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CN-121998691-A - Rapid quotation method based on parameterized BOM and multidimensional cost coupling

CN121998691ACN 121998691 ACN121998691 ACN 121998691ACN-121998691-A

Abstract

The invention discloses a rapid quotation method based on parameterized BOM and multidimensional cost coupling, which relates to the field of rapid quotation and comprises the following steps of S1, acquiring data, and checking a preset rule and a database; S2, marking to form a data set and storing the data set, S3, preprocessing the data set to extract core associated parameters and output a multi-version list, S4, presetting a scheme and a strategy, constructing a multi-dimensional cost coupling calculation model, S5, setting an adjustment rule introduction algorithm to generate a multi-dimensional cost quick quotation scheme, S6, generating a verification scheme, constructing a cost coupling feedback correction model, S7, performing verification adjustment, generating a report, and outputting the scheme and the report. According to the method, the self-adaptive parameterized BOM list is generated through the three-dimensional classification labeling mechanism and the four-dimensional dynamic parameter mapping model, so that the accuracy of multi-scene customized quotation is improved.

Inventors

  • JIANG ZHICHAO
  • YE BO
  • GAO ZHIHONG

Assignees

  • 武汉工学智联科技有限公司

Dates

Publication Date
20260508
Application Date
20260116

Claims (10)

