A method and system for controlling the production quality of crutch candy

Abstract

This invention discloses a method and system for quality control in the production of candy canes. The method includes: acquiring the design specifications of the candy canes and determining shape requirements, appearance requirements, and hardness requirements; determining standard cutting parameters for the candy strips based on the shape requirements; determining the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on the appearance requirements; determining the hardness requirement index of the finished candy cane based on the hardness requirement parameters; extracting qualified quality characteristics and constructing a quality assessment model based on the standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirement index; collecting images of the candy cane's stage production status and extracting the current quality characteristics; and performing quality control on each stage of the candy cane's production based on the current quality characteristics using the quality assessment model. This method can achieve more comprehensive quality assessment, improve objectivity, reliability, and stability, and reduce the product defect rate.

Description

Technical Field

[0001] This invention relates to the field of quality control technology, and in particular to a method and system for quality control in the production of candy canes. Background Technology

[0002] Currently, with the improvement of living standards, people's choices of candy are no longer limited to flavor. Delicious and uniquely shaped craft candies are increasingly favored by consumers due to their appealing visual effects. To adapt to this shift in consumer attitudes, candy manufacturers have designed and produced a wide variety of craft candies. Among them, candy canes, with their attractive appearance, good taste, and high quality, are gaining an increasingly larger share of the candy market. Currently, in the candy cane manufacturing process, one end of a straight strip of candy is bent to form a candy cane shape. However, to create this candy cane shape, manual bending is generally used, resulting in very low efficiency. While some have implemented mechanical bending to improve efficiency, quality control relies on evaluation of finished products based on human experience. This method is highly subjective and lacks targeted stage monitoring, leading to inadequate quality control, a large number of defective products, and increased production costs. Summary of the Invention

[0003] To address the problems mentioned above, this invention provides a method and system for quality control in the production of candy canes. This solves the problem mentioned in the background art that production quality control relies on human experience to evaluate finished products, which not only has serious subjectivity but also fails to provide targeted stage monitoring, resulting in inadequate quality control, a large number of defective products, and increased production costs.

[0004] A method for quality control in the production of candy canes includes the following steps: Obtain the design specifications for the candy cane, and determine the shape requirements, appearance requirements, and hardness requirements based on the design specifications. Based on the shape requirement parameters, the standard cutting parameters for the candy cane are determined; based on the appearance requirement parameters, the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane are determined; based on the hardness requirement parameters, the hardness requirement index of the finished candy cane is determined. Based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements, qualified quality characteristics are extracted and a quality assessment model is constructed. Images of the production status of candy canes at different stages are collected and current quality characteristics are extracted. Based on these current quality characteristics, a quality assessment model is used to control the quality of each production stage of the candy canes.

[0005] Preferably, before obtaining the design specifications of the candy cane and determining the shape requirements, appearance requirements, and hardness requirements based on the design specifications, the method further includes: Obtain the product standard documents for candy canes, and determine the specification range of candy canes based on the product standard documents; Based on the size range of the candy cane, consumer research and market competitor analysis were used to identify multiple target audiences for the candy cane and highlight the product specifications. Obtain the production process capability requirements, packaging and transportation requirements, and shelf display requirements for each audience's key product specifications; Associate the production process capabilities, packaging and transportation requirements, and shelf display requirements of each audience's highlighted product specifications with those specifications and assign strict quality control labels.

[0006] Preferably, the design specifications of the candy cane are obtained, and the shape requirements, appearance requirements, and hardness requirements are determined based on the design specifications, including: Obtain the production design documents for the candy canes; obtain sample images of the candy canes based on the production design documents; and obtain the design specifications of the candy canes based on the sample images. Based on the design specifications, determine the current strict quality control label for the candy canes, and determine the quality control details based on the current strict quality control label. Based on the details of quality control, quantitative standards for shape requirements, appearance requirements, and hardness requirements are determined separately. Based on the quantitative standards, determine the quantitative indicators and indicator thresholds, and then determine the shape requirement parameters, appearance requirement parameters, and hardness requirement parameters based on the quantitative indicators and indicator thresholds.

