Agricultural machinery maintenance service pricing method and system

Abstract

The invention discloses an agricultural machinery maintenance service pricing method and system, and relates to the technical field of agricultural machinery maintenance. The invention aims to solve the problems of strong subjectivity, lack of transparency, slow response speed and insufficient market adaptability of a traditional maintenance pricing mode. According to the method, the equipment state score, the maintenance historical factor, the market reference price, the labor cost and the maintenance difficulty addition are acquired, the comprehensive pricing model is established based on the acquired parameters, and the agricultural machinery maintenance service price is calculated by using the comprehensive pricing model. By introducing an intelligent pricing method and a data analysis technology, the agricultural machinery maintenance service pricing accuracy and transparency can be improved, the maintenance cost of agricultural machinery users can be reduced, the efficiency and quality of the maintenance service can be improved, and powerful support is provided for sustainable development of the agricultural machinery industry.

Description

Technical Field

[0001] The invention belongs to the technical field of agricultural machinery maintenance. Background Art

[0002] With the development of agricultural mechanization, the application of agricultural machinery and equipment in modern agricultural production is becoming increasingly popular, covering multiple links such as tillage, plant protection, harvesting, and transportation. However, since agricultural machinery and equipment operate in long-term high-load and high-intensity environments, their mechanical components are prone to wear, aging, and failure, resulting in a significant increase in maintenance needs. Reasonable maintenance pricing is crucial to ensuring stable agricultural production and reducing the economic burden on farmers. However, the current agricultural machinery maintenance market still has many problems and shortcomings in pricing, which are mainly reflected in the following aspects:

[0003] 1. Repair pricing lacks scientific basis and is subject to subjectivity and price opacity.

[0004] Currently, agricultural machinery repair costs are calculated primarily based on the experience and judgment of repair service providers or industry practices, lacking a systematic, standardized pricing model. This lack of a unified repair price standard leads to significant disparity between regions and repair facilities, resulting in significant discrepancies in repair costs for the same equipment and the same fault. Furthermore, some repair service providers employ opaque pricing methods, making it difficult for agricultural machinery users to compare and select appropriate repair options, impacting the fairness of repair services.

[0005] 2. Maintenance costs are affected by many factors, and traditional pricing methods are difficult to accurately reflect costs.

[0006] Agricultural machinery repair costs are influenced by a combination of factors, including but not limited to equipment type, age, type of failure, repair labor hours, parts prices, and market supply and demand fluctuations. However, traditional repair pricing models typically use fixed rates or manual estimates, making it difficult to dynamically adjust prices and failing to accurately reflect repair costs. For example, the cost of repairing the engine of a particular model of agricultural machinery may vary depending on the price of parts and labor costs in different regions. However, most current repair quotation methods cannot flexibly address these changes, resulting in repair prices that deviate from actual market conditions.

[0007] 3. Outdated maintenance data collection methods make it difficult to support intelligent pricing

[0008] Existing agricultural machinery maintenance management systems lag behind in data collection, relying primarily on manual maintenance record keeping, making it difficult to obtain real-time data. For example, some agricultural machinery lacks remote monitoring systems, requiring maintenance personnel to conduct on-site diagnosis to determine the fault and repair plan, which increases response time for repair quotes. Furthermore, historical maintenance data is not fully integrated, preventing maintenance service providers from optimizing pricing strategies through big data analysis, resulting in a lack of data support for calculating repair costs.

[0009] 4. The maintenance market is changing rapidly and lacks a flexible pricing adjustment mechanism.

[0010] The agricultural machinery repair industry is a rapidly evolving market. For example, spare parts prices fluctuate due to factors like raw material costs and market supply and demand. Repair labor costs can also fluctuate based on seasonal demand. However, existing repair service pricing models often lack dynamic adjustment mechanisms, preventing repair quotes from adapting to market changes. For example, during the busy farming season, repair demand surges, leading to rising labor costs. Fixed-rate pricing models fail to reflect this dynamic change, resulting in profit losses for repair service providers and unreasonable fees for agricultural machinery users.