  1. 1. A method for rapidly quoting based on parameterized BOM and multidimensional cost coupling, comprising the steps of: S1, acquiring product multi-scene customization demand data and product multi-scene customization historical data, presetting a product scene parameter bidirectional constraint rule and a multi-mode historical quotation database, and performing double verification on the customization demand data based on the product scene parameter bidirectional constraint rule; S2, customizing the multi-scene customization demand data of the double-checked product, carrying out three-dimensional classification labeling according to scene types, customization complexity and cost sensitivity to form a product parameter labeling data set, and carrying out associated structural storage with a historical quotation database; s3, carrying out standardized pretreatment on the product parameter labeling data set, extracting core associated parameters by adopting a parameter BOM mapping algorithm, presetting a BOM level self-adaptive generation rule, constructing a four-dimensional dynamic parameter mapping model, inputting the core associated parameters into the four-dimensional dynamic parameter mapping model, and outputting a multi-version configurable parameterized BOM list; S4, presetting a multi-dimensional full-life-cycle cost accounting scheme and a cost parameter dynamic mapping strategy, defining a time-varying corresponding relation and a weight coefficient of each parameter in the multi-version configurable parameterized BOM list and the multi-dimensional full-life-cycle cost accounting scheme through the cost parameter dynamic mapping strategy, and constructing a multi-dimensional cost coupling calculation model based on the time-varying corresponding relation and the weight coefficient and an LSTM time sequence prediction model; S5, setting a cost dynamic adjustment rule, introducing a self-adaptive chaotic sparrow search algorithm and a Bayesian fusion algorithm, defining a multi-objective optimization function and an enterprise cost constraint condition, and carrying out algorithm fusion iterative optimization on the self-adaptive chaotic sparrow search algorithm and the Bayesian fusion algorithm to obtain a cost accounting reference value, a cost fluctuation interval and a trend prediction curve, so as to generate a multi-dimensional cost rapid quotation scheme; S6, extracting a historical candidate cost parameter set from a multi-mode historical quotation database, carrying out combined optimization on the historical candidate cost parameter set through a self-adaptive chaotic sparrow search algorithm and a Bayesian fusion algorithm to generate a personalized multi-dimensional cost accounting scheme, and constructing a cost coupling feedback correction model based on a weighted summation algorithm, the self-adaptive chaotic sparrow search algorithm and the Bayesian fusion algorithm; And S7, inputting the personalized multi-dimensional cost accounting scheme into a cost coupling feedback correction model to verify and adjust the multi-dimensional cost quick quotation scheme, generating a five-dimensional quotation verification report, and outputting the multi-dimensional cost quick quotation scheme and the five-dimensional quotation verification report after verification and adjustment.
  2. 2. The method for quickly quoting based on parameterized BOM and multidimensional cost coupling according to claim 1, wherein the standardized pretreatment is performed on the product parameter labeling data set, a parameter BOM mapping algorithm is adopted to extract core association parameters, a BOM level self-adaptive generation rule is preset, a four-dimensional dynamic parameter mapping model is constructed, and the core association parameters are input into the four-dimensional dynamic parameter mapping model to output a multi-version configurable parameterized BOM list, and the method comprises the following steps: S31, removing abnormal values in the product parameter labeling data set by adopting a 3 sigma principle, supplementing missing key parameters by a K nearest neighbor interpolation method, deleting repeated data by utilizing a Hash deduplication method, converting the product parameter labeling data set into a [0,1] interval, and converting non-numerical classification parameters into numerical vectors by adopting single-heat coding to form a standardized parameter data set; S32, presetting a relevancy threshold, constructing a parameter BOM relevancy assessment matrix by adopting a parameter BOM mapping algorithm, bringing a standardized parameter data set into the parameter BOM relevancy assessment matrix, screening according to the relevancy threshold to obtain a screened core parameter set, and removing redundant parameters through a variance expansion factor to obtain the core relevancy parameter set; S33, defining a three-level basic framework of a top-level product assembly, a middle-level functional component and a bottom-level core part, adapting the level refinement degree according to a customized complexity quantization value, adding a priority identifier to a part with high cost sensitivity, and defining BOM level linkage logic when parameters are changed through an IF-THEN rule base to form a BOM level self-adaptive generation rule; S34, based on BOM level self-adaptive generation rules, building four-layer architectures of an input layer, a feature fusion layer, a mapping calculation layer and an output layer by taking product multi-scene customization historical data as samples, performing cross-validation optimization to obtain a dynamic mapping weight matrix, and inputting a core association parameter set into the dynamic mapping weight matrix to output a multi-version configurable parameterized BOM list.
