Production method of freshly squeezed camellia oleosa seed oil

Abstract

The invention relates to the technical field of edible oil production, in particular to a production method of freshly squeezed camellia oleosa seed oil, which comprises the following steps: decomposing a production process of the freshly squeezed camellia oleosa seed oil into a plurality of process units; in the production process, collecting a real-time process parameter set of the current process unit, and performing process deviation quantitative analysis on the real-time process parameter set and a preset guide process parameter set of the process unit to obtain a process quality risk index of the process unit; analyzing the accumulated influence of the process quality risk indexes corresponding to all the current and previous process units on the process quality of the next process unit, and obtaining the accumulated effect value of the influence of the next process unit; in response to the fact that the influence cumulative effect value exceeds a preset influence threshold value, inputting all the process quality risk indexes into a preset process influence compensation model, and obtaining a process operation compensation strategy of the next process unit; the production efficiency can be improved, and the production cost is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of edible oil production, in particular to a production method of freshly squeezed camellia seed oil. Background Art

[0002] Freshly pressed camellia seed oil has high nutritional value and health functions because it is rich in unsaturated fatty acids, vitamin E and various antioxidants. Its production process has extremely high requirements on raw material screening, process control and quality stability.

[0003] Existing fresh-pressing processes typically employ empirical, segmented operations, dividing the production process into raw material pretreatment, pressing, filtration, and storage. However, quality control at each stage is relatively independent, lacking a systematic correlation analysis of process parameters across the entire process. When parameter fluctuations occur in a particular stage, there is a lack of assessment of the coupled effects of quality risks across multiple stages, making it impossible to generate targeted compensation strategies based on historical data and real-time deviations. For example, if the oil output rate decreases due to equipment wear in the pressing stage, existing methods address this issue solely by manually adjusting the pressing pressure, without considering the cumulative impact of fluctuations in parameters such as residual impurities and crushing particle size during raw material pretreatment on pressing efficiency. This can easily lead to delayed or overly adjusted compensation measures. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a production method of fresh-pressed camellia seed oil, which can improve production efficiency and reduce production costs.

[0005] In a first aspect, the present invention provides a method for producing freshly squeezed camellia seed oil, the method comprising:

[0006] Decomposing the production process of the freshly pressed camellia oil into multiple process units;

[0007] During the production process, the real-time process parameter set of the current process unit is collected, and the process deviation is quantitatively analyzed with the set of guidance process parameters preset for the process unit to obtain the process quality risk index of the process unit;

[0008] Analyze the cumulative impact of the process quality risk index corresponding to all current and previous process units on the process quality of the next process unit, and obtain the cumulative effect value of the impact of the next process unit;

[0009] In response to the cumulative effect value exceeding a preset impact threshold, all the process quality risk indexes are input into a preset process impact compensation model to obtain a process operation compensation strategy for the next process unit.

[0010] Furthermore, the process unit at least includes a raw material pretreatment unit, a pressing unit, a filtering unit and a refining unit.

[0011] Furthermore, the process parameters of the raw material pretreatment unit include raw material moisture content, impurity content and crushing particle size;

[0012] The process parameters of the pressing unit include pressing pressure, pressing temperature and pressing time;

[0013] The process parameters of the filtration unit include filtration speed, filter residue residue and filtration accuracy;

[0014] The process parameters of the refining unit include degumming parameters, deacidification parameters, decolorization parameters and deodorization parameters.

[0015] Furthermore, the raw material pretreatment unit further includes a raw material cleaning subunit, and the process parameters of the raw material cleaning subunit include cleaning time, cleaning water temperature and cleaning agent concentration.

[0016] Furthermore, the pressing unit further includes a pressing equipment monitoring subunit, and the process parameters of the pressing equipment monitoring subunit include equipment vibration frequency, motor current and pressing chamber pressure fluctuation amplitude.

[0017] Furthermore, the degumming parameters include degumming agent dosage, degumming temperature and degumming time;

[0018] The deacidification parameters include deacidification agent dosage, deacidification temperature and deacidification time;

[0019] The decolorization parameters include decolorization agent dosage, decolorization temperature, decolorization time and stirring speed;

[0020] The deodorization parameters include deodorization temperature, deodorization time and vacuum degree.

[0021] Furthermore, the guiding process parameter set is determined according to the target oil grade.

[0022] Furthermore, the real-time process parameter set and its corresponding guidance process parameter set include process parameters of the same type.