[0011] To sum up, the existing pricing method for agricultural machinery maintenance services has many shortcomings and is difficult to adapt to the development needs of the modern agricultural machinery maintenance market. Summary of the Invention

[0012] The present invention aims to solve the problems of strong subjectivity, lack of transparency, slow response and insufficient market adaptability in the traditional maintenance pricing model, and now provides a pricing method and system for agricultural machinery maintenance services.

[0013] A pricing method for agricultural machinery maintenance services, comprising:

[0014] Collect equipment status score S, maintenance history factor H, market reference price M, labor cost L, and maintenance difficulty bonus A, establish a comprehensive pricing model based on the collected parameters, and use the comprehensive pricing model to calculate the price of agricultural machinery maintenance services;

[0015] The comprehensive pricing model includes:

[0016] C′ repair =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′,

[0017] Among them, C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

[0018] Furthermore, the above-mentioned agricultural machinery maintenance service pricing method also includes:

[0019] When the market maintenance price changes, the pricing will be adjusted dynamically:

[0020]

[0021] Where: C repair is the adjusted pricing of agricultural machinery maintenance services, and ΔM is the fluctuation range of market maintenance prices.

[0022] Furthermore, the expression of the above device status score S is:

[0023] S=β1F+β2D+β3U,

[0024] Among them, F is the current fault level, D is the cumulative operating days of the equipment, U is the usage frequency of the equipment in the last month, and β1, β2, and β3 are the weight coefficients of F, D, and U, respectively.

[0025] Furthermore, the above maintenance history factor H

[0026] H=γ1N repair +γ2ln(T usage +1),

[0027] Among them, N repair is the cumulative number of equipment maintenance times, T usage is the cumulative usage time of the device, γ1 and γ2 are N repair and T usage The weight coefficient of , ln(·) means taking the natural logarithm.

[0028] Furthermore, the expression of the above market reference price M is:

[0029] M=α1P market +α2ε,

[0030] Among them, P market is the current market average price of maintenance services, ε is the local price volatility, α1 and α2 are P market and the weight coefficient of ε.

[0031] Furthermore, the expression of the above labor cost L is:

[0032] L=ρ1R+ρ2T repair ,

[0033] Where R is the number of maintenance resources required; T repair is the actual maintenance time, ρ1 and ρ2 are R and T respectively repair The weight coefficient of .

[0034] Furthermore, the expression of the above maintenance difficulty bonus A is:

[0035] A=f5(C f )=ηC f ,

[0036] Among them, C f is the current labor cost, and η is the standard working time.

[0037] A pricing system for agricultural machinery maintenance services, comprising:

[0038] Collection unit: used to collect equipment status score S, maintenance history factor H, market reference price M, labor cost L and maintenance difficulty bonus A;

[0039] Calculation unit: used to establish a comprehensive pricing model based on the collected parameters and calculate the pricing of agricultural machinery maintenance services using the comprehensive pricing model;

[0040] The comprehensive pricing model includes:

[0041] C′ repair =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′,

[0042] Among them, C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

[0043] Furthermore, the above agricultural machinery maintenance service pricing system further includes:

[0044] The adjustment unit is used to dynamically adjust the pricing when the market maintenance price changes:

[0045]

[0046] Where: C repair is the adjusted pricing of agricultural machinery maintenance services, and ΔM is the fluctuation range of market maintenance prices.

[0047] Furthermore, the expression of the above device status score S is:

[0048] S=β1F+β2D+β3U,

[0049] Among them, F is the current fault level, D is the cumulative operating days of the equipment, U is the usage frequency of the equipment in the last month, and β1, β2, and β3 are the weight coefficients of F, D, and U, respectively.