[0007] Preferably, the steps of determining the standard cutting parameters for the candy cane based on shape requirement parameters, determining the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on appearance requirement parameters, and determining the hardness requirement index of the finished candy cane based on hardness requirement parameters include: Determine the standard size parameters of the candy strips based on the shape requirements, and then determine the standard cutting parameters for the candy strips based on the standard size parameters. The stripe contrast and surface contour parameters of each pigment are determined based on the appearance requirements parameters. The pigment concentration gradient distribution for the finished candy cane is determined based on the stripe contrast of each pigment and the spiral amplitude parameter of the pigment. The initial three-dimensional morphology data of the candy cane product is determined based on the surface contour parameters. The thermal expansion coefficient and stress relaxation factor of the candy cane product are determined based on the melting temperature and physical properties of the raw materials. The initial three-dimensional morphology data is then compensated using a morphology compensation algorithm based on the thermal expansion coefficient and stress relaxation factor to obtain the target three-dimensional morphology data. Based on the hardness requirement parameters, determine the instantaneous hardness requirement, elastic modulus requirement, and fracture toughness requirement for the finished candy cane.

[0008] Preferably, the step of extracting qualified quality features and constructing a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirement indicators includes: Cutting features are extracted based on standard cutting parameters, pigment features are extracted based on pigment concentration gradient distribution, morphology features are extracted based on three-dimensional morphology data, and hardness features are extracted based on hardness requirements. The characteristics of cutting features, pigment features, morphology features and hardness features are fused to obtain qualified quality features; The model input layer architecture is set based on the spatiotemporal alignment of spectral-mechanical-geometric data, and a neural network model based on attention mechanism and deep learning is selected according to the model input layer architecture. A quality assessment model is generated by training an attention-based and deep learning-based neural network model using qualified quality features.

[0009] Preferably, before acquiring images of the production status of the candy canes at different stages and extracting the current quality features, and before using a quality assessment model to perform quality control on each stage of the candy cane production based on the current quality features, the process further includes: Determine the reference production stage corresponding to each quality characteristic and obtain the stage process parameters of the reference production stage; Based on the stage process parameters, identify the operational factors that affect each quality characteristic, and obtain the monitoring methods for these operational factors; The operational factors at each stage of production are monitored and early warnings are issued through monitoring methods.

[0010] Preferably, the step of acquiring images of the production status of the candy canes at different stages and extracting current quality features, and then using a quality assessment model to perform quality control on each production stage of the candy canes based on the current quality features, includes: Identify the data acquisition devices for each production stage and use these devices to acquire images of the production status of the candy canes at each stage. Extract the current cutting features, current pigment features, current morphology features, and current hardness features from the stage production image; The production quality of candy canes is monitored using a quality assessment model based on current cutting characteristics, current pigment characteristics, current morphological characteristics, and current hardness characteristics. Based on the monitoring results, the unqualified quality characteristics of the candy canes were identified, and the unqualified production stage was located to issue an early warning.

[0011] Preferably, the determination of quality control details based on current strict quality control labels includes: The degree of quality control is determined based on the current strict quality control labeling, and the product status requirements are determined based on the degree of quality control. Determine the detailed quality characteristics based on the product status requirements, and determine the sequence of feedback indicators based on the detailed quality characteristics; The details of quality control are determined based on the feedback indicator sequence.

[0012] Preferably, the method further includes: The product design structure is determined based on the design specifications of the candy cane, and the equipment control parameters are determined based on the product design structure. The optimal state vector for each production stage of the candy cane is determined based on the equipment control parameters, and the quality change trend of the candy cane in each production stage is determined based on the optimal state vector. Based on the trend of quality changes, we determine the first production stage where qualitative quality declines and the second production stage where qualitative quality remains unchanged; The first stage of production will be closely monitored and data will be used for early warning.