[0023] Furthermore, the calculation formula of the process quality risk index is:

[0024]

[0025] Among them, R represents the process quality risk index, n represents the total number of process parameters that need to be monitored in the process unit, i represents the i-th process parameter, P ia represents the real-time collected value of the i-th process parameter, P ib represents the preset guidance value of the i-th process parameter, w i represents the weight of the i-th process parameter.

[0026] Furthermore, the process operation compensation strategy includes process parameter adjustment, raw material and semi-finished product processing optimization, production process optimization, emergency plan, and equipment maintenance and calibration.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows: the production process is decomposed into multiple process units, and the process parameters of each unit are defined in detail; the process control is made more refined, which helps to fully grasp each link in the production process and provides a basis for systematic correlation analysis; by collecting real-time process parameter sets and conducting quantitative analysis with preset guidance process parameter sets, the process quality risk index of each process unit can be accurately evaluated; it helps to timely discover process parameter fluctuations and provide a basis for subsequent risk assessment and compensation strategy formulation; it takes into account the cumulative impact of all current and previous process units on the process quality of the next process unit, and by calculating the cumulative effect value of the impact, it can more comprehensively evaluate the coupling effect of multi-link quality risks; it helps to more accurately judge process quality risks and avoid single-link evaluation Limitations; when the cumulative effect value exceeds the preset impact threshold, the preset process impact compensation model is used to generate the process operation compensation strategy for the next process unit; it can automatically generate targeted compensation measures based on historical data and real-time deviations to improve the accuracy and timeliness of compensation; compared with the existing method of only manually adjusting a single parameter to solve the problem of parameter fluctuations, this method comprehensively considers the coupling effects of multiple process units and parameters, can avoid lags or over-adjustments of compensation measures, and improve the stability of the production process and the consistency of product quality; by systematically correlating and analyzing the process parameters of the entire process and generating compensation strategies based on real-time data and models, this method helps to optimize the production process, improve production efficiency, while ensuring the nutritional value and health functions of the product, and improving product quality and market competitiveness;

[0028] This approach is no longer limited to the quality control of a single process unit. Instead, it takes a holistic approach, comprehensively considering all process units from raw material pretreatment to refining. This makes quality control more comprehensive and in-depth, enabling the timely identification and correction of potential quality issues, thereby improving the overall quality of the final product. By collecting process parameters in real time and conducting quantitative deviation analysis, this approach can dynamically assess the quality risks of each process unit, analyze the impact of these risks on subsequent process units, and generate targeted compensation strategies based on these impacts. This makes the production process more flexible and controllable, allowing it to quickly adapt to various parameter fluctuations and uncertainties. Compared with traditional post-process quality control methods, this approach focuses more on preventive quality control. By analyzing the cumulative impact of the quality risk index of the current and previous process units on the next process unit, it can predict potential quality risks before problems occur and take preventive measures in advance. It can significantly reduce quality risks in the production process and improve product stability and consistency. By systematically correlating and analyzing process parameters throughout the entire process, this approach helps identify bottlenecks and optimization points in the production process. It can also make targeted improvements and optimizations to the production process, thereby improving production efficiency, reducing production costs, and further enhancing product quality and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0030] The present application is described below in conjunction with the accompanying drawings.

[0031] like Figure 1 As shown, the production method of freshly squeezed camellia seed oil of the present invention specifically comprises the following steps:

[0032] S1, decomposing the production process of the freshly pressed camellia oil into multiple process units;

[0033] S2. During the production process, a real-time process parameter set of the current process unit is collected, and a process deviation quantitative analysis is performed on the real-time process parameter set compared with a preset guiding process parameter set for the process unit to obtain a process quality risk index for the process unit;

[0034] S3. Analyze the cumulative impact of the process quality risk index corresponding to all current and previous process units on the process quality of the next process unit to obtain the cumulative effect value of the impact of the next process unit;

[0035] S4. In response to the cumulative effect value exceeding a preset impact threshold, all the process quality risk indexes are input into a preset process impact compensation model to obtain a process operation compensation strategy for the next process unit.