[0050] Furthermore, the above maintenance history factor H

[0051] H=γ1N repair +γ2ln(T usage +1),

[0052] Among them, N repair is the cumulative number of equipment maintenance times, T usage is the cumulative usage time of the device, γ1 and γ2 are N repair and T usage The weight coefficient of , ln(·) means taking the natural logarithm.

[0053] Furthermore, the expression of the above market reference price M is:

[0054] M=α1P market +α2ε,

[0055] Among them, P market is the current market average price of maintenance services, ε is the local price volatility, α1 and α2 are P market and the weight coefficient of ε.

[0056] Furthermore, the expression of the above labor cost L is:

[0057] L=ρ1R+ρ2T repair ,

[0058] Where R is the number of maintenance resources required; T repair is the actual maintenance time, ρ1 and ρ2 are R and T respectively repair The weight coefficient of .

[0059] Furthermore, the expression of the above maintenance difficulty bonus A is:

[0060] A=f5(C f )=ηC f ,

[0061] Among them, C f is the current labor cost, and η is the standard working time.

[0062] A device for pricing agricultural machinery maintenance services, comprising a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement a method for pricing agricultural machinery maintenance services as described in any one of claims 1 to 8.

[0063] A computer storage medium having at least one instruction stored therein, wherein the at least one instruction is loaded and executed by a processor to implement a method for pricing agricultural machinery maintenance services as claimed in any one of claims 1 to 8.

[0064] It aims to improve the pricing accuracy and intelligence level of agricultural machinery maintenance services through data collection, analysis and dynamic pricing technology.

[0065] Compared with the prior art, the present invention has significant advantages and positive effects, as follows:

[0066] 1. Improve the accuracy and scientific nature of maintenance pricing

[0067] This invention utilizes a data-driven pricing approach. By collecting multi-dimensional data such as equipment status, maintenance history, market prices, and labor costs in real time, combined with analysis and modeling techniques, it dynamically adjusts maintenance fees. Unlike traditional pricing methods that rely on empirical estimates, this pricing system accurately reflects actual maintenance costs, thereby avoiding pricing bias and unreasonable charges, and improving the scientific nature and accuracy of pricing.

[0068] 2. Make intelligent pricing decisions

[0069] This invention incorporates machine learning and data analysis technologies to establish a comprehensive maintenance cost prediction model, making the pricing process intelligent and automated. The maintenance cost calculation is based not only on the repair time and component replacement, but also on multiple factors such as the type of equipment failure, age, and regional differences. This intelligent pricing mechanism can respond to factors such as equipment failures and market price fluctuations in real time, greatly improving the flexibility and adaptability of the pricing process.

[0070] 3. Reduce the cost of agricultural machinery maintenance services

[0071] Through a dynamically adjusted pricing mechanism, agricultural machinery users can receive more transparent and fair repair quotes based on the actual situation of their equipment failure, effectively avoiding overcharging. Furthermore, intelligent pricing reduces the scope for manual intervention and subjective judgment, reducing unnecessary repair expenses and lowering maintenance costs for agricultural machinery users.

[0072] 4. Improve the transparency and fairness of maintenance services

[0073] This system systematically integrates information such as equipment status, maintenance history, and aftermarket prices. This clearly displays the components of repair costs, allowing agricultural machinery users to accurately understand the source of each expense, eliminating price opacity and price discrepancies. This process allows agricultural machinery users to clearly understand repair quotes and make more rational and transparent decisions.

[0074] 5. Adapt to market changes and demand fluctuations

[0075] The dynamic pricing model of this invention can promptly respond to changes in market supply and demand, spare parts prices, labor costs, and other factors. For example, during the busy farming season, when repair demand increases and labor costs rise, the system will automatically adjust quotes to reflect these changes. This allows repair service providers to adjust pricing based on market dynamics, avoiding underpricing or overpricing, and protecting the interests of both service providers and users.