[0013] A quality control system for the production of candy canes, the system comprising: The first determining module is used to obtain the design specifications of the candy cane, and determine the shape requirements, appearance requirements, and hardness requirements based on the design specifications. The second determining module is used to determine the standard cutting parameters for the candy strips based on the shape requirement parameters, determine the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on the appearance requirement parameters, and determine the hardness requirement index of the finished candy cane based on the hardness requirement parameters. The module is used to extract qualified quality features and build a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements. The quality control module is used to collect images of the production status of the candy canes at different stages and extract the current quality characteristics. Based on the current quality characteristics, the quality assessment model performs quality control on each production stage of the candy canes.

[0014] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0017] Figure 1 A flowchart illustrating a production quality control method for candy canes provided by this invention; Figure 2 Another flowchart of a production quality control method for candy canes provided by the present invention; Figure 3 This invention provides another flowchart of a production quality control method for candy canes. Figure 4 This is a schematic diagram of a production quality control system for candy canes provided by the present invention. Detailed Implementation

[0018] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0019] Currently, with the improvement of living standards, people's choices of candy are no longer limited to flavor. Delicious and uniquely shaped craft candies are increasingly favored by consumers due to their appealing visual effects. To adapt to this shift in consumer attitudes, candy manufacturers have designed and produced a variety of craft candies, among which candy canes, with their attractive appearance, good taste, and high quality, are gaining an increasingly larger share of the candy market. Currently, in the candy cane manufacturing process, a straight strip of candy is typically bent at one end to form a candy cane shape. However, to create this candy cane shape, manual bending is generally used, resulting in very low efficiency. While some have implemented mechanical bending to improve efficiency, quality control relies on evaluation of finished products based on human experience. This method is highly subjective and lacks targeted stage monitoring, leading to inadequate quality control and a large number of defective products, increasing production costs. To address these issues, this embodiment discloses a method for quality control in the production of candy canes.

[0020] A method for quality control in the production of candy canes, such as Figure 1 As shown, it includes the following steps: Step S101: Obtain the design specifications of the candy cane, and determine the shape requirements, appearance requirements, and hardness requirements based on the design specifications. Step S102: Determine the standard cutting parameters for the candy strips based on the shape requirement parameters; determine the pigment concentration gradient distribution and three-dimensional morphology data for the finished candy cane based on the appearance requirement parameters; and determine the hardness requirement index for the finished candy cane based on the hardness requirement parameters. Step S103: Extract qualified quality features and construct a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirement indicators; Step S104: Collect images of the production status of the candy canes at different stages and extract the current quality characteristics. Then, use a quality assessment model to perform quality control on each production stage of the candy canes based on the current quality characteristics.

[0021] The working principle of the above technical solution is as follows: Obtain the design specifications of the candy cane; determine the shape requirements, appearance requirements, and hardness requirements based on these specifications; determine the standard cutting parameters for the candy strips based on the shape requirements; determine the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on the appearance requirements; determine the hardness requirements for the finished candy cane based on the hardness requirements; extract qualified quality characteristics and construct a quality assessment model based on the standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements; collect images of the candy cane's stage production status and extract the current quality characteristics; and use the quality assessment model to perform quality control on each stage of candy cane production based on these current quality characteristics.

[0022] The beneficial effects of the above technical solution are as follows: By determining multiple quality monitoring indicators and then identifying qualified quality characteristics to construct a quality assessment model, targeted stage quality control can be made based on the mapping characteristics of quality monitoring indicators at each production stage. This allows for rapid identification of production stages with substandard quality, optimization, and avoidance of delayed quality assessment of the finished candy cane, thus improving the reliability of pre-assessment. At the same time, using an intelligent big data model to replace manual quality assessment can achieve a more comprehensive quality assessment, improving objectivity, reliability, and stability, reducing product defect rate, and solving the problem mentioned in the existing technology that production quality control is based on the finished product and human experience. This not only has serious subjectivity but also cannot make targeted stage monitoring, resulting in inadequate quality control, a large number of defective products, and increased production costs.