[0036] In this embodiment, the production process is decomposed into multiple process units, and the process parameters of each unit are defined in detail; this makes process control more refined, helps to fully grasp all links in the production process, and provides a basis for systematic correlation analysis; by collecting real-time process parameter sets and conducting quantitative analysis with preset guidance process parameter sets, the process quality risk index of each process unit can be accurately evaluated; it helps to timely detect process parameter fluctuations, providing a basis for subsequent risk assessment and compensation strategy formulation; the cumulative impact of all current and previous process units on the process quality of the next process unit is taken into account, and by calculating the cumulative effect value of the impact, the coupling effect of multi-link quality risks can be more comprehensively evaluated; it helps to more accurately judge process quality risks and avoid the limitations of single-link evaluation; When the cumulative effect value exceeds the preset impact threshold, the preset process impact compensation model is used to generate a process operation compensation strategy for the next process unit. Targeted compensation measures can be automatically generated based on historical data and real-time deviations, improving the accuracy and timeliness of compensation. Compared with existing methods that only manually adjust a single parameter to solve the problem of parameter fluctuations, this method comprehensively considers the coupling effects of multiple process units and parameters, can avoid lags or over-adjustments in compensation measures, and improve the stability of the production process and the consistency of product quality. By systematically correlating and analyzing the process parameters of the entire process and generating compensation strategies based on real-time data and models, this method helps optimize the production process and improve production efficiency, while ensuring the nutritional value and health functions of the product, and enhancing product quality and market competitiveness.

[0037] This approach is no longer limited to the quality control of a single process unit. Instead, it takes a holistic approach, comprehensively considering all process units from raw material pretreatment to refining. This makes quality control more comprehensive and in-depth, enabling the timely identification and correction of potential quality issues, thereby improving the overall quality of the final product. By collecting process parameters in real time and conducting quantitative deviation analysis, this approach can dynamically assess the quality risks of each process unit, analyze the impact of these risks on subsequent process units, and generate targeted compensation strategies based on these impacts. This makes the production process more flexible and controllable, allowing it to quickly adapt to various parameter fluctuations and uncertainties. Compared with traditional post-process quality control methods, this approach focuses more on preventive quality control. By analyzing the cumulative impact of the quality risk index of the current and previous process units on the next process unit, it can predict potential quality risks before problems occur and take preventive measures in advance. It can significantly reduce quality risks in the production process and improve product stability and consistency. By systematically correlating and analyzing process parameters throughout the entire process, this approach helps identify bottlenecks and optimization points in the production process. It can also make targeted improvements and optimizations to the production process, thereby improving production efficiency, reducing production costs, and further enhancing product quality and market competitiveness.

[0038] S1, decomposing the production process of the freshly pressed camellia oil into multiple process units;

[0039] The process unit at least includes a raw material pretreatment unit, a pressing unit, a filtering unit and a refining unit;

[0040] The process parameters of the raw material pretreatment unit include raw material moisture content, impurity content and crushing particle size;

[0041] The moisture content of camellia seeds has a significant impact on the pressing effect. Too high a moisture content may lead to a decrease in oil yield during the pressing process and increase the difficulty of subsequent refining. Too low a moisture content may lead to insufficient crushing of the camellia seeds during the pressing process, affecting the oil quality. Therefore, the moisture content of the raw materials needs to be strictly controlled.

[0042] The presence of impurities not only affects the purity of camellia oil, but may also damage the pressing equipment and subsequent refining process; therefore, during the raw material pretreatment stage, impurities need to be removed through screening, air separation and other methods to ensure the purity of the raw materials;

[0043] The size of the crushed particle size directly affects the oil extraction efficiency and oil quality during the pressing process; if the particle size is too large, it may lead to insufficient pressing and low oil extraction rate; if the particle size is too small, it may increase friction and heat generation during the pressing process, affecting the oil quality; therefore, it is necessary to reasonably control the crushed particle size according to the characteristics of the pressing equipment and the quality requirements of the target oil product.

[0044] The process parameters of the pressing unit include pressing pressure, pressing temperature and pressing time;

[0045] The main function of the pressing unit is to extract oil from pre-treated camellia seeds by physical methods;

[0046] Pressing pressure is a key factor affecting oil yield and quality. Too low a pressure may result in insufficient oil extraction, while too high a pressure may destroy the beneficial components in camellia seeds and affect oil quality. Therefore, the pressing pressure needs to be adjusted appropriately based on the characteristics of the raw materials and the quality requirements of the target oil product.

[0047] Pressing temperature also has a significant impact on oil extraction efficiency and oil quality. Excessively high temperatures may cause oil oxidation and deterioration; while excessively low temperatures may reduce oil yield. Therefore, the temperature must be strictly controlled during the pressing process, usually through a heating or cooling system.