[0076] 6. Optimize maintenance resource allocation and improve efficiency

[0077] An intelligent repair pricing system enables agricultural machinery repair service providers to better plan and manage repair resources. Based on the equipment's fault type and repair complexity, the system can predict repair times and required parts in advance, helping repair personnel allocate time and resources more effectively and improving work efficiency. This not only improves repair service quality but also reduces equipment downtime, optimizing agricultural production efficiency.

[0078] 7. Support the accumulation and optimization of long-term operational data

[0079] This invention can collect and record equipment maintenance data over time. By analyzing and comparing historical data, the system can continuously optimize pricing models and provide reasonable maintenance recommendations based on the equipment's maintenance status. This not only improves the accuracy of subsequent repairs but also provides agricultural machinery users with long-term equipment maintenance plans, extending the equipment's service life and further reducing its operating costs.

[0080] 8. Improve the service level and competitiveness of the agricultural machinery maintenance industry

[0081] By implementing the agricultural machinery repair service pricing method provided by this invention, repair service providers can provide fairer, more transparent, and more accurate repair quotes in the market, thereby improving customer satisfaction. In the long term, this will promote the formation of industry standards, improve the overall level of repair services, and enhance the market competitiveness of service providers.

[0082] In summary, by introducing intelligent pricing methods and data analysis technologies, the present invention can not only improve the accuracy and transparency of agricultural machinery maintenance service pricing and reduce the maintenance costs of agricultural machinery users, but also improve the efficiency and quality of maintenance services, providing strong support for the sustainable development of the agricultural machinery industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 Flowchart for pricing farm machinery repair services. DETAILED DESCRIPTION

[0084] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other in the absence of conflict.

[0085] The existing technology urgently needs a pricing method and system for agricultural machinery maintenance services based on data collection, analytical modeling, and dynamic pricing calculations to address the problems of traditional maintenance pricing models, such as strong subjectivity, lack of transparency, slow response, and insufficient market adaptability. This embodiment optimizes the maintenance quotation method through intelligent means, which can not only improve the efficiency and fairness of maintenance services, but also enhance the predictability of maintenance costs for agricultural machinery users, reduce equipment maintenance risks during agricultural production, and thus promote the sustainable development of agricultural mechanization. The details are as follows:

[0086] Specific implementation method 1: refer to Figure 1 Specifically describing this embodiment, a pricing method for agricultural machinery maintenance services described in this embodiment includes:

[0087] 1. Data Collection

[0088] Collect various types of data related to agricultural machinery maintenance, including: equipment status score S, maintenance history factor H, market reference price M, labor cost L and maintenance difficulty bonus A.

[0089] The expression of the device status score S is:

[0090] S=f1(F,D,U)=β1F+β2D+β3U,

[0091] Among them, F is the current fault level, D is the cumulative operating days of the equipment, U is the usage frequency of the equipment in the last month, and β1, β2, and β3 are the weight coefficients of F, D, and U, respectively.

[0092] The expression of the maintenance history factor H is:

[0093] H=f2(N repair ,T usage )=γ1N repair +γ2ln(T usage +1),

[0094] Among them, N repair is the cumulative number of equipment maintenance times, T usage is the cumulative usage time of the device, γ1 and γ2 are N repair and T usage The weight coefficient is used to adjust the relative influence of the number of maintenance times and the length of use. ln(·) represents the natural logarithm to reduce the influence of extreme large values ​​on the model.

[0095] The expression of the market reference price M is:

[0096] M=f3(P market ,ε)=α1P market +α2ε,

[0097] Among them, P market is the current market average price of maintenance services, ε is the local price volatility, α1 and α2 are P market The weight coefficients of and ε are used to reflect the impact of market prices and price fluctuations on pricing.

[0098] The expression of the labor cost L is:

[0099] L=f4(R,T repair )=ρ1R+ρ2T repair ,

[0100] Where R is the number of maintenance resources required; T repair is the actual maintenance time, ρ1 and ρ2 are R and T respectively repair The weight coefficient of .

