A life cycle-based after-sales spare parts safety inventory calculation method

Abstract

This invention provides a lifecycle-based method for calculating safety stock of after-sales spare parts. It involves collecting and preprocessing raw data on spare parts to obtain structured data; dividing the lifecycle stage of the spare parts based on the structured dataset; analyzing the structured dataset according to the procurement cycle to obtain a baseline safety stock value for the spare parts; adjusting the baseline safety stock value based on the lifecycle stage of the spare parts to obtain the final safety stock value; and optimizing the safety stock value based on the cost data of the spare parts to obtain the final safety stock value. By dynamically adapting to the demand characteristics of each stage of the product lifecycle and optimizing the safety stock calculation logic with multi-dimensional parameters, this method ensures that appropriate spare parts inventory values ​​can be accurately determined at all stages throughout the entire lifecycle, ensuring a normal and stable supply of spare parts and avoiding inventory backlog.

Description

Technical Field

[0001] This invention relates to the field of supply chain, and more particularly to a lifecycle-based method for calculating safety stock of after-sales spare parts. Background Technology

[0002] After-sales spare parts for consumer electronics products such as mobile phones and computers are characterized by large demand fluctuations, short lifecycles, and significant price differences. Traditional safety stock calculation methods, such as fixed formula methods and static historical data fitting methods, have the following drawbacks: First, they fail to consider the differences in demand characteristics at different stages of the product lifecycle, leading to stockouts during the growth stage that affect customer satisfaction or inventory backlogs during the decline stage that tie up large amounts of capital and increase costs. Second, they lack targeted and effective strategies for inventory calculation during the introduction of new products, easily resulting in overstocking or stockouts. Third, they fail to optimize costs by incorporating spare parts prices, resulting in excessively high costs for high-value inventory. Therefore, there is an urgent need for an after-sales spare parts inventory safety calculation method that can dynamically adapt to the product lifecycle and integrate multi-dimensional parameters. Summary of the Invention

[0003] The purpose of this invention is to provide a lifecycle-based method for calculating safety stock of after-sales spare parts. This method involves collecting and preprocessing raw data about spare parts to obtain structured data; dividing the lifecycle stage of the spare parts based on the structured dataset; analyzing the structured dataset according to the procurement cycle to obtain a baseline safety stock value for the spare parts; adjusting the baseline safety stock value based on the lifecycle stage of the spare parts to obtain the final safety stock value; and optimizing the safety stock value based on the cost data of the spare parts to obtain the final safety stock value. By dynamically adapting to the demand characteristics of each stage of the product lifecycle and optimizing the safety stock calculation logic with multi-dimensional parameters, this method ensures that appropriate spare parts inventory values ​​can be accurately determined at all stages throughout the entire lifecycle, ensuring a normal and stable supply of spare parts and avoiding inventory backlog.

[0004] This invention is achieved through the following technical solution:

[0005] A lifecycle-based method for calculating safety stock of aftermarket spare parts includes:

[0006] Collect raw data about spare parts and preprocess the raw data into a structured dataset; wherein, the raw data includes spare part attribute data and spare part historical demand data;

[0007] Based on the structured dataset, the lifecycle stages of spare parts are divided; based on the procurement cycle, the structured dataset is analyzed to obtain the basic safety stock value of spare parts.

[0008] Based on the life cycle stage of the spare parts, the baseline value of the safety stock is adjusted to obtain the safety stock value.

[0009] Based on the cost data of spare parts, the safety stock value is optimized to obtain the final safety stock value.

[0010] Optionally, raw data about spare parts may be collected, including:

[0011] The system obtains spare parts attribute data and historical spare parts demand data from the after-sales system and the procurement system. The spare parts attribute data includes spare parts type, launch date, procurement cycle, logistics timeliness and unit price information. The historical spare parts demand data includes the daily demand for spare parts within a preset historical period.

[0012] Optionally, the raw data is preprocessed into a structured dataset, including:

[0013] The raw data is then cleaned and denoised.