[0023] In one embodiment, before obtaining the design specifications of the candy cane and determining the shape requirements, appearance requirements, and hardness requirements based on the design specifications, the method further includes: Obtain the product standard documents for candy canes, and determine the specification range of candy canes based on the product standard documents; Based on the size range of the candy cane, consumer research and market competitor analysis were used to identify multiple target audiences for the candy cane and highlight the product specifications. Obtain the production process capability requirements, packaging and transportation requirements, and shelf display requirements for each audience's key product specifications; Associate the production process capabilities, packaging and transportation requirements, and shelf display requirements of each audience's highlighted product specifications with those specifications and assign strict quality control labels.

[0024] The beneficial effects of the above technical solution are as follows: by determining the quality control labels for each product specification, reasonable and reliable quality assessment indicators can be determined based on the transportation, display and production requirements of each specification of product, thereby achieving high-precision quality control for each specification of candy cane, and further improving stability and practicality.

[0025] In one embodiment, such as Figure 2 As shown, the design specifications for the candy cane are obtained, and based on these specifications, the shape requirements, appearance requirements, and hardness requirements are determined, including: Step S201: Obtain the production design document for the candy cane, obtain sample images of the candy cane based on the production design document, and obtain the design specifications of the candy cane based on the sample images. Step S202: Determine the current strict quality control label for the candy canes based on the design specifications, and determine the quality control details based on the current strict quality control label; Step S203: Determine the quantitative standards for shape requirement parameters, appearance requirement parameters, and hardness requirement parameters based on the quality control details; Step S204: Determine the quantitative indicators and indicator thresholds according to the quantitative standards, and determine the shape requirement parameters, appearance requirement parameters, and hardness requirement parameters according to the quantitative indicators and indicator thresholds.

[0026] The beneficial effects of the above technical solution are as follows: by determining the details of quality control, the detailed texture of the finished candy cane ...

[0027] In one embodiment, determining the standard cutting parameters for the candy cane based on shape requirement parameters, determining the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on appearance requirement parameters, and determining the hardness requirement index of the finished candy cane based on hardness requirement parameters include: Determine the standard size parameters of the candy strips based on the shape requirements, and then determine the standard cutting parameters for the candy strips based on the standard size parameters. The stripe contrast and surface contour parameters of each pigment are determined based on the appearance requirements parameters. The pigment concentration gradient distribution for the finished candy cane is determined based on the stripe contrast of each pigment and the spiral amplitude parameter of the pigment. The initial three-dimensional morphology data of the candy cane product is determined based on the surface contour parameters. The thermal expansion coefficient and stress relaxation factor of the candy cane product are determined based on the melting temperature and physical properties of the raw materials. The initial three-dimensional morphology data is then compensated using a morphology compensation algorithm based on the thermal expansion coefficient and stress relaxation factor to obtain the target three-dimensional morphology data. Based on the hardness requirement parameters, determine the instantaneous hardness requirement, elastic modulus requirement, and fracture toughness requirement for the finished candy cane.

[0028] In this embodiment, the pigment concentration gradient distribution represents the spatial concentration variation of different colored pigments in the striped or spiral regions of the candy cane. It can be indirectly characterized by analyzing the pixel intensity distribution of a color image in different color channels.

[0029] In this embodiment, the three-dimensional topography data is represented as a set of data that characterizes the three-dimensional point cloud or mesh model of the candy cane surface, acquired by a laser scanner or a structured light three-dimensional camera. In this embodiment, the shape compensation algorithm is as follows: ; in, This is represented as the compensated size. This represents the initial dimensions of the finished candy cane. This represents the coefficient of thermal expansion of the finished candy cane. It is expressed as the melting temperature of the raw material. This indicates the temperature at which the candy cane is formed. Represented as stress relaxation factor, This represents the holding time of the candy cane syrup in the molding fixture. This refers to the drying time after the candy cane is removed from the molding fixture.

[0030] The beneficial effects of the above technical solution are: it can more precisely determine multiple quality requirements for the finished candy cane, thus laying a reference basis for subsequent comprehensive quality assessment and further improving practicality and reliability.