[0048] The length of pressing time will also affect the oil yield and oil quality; too short a time may lead to insufficient oil output; too long a time may increase energy consumption and production costs; therefore, it is necessary to reasonably determine the pressing time based on actual conditions.

[0049] The process parameters of the filtration unit include filtration speed, filter residue residue and filtration accuracy;

[0050] The main function of the filtration unit is to remove impurities and suspended matter from the squeezed oil and fat, and to improve the purity and transparency of the oil and fat;

[0051] The selection of filtration speed requires a balance between filtration efficiency and filtration effect. Too fast a speed may result in incomplete filtration; too slow a speed may increase production costs. Therefore, the filtration speed needs to be reasonably adjusted according to the characteristics of the filtration equipment and the quality requirements of the target oil.

[0052] The amount of filter residue is an important indicator of filtration effectiveness. Excessive residue may lead to a decline in oil quality, while too little residue may increase filtration costs. Therefore, it is necessary to control the amount of filter residue by regularly cleaning the filter or replacing the filter material.

[0053] The filtration accuracy determines the degree of removal of impurities and suspended matter in oil and grease; too high an accuracy may lead to reduced filtration efficiency; too low an accuracy may not meet the quality requirements of the target oil; therefore, it is necessary to select the appropriate filtration accuracy based on the quality requirements of the target oil.

[0054] The process parameters of the refining unit include degumming parameters, deacidification parameters, decolorization parameters and deodorization parameters;

[0055] The main function of the refining unit is to further process the filtered oil to remove impurities such as free fatty acids, phospholipids, pigments, odor substances, etc., to improve the stability and quality of the oil;

[0056] Degumming is an important step in the refining process, mainly used to remove phospholipids and other colloidal substances in oils and fats. Degumming parameters include degumming agent dosage, degumming temperature, degumming time, etc., which need to be reasonably adjusted according to the characteristics of the oil and fat and the quality requirements of the target oil product.

[0057] Deacidification is mainly used to remove free fatty acids in oils and fats. Deacidification parameters include deacidification agent dosage, deacidification temperature, deacidification time, etc., which also need to be determined according to actual conditions.

[0058] Decolorization parameters: Decolorization is mainly used to remove pigments from oils and fats to improve their transparency and color. Decolorization parameters include the amount of decolorizer, decolorization temperature, decolorization time, and stirring speed.

[0059] Deodorization is mainly used to remove odorous substances in oils and fats and improve the sensory quality of oils and fats; deodorization parameters include deodorization temperature, deodorization time, vacuum degree, etc., which need to be fine-tuned according to the characteristics of the oils and fats and the quality requirements of the target oils.

[0060] In this embodiment, by breaking down the production process into multiple units, each unit has clear process parameters and control requirements, making the production process clearer and more controllable. This helps to promptly detect and correct deviations in the production process, ensuring the stability of product quality. By clarifying the process parameters of each process unit, fine-tuning can be performed according to actual conditions to maximize production efficiency. For example, in the pressing unit, reasonable adjustment of the pressing pressure, temperature, and time can increase the oil yield and reduce energy consumption and production costs.

[0061] By strictly controlling the process parameters of each process unit, impurities and harmful substances in oils and fats can be effectively removed, improving the purity and transparency of the oils and fats. At the same time, the refining unit can further remove free fatty acids, phospholipids, pigments and odor substances, thereby improving the stability and sensory quality of the oils and fats.

[0062] When problems arise during the production process, the problem can be quickly located and corresponding solutions can be taken based on the process parameters and records of each process unit; this helps shorten the time for problem investigation and reduce production losses; since the characteristics of camellia seed raw materials may vary from different origins and seasons, by decomposing the production process and clarifying the process parameters of each unit, flexible adjustments can be made based on the characteristics of the raw materials to ensure the stability of the production process and the uniformity of product quality.

[0063] Furthermore, the raw material pretreatment unit further includes a raw material cleaning subunit, and the process parameters of the raw material cleaning subunit include cleaning time, cleaning water temperature and cleaning agent concentration;

[0064] The main function of the raw material cleaning sub-unit is to thoroughly clean the oil-tea camellia seed raw materials to remove dirt, dust, pesticide residues and other possible impurities on the surface of the raw materials. Through cleaning, the purity of the raw materials can be significantly improved, the burden of subsequent processing can be reduced, and the quality and safety of the final product can be improved.