[0014] Then, structured features are extracted from the original data to generate a structured dataset; wherein, the structured features include the mean, standard deviation, maximum and minimum demand of spare parts during the collection period.

[0015] Optionally, based on the structured dataset, the lifecycle stages of the spare parts are divided, including:

[0016] Based on the structured dataset, determine the time to market for spare parts. ;

[0017] Based on the aforementioned time to market and historical spare parts demand data, the threshold for lifecycle stage division is determined;

[0018] The life cycle stage of a spare part is determined based on the life cycle stage threshold; wherein, the life cycle stage includes growth stage, maturity stage, and decline stage.

[0019] Optionally, based on the time to market and historical spare parts demand data, a lifecycle stage segmentation threshold is determined, including:

[0020] Based on the product category to which the spare parts belong, determine the demand mean sequence corresponding to the time to market. And extract the peak demand value from the mean demand sequence. and standard deviation This determines the threshold for lifecycle stage segmentation. ;in, ;

[0021] Based on the aforementioned lifecycle stage segmentation threshold, the lifecycle stage of the spare parts is segmented, including:

[0022] Thresholds are defined based on the life cycle stages to determine the compliance range. ;in, ;

[0023] The minimum time to market corresponding to the aforementioned achievement range is defined as the growth period endpoint. The maximum value is defined as the end of the maturity period. This allows us to define the growth, maturity, and decline stages of spare parts; among which, the growth stage is... Maturity period is The recession period is .

[0024] Optionally, the structured dataset is analyzed based on the procurement cycle to obtain the baseline safety stock value for spare parts, including:

[0025] Determine the recent demand standard deviation based on historical spare parts demand data aggregated over the procurement cycle. and the standard deviation of full-cycle demand Wherein, the standard deviation of recent demand This represents the standard deviation of demand fluctuations for the sample size in the most recent half-purchase cycle, and the standard deviation of demand over the entire cycle. It is the standard deviation of demand fluctuations across the entire recent procurement cycle.

[0026] Use the following formula to determine the baseline safety stock value for spare parts. ,

[0027] in, This indicates the preset rating value. express Take the sum The maximum of the two.

[0028] Optionally, the safety stock base value is adjusted according to the lifecycle stage of the spare parts to obtain the safety stock value, including:

[0029] Determine the growth factor for adjusting the baseline value of the safety stock;

[0030] The safety stock base value is adjusted based on the growth coefficient and the life cycle stage of the spare parts to obtain the safety stock value.

[0031] Optionally, determining the growth factor for adjusting the baseline value of the safety stock includes:

[0032] Based on the historical spare parts demand data aggregated during the procurement cycle, a demand aggregation sequence is generated. , in, This represents the demand on the k-th day before time point t. It is an integer index, with a value range from 0 to... -1 is used to iterate through each day within the procurement cycle. Indicates the procurement cycle;

[0033] Use the following formula to determine the total demand within the future logistics timeframe corresponding to the current time t. , in, This represents the aggregate demand over time. It is an index of the number of cycles covered by logistics timeliness, with values ​​ranging from 1 to N. Indicates the procurement cycle. Indicates logistics timeliness. Indicates will The result is rounded up to the nearest integer as the number of cycles covered by the logistics timeliness;

[0034] Use the following formula to determine the demand growth ratio of spare part i. , ;

[0035] Use the following formula to determine the growth factor for adjusting the baseline value of the safety stock. ,

[0036] in, This represents the set of valid spare parts. Indicates the number of available spare parts.

[0037] Optionally, the safety stock base value is adjusted based on the growth coefficient and the life cycle stage of the spare parts to obtain the safety stock value, including:

[0038] When spare parts are in the growth stage, if the current period is the introduction phase of a new product and there is no historical demand data, then the preset new product introduction phase baseline value NPI will be used as the safety stock value. ;in, , Indicates the corresponding time within the demand aggregation sequence. The sample, , Indicates the quantity of similar equipment. This represents the cycle data from the first use of the m-th product to its first delivery;

[0039] If the current period is not the product introduction phase, meaning historical demand data exists, then the maximum value of the demand aggregation sequence will be used. Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now When spare parts are in the maturity stage, the maximum value of the demand aggregation sequence is used. and minimum value Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now ;

[0040] When spare parts are in a decline phase, based on the safety stock baseline value Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now .