[0031] In one embodiment, the step of extracting qualified quality features and constructing a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirement indicators includes: Cutting features are extracted based on standard cutting parameters, pigment features are extracted based on pigment concentration gradient distribution, morphology features are extracted based on three-dimensional morphology data, and hardness features are extracted based on hardness requirements. The characteristics of cutting features, pigment features, morphology features and hardness features are fused to obtain qualified quality features; The model input layer architecture is set based on the spatiotemporal alignment of spectral-mechanical-geometric data, and a neural network model based on attention mechanism and deep learning is selected according to the model input layer architecture. A quality assessment model is generated by training an attention-based and deep learning-based neural network model using qualified quality features.

[0032] The beneficial effects of the above technical solution are as follows: feature fusion can ensure the training stability of the model; furthermore, by setting the model input architecture, the model can receive different forms of collected data for quality evaluation, which improves the model's adaptability; furthermore, by selecting a neural network model based on attention mechanism and deep learning, it is possible to ensure the focused analysis and evaluation of various forms of collected data, while accumulating experience from historical analysis results to achieve more efficient and stable quality evaluation.

[0033] In one embodiment, before acquiring stage production status images of the candy canes and extracting current quality features, and before performing quality control on each production stage of the candy canes based on the current quality features using a quality assessment model, the method further includes: Determine the reference production stage corresponding to each quality characteristic and obtain the stage process parameters of the reference production stage; Based on the stage process parameters, identify the operational factors that affect each quality characteristic, and obtain the monitoring methods for these operational factors; The operational factors at each stage of production are monitored and early warnings are issued through monitoring methods.

[0034] The beneficial effects of the above technical solution are as follows: by monitoring and issuing early warnings for operational factors in the production stage, the impact on the finished candy cane product caused by abnormal operating parameters can be avoided, thus ensuring the stability and reliability of the production process.

[0035] In one embodiment, such as Figure 3 As shown, the process involves collecting images of the production status of the candy canes at different stages and extracting current quality features. A quality assessment model is then used to perform quality control for each production stage based on these current quality features. This includes: Step S301: Determine the acquisition equipment for each production stage and use the acquisition equipment to acquire images of the production status of the candy cane at each stage; Step S302: Extract the current cutting features, current pigment features, current morphology features, and current hardness features from the stage production image; Step S303: Monitor the production quality of candy canes using a quality assessment model based on current cutting characteristics, current pigment characteristics, current morphology characteristics, and current hardness characteristics; Step S304: Based on the monitoring results, determine the unqualified quality characteristics of the candy canes and locate the unqualified production stage to issue an early warning.

[0036] In this embodiment, the current hardness feature is not a directly measured value, but an indirect feature vector related to hardness extracted from the surface image. It is obtained by: collecting a large number of sample sugar images with known hardness, extracting their texture features (such as contrast and energy based on the gray-level co-occurrence matrix) and gloss features, performing regression training with the measured hardness values, establishing a visual feature-hardness prediction model, and inputting the extracted visual features into the model during online detection, the output of which is the "current hardness feature".

[0037] The beneficial effects of the above technical solution are as follows: by conducting model evaluation, the unqualified production stage can be quickly located and an effective reminder can be issued. Furthermore, the quality of the production stage can be evaluated and controlled in stages to ensure the stability of the production process.

[0038] In one embodiment, determining quality control details based on current strict quality control labels includes: The degree of quality control is determined based on the current strict quality control labeling, and the product status requirements are determined based on the degree of quality control. Determine the detailed quality characteristics based on the product status requirements, and determine the sequence of feedback indicators based on the detailed quality characteristics; The details of quality control are determined based on the feedback indicator sequence.

[0039] The beneficial effects of the above technical solution are as follows: by determining the sequence of feedback indicators and thus the details of quality control, the statistical description of the details of quality control can be comprehensively carried out based on multiple feedback indicators of the series of quality requirements, thus ensuring the reliability of quality assessment.

