A data management method and system for the wine industry

Abstract

The present application relates to the field of wine data management, and particularly relates to a wine industry-oriented data management method and system. The wine industry-oriented data management method provided by the present application, for a plurality of wine production batches, realizes management through the following steps: based on each wine production batch, a corresponding batch data object is established, which is used to store data of the corresponding production batch in the production process; based on each batch data object, production parameters reflecting the current production situation of the corresponding production batch are obtained, and the production parameters are stored in the corresponding batch data object, wherein, in the process of storing the production parameters in the corresponding batch data object, when it is detected that the production state of a wine production batch satisfies a preset state change condition, corresponding state version data is generated based on the production state change event, and the state version data is written into the corresponding batch data object as an independent data record.

Description

Technical Field

[0001] This invention relates to the field of data management, and more particularly to a data management method and system for the wine industry. Background Technology

[0002] The wine industry is a typical process-oriented industry characterized by long production cycles, multiple production stages, and continuous changes in production status. From grape planting, harvesting, processing in the winery, winemaking, to bottling, wine typically goes through several interconnected but time-spanning production stages, with significant differences in technological activities, quality control requirements, and data collection content at each stage.

[0003] During the wine production process, a large amount of production data is continuously generated around specific wine production batches. This includes raw material sources and environmental parameters during the planting stage, testing parameters during harvesting and bottling, process parameters during the winemaking stage, and finished product quality inspection parameters during the bottling stage. This production data is typically collected and recorded by different systems or personnel at different stages of production, resulting in fragmented data sources, inconsistent data structures, and a lack of a unified organizational method for each individual production batch. Summary of the Invention

[0004] In one embodiment of the present invention, a data management method for the wine industry is provided, which manages several wine production batches through the following steps: establishing a corresponding batch data object for each wine production batch, each batch data object being used to store data of the corresponding production batch during the production process; obtaining production parameters reflecting the current production status of the corresponding production batch based on each batch data object, and storing the production parameters in the corresponding batch data object, wherein storing the production parameters in the corresponding batch data object includes: when it is detected that the production status of a wine production batch meets a preset status change condition, generating corresponding status version data based on this production status change event, and writing this status version data as an independent data record into the corresponding batch data object.

[0005] In a further embodiment, the creation of a batch data object for a wine production batch includes the following steps:

[0006] Based on the multiple production stages in the wine production process, a parameter storage structure corresponding to each of the multiple production stages is configured for the batch data object.

[0007] In a further embodiment, each batch of wine production goes through at least one or more of the following production stages: planting, harvesting, bottling, brewing, and bottling.

[0008] In a further embodiment, the parameter storage structure corresponding to each production stage is configured through the following steps:

[0009] Based on the set of process activities and / or quality control points of the corresponding production stage, configure the production parameters that can be stored in the corresponding parameter storage structure, and configure parameter feature information for this production parameter. The parameter feature information includes at least the production stage identifier, parameter unit, and parameter value range.

[0010] Based on the parameter feature information, the parameter writing rules of the corresponding parameter storage structure are configured. The parameter writing rules are used to verify at least the production stage, parameter type and parameter value range of the production parameter when the production parameter is written, so that the corresponding production parameter is allowed to be written to the corresponding parameter storage structure only when the verification is passed.

[0011] In a further embodiment, the preset state change condition is a combination of at least one or more of the following:

[0012] Production stage change conditions, which characterize the transition of a wine production batch from one production stage to another;

[0013] Production parameter out-of-bounds condition, wherein the production parameter out-of-bounds condition represents at least one production parameter corresponding to the current production stage whose parameter value exceeds a preset parameter threshold range;

[0014] The parameter change trend condition indicates that at least one production parameter, within a preset time window, has a change magnitude or change rate that meets a preset change judgment condition.

[0015] Production process event triggering conditions, wherein the production process event triggering conditions characterize the occurrence of preset process events and / or quality control events during the production process.