[0041] Optionally, optimizing the safety stock value based on spare parts cost data to obtain a final safety stock value includes: determining an adjustment factor based on spare parts cost data using the following formula. ,

[0042] in, This indicates the preset price coefficient. Indicates the unit price of the spare parts;

[0043] When spare parts are in the growth or maturity stage, the final safety stock value = safety stock value ;

[0044] When spare parts are in their decline phase, the adjustment factor will be adjusted. Set to 1, and the final safety stock value = safety stock value .

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The lifecycle-based safety stock calculation method for after-sales spare parts provided in this application achieves significant breakthroughs in improving demand fulfillment rates and reducing Word of Inventory (WOI) by dynamically adapting to the demand characteristics of each stage of the product lifecycle and optimizing the safety stock calculation logic with multi-dimensional parameters. It has the following technical effects:

[0047] First, it can comprehensively improve the demand fulfillment rate. In response to the rapid fluctuations in demand during the growth stage, it accurately captures the growth trend of demand through special rules and dynamic correction of growth coefficients during the new product introduction period, effectively avoiding stockouts caused by delayed inventory preparation. The demand fulfillment capability is a qualitative leap compared to traditional methods. During the maturity stage, it relies on a correction logic that is deeply adapted to the characteristics of demand fluctuations, and can stably respond to both regular and sudden demands, maintaining a very high level of demand fulfillment. During the decline stage, it usually focuses on the refined analysis of recent demand data, and can still efficiently guarantee after-sales needs during the demand contraction stage, avoiding service gaps caused by rigid inventory strategies.

[0048] Secondly, it can optimize the display of WOI (Working Value Indicator) for inventory holding days. With the precise control of price adjustment factors, the inventory turnover efficiency of high-value spare parts is greatly improved, and the WOI for inventory holding days is significantly shortened compared with the traditional model. During the growth period, by scientifically predicting the pace of demand growth, the excess inventory caused by blind stockpiling is reduced, and the WOI for inventory holding days is substantially compressed. During the decline period, by forcibly constraining the upper limit of adjustment factors, inventory backlog is avoided from the mechanism, and the WOI for inventory holding days is significantly lower than the industry average. Especially at the end of the product cycle, the effect of inventory lightening is more prominent.

[0049] Third, it achieves a breakthrough in supply and demand balancing capabilities and synergistic optimization of demand fulfillment rate and Word of Inventory (WOI) of inventory holding days; for high-frequency demand spare parts, it significantly reduces inventory holding costs while ensuring service levels; for long-tail spare parts, it avoids ineffective inventory accumulation through dynamic lifecycle segmentation, significantly improves inventory turnover efficiency while maintaining stable service capabilities, and breaks the inherent contradiction of "high service inevitably leads to high inventory" in traditional methods. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0051] Figure 1 This invention provides a flowchart illustrating a lifecycle-based method for calculating safety stock of after-sales spare parts. Detailed Implementation

[0052] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, it should be noted that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, not the entire structure. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0053] The terms “comprising” and “having”, and any variations thereof, used in this application are intended to cover non-exclusive inclusion. For example, a process, method, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0054] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0055] Please see Figure 1 As shown in the figure, an embodiment of this application provides a method for calculating aftermarket spare parts safety stock based on the product lifecycle. This method includes:

[0056] Collect raw data about spare parts and preprocess the raw data into a structured dataset; the raw data includes spare part attribute data and historical spare part demand data.

[0057] Based on the structured dataset, the lifecycle stages of spare parts are divided; based on the procurement cycle, the structured dataset is analyzed to obtain the basic safety stock value of spare parts.

[0058] Based on the life cycle stage of the spare parts, adjust the base value of the safety stock to obtain the safety stock value;

[0059] Based on the cost data of spare parts, the safety stock value is optimized to obtain the final safety stock value.