[0040] In this embodiment, quality detail characteristics are determined based on product status requirements, and a feedback indicator sequence is determined based on these quality detail characteristics, including: Based on the product status requirements, determine the top-level state variables and their quantification ranges, and based on the top-level state variables and their quantification ranges, determine the macroscopic quality scale characteristics, mesoscopic quality scale characteristics and microscopic quality scale characteristics. The logical sequence for quality compliance assessment is determined based on the mapping relationship between macroscopic quality scale characteristics, mesoscopic quality scale characteristics and microscopic quality scale characteristics; Based on the quality qualification assessment logic sequence, determine the product mapping form of quality detail features, and obtain the texture detail fullness characterization and texture detail fatigue characterization under the product mapping form; By comparing the texture detail fullness representation and the texture detail fatigue representation, differential representations are obtained, and the mapped texture features of the differential representations are determined. Obtain the set of feedback feature indicators for the mapped texture features, and determine the sequence of feedback indicators for the quality detail features based on the set of feedback feature indicators.

[0041] The beneficial effects of the above technical solution are as follows: by acquiring macroscopic, mesoscopic, and microscopic scale features, it ensures that quality control covers all physical levels of product functions and avoids control blind spots. Furthermore, by determining the mapped texture features based on differentiated representation, it is possible to more accurately determine the set of reference indicators for candy cane quality control, thereby ensuring the reliability and stability of processing quality.

[0042] In one embodiment, the method further includes: The product design structure is determined based on the design specifications of the candy cane, and the equipment control parameters are determined based on the product design structure. The optimal state vector for each production stage of the candy cane is determined based on the equipment control parameters, and the quality change trend of the candy cane in each production stage is determined based on the optimal state vector. Based on the trend of quality changes, we determine the first production stage where qualitative quality declines and the second production stage where qualitative quality remains unchanged; The first stage of production will be closely monitored and data will be used for early warning.

[0043] The beneficial effects of the above technical solution are as follows: by assessing the quality development trend of the production stage and then selecting the key production stages for monitoring, it is possible to effectively screen out the production stages where the production quality is unstable and carry out targeted key monitoring to avoid defects in subsequent finished products, thereby further improving production stability.

[0044] In one embodiment, this embodiment also discloses a production quality control system for candy canes, such as... Figure 4 As shown, the system includes: The first determining module 401 is used to obtain the design specification parameters of the candy cane, and determine the shape requirement parameters, appearance requirement parameters, and hardness requirement parameters based on the design specification parameters. The second determining module 402 is used to determine the standard cutting parameters for the candy bar according to the shape requirement parameters, determine the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane according to the appearance requirement parameters, and determine the hardness requirement index of the finished candy cane according to the hardness requirement parameters. Module 403 is used to extract qualified quality features and build a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirement indicators. The quality control module 404 is used to collect images of the stage production status of candy canes and extract the current quality characteristics. Based on the current quality characteristics, the quality assessment model performs quality control on each stage of the candy cane production.

[0045] The working principle and beneficial effects of the above technical solution have been explained in the method embodiments, and will not be repeated here.

[0046] Those skilled in the art should understand that the "first" and "second" in this invention simply refer to different application stages.