[0065] The length of cleaning time directly affects the cleaning effect. If the cleaning time is too short, impurities on the surface of the raw materials may not be completely removed. If the cleaning time is too long, the camellia seeds may absorb too much water, affecting the subsequent pressing efficiency. Therefore, it is necessary to reasonably determine the cleaning time based on the actual situation of the camellia seeds and the performance of the cleaning equipment.

[0066] The water temperature of the washing process is also an important factor affecting the washing effect. The appropriate water temperature can accelerate the dissolution and removal of impurities, improving the washing efficiency. At the same time, too high a water temperature may cause the loss or deterioration of nutrients in the camellia seeds, while too low a water temperature may reduce the washing effect. Therefore, it is necessary to select the appropriate water temperature for washing according to the characteristics of the camellia seeds and the washing requirements.

[0067] In some cases, in order to enhance the cleaning effect, an appropriate amount of cleaning agent may be used; the concentration of the cleaning agent needs to be strictly controlled. If it is too high, the cleaning agent may remain on the surface of the camellia seeds, affecting the subsequent pressing and refining process; if it is too low, the expected cleaning effect may not be achieved. Therefore, the concentration of the cleaning agent needs to be reasonably determined according to the characteristics of the cleaning agent and the cleaning requirements.

[0068] In this embodiment, by thoroughly cleaning the camellia seed raw material, impurities such as dirt, dust, and pesticide residues on the surface can be effectively removed, significantly improving the purity of the raw material and providing a high-quality raw material foundation for subsequent processing steps. The improved purity of the cleaned raw material can reduce the wear and clogging of equipment caused by impurities in subsequent pressing and filtration steps, reduce equipment failure rate, extend equipment service life, and improve overall production efficiency. Removing impurities and harmful substances from the raw material surface helps to improve the quality and safety of the final camellia seed oil, reduce potential risks to human health, and meet consumer demand for high-quality edible oil. By properly controlling the cleaning time, cleaning water temperature, and cleaning agent concentration, the best cleaning effect can be achieved. Appropriate cleaning time and water temperature can ensure that impurities are fully dissolved and removed, while a reasonable cleaning agent concentration can prevent the impact of cleaning agent residue on subsequent processing. Excessive cleaning time may cause the camellia seeds to absorb too much water, affecting the efficiency of subsequent pressing. Strictly controlling the cleaning time can avoid this problem, ensure the smooth progress of the pressing process, and improve the oil yield. Appropriate water temperature can prevent the loss or deterioration of nutrients in the camellia seeds, thereby preserving the natural nutritional value and health benefits of the camellia seed oil.

[0069] Furthermore, the pressing unit further comprises a pressing equipment monitoring subunit, the process parameters of which include equipment vibration frequency, motor current and pressing chamber pressure fluctuation amplitude;

[0070] The main function of the press equipment monitoring subunit is to provide real-time monitoring of key equipment parameters during the pressing process, including equipment vibration frequency, motor current, and pressure fluctuation amplitude in the pressing chamber. By continuously monitoring these parameters, the operating status of the equipment can be assessed, potential failures can be predicted, and alarms can be triggered or process parameters can be automatically adjusted when necessary to ensure the stability and efficiency of the pressing process.

[0071] Equipment vibration frequency is one of the important indicators reflecting the operating status of the pressing equipment. Abnormal vibration frequency may indicate problems such as imbalance, looseness or wear of the equipment. If not promptly addressed, it may cause equipment failure or affect the pressing effect. Therefore, by monitoring the equipment vibration frequency in real time, potential problems can be discovered and addressed in a timely manner.

[0072] Motor current is a key parameter that reflects the load condition of the pressing equipment. During the pressing process, if the motor current increases abnormally, it may mean that the equipment is overloaded or there is a mechanical failure. By monitoring the motor current, pressing parameters can be adjusted in time or the machine can be shut down for inspection to prevent equipment damage or affect production efficiency.

[0073] The amplitude of the pressure fluctuation in the pressing chamber is an important indicator for evaluating the stability of the pressing process. Stable pressure in the pressing chamber helps to ensure the oil yield and quality. If the pressure fluctuation amplitude is too large, it may indicate that there are unstable factors in the pressing process, such as uneven raw material supply, poor equipment sealing, etc. By real-time monitoring of the amplitude of the pressure fluctuation in the pressing chamber, these problems can be discovered and adjusted in time to ensure the stability of the pressing process.

