which specifically includes: the number of days PG for component warranty is obtained from the device information to be tested, and the annual component replacement rate YPGR = ROUND (365 ÷ number of days for component warranty, 2) is calculated from the number of days PG for component warranty. It is understood that ROUND (numerical value/formula, decimal) is a rounding function, wherein "numerical value/formula" can be either a number or a calculation formula; "decimal place" represents the number of decimal places remaining after rounding.
And step two, acquiring the total quantity of the part demand of the annual regional warranty period according to the demand of the regional maintenance parts, the quantity of the part in the set time period and the annual part replacement rate.
Specifically, the total annual regional warranty part demand amount PRA _ YGPBT can be obtained by multiplying the sum of the regional maintenance part demand amount PRA _ MTPC and the set period part amount PRA _ GPBPRT by the annual part replacement rate. Namely: the total quantity of parts required in the local warranty period PRA _ YGPBT ∈ (Σ by parts (regional maintenance part requirement PRA _ MTPC +100 hour period parts quantity PRA _ GPBPRT) × annual parts replacement rate YPGR). The meaning of "distinguish by accessories" is to calculate the number of accessories to be stored in each area according to the brand, specification and model of the accessories.
In specific implementation, in the method for predicting demand for equipment parts provided in the embodiment of the present invention, step S103 obtains a total demand for equipment parts reserved in an annual area by using information of equipment to be tested, which may specifically include:
firstly, according to the information of the equipment to be tested, the fault accessory consumption, the area accessory sales volume and the area external equipment growth coefficient of the area external equipment are obtained.
In specific implementation, the obtaining of the usage amount of the fault accessories of the area external protection device according to the information of the device to be tested may specifically include: obtaining a fault accessory BP and a fault accessory replacement amount BPRT in a fault report of the previous annual equipment from the information of the equipment to be tested; and counting the consumption PRA _ OPBPT of the fault accessories of the external equipment in the region according to the BP and the replacement quantity BPRT of the fault accessories in the fault report of the external equipment in the last year and the BOM version of the product resource. Wherein, the "last year" refers to the last year of the year requiring statistics.
In specific implementation, the obtaining of the sales volume of the area accessories according to the information of the device to be tested may specifically include: acquiring a PSD (Power sensitive Detector) of accessory sales orders of all regions in the last year from the information of the equipment to be tested; and obtaining the area part sales volume PRA _ YPSDT according to the PSD of each area part sales order in the previous year.
In specific implementation, according to the information of the device to be tested, the region protection device growth coefficient may specifically include: obtaining the last annual protection inventory OPT, the annual protection inventory OPT and the distribution condition of the external protection equipment in each area from the information of the equipment to be tested; and obtaining the increase coefficient PRA _ OPT _ GF of the area external equipment according to the previous annual external storage amount OPT, the annual external storage amount OPT and the distribution condition of the external equipment in each area. Wherein the region outside reserve amount PRA _ OPT = region market reserve amount PRA _ MPT-region inside reserve amount PRA _ GPT.
Then, the total quantity of the requirement of the equipment parts of the regional external equipment is obtained according to the fault part using quantity PRA _ OPBPT, the annual part replacement rate YPGR, the regional part sales quantity PRA _ YPSDT and the growth coefficient PRA _ OPT _ GF of the regional external equipment.
The method for predicting the demand of the equipment accessories provided by the embodiment of the invention is described in detail below by taking the year as the current year, the equipment as an excavator and the set time period as a statistical time period set every 100 hours, and specifically comprises the following steps:
firstly, counting the product resource holding amount PR _ MPT corresponding to each version in the market holding equipment according to the product resource correspondence.
And secondly, counting the regional market reserve PRA _ MPT, the regional inside reserve PRA _ GPT and the regional outside reserve PRA _ OPT of the equipment corresponding to the equipment of each type and product resource of the reserved market in each region in the year according to the reserved equipment positioning data. Wherein: area reserved volume PRA _ GPT = area market reserved volume PRA _ MPT-the area is expecting reserved volume PRA _ TOPT + total area sales PRA _ SMT. Area outside reserve amount PRA _ OPT = area market reserve amount PRA _ MPT-area inside reserve amount PRA _ GPT.
And thirdly, according to the current year, the specified region, the regional maintenance amount, the regular maintenance template, the equipment maintenance record and the working hour information of each piece of equipment, counting and calculating each piece of 'equipment regular maintenance total amount' PRA _ MT = sigma (maintenance frequency MT) to be completed in the region in the current year and 'regional maintenance part demand amount' PRA _ MTPC = sigma (equipment regular maintenance total amount PRA _ MT multiplied by market maintenance amount MPT) to be replaced or used corresponding to each type of regular maintenance template.