[0101] The expression of the repair difficulty bonus A is:

[0102] A=f5(C f )=ηC f ,

[0103] Among them, C f is the current labor cost, and η is the standard working time.

[0104] 2. Process the collected data to ensure data quality and timeliness.

[0105] 2.1 Fill in the equipment status data

[0106] Missing value filling:

[0107]

[0108] Among them, x i represents a data in the device status dataset X, and mean(X) represents the mean of all data in the device status dataset X.

[0109] 2.2 Outlier Processing

[0110]

[0111] Among them, Z i is the standard score, and σ is the standard deviation.

[0112] When | Z i |>3, then x i If it is an exception, delete the abnormal value.

[0113] 2.3 Normalization of device status data

[0114]

[0115] Where: x i and x i ′ are the device status data before and after normalization, and their value range is [0,1]; x min and x max are the minimum and maximum values ​​in the device status dataset X, respectively.

[0116] 3. Analysis and Modeling

[0117] Establish a calculation model for maintenance costs:

[0118] C repair =w1S′+w2H′+w3M′+w4L′+w5A′,

[0119] Where: C repair is the maintenance cost, w1, w2, w3, w4, and w5 are the weight coefficients of S′, H′, M′, L′, and A′, respectively, which are determined through historical data training; S′, H′, M′, L′, and A′ are the normalized results of S, H, M, L, and A, respectively.

[0120] 4. Pricing

[0121] Build a comprehensive pricing model:

[0122] C′ repair =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′,

[0123] Where: C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

[0124] Dynamic pricing adjustment (taking market fluctuations into account):

[0125]

[0126] Where: C repair is the adjusted pricing of agricultural machinery maintenance services, and ΔM is the fluctuation range of market maintenance prices.

[0127] 5. User Interface

[0128] Provide users with query and reporting functions to display maintenance costs and history.

[0129] The user provides parameters for estimating the pricing of agricultural machinery maintenance services, which include: the equipment status score S entered by the user user , user-entered maintenance history factor H user , the market reference price M entered by the user user , labor cost L entered by the user user and the user-entered repair difficulty bonus A user, and then make an estimate of the pricing of agricultural machinery maintenance services:

[0130] C query =(w1S user +w2H user +w3M user )×(1+β4)+w4L user +w5A user ,

[0131] Among them, C query Estimate results for pricing agricultural machinery repair services.

[0132] Specific embodiment 2: The agricultural machinery maintenance service pricing system described in this embodiment includes:

[0133] Collection unit: used to collect equipment status score S, maintenance history factor H, market reference price M, labor cost L and maintenance difficulty bonus A;

[0134] Calculation unit: used to establish a comprehensive pricing model based on the collected parameters and calculate the pricing of agricultural machinery maintenance services using the comprehensive pricing model;

[0135] The comprehensive pricing model includes:

[0136] C′ repair =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′,

[0137] Among them, C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

[0138] Specific embodiment three: This embodiment describes an agricultural machinery maintenance service pricing device, which includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement an agricultural machinery maintenance service pricing method as described in specific embodiment one.

[0139] Specific embodiment 4: This embodiment describes a computer storage medium, in which at least one instruction is stored. The at least one instruction is loaded and executed by a processor to implement a method for pricing agricultural machinery maintenance services as described in specific embodiment 1.

[0140] Example: Repair Pricing for Agricultural Tractors

[0141] Assume that a tractor needs repair due to engine failure. The collected data is as follows:

[0142] Equipment status score: S=8.5;

[0143] Maintenance history factor: H = 3.2;

[0144] Market reference price: M = 2000 yuan;

[0145] Labor cost: L = 80 yuan / hour, actual maintenance time T repair =5 hours;

[0146] Repair difficulty bonus: A = 100;

[0147] Assume that the weight parameters are:

[0148] w1=10, w2=5, w3=0.8, w4=1.2, w5=1.5, β4=0.05.