[0074] In this embodiment, by real-time monitoring of the equipment's vibration frequency, potential equipment problems such as imbalance, looseness, or wear can be promptly detected, thereby preventing potential equipment failures and ensuring stable operation of the pressing equipment. Monitoring motor current can reflect the equipment's load. An abnormal increase in current may indicate overload or mechanical failure. Timely adjustment of pressing parameters or shutdown inspections can effectively prevent equipment damage and extend its service life. Real-time monitoring of the fluctuation amplitude of the pressing chamber pressure helps assess the stability of the pressing process. Stable pressing chamber pressure is key to ensuring oil yield and quality. By timely adjusting unstable factors such as uneven raw material supply or poor equipment sealing, the continuity and efficiency of the pressing process can be ensured. The pressing equipment monitoring subunit can automatically trigger alarms or adjust process parameters, realizing intelligent management of the pressing process. This reduces the frequency of manual inspections and adjustments, reduces labor intensity, and improves the accuracy and timeliness of production management. By ensuring the stable operation of the pressing equipment and the stability of the pressing process, the quality and safety of the final camellia oil product can be indirectly improved. Stable pressing conditions help preserve the nutrients and natural flavor of the camellia seeds while reducing the production of impurities and harmful substances.

[0075] S2. During the production process, collect the real-time process parameter set of the current process unit and perform a quantitative process deviation analysis on the real-time process parameter set compared with the preset guiding process parameter set for the process unit to obtain a process quality risk index for the process unit; the guiding process parameter set is determined based on the target oil grade; and the real-time process parameter set and its corresponding guiding process parameter set contain the same type of process parameters;

[0076] In each process unit, corresponding sensors and monitoring equipment are arranged according to process requirements; the arranged sensors and monitoring equipment can accurately and real-timely collect process parameters and obtain a set of process parameters;

[0077] According to the target oil grade, analyze the specific requirements of the oil grade on the process parameters;

[0078] Based on the analysis results of the target oil grade, a corresponding set of guiding process parameters is set for each process unit. The set process parameters can reflect the operating conditions of the process unit under ideal conditions and provide a benchmark for subsequent quantitative analysis of process deviations.

[0079] Compare the collected real-time process parameter set with the corresponding preset guidance process parameter set and calculate the deviation value of each parameter;

[0080] Assign corresponding weights to each process parameter according to its influence on process quality;

[0081] Calculate the process quality risk index based on the real-time process parameter set, the corresponding preset guidance process parameter set, and the corresponding weights;

[0082] The calculation formula of process quality risk index is:

[0083]

[0084] Among them, R represents the process quality risk index, n represents the total number of process parameters that need to be monitored in the process unit, i represents the i-th process parameter, P ia represents the real-time collected value of the i-th process parameter, P ib represents the preset guidance value of the i-th process parameter, w i represents the weight of the i-th process parameter.

[0085] In this embodiment, by deploying sensors and monitoring equipment, process parameters can be accurately and in real time collected, enabling continuous monitoring of the production process. Once a parameter deviates from a preset range, a timely warning can be issued to prevent potential quality issues from further deteriorating. By comparing real-time process parameters with preset guidance process parameters and calculating deviation values, the quality risk of each process unit can be quantitatively assessed, making quality risk more intuitive and measurable, facilitating decision-making by production managers. This step not only focuses on the deviation of a single parameter but also comprehensively considers the impact of each parameter on process quality by assigning weights to each process parameter. This helps to more comprehensively reflect the overall quality risk status of the process unit and avoids delayed or over-adjusted compensation measures caused by ignoring the coupling effects of multiple parameters. The calculated process quality risk index provides a scientific basis for subsequent process impact compensation strategies. When the risk index exceeds a preset threshold, a compensation mechanism can be promptly activated to adjust the process parameters to ensure production process stability and product quality consistency. Through continuous monitoring and analysis of the process quality risk index, bottlenecks and problems in the production process can be promptly identified, providing direction for process optimization and improvement, thereby improving production efficiency, reducing production costs, and enhancing the market competitiveness of products.