[0060] The beneficial effects of the above embodiments are as follows: This lifecycle-based after-sales spare parts safety stock calculation method collects and preprocesses raw data about spare parts to obtain structured data; based on the structured dataset, it divides the lifecycle stage of the spare parts; it analyzes the structured dataset according to the procurement cycle to obtain the basic safety stock value of the spare parts; based on the lifecycle stage of the spare parts, it corrects the basic safety stock value to obtain the safety stock value; based on the cost data of the spare parts, it optimizes the safety stock value to obtain the final safety stock value. By dynamically adapting to the demand characteristics of each stage of the product lifecycle and combining multi-dimensional parameters to optimize the safety stock calculation logic, it ensures that appropriate spare parts inventory values ​​can be accurately determined at all stages throughout the entire lifecycle, ensuring a normal and stable supply of spare parts and avoiding inventory backlog.

[0061] In another embodiment, raw data about the spare parts is collected, including:

[0062] Obtain spare parts attribute data and historical spare parts demand data from the after-sales system and the procurement system; among them, spare parts attribute data includes spare parts type, launch date, procurement cycle, logistics timeliness and unit price information; spare parts historical demand data includes the daily demand for spare parts within a preset historical period.

[0063] In another embodiment, preprocessing the raw data into a structured dataset includes:

[0064] The raw data is cleaned and denoised.

[0065] Then, structured features are extracted from the raw data to generate a structured dataset; the structured features include the mean, standard deviation, maximum and minimum demand of spare parts during the collection period.

[0066] During the data acquisition phase, spare parts attribute data and historical spare parts demand data can be obtained from data sources such as the enterprise's internal after-sales system and procurement system. Spare parts attribute data includes basic information such as spare parts type, launch date, procurement cycle, logistics timeliness, and unit price. Historical spare parts demand data includes daily spare parts demand for at least 730 days. In the data preprocessing phase, the raw data of the collected spare parts attribute data and historical spare parts demand data undergoes data cleaning operations such as data consistency processing and handling invalid and missing values, as well as noise reduction processing such as Kalman filtering to reduce erroneous data and noise components. Then, structured features such as the mean, standard deviation, maximum, and minimum demand for spare parts during the acquisition period are extracted from the raw data. These raw data and structured features are then combined to generate a structured dataset, providing a reliable data basis for subsequent determination of safety stock at various stages of the product lifecycle.

[0067] In another embodiment, the lifecycle stage of spare parts is divided based on a structured dataset, including:

[0068] Based on the structured dataset, determine the time to market for spare parts. ;

[0069] Based on the time to market and historical spare parts demand data, determine the threshold for lifecycle stage division;

[0070] The life cycle stage of a spare part is determined by the threshold of the life cycle stage. The life cycle stage includes the growth stage, maturity stage, and decline stage.

[0071] In another embodiment, the lifecycle stage segmentation threshold is determined based on the time to market and historical spare parts demand data, including:

[0072] Based on the product category to which the spare parts belong, determine the demand mean sequence corresponding to the time to market. And extract the peak demand from the demand mean sequence. and standard deviation This determines the threshold for lifecycle stage segmentation. ;in, ;

[0073] Based on the threshold for lifecycle stage division, the lifecycle stage of spare parts is divided, including:

[0074] Thresholds are defined based on lifecycle stages to define compliance ranges. ;in, ;

[0075] The minimum time to market corresponding to the target range is defined as the growth period endpoint. The maximum value is defined as the end of the maturity period. This allows us to define the growth, maturity, and decline stages of spare parts; among which, the growth stage is... Maturity period is The recession period is .