[0016] In a further embodiment, generating corresponding status version data based on a production status change event includes the following steps:

[0017] When generating the state version data, the moment when the production state change event occurs is determined as the state boundary point. Production parameters collected before the state boundary point are written into the previous state version data, and production parameters collected after the state boundary point are written into the next state version data.

[0018] After generating the status version data, based on the production batch identifier corresponding to this status version data, the current status version data is associated with at least one historical status version data of the production batch to generate a status version association structure that reflects the evolution of the production status.

[0019] In a further embodiment, the process of generating the state version association structure further includes the following steps:

[0020] A stage consistency constraint is applied to two or more associated state version data. The stage consistency constraint is used to limit the production stage corresponding to any two adjacent associated state version data to satisfy a preset production stage evolution relationship.

[0021] In a further embodiment, when a wine production batch is split or merged, the process of generating the state version association structure further includes the following steps: based on the state version association structure, all state version data corresponding to the original production batch are mapped to the batch data object corresponding to the split or merged production batch according to a preset inheritance mapping rule.

[0022] In a further embodiment, when the production status change event is triggered by abnormal production parameters or an abnormal production event, the process of generating the status version association structure further includes the following steps:

[0023] The state version data generated based on this production state change event is used as an abnormal state node. Within the corresponding state version association structure, an abnormal evolution path is established based on these abnormal state nodes to characterize the location of the abnormal state and its impact on subsequent production state evolution.

[0024] In a further embodiment, the present invention also provides a data management system for the wine industry, including a processor and a memory, wherein the memory stores a computer program, and the computer program is executed by the processor to perform the data management method for the wine industry proposed in any of the above embodiments.

[0025] The data management method and system for the wine industry provided by this invention have the following benefits:

[0026] This invention establishes batch data objects with wine production batches as the management object, and configures corresponding parameter storage structures and parameter writing rules for different production stages. This achieves unified carrying and phased constraint storage of production data at the production batch dimension, thereby avoiding the data fragmentation problem caused by scattered storage of data at different production stages and improving the consistency and reliability of multi-stage production data in terms of structure and stage attributes.

[0027] Furthermore, this invention generates state version data by using changes in production state as triggering conditions during the production process, and uses the moment when the production state change occurs as the state boundary point to divide the production data into distinct state versions. It also constructs a state version association structure that reflects the evolution of production state, so that the state change process of a production batch in multiple production stages can be continuously expressed in a structured manner, solving the problems of unclear data boundaries before and after changes in production state and difficulty in depicting the state evolution process in the prior art.

[0028] Furthermore, by introducing a stage consistency constraint mechanism, a state version inheritance mapping mechanism under the condition of production batch splitting or merging, and an abnormal evolution path construction mechanism under the triggering of abnormal production state in the state version association structure, the present invention enables the data management method to maintain the continuity and expressibility of the production state evolution relationship when the production batch structure changes or abnormal production state occurs, thereby avoiding the destruction of the production state evolution structure by production batch changes or abnormal state, and helping to improve the stability and integrity of the production state evolution expression under complex production conditions. Attached Figure Description

[0029] From the following description of embodiments in conjunction with the accompanying drawings, aspects, features, and advantages of the present invention will become clearer and more readily understood, in which:

[0030] Figure 1 A flowchart of a data management method for the wine industry provided as an embodiment of the present invention;

[0031] Figure 2 A schematic diagram illustrating the configuration process of a parameter storage structure provided in one embodiment of the present invention;

[0032] Figure 3 This is a schematic diagram of a data management system for the wine industry provided as an embodiment of the present invention. Detailed Implementation

[0033] To facilitate understanding of the present invention by those skilled in the art, several embodiments are now described in detail with reference to the accompanying drawings. It should be understood that the embodiments are for illustrative purposes only and not for limiting the scope of protection of the present invention; the scope of protection of the present invention is defined by the claims, and includes equivalent schemes and equivalent transformations of the claims.