And fourthly, dividing the fault equipment into different parts according to the working hours BWH of the fault equipment in the fault maintenance record BMR and the product resources PR, wherein every 100 hours are set as a statistical time period (data of the statistical time period can be adjusted according to actual requirements in actual application), and the fault occurrence quantity PR _ BMT epsilon (fault parts and the replacement quantity sigma (fault parts BP multiplied by fault part replacement quantity BPRT)) of each 100 hours area is counted. Here, the occurrence probability of the failure of the device in each pack at different 100-hour stages can be predicted by the occurrence amount of the failure PR _ BMT per 100-hour area. The data is embodied in a matrix.
And fifthly, calculating the 'fitting fault rate' BPFT ∈ (ROUND (according to the area fault occurrence amount PR _ BMT/the area market retention amount PRA _ MPT, 4)) according to the area market retention amount PRA _ MPT.
And sixthly, respectively counting the total working hours PRA _ WHT of the equipment in each regional security in the year according to the product resources and the stored quantity PRA _ GPT and the working hours WH of the equipment according to the product resources (sigma (working hours WH)).
And seventhly, calculating the average daily working hours PRA _ ADWH e of the equipment in the region protection (PRA _ WHT/regional conservation quantity PRA _ GPT/days which have passed in the year, 2)) according to the total working hours PRA _ WHT of the equipment in the region protection and the regional conservation quantity PRA _ GPT.
And eighthly, predicting the working hours PRA _ GPWH of the equipment kept in the area according to the area keeping quantity PRA _ GPT and the average daily working hours PRA _ ADWH of the equipment kept in the area (the working hours WH of the equipment kept in the area + the area keeping quantity PRA _ GPT multiplied by the average daily working hours PRA _ ADWH multiplied by the number of the remaining days in the area). The working hours of each reserved device in the area are multiplied by the reserved quantity in the area, the average working hours and the remaining days of the year to obtain the possible working hours of each reserved device predicted to reach the end of the year. The data is embodied in a matrix. In actual application, the working hours of each equipment in the year are calculated.
And ninthly, calculating the number of 100-hour periods respectively contained in the operation of the equipment kept in each product resource in the area according to the working hours PRA _ GPWH of the equipment kept in the year and the period of every 100 hours, and according to the budget 100-hour period, estimating the component quantity PRA _ GPBPRT epsilon (100-hour period sigma (fault component BP x fault component replacement quantity BPRT) × component fault rate BPFT). In the method, the failure of different product resources corresponding to each 100-hour period is calculated according to the failure rate BPFT of the parts, and once the failure occurs, the number of the parts needs to be replaced. Here a matrix in two dimensions of 100 hours and a faulty accessory.
Here, the calculation is performed to calculate how many 100-hour periods each include the job of the device held in each product resource in the area. For example: product resources: PR3LD0005, PR4LZ0001. The market reserves are 3 resources, the online time of 2000 working hours is taken as the quality guarantee period, and as shown in table one, the method respectively calculates how many 100-hour time periods each trolley may experience in the year.
Watch 1
From this data it is possible to determine how many faults, respectively what faults, and how much probability of a fault may occur by the 6 trolleys by the end of the year. This allows to obtain a measurement of how many accessories the service of these 6 trolleys needs to deploy in the area this year.
The tenth step is to calculate the total quantity of parts required in the local warranty period PRA _ YGPBT e (the parts replacement rate YPGR) by parts division Σ (the area maintenance part required quantity PRA _ MTPC + the part quantity PRA _ GPBPRT in the 100-hour period). The guaranteed internal inventory GPT is used as a statistical range, and is used for calculating the total quantity of accessory requirements corresponding to equipment in the quality guarantee period of each region in each year in different regions on the basis of all guaranteed internal equipment in the whole country. The distinction according to the accessories means that the storage quantity of the accessories in each area is calculated according to the brand, specification and model of the accessories.
And step eleven, according to the information of the fault report BMR of the equipment OP outside the equipment protected in the previous year, counting the use amount PRA _ OPBPT epsilon of the fault accessories of the equipment outside the equipment protected in each area according to the BOM version of the product resource PR (the fault report BMR, the fault accessory BP multiplied by the fault accessory replacement amount BPRT) of the product resource PR belonging to the equipment outside the area OP in the previous year.
The twelfth step is to count up the part sales order PSD of each area in the previous year, and count up the part sales amount PRA _ YPSDT e of each area (sigma of part sales order PSD) in the previous year.
And a thirteenth step of calculating the growth coefficient of the product resource PR corresponding to each regional external protection device, namely the growth coefficient PRA _ OPT _ GF of the regional external protection device (product resource ROUND in each region (the external protection amount OPT in the year divided by the external protection amount OPT in the last year, 2)) according to the external protection amount OPT in the last year, the external protection amount OPT in the year and the distribution condition of the external protection devices in each region.