  3. 3. The method for rapidly quoting based on parameterized BOM and multidimensional cost coupling according to claim 1, wherein the preset multidimensional full life cycle cost accounting scheme and cost parameter dynamic mapping strategy defines a time-varying corresponding relation and a weight coefficient of each parameter in the multi-version configurable parameterized BOM list and the multidimensional full life cycle cost accounting scheme through the cost parameter dynamic mapping strategy, and constructs a multidimensional cost coupling calculation model based on the time-varying corresponding relation and the weight coefficient and the LSTM time sequence prediction model, comprising the following steps: S41, definitely designing cost accounting dimensions in five stages of research and development, purchasing, production, operation and maintenance and scrapping, and defining quantifiable indexes of each cost accounting dimension to form a multi-dimension full life cycle cost accounting scheme; S42, presetting a cost parameter dynamic mapping strategy, constructing a parameter cost time-varying corresponding relation matrix, wherein the specification, the materials and the process parameters in a multi-version configurable parameterized BOM list are used as row vectors, a life cycle cost accounting item is used as column vector, matrix elements are used as time-varying association coefficients, and weight coefficients are set according to cost sensitivity; S43, constructing a multidimensional cost coupling calculation model of a four-layer architecture of an input layer, a characteristic fusion layer, a time sequence prediction layer and a coupling calculation layer based on a time-varying corresponding relation, a weight coefficient and an LSTM time sequence prediction model; S44, verifying and optimizing the multi-dimensional cost coupling calculation model, and outputting the multi-dimensional cost coupling calculation model after verifying and optimizing.
  4. 4. The method for rapidly quoting based on parameterized BOM and multidimensional cost coupling according to claim 1, wherein the method is characterized in that a cost dynamic adjustment rule is set, a self-adaptive chaotic sparrow search algorithm and a Bayesian fusion algorithm are introduced, a multi-objective optimization function and an enterprise cost constraint condition are defined, algorithm fusion iterative optimization is carried out on the self-adaptive chaotic sparrow search algorithm and the Bayesian fusion algorithm, a cost accounting reference value, a cost fluctuation interval and a trend prediction curve are obtained, and a multidimensional cost rapid quoting scheme is generated: s51, defining cost adjustment logic and cost response rules of raw material prices, exchange rates and logistics freight market factors, and integrating to form cost dynamic adjustment rules; s52, defining a multi-objective optimization function with the lowest cost, the optimal profit and the strongest quotation competitiveness as targets, and defining an enterprise cost constraint condition according to the unit product profit margin, the total cost upper limit and the quotation response time requirement; And S53, introducing a self-adaptive chaotic sparrow search algorithm and a Bayesian fusion algorithm to perform fusion iterative optimization, searching an optimal solution through the self-adaptive chaotic sparrow search algorithm, and correcting an optimization result by utilizing the Bayesian fusion algorithm to obtain a cost accounting reference value, a cost fluctuation interval and a trend prediction curve, and integrating to form a multi-dimensional cost rapid quotation scheme.
  5. 5. The method for quickly quoting based on parameterized BOM and multidimensional cost coupling according to claim 1, wherein the steps of extracting a historical candidate cost parameter set from a multi-mode historical quotation database, performing combined optimization on the historical candidate cost parameter set through a self-adaptive chaotic sparrow search algorithm and a bayesian fusion algorithm to generate a personalized multidimensional cost accounting scheme, and constructing a cost coupling feedback correction model based on a weighted summation algorithm, the self-adaptive chaotic sparrow search algorithm and the bayesian fusion algorithm comprise the following steps: s61, extracting a historical candidate cost parameter set from a multi-mode historical quotation database; s62, performing global optimization on the historical candidate cost parameter set through a self-adaptive chaotic sparrow searching algorithm, and screening out an initial parameter combination meeting the cost precision requirement; S63, performing deviation correction and probability optimization on the initial parameter combination by using a Bayesian fusion algorithm, obtaining a cost parameter combination by using a fusion iteration mechanism of optimization correction, and generating a personalized multidimensional cost accounting scheme according to the cost parameter combination; S64, based on a weighted summation algorithm, the optimizing capability of the self-adaptive chaotic sparrow search algorithm and the correction characteristic of the Bayesian fusion algorithm are fused, a cost coupling feedback correction model is constructed, and the input of the cost coupling feedback correction model is definitely a quotation scheme, personalized accounting data and the output of the cost coupling feedback correction model is a deviation correction coefficient.
  6. 6. The method for rapidly quoting based on coupling of parameterized BOM and multidimensional cost according to claim 2, wherein the preset association threshold is adopted, a parameter BOM association evaluation matrix is constructed by adopting a parameter BOM mapping algorithm, a standardized parameter data set is brought into the parameter BOM association evaluation matrix, screening is carried out according to the association threshold to obtain a screened core parameter set, redundant parameters are removed through a variance expansion factor, and the core association parameter set is obtained, and the method comprises the following steps: s321, carrying out fitting analysis on the multi-scene customization historical data of the product, and presetting a correlation threshold based on fitting analysis results; S322, constructing a standardized parameter and BOM core element association degree evaluation matrix by adopting a parameter BOM mapping algorithm, and calculating matrix elements in the association degree evaluation matrix through pearson correlation coefficients, wherein row vectors in the association degree evaluation matrix are standardized product parameters, and column vectors in the association degree evaluation matrix are BOM core elements; s323, carrying the standardized parameter data set into a relevance evaluation matrix to calculate a relevance value, screening the relevance value to obtain a primary screening core parameter set, and eliminating multiple collinearity redundancies in the primary screening core parameter set through a variance expansion factor to obtain a secondary screening core parameter set; S324, the secondary screening core parameters in the secondary screening core parameter set are subjected to priority ranking according to the parameter sizes, and a core association parameter set is formed.