[0047] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0048] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for quality control of crutch candy production, characterized by, Includes the following steps: Obtain the design specifications for the candy cane, and determine the shape requirements, appearance requirements, and hardness requirements based on the design specifications. Based on the shape requirement parameters, the standard cutting parameters for the candy cane are determined; based on the appearance requirement parameters, the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane are determined; based on the hardness requirement parameters, the hardness requirement index of the finished candy cane is determined. Based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements, qualified quality characteristics are extracted and a quality assessment model is constructed. Collect images of the production status of candy canes at different stages and extract the current quality characteristics. Then, use a quality assessment model to perform quality control on each production stage of the candy canes based on the current quality characteristics. The process of determining standard cutting parameters for candy strips based on shape requirements, determining the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on appearance requirements, and determining the hardness requirements for the finished candy cane based on hardness requirements includes: Determine the standard size parameters of the candy strips based on the shape requirements, and then determine the standard cutting parameters for the candy strips based on the standard size parameters. The stripe contrast and surface contour parameters of each pigment are determined based on the appearance requirements parameters. The pigment concentration gradient distribution for the finished candy cane is determined based on the stripe contrast of each pigment and the spiral amplitude parameter of the pigment. The initial three-dimensional morphology data of the candy cane product is determined based on the surface contour parameters. The thermal expansion coefficient and stress relaxation factor of the candy cane product are determined based on the melting temperature and physical properties of the raw materials. The initial three-dimensional morphology data is then compensated using a morphology compensation algorithm based on the thermal expansion coefficient and stress relaxation factor to obtain the target three-dimensional morphology data. Based on the hardness requirement parameters, determine the instantaneous hardness requirement, elastic modulus requirement, and fracture toughness requirement for the finished candy cane product. The shape compensation algorithm is as follows: ； in, This is represented as the compensated size. This represents the initial dimensions of the finished candy cane. This represents the coefficient of thermal expansion of the finished candy cane. It is expressed as the melting temperature of the raw material. This indicates the temperature at which the candy cane is formed. Represented as stress relaxation factor, This represents the holding time of the candy cane syrup in the molding fixture. This refers to the drying time after the candy cane is removed from the molding fixture; The method further includes: The product design structure is determined based on the design specifications of the candy cane, and the equipment control parameters are determined based on the product design structure. The optimal state vector for each production stage of the candy cane is determined based on the equipment control parameters, and the quality change trend of the candy cane in each production stage is determined based on the optimal state vector. Based on the trend of quality changes, we determine the first production stage where qualitative quality declines and the second production stage where qualitative quality remains unchanged; The first stage of production will be closely monitored and data will be used for early warning.

2. The method for quality control in the production of candy canes according to claim 1, characterized in that, Before obtaining the design specifications of the candy cane, and determining the shape requirements, appearance requirements, and hardness requirements based on the design specifications, the method further includes: Obtain the product standard documents for candy canes, and determine the specification range of candy canes based on the product standard documents; Based on the size range of the candy cane, consumer research and market competitor analysis were used to identify multiple target audiences for the candy cane and highlight the product specifications. Obtain the production process capability requirements, packaging and transportation requirements, and shelf display requirements for each audience's key product specifications; Associate the production process capabilities, packaging and transportation requirements, and shelf display requirements of each audience's highlighted product specifications with those specifications and assign strict quality control labels.

3. The method for quality control in the production of candy canes according to claim 2, characterized in that, Obtain the design specifications for the candy cane, and based on these specifications, determine the shape requirements, appearance requirements, and hardness requirements, including: Obtain the production design documents for the candy canes; obtain sample images of the candy canes based on the production design documents; and obtain the design specifications of the candy canes based on the sample images. Based on the design specifications, determine the current strict quality control label for the candy canes, and determine the quality control details based on the current strict quality control label. Based on the details of quality control, quantitative standards for shape requirements, appearance requirements, and hardness requirements are determined separately. Quantitative indicators and thresholds are determined based on quantitative standards. Shape requirements, appearance requirements, and hardness requirements.

4. The method for quality control in the production of candy canes according to claim 1, characterized in that, The process of extracting qualified quality characteristics and constructing a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements includes: Cutting features are extracted based on standard cutting parameters, pigment features are extracted based on pigment concentration gradient distribution, morphology features are extracted based on three-dimensional morphology data, and hardness features are extracted based on hardness requirements. The characteristics of cutting features, pigment features, morphology features and hardness features are fused to obtain qualified quality features; The model input layer architecture is set based on the spatiotemporal alignment of spectral-mechanical-geometric data, and a neural network model based on attention mechanism and deep learning is selected according to the model input layer architecture. A quality assessment model is generated by training an attention-based and deep learning-based neural network model using qualified quality features.

5. The method for quality control in the production of candy canes according to claim 1, characterized in that, Before collecting images of the production status of the candy canes at each stage and extracting the current quality features, and before using a quality assessment model to perform quality control on each stage of the candy cane production based on the current quality features, the following steps are also included: Determine the reference production stage corresponding to each quality characteristic and obtain the stage process parameters of the reference production stage; Based on the stage process parameters, identify the operational factors that affect each quality characteristic, and obtain the monitoring methods for these operational factors; The operational factors at each stage of production are monitored and early warnings are issued through monitoring methods.