[0086] S3. Analyze the cumulative impact of the process quality risk index corresponding to all current and previous process units on the process quality of the next process unit to obtain the cumulative effect value of the impact of the next process unit;

[0087] Collect the process quality risk index of the current process unit and all previous process units;

[0088] Verify the accuracy of the collected process quality risk index to ensure that the collected data is accurate, complete and timely for subsequent analysis;

[0089] Determine the factors that influence the process quality risk index of each process unit on the process quality of the next process unit;

[0090] The analytic hierarchy process is used to determine the corresponding weight for each influencing factor; the weight reflects the relative importance of each factor in affecting the process quality of the next process unit;

[0091] According to the determined influencing factors and weights, the cumulative effect value is calculated;

[0092] In this embodiment, a systematic correlation analysis of process parameters throughout the entire process is achieved, breaking through the limitation of relatively independent quality control of each link in the existing process. By comprehensively considering the quality risk index of the current and previous process units, a more comprehensive understanding of the interactions and influences between the various links can be achieved, providing strong support for the optimization of the production process. The coupling effect of quality risks in multiple links can be accurately assessed, avoiding the one-sidedness that may result from the analysis of a single link. By calculating the cumulative effect value of the impact, the comprehensive impact of each process unit on the next process unit can be intuitively understood, providing a scientific basis for formulating targeted compensation strategies.

[0093] By promptly identifying and assessing potential quality risks, this step helps take preventive measures during the production process and reduce the occurrence of quality issues. At the same time, adjustments and optimizations based on the cumulative effect value can improve the stability of the production process and the consistency of product quality, meeting the market demand for high-quality fresh-pressed camellia oil. This emphasizes the accuracy and timeliness of data, ensuring the reliability of the collected process quality risk index through accuracy verification. This makes subsequent analysis and decision-making more data-driven, improving the scientific nature and effectiveness of decision-making.

[0094] By accurately evaluating the impact of each process unit on the next process unit, resources can be allocated more rationally and unnecessary waste can be avoided. At the same time, adjustment strategies based on the cumulative effect value of the impact can help reduce abnormal situations and downtime in the production process, thereby reducing production costs.

[0095] S4. In response to the cumulative impact value exceeding a preset impact threshold, inputting all the process quality risk indexes into a preset process impact compensation model to obtain a process operation compensation strategy for the next process unit;

[0096] Setting the preset impact threshold is a key step in ensuring that the process impact compensation strategy can be triggered in a timely and effective manner. The steps for setting the preset impact threshold include the following aspects:

[0097] The setting objectives of the preset impact thresholds need to be clearly defined. In the production process of fresh camellia oil, the setting objectives of the preset impact thresholds are to ensure product quality stability, improve production efficiency, reduce production costs, and avoid potential quality risks. By setting reasonable impact thresholds, compensation strategies can be triggered in a timely manner when quality risks accumulate to a certain level, thereby maintaining the stability of the production process and the consistency of product quality.

[0098] Collect a large amount of historical production data, including process quality risk index, actual production parameters, product quality test results, etc. of each process unit; this data should cover different production batches, raw material conditions, equipment status, etc. to ensure the comprehensiveness and representativeness of the data;

[0099] Conduct in-depth analysis of collected historical data to understand the transmission patterns and cumulative effects of quality risks between various process units; identify key factors and potential risk points that affect product quality stability through statistical analysis, correlation analysis, and other methods;

[0100] Based on the data analysis results, select key indicators that have a significant impact on the process quality of the next process unit as the basis for calculating the cumulative effect value. These indicators may include the process quality risk index of the current and previous process units, the deviation values of key process parameters, etc. Assign a corresponding weight to each key indicator to reflect its relative importance in affecting the process quality of the next process unit. The allocation of weights should be based on process experience, expert evaluation or data analysis results to ensure the rationality and accuracy of the weights.

[0101] Based on technical experience and industry standards in the edible oil production field, a preliminary threshold range for the cumulative effect value is set; this threshold should be able to cover the cumulative effect of quality risks under most normal production conditions, while leaving a certain margin to deal with unexpected situations;

[0102] Refer to the distribution of the cumulative effect values of quality risks in historical data to fine-tune the initially set thresholds. Ensure that the thresholds are neither too strict, resulting in frequent triggering of compensation strategies, nor too loose, resulting in inability to respond to potential quality risks in a timely manner.