  7. 7. The method for rapidly quoting based on parameterized BOM and multidimensional cost coupling according to claim 3, wherein the multidimensional cost coupling calculation model based on the time-varying correspondence, the weight coefficient and the LSTM time sequence prediction model is constructed by an input layer, a feature fusion layer, a time sequence prediction layer and a coupling calculation layer four-layer architecture, and comprises the following steps: S431, the input layer receives specification, materials and process parameters in the multi-version configurable parameterized BOM list, combines time-varying corresponding relations and weight coefficients in a cost parameter dynamic mapping strategy, and outputs standardized fusion input vectors after Min-Max normalization processing; S432, a feature fusion layer receives a standardized fusion input vector, adopts a weighting splicing mechanism of parameter features and time-varying associated features, distributes fusion weights according to cost sensitivity, and outputs a high-dimensional fusion feature vector through feature dimension alignment and redundancy elimination processing; S433, embedding an LSTM time sequence prediction model into the time sequence prediction layer, inputting a standardized fusion input vector for iterative training by taking historical cost time sequence data as a training basis, learning and analyzing a cost time sequence change rule, and outputting a time sequence trend correction coefficient; and S434, the coupling calculation layer combines the parameter cost time-varying corresponding relation matrix, performs matrix operation coupling on the high-dimensional fusion feature vector and the time sequence trend correction coefficient to generate a multi-dimensional full life cycle cost calculation result, and integrates the multi-dimensional full life cycle cost calculation result according to the hierarchical structures of the input layer, the feature fusion layer, the time sequence prediction layer and the coupling calculation layer to form a multi-dimensional cost coupling calculation model of a four-layer structure.
  8. 8. The method for rapidly quoting based on parameterized BOM and multidimensional cost coupling according to claim 4, wherein the method for performing fusion iterative optimization by introducing the adaptive chaotic sparrow search algorithm and the Bayesian fusion algorithm, searching the optimal solution by the adaptive chaotic sparrow search algorithm, and correcting the optimal result by using the Bayesian fusion algorithm to obtain a cost accounting reference value, a cost fluctuation interval and a trend prediction curve, and integrating to form a multidimensional cost rapid quoting scheme comprises the following steps: s531, the optimization target and the boundary of the self-adaptive chaotic sparrow search algorithm are determined by taking the multi-target optimization function as a guide and combining the enterprise cost constraint condition and the cost dynamic adjustment rule; s532, performing global optimization on the output result of the multi-dimensional cost coupling calculation model through a self-adaptive chaotic sparrow search algorithm, and screening a candidate optimal solution set meeting the constraint condition of the enterprise cost; S533, introducing a Bayesian fusion algorithm, carrying out deviation correction and probability verification on the candidate optimal solution based on the product multi-scene customization historical data, and outputting a cost accounting reference value and a confidence interval; S534, combining the cost accounting reference value and the confidence interval with a cost dynamic adjustment rule to generate a cost fluctuation interval, associating a trend prediction curve, and integrating to form a multi-dimensional cost rapid quotation scheme.
  9. 9. The method for quickly quoting based on parameterized BOM and multidimensional cost coupling according to claim 5, wherein the method for performing bias correction and probability optimization on the initial parameter combination by using a Bayesian fusion algorithm, obtaining a cost parameter combination by using a fusion iteration mechanism of optimization correction, and generating a personalized multidimensional cost accounting scheme according to the cost parameter combination comprises the following steps: s631, taking the initial parameter combination and the product multi-scene customized historical data as historical reference combination, and calculating a cost deviation value of the initial parameter combination and the historical reference combination; S632, introducing a Bayesian fusion algorithm, constructing a deviation correction model based on the historical reference combination and the cost deviation value, and performing probability optimization on the initial parameter combination through the deviation correction model to obtain a probability optimization parameter combination; S633, feeding back the probability optimization parameter combination to a self-adaptive chaotic sparrow searching algorithm for secondary optimization through an optimization correction fusion iteration mechanism, and repeating iteration until the enterprise cost constraint condition is met, so as to obtain a cost parameter combination; S634, substituting the cost parameter combination into the multi-dimensional full life cycle cost accounting scheme to generate an adaptive personalized multi-dimensional cost accounting scheme.
  10. 10. The method for rapidly quoting based on parameterized BOM and multidimensional cost coupling according to claim 8, wherein the method for globally optimizing the output result of the multidimensional cost coupling calculation model by the adaptive chaotic sparrow search algorithm and screening the candidate optimal solution set meeting the constraint condition of the enterprise cost comprises the following steps: S5321, initializing core parameters of a self-adaptive chaotic sparrow search algorithm based on an optimizing target and a boundary, and taking an output result of a multi-dimensional cost coupling calculation model as an initial population; S5322, carrying out algorithm iteration, improving population diversity through a chaotic disturbance mechanism, executing global optimization by combining a sparrow population finder and a joiner division mechanism, and calculating the fitness value of each individual by taking a multi-objective optimization function as a fitness function for sorting; S5323, based on the fitness value sequencing result, performing compliance verification on each cost accounting candidate scheme against the enterprise cost constraint condition, removing schemes which do not meet the constraint condition, and performing de-duplication processing on the remaining compliance schemes to form a candidate optimal solution set.