[0034] As mentioned above, existing wine production data management mainly records data in units of production stages. The data is fragmented between stages, making it difficult to reflect the continuous changes in the state characteristics of production batches as the production process progresses. This results in a lack of effective data recording and correlation mechanisms for changes in production state, making it difficult to effectively utilize historical production data in the current production process.

[0035] Please see Figure 1 , Figure 2 and Figure 3 , Figure 1 A flowchart of a data management method for the wine industry provided as an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the configuration process of a parameter storage structure provided in one embodiment of the present invention. Figure 3 This is a schematic diagram of a data management system for the wine industry provided as an embodiment of the present invention.

[0036] like Figure 1 As shown, the data management method for the wine industry provided by this invention manages several wine production batches through the following steps:

[0037] S01. Establish a corresponding batch data object for each wine production batch, and each batch data object is used to store the data of the corresponding production batch during the production process.

[0038] In this invention, the batch data object is a data entity created for each batch of wine production to carry the data generated by that batch throughout the entire production process.

[0039] In one specific embodiment, each batch of wine production undergoes at least one or more of the following production stages: planting, harvesting, aging, winemaking, and bottling. It should be noted that the data types and contents generated at different production stages differ.

[0040] This invention establishes a corresponding batch data object for each batch of wine production, enabling the data generated at each stage of production for that batch to be uniformly stored in the same data entity, thereby avoiding data fragmentation caused by the scattered storage of data at different production stages.

[0041] In yet another specific embodiment, the establishment of a batch data object for any wine production batch, considering the differentiated production parameters generated at multiple stages of the wine production process, specifically includes the following steps:

[0042] S011. Based on the multiple production stages that wine production goes through, configure parameter storage structures for the batch data objects that correspond one-to-one with the multiple production stages.

[0043] It should be noted that the parameter storage structure proposed in this invention is used to store production parameters generated in the corresponding production stage, and the production parameters are limited to being written within the corresponding production stage.

[0044] In this embodiment, step S01 introduces a parameter storage structure corresponding to different production stages, enabling production parameters to have stage awareness during the writing process. This allows for the orderly organization and controlled writing of multi-stage production parameters within the same batch of data objects, improving the structural consistency and traceability of multi-stage production data.

[0045] Furthermore, in this embodiment, the parameter storage structure corresponding to each production stage is configured as follows: Figure 2 Configure the steps shown:

[0046] S0111. Based on the set of process activities and / or quality control points of the corresponding production stage, configure the production parameters that can be stored in the corresponding parameter storage structure, and configure parameter feature information for this production parameter. The parameter feature information includes at least the production stage identifier, parameter unit, and parameter value range.

[0047] For the set of process activities in the brewing stage (e.g., temperature-controlled fermentation, transfer to another tank, etc.) and / or quality control points (e.g., to prevent fermentation abnormalities from causing fermentation stagnation or producing undesirable flavors), the production parameters used to characterize the state of the brewing stage should include at least fermentation temperature and sugar content.

[0048] Furthermore, taking fermentation temperature as an example, the parameter characteristics configured for this production parameter should at least include: the production stage is identified as the brewing stage, the parameter unit is ℃, and the parameter value range is a preset temperature range (e.g., 10℃~35℃). It should be understood that this parameter and value range are only examples, and can be set according to the type of wine, process requirements, and quality control needs.

[0049] S0112. Based on the parameter feature information, configure the parameter writing rules for the corresponding parameter storage structure. The parameter writing rules are used to verify at least the production stage, parameter type and parameter value range of the production parameter when writing the production parameter, so that the corresponding production parameter is allowed to be written to the corresponding parameter storage structure only when the verification is passed.

[0050] Based on the above example, when the production batch is in the brewing stage and the collected production parameter is fermentation temperature, before writing it into the corresponding parameter storage structure, it verifies whether the parameter type of the collected production parameter corresponds to the fermentation temperature, verifies whether the collected value is within the preset temperature range, and also verifies whether the current production batch is in the brewing stage.