[0076] In practice, the product's launch date and current date are extracted from the structured dataset, and the time to market for spare parts is calculated using the following formula. ,in Indicates to The results are rounded down, and the unit for the above-mentioned listing duration can be, but is not limited to, "months". By calculating the lifecycle stage segmentation threshold, all time intervals within the lifecycle are identified. Only time intervals whose duration is greater than or equal to the lifecycle stage segmentation threshold are determined to be compliant intervals. This ensures accurate segmentation of the entire product lifecycle. The entire lifecycle is divided into a growth phase (where product demand increases), a maturity phase (where product demand remains relatively stable), and a decline phase (where product demand decreases). This facilitates dynamic adaptation to the demand characteristics of each stage of the product lifecycle and allows for targeted determination of spare parts inventory.

[0077] In another embodiment, the basic safety stock value for spare parts is obtained by analyzing a structured dataset based on the procurement cycle, including:

[0078] Determine the recent demand standard deviation based on historical spare parts demand data aggregated over the procurement cycle. and the standard deviation of full-cycle demand Among them, the recent demand standard deviation This represents the standard deviation of demand fluctuations for the sample size in the most recent half-purchase cycle, and the standard deviation of demand over the entire cycle. It is the standard deviation of demand fluctuations for the sample size throughout the most recent procurement cycle;

[0079] Use the following formula to determine the baseline safety stock value for spare parts. ,

[0080] in, This indicates the preset rating value. The value can be, but is not limited to, 3.09. express Take the sum The maximum of the two.

[0081] Through the above process, the inventory value of spare parts can be determined at the procurement cycle level, ensuring that the determined safety stock base value can basically match the entire life cycle and will not deviate significantly from the actual inventory demand for spare parts throughout the entire life cycle.

[0082] In another embodiment, the safety stock base value is adjusted according to the lifecycle stage of the spare part to obtain the safety stock value, including:

[0083] Determine the growth factor for adjusting the baseline value of safety stock;

[0084] The safety stock base value is adjusted based on the growth factor and the life cycle stage of the spare parts to obtain the safety stock value.

[0085] In another embodiment, determining the growth factor for adjusting the safety stock base value includes:

[0086] Based on the historical spare parts demand data aggregated during the procurement cycle, a demand aggregation sequence is generated. ,in, This represents the demand on the k-th day before time point t. It is an integer index, with a value range from 0 to... -1 is used to iterate through each day within the procurement cycle. Indicates the procurement cycle;

[0087] Use the following formula to determine the total demand within the future logistics timeframe corresponding to the current time t. , in, This represents the aggregate demand over time. It is an index of the number of cycles covered by logistics timeliness, with values ​​ranging from 1 to N. Indicates the procurement cycle. Indicates logistics timeliness. Indicates will The result is rounded up to the nearest integer as the number of cycles covered by the logistics timeliness;

[0088] Use the following formula to determine the demand growth ratio of spare part i. , ;

[0089] Use the following formula to determine the growth factor for the adjusted safety stock base value. , in, This represents the set of valid spare parts. Indicates the number of available spare parts.

[0090] The growth coefficient for determining the base value of safety stock through the above process facilitates subsequent matching of the base value of safety stock to the growth, maturity, and decline phases of the life cycle, ensuring that the adjusted safety stock value is adapted to the actual needs of each stage of the life cycle.

[0091] In another embodiment, the safety stock base value is adjusted based on the growth factor and the lifecycle stage of the spare parts to obtain the safety stock value, including:

[0092] When spare parts are in the growth stage, if the current period is the introduction phase of a new product and there is no historical demand data, then the preset new product introduction phase baseline value NPI will be used as the safety stock value. ;in, , Indicates the corresponding time within the demand aggregation sequence. The sample, , Indicates the quantity of similar equipment. This represents the cycle data from the first use of the m-th product to its first delivery;

[0093] If the current period is not the product introduction phase, meaning historical demand data exists, then the maximum value of the demand aggregation sequence will be used. Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now ;

[0094] When spare parts are in the maturity stage, the maximum value is based on the demand aggregation sequence. and minimum value Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now ;

[0095] When spare parts are in a decline phase, based on the safety stock baseline value Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now .

[0096] Through the above process, the safety stock base value is adjusted differently for different stages of the spare parts' life cycle, such as growth, maturity, and decline, to ensure that accurate safety stock values ​​can be obtained for each stage, effectively avoiding inventory backlog throughout the entire life cycle.