[0149] Use the calculation formula:

[0150] C′ repair =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′

[0151] The agricultural machinery maintenance pricing method and system of the present invention realizes intelligent, precise and transparent calculation of maintenance costs in a data-driven manner, improves the efficiency and rationality of agricultural machinery maintenance services, and promotes the development of agricultural mechanization.

[0152] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. A pricing method for agricultural machinery maintenance services, characterized in that: include: Collect equipment status score S, maintenance history factor H, market reference price M, labor cost L, and maintenance difficulty bonus A, establish a comprehensive pricing model based on the collected parameters, and use the comprehensive pricing model to calculate the price of agricultural machinery maintenance services; The comprehensive pricing model includes: <h2 style=";text-align:left;direction:ltr">C′<h2 style=";text-align:left;direction:ltr"> repair <h2 style=";text-align:left;direction:ltr"> =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′, Among them, C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

2. The agricultural machinery maintenance service pricing method according to claim 1, characterized in that: Also includes: When the market maintenance price changes, the pricing will be adjusted dynamically: Where: C repair is the adjusted pricing of agricultural machinery maintenance services, and ΔM is the fluctuation range of market maintenance prices.

3. A pricing method for agricultural machinery maintenance services according to claim 1 or 2, characterized in that: The expression of the device status score S is: S=β1F+β2D+β3U, Among them, F is the current fault level, D is the cumulative operating days of the equipment, U is the usage frequency of the equipment in the last month, and β1, β2, and β3 are the weight coefficients of F, D, and U, respectively.

4. A pricing method for agricultural machinery maintenance services according to claim 1 or 2, characterized in that: The maintenance history factor H H=γ1N repair +γ2ln(T usage +1), Among them, N repair is the cumulative number of equipment maintenance times, T usage is the cumulative usage time of the device, γ1 and γ2 are N repair and T usage The weight coefficient of , ln(·) means taking the natural logarithm.

5. A pricing method for agricultural machinery maintenance services according to claim 1 or 2, characterized in that: The expression of the market reference price M is: M=α1P market +α2ε, Among them, P market is the current market average price of maintenance services, ε is the local price volatility, α1 and α2 are P market and the weight coefficient of ε.

6. A pricing method for agricultural machinery maintenance services according to claim 1 or 2, characterized in that: The expression of the labor cost L is: L=ρ1R+ρ2T repair , Where R is the number of maintenance resources required; T repair is the actual maintenance time, ρ1 and ρ2 are R and T respectively repair The weight coefficient of .

7. A pricing method for agricultural machinery maintenance services according to claim 1 or 2, characterized in that: The expression of the repair difficulty bonus A is: A=f5(C f )=ηC f , Among them, C f is the current labor cost, and η is the standard working time.

8. A pricing system for agricultural machinery maintenance services, characterized in that: include: Collection unit: used to collect equipment status score S, maintenance history factor H, market reference price M, labor cost L and maintenance difficulty bonus A; Calculation unit: used to establish a comprehensive pricing model based on the collected parameters and calculate the pricing of agricultural machinery maintenance services using the comprehensive pricing model; The comprehensive pricing model includes: <h2 style=";text-align:left;direction:ltr">C′<h2 style=";text-align:left;direction:ltr"> repair <h2 style=";text-align:left;direction:ltr"> =(w1S′+w2H′+w3M′)×(1+β4)+w4L′+w5A′, Among them, C′ repair The price of agricultural machinery maintenance services is set, and β4 is the inflation adjustment coefficient.

9. An agricultural machinery maintenance service pricing device, characterized in that: The agricultural machinery maintenance service pricing device includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the agricultural machinery maintenance service pricing method as described in one of claims 1 to 8.

10. A computer storage medium, characterized in that The computer storage medium stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the agricultural machinery maintenance service pricing method according to any one of claims 1 to 8.

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