[0051] Only when all of the above checks pass will the production parameter be allowed to be written to the parameter storage structure corresponding to the brewing stage; if any of the above checks fail, the production parameter will be refused to be written or will be marked as abnormal data.

[0052] In this embodiment, by introducing a joint verification mechanism for parameter type, value range, and production stage during the parameter writing stage, production parameters that do not conform to the stage attributes are intercepted before being written, thereby reducing the possibility of abnormal data entering the valid dataset and improving the reliability of multi-stage production data.

[0053] S02. Based on each batch data object, obtain the production parameters reflecting the current production status of the corresponding production batch, and store the production parameters into the corresponding batch data object.

[0054] Furthermore, in the above embodiments, for the planting stage, the production parameters stored in the batch data object for each batch of wine production include at least one or more parameters used to characterize the source of grape raw materials and the state of the growing environment.

[0055] Specifically, the production parameters involved in the above-mentioned planting stages include, for example, grape variety information, planting plot identification, ambient temperature, rainfall, light conditions, soil type, soil moisture content, irrigation conditions, and parameters used to reflect grape maturity.

[0056] Furthermore, in the above embodiments, for the harvesting stage, the production parameters stored in the batch data object for each wine production batch include at least one or more parameters used to characterize the grape harvesting process and harvesting status.

[0057] Specifically, the production parameters involved in the above-mentioned harvesting stage include, for example, harvesting time, harvesting method, harvesting batch identification, harvesting quantity, and grape maturity parameters at the time of harvest.

[0058] Furthermore, in the above embodiments, for the factory entry stage, the production parameters stored in the batch data object for each batch of wine production include at least one or more parameters used to characterize the factory entry status and test results of grape raw materials.

[0059] Specifically, the production parameters involved in the above-mentioned entry stage include, for example, entry time, entry weight, sugar content, acidity, fruit integrity parameters, and entry test results.

[0060] Furthermore, in the above embodiments, for the brewing stage, the production parameters stored in the batch data object for each batch of wine production include at least one or more parameters used to characterize the fermentation process status and technological operation.

[0061] Specifically, the production parameters involved in the above-mentioned brewing stage include, for example, fermentation container markings, fermentation temperature, fermentation time, sugar content changes, alcohol content, and process operation parameters related to the fermentation process.

[0062] Furthermore, in the above embodiments, for the bottling stage, the production parameters stored in the batch data object for each wine production batch include at least one or more parameters used to characterize the bottling process and the state of the finished product.

[0063] Specifically, the production parameters involved in the filling stage include, for example, filling time, filling equipment identification, filling quantity, packaging specifications, and finished product quality inspection parameters.

[0064] It should be noted that the production parameters listed above for the planting, harvesting, processing, brewing, and bottling stages are merely illustrative examples used to illustrate the types of parameters that can be collected and stored in different production stages, and do not constitute a limitation on the scope of protection of this invention. In practical applications, the production parameters can be added, subtracted, replaced, or adjusted according to the wine variety, production process, quality control requirements, and management needs.

[0065] In this invention, to form independently associative data records when production status changes, the step of storing the production parameters into the corresponding batch data object further includes the following steps for storing data for each production batch:

[0066] S021. When it is detected that the production status of a wine production batch meets the preset status change conditions, the corresponding status version data is generated based on this production status change event, and this status version data is written as an independent data record into the corresponding batch data object.

[0067] The preset state change condition is a technical judgment condition used to determine whether the production state of a production batch has changed; the preset state change condition is not limited to a single judgment method, but can be comprehensively set according to different state characteristics in the production process.

[0068] In this embodiment, the preset state change condition is at least one or more of the following combinations: production stage change condition, production parameter out-of-bounds condition, parameter change trend condition, and production process event triggering condition.