And fourteenth, calculating the total quantity of the demand of the local annual area external equipment accessories PRA _ YOPBT e according to the external equipment protection quantity OPT (the fault accessory consumption PRA _ OPBPT multiplied by the annual accessory replacement rate YPGR of the local area external equipment + the area accessory sales quantity PRA _ YPSDT multiplied by the external area equipment growth coefficient PRA _ OPT _ GF).
And fifteenth, calculating the local annual part demand amount PRA _ YPQD e of the area market according to the obtained data of the local annual area warranty period part demand total amount PRA _ YGPBT and the local annual area warranty period equipment demand total amount PRA _ YOPBT (the local annual area warranty period part demand total amount PRA _ YGPBT + the local annual area warranty period equipment demand total amount PRA _ YOPBT).
Sixthly, the part demand PRA _ YPQD of each regional market in the current year is displayed on the map in an assignment mode according to regional coordinates through the combination of a digital twinning technology and a GIS map.
Based on the same inventive concept, the embodiment of the invention also provides an equipment part demand forecasting system, and as the principle of the system for solving the problems is similar to the method for forecasting the equipment part demand based on the digital twin, the implementation of the system can refer to the implementation of the method for forecasting the equipment part demand based on the digital twin, and repeated parts are not described again.
In specific implementation, the system for predicting demand for equipment accessories provided in the embodiment of the present invention, as shown in fig. 3, specifically includes:
the model establishing module 11 is used for establishing a digital twin equipment model according to a product resource material accessory list;
the information acquisition module 12 is used for acquiring information of the equipment to be tested according to the digital twin equipment model;
the data processing module 13 is configured to obtain a total quantity of equipment requirements in a warranty period and a total quantity of equipment requirements in an annual region protection device by using the information of the equipment to be tested;
and the demand forecasting module 14 is configured to forecast the annual regional demand total amount of the accessories according to the acquired quality guarantee period accessory demand total amount and the annual regional reserve peripheral equipment accessory demand total amount.
In the system for predicting the demand of the equipment accessories provided by the embodiment of the invention, the potential demand of the after-sale service accessories of the equipment in the market can be tracked and accurately predicted in real time through the interaction of the four modules, a manufacturer can be helped to quickly master the change of the demands of market customers, the inventory of market accessories can be adjusted and deployed in time, the turnover rate and the fund utilization rate of the accessories are improved, the cost input of the market accessories is reduced, and the effective supply of the market accessories is met.
Further, in a specific implementation, in the system for predicting demand for equipment accessories provided in the embodiment of the present invention, the system may further include:
and the result display module is used for carrying out assignment display on the predicted annual regional accessory demand total amount on the GIS map according to the regional coordinates.
In specific implementation, in the system for predicting demand for equipment accessories provided in the embodiment of the present invention, the data processing module 13 may include:
the first processing unit is used for calculating the demand of regional maintenance parts, the quantity of parts in a set time period and the annual part replacement rate according to the information of the equipment to be tested; acquiring the total quantity of the part demand of the annual regional warranty period according to the demand of regional maintenance parts, the quantity of the part in a set period and the replacement rate of annual parts;
the second processing unit is used for obtaining the fault accessory using amount, the area accessory sales amount and the area outside protection equipment growth coefficient of the area outside protection equipment according to the information of the equipment to be tested; and acquiring the total quantity of the requirements of the equipment parts of the annual regional external protection equipment according to the fault part using amount, the annual part replacement rate, the regional part sales amount and the regional external protection equipment growth coefficient of the regional external protection equipment.
For more specific working processes of the modules, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
Further, the present invention also discloses a computer readable storage medium for storing a computer program; the computer program when executed by the processor implements the digital twin based device part demand prediction method disclosed previously. For more specific processes of the above method, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
In the present specification, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, and the same or similar parts between the embodiments are referred to each other. The system and the storage medium disclosed by the embodiment correspond to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the components and steps of the various examples have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The method, the system and the medium for predicting the demand of the equipment accessories based on the digital twin are described in detail, the principle and the implementation mode of the invention are explained by applying specific examples, and the description of the examples is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A demand quantity forecasting method for equipment accessories based on digital twinning is characterized by comprising the following steps:
establishing a digital twin equipment model according to a product resource material accessory list;
acquiring information of the equipment to be tested according to the digital twin equipment model;
respectively acquiring the total quantity of the requirements of the equipment in the warranty period and the total quantity of the requirements of the equipment in the protected area of the year by using the information of the equipment to be tested;
and predicting the annual regional accessory demand total according to the acquired quality guarantee period accessory demand total and the annual regional external equipment accessory demand total.