6. The method for quality control in the production of candy canes according to claim 1, characterized in that, The process involves collecting images of the production status of the candy canes at different stages and extracting current quality features. Based on these current quality features, a quality assessment model is used to perform quality control for each stage of the candy cane production process, including: Identify the data acquisition devices for each production stage and use these devices to acquire images of the production status of the candy canes at each stage. Extract the current cutting features, current pigment features, current morphology features, and current hardness features from the stage production image; The production quality of candy canes is monitored using a quality assessment model based on current cutting characteristics, current pigment characteristics, current morphological characteristics, and current hardness characteristics. Based on the monitoring results, the unqualified quality characteristics of the candy canes were identified, and the unqualified production stage was located to issue an early warning.

7. The method for quality control in the production of candy canes according to claim 3, characterized in that, The details of quality control based on strict labeling under current quality management include: The degree of quality control is determined based on the current strict quality control labeling, and the product status requirements are determined based on the degree of quality control. Determine the detailed quality characteristics based on the product status requirements, and determine the sequence of feedback indicators based on the detailed quality characteristics; The details of quality control are determined based on the feedback indicator sequence.

8. A production quality control system for candy canes, characterized in that, The system includes: The first determining module is used to obtain the design specifications of the candy cane, and determine the shape requirements, appearance requirements, and hardness requirements based on the design specifications. The second determining module is used to determine the standard cutting parameters for the candy strips based on the shape requirement parameters, determine the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on the appearance requirement parameters, and determine the hardness requirement index of the finished candy cane based on the hardness requirement parameters. The module is used to extract qualified quality features and build a quality assessment model based on standard cutting parameters, pigment concentration gradient distribution, three-dimensional morphology data, and hardness requirements. The quality control module is used to collect images of the production status of the candy canes at different stages and extract the current quality characteristics. Based on the current quality characteristics, the quality assessment model is used to control the quality of each production stage of the candy canes. The process of determining standard cutting parameters for candy strips based on shape requirements, determining the pigment concentration gradient distribution and three-dimensional morphology data of the finished candy cane based on appearance requirements, and determining the hardness requirements for the finished candy cane based on hardness requirements includes: Determine the standard size parameters of the candy strips based on the shape requirements, and then determine the standard cutting parameters for the candy strips based on the standard size parameters. The stripe contrast and surface contour parameters of each pigment are determined based on the appearance requirements parameters. The pigment concentration gradient distribution for the finished candy cane is determined based on the stripe contrast of each pigment and the spiral amplitude parameter of the pigment. The initial three-dimensional morphology data of the candy cane product is determined based on the surface contour parameters. The thermal expansion coefficient and stress relaxation factor of the candy cane product are determined based on the melting temperature and physical properties of the raw materials. The initial three-dimensional morphology data is then compensated using a morphology compensation algorithm based on the thermal expansion coefficient and stress relaxation factor to obtain the target three-dimensional morphology data. Based on the hardness requirement parameters, determine the instantaneous hardness requirement, elastic modulus requirement, and fracture toughness requirement for the finished candy cane product. The shape compensation algorithm is as follows: ； in, This is represented as the compensated size. This represents the initial dimensions of the finished candy cane. This represents the coefficient of thermal expansion of the finished candy cane. It is expressed as the melting temperature of the raw material. This indicates the temperature at which the candy cane is formed. Represented as stress relaxation factor, This represents the holding time of the candy cane syrup in the molding fixture. This refers to the drying time after the candy cane is removed from the molding fixture; The system is also used for: The product design structure is determined based on the design specifications of the candy cane, and the equipment control parameters are determined based on the product design structure. The optimal state vector for each production stage of the candy cane is determined based on the equipment control parameters, and the quality change trend of the candy cane in each production stage is determined based on the optimal state vector. Based on the trend of quality changes, we determine the first production stage where qualitative quality declines and the second production stage where qualitative quality remains unchanged; The first stage of production will be closely monitored and data will be used for early warning.

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