[0069] Furthermore, the production stage change condition indicates that a wine production batch is switched from one production stage to another; the production parameter out-of-bounds condition indicates that at least one production parameter corresponding to the current production stage has a value exceeding a preset parameter threshold range; the parameter change trend condition indicates that at least one production parameter has a change magnitude or change rate that meets preset change judgment conditions within a preset time window; and the production process event triggering condition indicates that a preset process event and / or quality control event occurs during the production process.

[0070] Specifically, in one embodiment, when a production batch is detected to have switched from one production stage to another, it can be determined that the production status of the production batch has changed. In another embodiment, when it is detected that the value of at least one production parameter corresponding to the current production stage exceeds a pre-configured parameter threshold range for that production stage, it can be determined that the production status of the production batch has changed. Further, in yet another embodiment, when it is detected that the magnitude or rate of change of a production parameter within a preset time window meets a preset change determination condition, it can also be determined that the production status of the production batch has changed. In addition, during the production process, when a preset production event related to the process flow or quality control occurs, it can also be used as a basis for determining that the production status of the production batch has changed.

[0071] Among them, the aforementioned production parameters, parameter threshold ranges, change judgment conditions, and production events can all be pre-configured according to the production process requirements or quality control needs corresponding to different production stages, so as to ensure the objectivity and consistency of the judgment on changes in production status.

[0072] Furthermore, the step S021, which involves generating corresponding status version data based on a production status change event, includes the following steps:

[0073] S0211. When generating the state version data, the time when the production state change event occurs is determined as the state boundary point. The production parameters collected before the state boundary point are written into the previous state version data, and the production parameters collected after the state boundary point are written into the next state version data.

[0074] The previous state version data refers to the state version data formed before the state boundary point for the same batch of wine production, and before any new production state change event was detected; the next state version data refers to the new state version data formed after the production state change event was detected, starting from the state boundary point.

[0075] In this way, production parameters can be clearly assigned to different state versions of data during the data storage process based on the time and location of the production state change event, thereby achieving automatic differentiation and orderly storage of data before and after the production state change without relying on manual division.

[0076] S0212. After generating the status version data, based on the production batch identifier corresponding to the status version data, the current status version data is associated with at least one historical status version data of the production batch to generate a status version association structure that reflects the evolution of the production status.

[0077] It should be noted that the production batch identifier corresponding to the status version data is used to characterize the correspondence between the status version data and the specific wine production batch, so as to ensure that the status version data of different production batches will not be confused during the association process.

[0078] Furthermore, the current status version data refers to the status version data generated based on the most recent production status change event and corresponding to the production batch; the historical status version data refers to at least one status version data that has been generated and stored for the same production batch before the current status version data was generated.

[0079] Step S0212, based on the production batch identifier, establishes an association at the data structure level to represent the sequential relationship of status versions, so that the current status version data and the historical status version data are logically connected.

[0080] Through the above association method, multiple state version data generated for the same production batch can form an association structure to reflect the process of production state change according to their generation order, thereby continuously expressing the evolution process of production state at the data level.

[0081] It should be further explained that the state version association structure is used to characterize the state version evolution relationship of the same production batch in the production process. Its specific form can be a chain structure, a graph structure, or other data structure forms that can represent the association relationship between state versions. This invention does not make specific limitations on this.

[0082] In some other embodiments, the process of generating the state version association structure further includes the following steps: applying a stage consistency constraint to two or more associated state version data, wherein the stage consistency constraint is used to limit the production stages corresponding to any two adjacent associated state version data to satisfy a preset production stage evolution relationship.

[0083] It should be noted that, during the generation of the state version association structure, the stage consistency constraint applied to the two or more associated state version data is used to limit the logical order of adjacent associated state version data to conform to the preset production stage evolution relationship, so as to ensure that the association order between state versions is consistent with the stage evolution order in the wine production process.

[0084] The production stage evolution relationship is a pre-defined logical constraint on the sequential relationship between different production stages in the wine production process, used to characterize the reasonable evolution path between different production stages. When establishing the state version association structure, state version data are only allowed to form an adjacent association in the state version association structure if the production stages corresponding to adjacent state version data satisfy the production stage evolution relationship.