2. The equipment parts demand quantity prediction method according to claim 1, characterized by further comprising:
and performing assignment display on the predicted annual area part demand total amount on a GIS map according to the area coordinates.
3. The method for predicting the demand quantity of equipment accessories according to claim 2, wherein obtaining the total demand quantity of the equipment accessories in warranty period by using the information of the equipment to be tested comprises:
calculating the demand of regional maintenance parts, the quantity of parts in a set time period and the annual part replacement rate according to the information of the equipment to be tested;
and acquiring the total quantity of the required parts in the annual regional warranty period according to the required quantity of the regional maintenance parts, the quantity of the parts in the set period and the annual part replacement rate.
4. The method of predicting demand for equipment items according to claim 3, wherein calculating a demand for area maintenance items based on the information on the equipment under test comprises:
obtaining equipment material assembling accessory information, equipment holding capacity, equipment positioning data, a regular maintenance template, equipment maintenance records and equipment working hours from the to-be-tested equipment information;
obtaining the area market holding capacity and the area storage holding capacity of the equipment in each region in the year according to the equipment holding capacity and the equipment positioning data;
calculating the total amount of the equipment regular maintenance according to the area protection inventory, the regular maintenance template, the equipment maintenance record and the working hours of the equipment;
and calculating the demand of the regional maintenance part according to the regional market holding amount, the total periodic maintenance amount of the equipment and the information of the equipment material assembling accessory.
5. The method for predicting the demand of equipment accessories according to claim 4, wherein calculating the quantity of accessories in a set time period according to the information of the equipment to be tested comprises:
acquiring annual fault equipment working hours, fault accessories and fault accessory replacement quantity from the to-be-tested equipment information;
obtaining the fault occurrence amount of a region in a set time period according to the working hours of the fault equipment, the fault accessories and the replacement amount of the fault accessories in the year;
calculating the failure rate of the accessories according to the occurrence quantity of the regional failures in the set time period and the market reserve quantity of the region;
predicting the working hours of the equipment kept in the current year according to the area keeping quantity and the working hours of the equipment;
and calculating the quantity of the accessories in a set time period according to the accessory failure rate, the failed accessories, the replacement quantity of the failed accessories and the working hours of the equipment kept in the current year.
6. The method for predicting the demand quantity of equipment accessories according to claim 5, wherein obtaining the total demand quantity of equipment accessories reserved in an annual area by using the information of the equipment to be tested comprises:
obtaining the fault accessory consumption, the area accessory sales volume and the area outside protection equipment growth coefficient of the area outside protection equipment according to the information of the equipment to be tested;
and acquiring the total quantity of the requirements of the annual region external equipment according to the fault accessory consumption of the region external equipment, the annual accessory replacement rate, the region accessory sales volume and the region external equipment growth coefficient.
7. The method for predicting the demand of equipment accessories according to claim 6, wherein obtaining the consumption of fault accessories of the area outside protection equipment according to the information of the equipment to be tested comprises:
obtaining fault accessories and fault accessory replacement quantity in the fault report of the previous annual equipment protection device from the information of the equipment to be tested;
and according to the fault accessories and the replacement quantity of the fault accessories in the fault report of the equipment outside the regional protection equipment, counting the consumption of the fault accessories of the equipment outside the regional protection equipment according to the BOM version of the product resource.
8. The method for predicting the demand of equipment accessories according to claim 7, wherein obtaining the sales volume of area accessories and the growth coefficient of area peripheral equipment according to the information of the equipment to be tested comprises:
obtaining part sales orders, annual external preservation quantity and distribution conditions of external preservation equipment in each area in the last year from the information of the equipment to be tested;
obtaining the sales volume of the regional accessories according to the sales orders of the regional accessories in the last year;
and obtaining a region outside protection equipment growth coefficient according to the previous year outside protection holding capacity, the year outside protection holding capacity and the distribution condition of the outside protection equipment in each region.
9. An equipment part demand prediction system, comprising:
the model establishing module is used for establishing a digital twin equipment model according to a product resource material accessory list;
the information acquisition module is used for acquiring the information of the equipment to be tested according to the digital twin equipment model;
the data processing module is used for respectively acquiring the total quantity of the accessory requirements in the warranty period and the total quantity of the accessory requirements of the equipment reserved in the annual region by using the information of the equipment to be detected;
and the demand forecasting module is used for forecasting the demand total of the annual region accessories according to the acquired demand total of the warranty period accessories and the demand total of the annual region peripheral equipment accessories.
10. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the digital twin-based equipment part demand prediction method according to any one of claims 1 to 8.
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