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CN-121981497-A - Spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data

CN121981497ACN 121981497 ACN121981497 ACN 121981497ACN-121981497-A

Abstract

The invention discloses a spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data, which relates to the technical field of after-sales spare part scheduling and comprises that when a work order initiates a spare part demand request, solidifying inventory, in transit, reservation frozen, reconciliation, and availability of alternatives at the time of request, forming a supply availability evidence snapshot and generating a shadow demand entry registration shadow demand ledger. And receiving business events such as receiving, transferring, arriving, waiting, canceling an external acquisition transfer list and the like, reconciling the shadow demand items, and generating a real demand recovery record and a substitute migration relation account and offset record. And generating scheduling, renovating, outsourcing, allocating and site allocation schemes and write-back correction in a rolling time window, improving traceability, reducing demand cut-off deviation and enhancing performance and inventory stability.

Inventors

  • LI ZHIMING

Assignees

  • 湖南唐米力科技有限公司

Dates

Publication Date
20260505
Application Date
20260407

Claims (10)

  1. 1. Spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data comprises the following steps: Receiving a maintenance work order spare part demand request, collecting inventory, on-the-way, reservation/freezing occupation, allocating sources and substitute availability at the request moment, and solidifying and supplying availability evidence snapshots; receiving a business event sequence associated with the shadow demand item, wherein the business event sequence comprises a receiving event or a leaving event, an allocating event, a canceling event, an external acquisition event and a transfer event; The real demand recovery record and the instant receiving record are aggregated according to spare part material numbers and net points or areas to generate a distributed demand result; Taking the hard constraint demand, the semi-hard constraint demand, the soft constraint demand and the shortage risk exposure and cutoff risk index as inputs, generating a self-made production scheduling scheme, a renovation scheduling scheme, an external cooperation ordering scheme, a cross-bin allocation scheme and a website allocation scheduling scheme in a rolling time window, and writing back the result.
  2. 2. The spare part demand forecasting and flexible production scheduling method of claim 1, wherein: The availability-providing evidence snapshot reads available inventory, in-transit quantity and expected arrival time, reservation occupancy, freezing occupancy, adjustable sources and expected arrival time, available substitute list and availability thereof at the request time and solidifies, and the shadow demand entry comprises request time, promise completion time limit, gap quantity, candidate substitute, evidence abstract check code, version number and state circulation record.
  3. 3. The spare part demand forecasting and flexible production scheduling method of claim 2, wherein: When the available inventory is smaller than the required quantity and the expected arrival time of the in-transit quantity corresponding to the adjustable source is later than the promise completion time limit, a shadow requirement item is generated and the initial state of the shadow requirement item is marked as the shortage waiting material, and when the available substitute list exists and the availability of the available substitute list meets the promise completion time limit, the initial state of the shadow requirement item is marked as the high risk waiting for confirmation and the available substitute list is reserved.
  4. 4. The spare part demand forecasting and flexible production scheduling method of claim 3, wherein: The system comprises a service event sequence, a shadow requirement item and a system, wherein the service event sequence comprises a receiving event, an ex-warehouse event, a cross-warehouse transfer sending event, a cross-warehouse transfer arrival event, an arrival warehouse event, a work order waiting suspension event, a work order change event, a cancellation event, an outer picking event, a transfer event, an on-the-way estimated arrival time change event and a work order closing event, and the system is used for updating the state flow record of the shadow requirement item successively according to the service event sequence.
  5. 5. The spare part demand forecasting and flexible production scheduling method of claim 4, wherein the method comprises the following steps of: The account checking attribution is based on the business event sequence to update the state flow record so as to determine a final path, the final path is limited to original delay meeting, substitution meeting, cancellation loss, outer picking meeting and transfer bill meeting, the real demand recovery record is synchronously written into the offset record according to the backfill request moment of the final path, and each receiving, substitution, outer picking and transfer bill event corresponds to the offset shadow demand item.
  6. 6. The spare part demand forecasting and flexible production scheduling method of claim 5, wherein the method comprises the following steps of: When the ending path is the replacement meeting, the substitute receiving amount is reflected to the target spare part material number according to the replacement reflection weight and the replacement migration relation ledger is synchronously updated, the replacement migration relation ledger records the multi-stage replacement chain backtracking relation, and when the ending path is the cancellation loss, the outer picking meeting and the transfer meeting, the conversion probability is generated according to the waiting time, the client grade and the inner and outer protection and the confidence weight is written.
  7. 7. The spare part demand forecasting and flexible production scheduling method of claim 6, wherein: The real demand recovery record and the instant receiving record are aggregated according to spare part material numbers, site positions and time granularity to form a deviation correction real demand sequence, a distributed demand result is output based on the deviation correction real demand sequence, the distributed demand result comprises demand under a guarantee level, short risk exposure is calculated by combining with supply availability evidence snapshot, and a cut-off risk index is generated based on cut-off rate, waiting duration distribution, conversion probability and replacement reflection weight.
  8. 8. The spare part demand forecasting and flexible production scheduling method of claim 7, wherein: The hard constraint demand and the semi-hard constraint demand are both extracted from registered shadow demand items and carry promise completion time limit and work order priority, the soft constraint demand is generated by an aggregation result of a real demand recovery record and an immediate acceptance record, and the hard constraint demand is ordered from early to late according to the promise completion time limit and takes the work order priority as an ordered ordering key.
  9. 9. The spare part demand forecasting and flexible production scheduling method of claim 8, wherein: Generating a flexible supply execution scheme in a rolling time window according to the sequence of the hard constraint requirement, the semi-hard constraint requirement and the soft constraint requirement, wherein the flexible supply execution scheme covers homemade production scheduling, renovation scheduling, external agreement ordering, cross-bin allocation and site allocation, and triggers local rescheduling when the shortage risk exposure exceeds a threshold value and triggers local rescheduling when the cut-off risk index exceeds the threshold value.
  10. 10. The spare part demand forecasting and flexible production scheduling method of claim 9, wherein: freezing the started homemade production scheduling and the issued cross-bin scheduling when the local rescheduling is performed, and only rescheduling the affected renovation scheduling, the outsourcing ordering and the network point allocation, adopting a deterministic bottom-covering strategy when the solving time is out, adopting a deterministic bottom-covering strategy when the data is missing, and writing back an execution result to a shadow demand ledger and updating the replacement reflection weight, the conversion probability and the triggering threshold value.