[0097] In another embodiment, optimizing the safety stock value based on spare parts cost data to obtain the final safety stock value includes: determining an adjustment factor based on the spare parts cost data using the following formula. ,

[0098] in, This indicates the preset price coefficient. Indicates the unit price of the spare parts;

[0099] When spare parts are in the growth or maturity stage, the final safety stock value = safety stock value ;

[0100] When spare parts are in their decline phase, the adjustment factor will be adjusted. Set to 1, and the final safety stock value = safety stock value .

[0101] Through the above process, the price and cost of spare parts are taken into account when determining inventory. For high-frequency spare parts, the inventory holding cost is significantly reduced while ensuring service level. For long-tail spare parts, the ineffective inventory accumulation is avoided by dynamically dividing the life cycle. Under the premise of maintaining stable service capabilities, the inventory turnover efficiency is significantly improved, and large amounts of capital and cost burdens are avoided.

[0102] In summary, this lifecycle-based after-sales spare parts safety stock calculation method collects and preprocesses raw data on spare parts to obtain structured data; based on the structured dataset, it divides the lifecycle stage of the spare parts; analyzes the structured dataset according to the procurement cycle to obtain the baseline safety stock value for the spare parts; adjusts the baseline safety stock value according to the lifecycle stage of the spare parts to obtain the final safety stock value; and optimizes the safety stock value based on the cost data of the spare parts to obtain the final safety stock value. By dynamically adapting to the demand characteristics of each stage of the product lifecycle and optimizing the safety stock calculation logic with multi-dimensional parameters, it ensures that appropriate spare parts inventory values ​​can be accurately determined at all stages throughout the entire lifecycle, ensuring a normal and stable supply of spare parts and avoiding inventory backlog.

[0103] The above is only one specific embodiment of the present invention, and any improvements made based on the concept of the present invention shall be considered within the scope of protection of the present invention.

Claims

1. A life cycle based after-sales spare parts safety stock calculation method, characterized in that, The method comprises the following steps: Collecting original data about spare parts, and preprocessing the original data into a structured data set; wherein the original data comprises spare part attribute data and spare part historical demand data; According to the structured data set, dividing the life cycle stage of the spare parts; and according to the analysis of the structured data set based on the procurement cycle, obtaining the safety stock base value of the spare parts; According to the life cycle stage of the spare parts, correcting the safety stock base value to obtain the safety stock value; According to the cost data of the spare parts, optimizing the safety stock value to obtain the final safety stock value; According to the analysis of the structured data set based on the procurement cycle, obtaining the safety stock base value of the spare parts, comprising: Determine the recent demand standard deviation based on historical spare parts demand data aggregated over the procurement cycle. and the standard deviation of full-cycle demand Wherein, the standard deviation of recent demand This represents the standard deviation of demand fluctuations for the sample size in the most recent half-purchase cycle, and the standard deviation of demand over the entire cycle. It is the standard deviation of demand fluctuations for the sample size throughout the most recent procurement cycle; The safety stock base value of spare parts is determined by the following formula , wherein, represents a preset score value, represents the maximum of the sum and the maximum of both.

2. The life cycle-based after-sales spare part safety stock calculation method according to claim 1, wherein: Collecting original data about spare parts comprises: Obtaining spare part attribute data and spare part historical demand data from after-sales systems and procurement systems; wherein the spare part attribute data comprises spare part type, market date, procurement cycle, logistics time limit and unit price information; and the spare part historical demand data comprises daily demand amount of the spare parts in a preset length of historical period.

3. The life cycle-based after-sales spare part safety stock calculation method according to claim 2, wherein: The preprocessing of the original data into a structured data set comprises: Cleaning and denoising the original data; And then extracting structured features from the original data to generate a structured data set; wherein the structured features comprise demand mean, standard deviation, maximum and minimum demand amount of the spare parts in the collection cycle.