[0085] If the predefined production stage evolution relationship is: harvesting stage precedes factory entry stage, and factory entry stage precedes winemaking stage, then when multiple status version data are generated for the same wine production batch, if the production stage corresponding to a certain status version data is the harvesting stage, then its subsequent adjacent status version data should correspond to the factory entry stage or subsequent production stages, and should not be directly associated with production stages that do not have an evolutionary relationship before the winemaking stage.

[0086] By using the above methods, we can avoid the situation where state versions at different production stages form associations in the association structure that do not conform to the actual production process due to abnormal state version generation order or inconsistent data writing order.

[0087] In some other embodiments, when a wine production batch is split or merged, the process of generating the state version association structure further includes the following steps: based on the state version association structure, all state version data corresponding to the original production batch are mapped to the batch data object corresponding to the split or merged production batch according to a preset inheritance mapping rule.

[0088] In these embodiments, the inheritance mapping rules are used to determine the correspondence between the status version data corresponding to the original production batch and the split or merged production batch at the data structure level, so that the production status information formed by the original production batch before splitting or merging can be continuously retained and associated with the new production batch.

[0089] Furthermore, these embodiments re-associate the status version data with the production batch identifier at the logical level without changing the production status content represented by the status version data itself. This ensures that when the production batch structure changes, the loss or breakage of historical production status information due to changes in the batch identifier can be avoided, thereby guaranteeing the continuity of production status evolution information before and after batch changes.

[0090] If a wine production batch is split into two sub-batches during the brewing stage for further processing, the state version data generated before the split is simultaneously mapped to the batch data objects corresponding to the two sub-batches, so that the sub-batch can be traced back to the production state evolution process before the split in the subsequent state version association structure.

[0091] For example, if multiple wine production batches are merged into a new production batch in a subsequent production stage, the state version data corresponding to each original production batch will be uniformly mapped to the batch data object corresponding to the merged production batch according to the inheritance mapping rules, and the original state evolution relationship will be maintained in the state version association structure.

[0092] In some other embodiments, when the production state change event is an abnormal production parameter or an abnormal production event, the process of generating the state version association structure further includes the following steps: taking the state version data generated based on the production state change event as an abnormal state node, and establishing an abnormal evolution path in the corresponding state version association structure based on the abnormal state node to characterize the location of the abnormal state occurrence and its impact on the subsequent production state evolution.

[0093] In these embodiments, by introducing the abnormal evolution path, the position and impact of the abnormal production state in the production state evolution process can be expressed without disrupting the overall continuity of the original state version association structure.

[0094] For example, when a batch of wine production triggers a change in production status due to abnormal fermentation temperature during the brewing stage, the status version data generated based on this event is used as an abnormal status node. An abnormal evolution path is established in the status version association structure with this abnormal status node as the starting point to characterize the location of the abnormal status during the brewing stage and the relationship between the subsequent production status and the abnormal status.

[0095] For example, when an abnormal production event such as equipment failure occurs during the production process and triggers a change in production status, the system will use the corresponding generated status version data as an abnormal status node and construct an abnormal evolution path in the status version association structure to reflect the impact of the abnormal production event on the subsequent production status evolution process.

[0096] In one embodiment of the present invention, a data management system for the wine industry is also provided, for executing the data management method for the wine industry proposed in any of the foregoing embodiments, such as... Figure 3 As shown, it includes a processor and a memory, wherein the memory stores computer program instructions, and the processor, when executing the computer program instructions, is used to implement the data management method for the wine industry described in the foregoing embodiments.

[0097] In this embodiment, the processor can be a general-purpose processor, a special-purpose processor, a digital signal processor, a field-programmable gate array (FPGA), or a combination of the above processors; the memory can be volatile memory, non-volatile memory, or a combination thereof, used to store the computer program instructions and intermediate and result data generated during system operation. It should be understood that the specific types and connection methods of the processor and memory described above do not constitute a limitation on the scope of protection of this invention.