Description

Spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data Technical Field The invention relates to the technical field of after-sales spare part scheduling, in particular to a spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data. Background After-sales maintenance of mobile terminals (such as smartphones, tablets and handheld devices) often adopts a business process of 'customer repair-site detection diagnosis-spare part lead replacement-function verification-work order closing', and a service center, a direct-camping site and a third-party authorized site are established in the whole country or region to construct 'spare part bins' of 'center bin-region bin-site bin positions'. In order to meet the maintenance time, the primary repair rate and the quality insurance claim payment control, a work order management system, a warehouse management system and a purchasing production planning system of a common enterprise are provided with spare part replacement rules, cross-warehouse allocation, on-road tracking and emergency mechanism in the process, spare part demand prediction, replenishment and production decision making are carried out based on historical ex-warehouse, lead or replacement records, balance between the service level and inventory occupation is realized, and part of enterprises also adopt prediction results to develop self-made spare part production and outer cooperative scheduling. In the prior art, under the environment of product updating iteration of a mobile terminal, various models and material numbers, centralized key parts and long tail parts, large regional difference and strong requirement intermittence, a plurality of 'requirement observation deviation' processes exist in an objective maintenance link, such as the condition that a spare part is possibly lack of part to enter into to be filled or changed when a spare part request is made after diagnosis, so that the requirement occurrence time is separated from the actual lead time, the requirement of an original target spare part is consumed and absorbed by the replacement part to ensure that the aging can be completed by using a compatible part and a replacement part, a meeting path can be prolonged when the spare part is transferred from a warehouse or the stock is picked out, the record caliber of the cross system is inconsistent, or a customer waits for overtime, quotation change or channel strategy change, and the like, the condition that the spare part is cancelled to be transferred to external maintenance is caused, wherein part of the requirement does not exist in the system. The data caliber taking the lead/delivery as the center can not accurately describe the real demand and is accumulated in the prediction, the replenishment and the production scheduling to cause the repetition of the missing parts of the key parts, the increase of the urgent frequency, the unbalance of the stock structure and the fluctuation of the work order performance. Under the conditions of maintenance of multiple network points, multiple bins and multiple source supply of the mobile terminal, under the conditions of delay, migration or deletion of demand records caused by the business processes of material shortage, alternative collusion, cross-bin allocation, cancel transfer-out and the like, how to describe the occurrence time point and quantity of real demands of spare parts and uncertainty thereof, and systematic deviation easily occurs between the ex-warehouse collusion result and the real demands in quantity and time point. Disclosure of Invention (One) solving the technical problems Aiming at the defects of the prior art, the invention provides a spare part demand prediction and flexible production scheduling method based on mobile terminal maintenance data, which comprises the steps of receiving business events such as receiving, transferring, arriving, waiting, canceling an external acquisition transfer list, and the like, reconciling shadow demand items, generating a real demand recovery record, and replacing migration relation account and offset record. The method comprises the steps of forming distributed demands based on recovery records and instant receiving records, calculating short risk exposure and cut-off risk indexes to realize demand layering, generating production scheduling, renovating, external cooperation, allocation and site allocation schemes in a rolling time window, writing back and correcting, reducing demand cut-off deviation, enhancing track and stock stability, and solving the technical problems recorded in the background technology. (II) technical scheme In order to achieve the above purpose, the invention is realized by the following technical scheme: The spare part demand prediction and flexible production scheduling method based on the mobile terminal maintenance data comprises the steps of receivin