Description

Rapid quotation method based on parameterized BOM and multidimensional cost coupling Technical Field The invention relates to the technical field of quick quotation. And more particularly, to a fast quotation method based on parameterized BOM and multidimensional cost coupling. Background In the era of cooperative upgrading of manufacturing customization transformation and global supply chain, a rapid quotation technology under multi-scenario customization demand is used as a core hub for linking customer demands and enterprise production, and is widely applied to key fields such as automobile customization modification, engineering equipment purchasing, industrial part customization, intelligent hardware personalized production and the like, and the timeliness of quotation, the accuracy of cost accounting and the flexibility of scenario adaptation are directly related to enterprise order conversion rate, production cost control efficiency and market competitiveness, so that the rapid quotation technology becomes a core technical bottleneck which needs to break through in the manufacturing digitization transformation. The parameterized BOM technology and the full life cycle cost accounting method are deeply fused, the breakthrough value is shown in the field of rapid quotation by virtue of the rapid response capability to customized requirements and the full coverage advantage of cost dimension, and the core technical elements such as demand parameter analysis, dynamic BOM generation, multi-stage cost coupling, algorithm optimization decision and the like are integrated to construct a demand-BOM-cost-quotation integrated synergistic system, so that the parameterized BOM technology and the full life cycle cost accounting method become key technical directions for breaking through the limitations of the traditional quotation method and improving the quotation efficiency of customized scenes, and have important significance for improving the service level of clients, optimizing resource allocation and enhancing market competitiveness. However, when the existing rapid quotation method based on parameterized BOM and multidimensional cost coupling is used, most schemes adopt static BOM templates for quotation accounting, dynamic adaptation capability on custom complexity and cost sensitivity is lacked, personalized requirements of various scenes are difficult to match, cost accounting is limited to single production or purchasing stages, multidimensional coupling mechanisms of design research and development, purchasing, production, operation and maintenance and scrapping full life cycles are not formed, cost accounting is single-sided and has large deviation, meanwhile, the existing method relies on a single algorithm for cost optimization, closed loop iteration mechanisms supported by historical data are lacked, time-varying association relation between parameters and cost is not established, influences of market dynamic factors such as raw material price fluctuation and exchange rate adjustment are difficult to cope, finally, quotation response lag, insufficient precision and poor personalized adaptation are caused, and core requirements of enterprises cannot be met. For the problems in the related art, no effective solution has been proposed at present. Disclosure of Invention Aiming at the problems in the related art, the invention provides a rapid quotation method based on parameterized BOM and multidimensional cost coupling, so as to overcome the technical problems in the prior art. In order to achieve the above purpose, the specific technical scheme adopted by the invention is as follows: a method for fast quotation based on parameterized BOM and multidimensional cost coupling, comprising the steps of: S1, acquiring product multi-scene customization demand data and product multi-scene customization historical data, presetting a product scene parameter bidirectional constraint rule and a multi-mode historical quotation database, and performing double verification on the customization demand data based on the product scene parameter bidirectional constraint rule; S2, customizing the multi-scene customization demand data of the double-checked product, carrying out three-dimensional classification labeling according to scene types, customization complexity and cost sensitivity to form a product parameter labeling data set, and carrying out associated structural storage with a historical quotation database; s3, carrying out standardized pretreatment on the product parameter labeling data set, extracting core associated parameters by adopting a parameter BOM mapping algorithm, presetting a BOM level self-adaptive generation rule, constructing a four-dimensional dynamic parameter mapping model, inputting the core associated parameters into the four-dimensional dynamic parameter mapping model, and outputting a multi-version configurable parameterized BOM list; As a preferred scheme, the standardized preprocessing