[0098] Furthermore, during the execution of the computer program instructions by the processor, the system establishes a batch data object corresponding to each of the several wine production batches, and uses the batch data object as a data entity for storing the data generated by the corresponding production batch during the production process, so that different wine production batches have a clear data ownership relationship in the system.

[0099] Furthermore, when executing the computer program instructions, the processor also obtains production parameters reflecting the current production status of the corresponding wine production batch based on each batch data object, and writes the production parameters into the corresponding batch data object.

[0100] During the process of writing the production parameters, the system configures corresponding parameter storage structures for different production stages based on the multiple production stages that wine production goes through. According to the parameter writing rules of the parameter storage structure, the system verifies the production stage, parameter type, and parameter value range of the production parameters, and only allows the production parameters to be written to the corresponding parameter storage structure when the verification passes.

[0101] During the execution of the computer program instructions by the processor, the system detects the production status of the wine production batch based on the collected production parameters to determine whether the production status meets the preset status change conditions: when the production status of a certain wine production batch is detected to meet the preset status change conditions, status version data is generated based on the corresponding production status change event, and the status version data is written as an independent data record into the corresponding batch data object.

[0102] During the execution of the computer program instructions by the processor, when the system generates the state version data, the system determines the moment when the production state change event occurs as the state boundary point, writes the production parameters collected before the state boundary point into the previous state version data, and writes the production parameters collected after the state boundary point into the next state version data, so that the production parameters under different production states have clear data ownership boundaries.

[0103] During the execution of the computer program instructions by the processor, after generating state version data, the system associates the current state version data with at least one historical state version data of the production batch based on the production batch identifier corresponding to the state version data, thereby constructing a state version association structure to reflect the evolution of the production state of the wine production batch. In constructing the state version association structure, the system applies stage consistency constraints to adjacent associated state version data to ensure that the production stages corresponding to adjacent state version data satisfy a preset production stage evolution relationship.

[0104] In the wine production process, when production batches are split or merged, the system, during the generation of the status version association structure, maps the status version data corresponding to the original production batch to the batch data object corresponding to the split or merged production batch according to the preset inheritance mapping rules, based on the status version association structure, thereby realizing the continuous inheritance and association of production status information before and after the production batch change.

[0105] In a further embodiment, when the production state change event is triggered by abnormal production parameters or abnormal production events, the system, in the process of generating the state version association structure, uses the state version data generated based on the production state change event as an abnormal state node, and establishes an abnormal evolution path based on the abnormal state node in the corresponding state version association structure, which is used to characterize the location of the abnormal state in the production state evolution process and its impact on the subsequent production state evolution.

[0106] Through the above system structure and operation mode, the data management system for the wine industry can achieve state-driven version management of production data under multiple production stages, multiple production batches and continuous changes in production status, and can express the evolution process of production status in a structured way, thereby meeting the data management needs of long-cycle, multi-stage and batch variable production processes in the wine industry.

[0107] In the above embodiments, the descriptions of different embodiments have different emphases; technical features not detailed or recorded in a certain embodiment can be understood and implemented by referring to the corresponding records of other embodiments. Unless otherwise expressly stated to the contrary: technical features in each embodiment can be substituted or combined with each other without technical conflict; the order of method steps can be adjusted without affecting the function; the device / module / unit can be implemented by hardware, software or a combination thereof, and can be centralized or distributed; parameters, values ​​or ranges include reasonable errors and equivalent values, and the terms "about", "greater than / less than", "between", and range endpoints are all covered without affecting the technical effect; ordinal numbers such as "first / second" are only used for distinction and do not limit the quantity, priority or structural relationship; the reference numerals and names in the specification and drawings are only illustrative and do not limit the structural form, size ratio or installation position; improvements, substitutions or equivalent solutions that are not explicitly stated but can be obtained by those skilled in the art without creative effort should all be included in the protection scope of this invention.