4. The life cycle-based after-sales spare part safety stock calculation method according to claim 1, wherein: According to the structured data set, dividing the life cycle stage of the spare parts comprises: determining a time-to-market of a spare part based on the structured data set ; Determining a life cycle stage division threshold according to the market length and the spare part historical demand data; According to the life cycle stage division threshold, dividing the life cycle stage of the spare parts; wherein the life cycle stage comprises a growth period, a mature period and a recession period.

5. The life cycle-based after-sales spare part safety stock calculation method according to claim 4, wherein: Determining a life cycle stage division threshold according to the market length and the spare part historical demand data comprises: According to the product category clustering to which the spare parts belong, determine the demand mean sequence corresponding to the time length of listing , extract the demand peak value of the demand mean sequence , and the standard deviation , thereby determining the life cycle stage division threshold ; wherein ; According to the life cycle stage division threshold, dividing the life cycle stage of the spare parts comprises: According to the life cycle phase division threshold, a compliance interval is defined ; wherein ; The minimum value of the listing duration corresponding to the target interval is defined as the end of the growth period , and the maximum value is defined as the end of the mature period , thereby defining the growth period, the mature period, and the recession period of the spare parts; wherein the growth period is , the mature period is , and the recession period is .

6. The life cycle-based after-sales spare part safety stock calculation method according to claim 1, wherein: According to the life cycle stage of the spare parts, correcting the safety stock base value to obtain the safety stock value comprises: Determining a growth coefficient for correcting the safety stock base value; According to the growth coefficient and the life cycle stage of the spare parts, correcting the safety stock base value to obtain the safety stock value.

7. The life cycle-based after-sales spare part safety stock calculation method according to claim 6, wherein: Determining a growth coefficient for correcting the safety stock base value comprises: Aggregating spare parts historical demand data according to procurement cycle to generate demand aggregation sequence , wherein, denotes the demand quantity at day k before time point t, is an integer index ranging from 0 to -1 for iterating over each day within the procurement period, denotes the procurement period; The total demand within the future logistics time limit corresponding to the current time t is determined by using the following formula , wherein, denotes time of the aggregated demand quantity, is an index of the number of periods covered by the logistics time horizon, taking values from 1 to N, denotes the procurement period, denotes the logistics time horizon, denotes rounding up the result of as the number of periods covered by the logistics time horizon; The demand growth ratio for spare part i is determined using the following formula , The growth factor to modify the safety stock base value is determined using the following formula , wherein, denotes the set of valid spare parts, denotes the number of valid spare parts.

8. The life cycle-based after-sales spare part safety stock calculation method according to claim 7, wherein: According to the growth coefficient and the life cycle stage of the spare parts, the safety stock base value is corrected to obtain a safety stock value, including: When the spare parts are in the growth period, if the current belongs to the new product introduction period, that is, there is no historical demand data, the preset new product introduction period benchmark value NPI is taken as the safety stock value ; wherein, , represents the sample of the corresponding time in the demand aggregation sequence, , represents the number of similar devices, represents the cycle data from the first consumption of the mth product to the first arrival. If the current does not belong to the product introduction period, that is, there is historical demand data, the maximum value based on the demand aggregation sequence , growth coefficient , the number of periods covered by logistics timeliness , determine the safety stock value , that is ; When spare parts are in the maturity stage, the maximum value is based on the demand aggregation sequence. and minimum value Growth coefficient The number of cycles covered by logistics timeliness Determine the safety stock value ,Right now ; When the spare parts are in the recession period, based on the safety stock base value , growth coefficient , the number of periods covered by logistics timeliness , determine the safety stock value , that is .

9. The life cycle-based safety stock calculation method for after-sales spare parts according to claim 1, characterized in that: According to the cost data of the spare parts, the safety stock value is optimized to obtain a final safety stock value, including: Using the following formula, the adjustment factor is determined from the cost data of the spare parts , wherein, represents a preset price coefficient, represents a unit price of the spare part; When the spare parts are in the growth period or the mature period, the final safety stock value = safety stock value ; When the spare part is in the decline phase, the adjustment factor is set to 1 and the final safety stock value = safety stock value .

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