Claims

1. A data management method for the wine industry, characterized in that, For a number of wine production batches, management is achieved through the following steps: For each wine production batch, a corresponding batch data object is created, and each batch data object is used to store the data of the corresponding production batch during the production process; For each batch data object, production parameters reflecting the current production status of the corresponding production batch are obtained, and these production parameters are stored in the corresponding batch data object. The process of storing the production parameters in the corresponding batch data object includes: When a wine production batch is detected to meet a preset state change condition, corresponding state version data is generated based on this production state change event, and this state version data is written as an independent data record into the corresponding batch data object.

2. The data management method for the wine industry according to claim 1, characterized in that, Creating a batch data object for a wine production batch includes the following steps: Based on the multiple production stages in the wine production process, a parameter storage structure corresponding to each of the multiple production stages is configured for the batch data object.

3. The data management method for the wine industry according to claim 2, characterized in that, Each batch of wine production goes through at least one or more of the following production stages: planting, harvesting, bottling, winemaking, and bottling.

4. The data management method for the wine industry according to claim 2, characterized in that, The parameter storage structure for each production stage is configured through the following steps: Based on the set of process activities and / or quality control points of the corresponding production stage, configure the production parameters that can be stored in the corresponding parameter storage structure, and configure parameter feature information for this production parameter. The parameter feature information includes at least the production stage identifier, parameter unit, and parameter value range. Based on the parameter feature information, the parameter writing rules of the corresponding parameter storage structure are configured. The parameter writing rules are used to verify at least the production stage, parameter type and parameter value range of the production parameter when the production parameter is written, so that the corresponding production parameter is allowed to be written to the corresponding parameter storage structure only when the verification is passed.

5. The data management method for the wine industry according to claim 2, characterized in that, The preset state change condition is a combination of at least one or more of the following: Production stage change conditions, which characterize the transition of a wine production batch from one production stage to another; Production parameter out-of-bounds condition, wherein the production parameter out-of-bounds condition represents at least one production parameter corresponding to the current production stage whose parameter value exceeds a preset parameter threshold range; The parameter change trend condition indicates that at least one production parameter, within a preset time window, has a change magnitude or change rate that meets a preset change judgment condition. Production process event triggering conditions, wherein the production process event triggering conditions characterize the occurrence of preset process events and / or quality control events during the production process.

6. The data management method for the wine industry according to claim 2, characterized in that, Based on a production status change event, generate corresponding status version data, including the following steps: When generating the state version data, the moment when the production state change event occurs is determined as the state boundary point. Production parameters collected before the state boundary point are written into the previous state version data, and production parameters collected after the state boundary point are written into the next state version data. After generating the status version data, based on the production batch identifier corresponding to this status version data, the current status version data is associated with at least one historical status version data of the production batch to generate a status version association structure that reflects the evolution of the production status.

7. The data management method for the wine industry according to claim 6, characterized in that, The process of generating the state version association structure also includes the following steps: A stage consistency constraint is applied to two or more associated state version data. The stage consistency constraint is used to limit the production stage corresponding to any two adjacent associated state version data to meet a preset production stage evolution relationship.

8. The data management method for the wine industry according to claim 6, characterized in that, When a wine production batch is split or merged, the process of generating the state version association structure also includes the following steps: based on the state version association structure, all state version data corresponding to the original production batch are mapped to the batch data object corresponding to the split or merged production batch according to a preset inheritance mapping rule.

9. The data management method for the wine industry according to claim 6, characterized in that, When the production status change event is triggered by abnormal production parameters or abnormal production events, the process of generating the status version association structure also includes the following steps: The state version data generated based on the production state change event is used as an abnormal state node. In the corresponding state version association structure, an abnormal evolution path is established based on the abnormal state node to characterize the location of the abnormal state and its impact on the subsequent production state evolution.

10. A data management system for the wine industry, characterized in that, The device includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the device performs a data management method for the wine industry as described in any one of claims 1 to 9.

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