[0103] Use historical data or simulated production environments to verify the initially set thresholds;

[0104] When the cumulative effect value exceeds the preset impact threshold, the generation and implementation of the process operation compensation strategy will be triggered; the process operation compensation strategy includes the following:

[0105] Adjustments to process parameters may require adjustments to the pressing pressure, pressing temperature, or pressing time based on the risks in the pressing process reflected in the cumulative effect value. For example, if the pressing efficiency decreases due to excessive impurity content in the raw material pretreatment stage, the pressing pressure can be appropriately increased to compensate for the insufficient oil output rate. For risks that may arise in the filtration stage, such as increased filter residue or decreased filtration accuracy, the filtration speed can be adjusted or the filter material can be replaced to ensure that the filtration effect meets the requirements of subsequent processes. In the refining stage, if the oil quality is unstable due to fluctuations in the previous process, parameters such as degumming, deacidification, decolorization, or deodorization can be adjusted to improve the oil quality.

[0106] Optimize the processing of raw materials and semi-finished products. If fluctuations in raw material pretreatment parameters significantly affect subsequent processes, the raw materials can be screened again, cleaned, or the crushing size can be adjusted to reduce impurity content and increase oil yield. For semi-finished products that have entered subsequent processes but have affected quality, reprocessing such as re-filtration, degumming, or deacidification can be considered to restore their quality.

[0107] Equipment maintenance and calibration: In response to fluctuations in process parameters caused by equipment wear or failure, equipment should be inspected, repaired, or wearing parts replaced in a timely manner to ensure that the equipment is in good operating condition. Key equipment should be calibrated regularly to ensure its measurement and control accuracy and reduce process risks caused by equipment errors.

[0108] Production process optimization: When necessary, the order of each process unit in the production process can be adjusted or certain links can be processed in parallel to shorten the production cycle or reduce the accumulation of quality risks; intermediate testing links can be added between key process units to monitor changes in oil quality in real time, so as to promptly identify and address potential problems;

[0109] Emergency plans should be formulated to address possible major process risks or equipment failures, clarify emergency response processes and responsible persons, and ensure that measures can be taken quickly and effectively in emergency situations.

[0110] In this embodiment, by setting a reasonable impact threshold, it is possible to timely capture signals of quality risk accumulation and trigger a compensation strategy when the risk reaches a certain level; this helps ensure that product quality remains stable during the production process and reduces product quality instability caused by process fluctuations; the process operation compensation strategy can quickly respond to and adjust specific process risks, avoiding production interruptions or delays caused by quality risk accumulation; by optimizing process parameters, adjusting production processes, and other measures, production efficiency can be improved and production cycle shortened; timely process compensation can reduce costs such as rework and scrap caused by quality problems; at the same time, by optimizing equipment maintenance and calibration plans, equipment service life can be extended and equipment failures and repair costs can be reduced;

[0111] The combination of preset impact thresholds and process operation compensation strategies forms a complete risk management system. When faced with emergencies or major process risks, emergency plans can be quickly activated, emergency response processes and responsible individuals can be clearly defined, and the continuity and stability of the production process can be ensured. By collecting and analyzing historical production data and continuously optimizing preset impact thresholds and process operation compensation strategies, continuous improvement of the production process can be achieved. This helps companies continuously improve product quality and production efficiency, thereby enhancing their market competitiveness.

[0112] The formulation and implementation of process operation compensation strategies require operators to have certain process control and problem-solving capabilities. Through training and practice, the operator's skills can be improved to ensure the standardization and controllability of the production process.

[0113] This step achieves timely warning and effective control of quality risks in the production process of fresh-pressed camellia oil by generating and implementing preset impact thresholds and process operation compensation strategies, thereby improving product quality stability, production efficiency, and reducing production costs.

[0114] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for producing freshly squeezed camellia seed oil, characterized in that: The method comprises: Decomposing the production process of the freshly pressed camellia oil into multiple process units; During the production process, the real-time process parameter set of the current process unit is collected, and the process deviation is quantitatively analyzed with the set of guidance process parameters preset for the process unit to obtain the process quality risk index of the process unit; Analyze the cumulative impact of the process quality risk index corresponding to all current and previous process units on the process quality of the next process unit, and obtain the cumulative effect value of the impact of the next process unit; In response to the cumulative effect value exceeding a preset impact threshold, all the process quality risk indexes are input into a preset process impact compensation model to obtain a process operation compensation strategy for the next process unit.

2. The production method of freshly squeezed camellia seed oil as claimed in claim 1, wherein The process unit at least includes a raw material pretreatment unit, a pressing unit, a filtering unit and a refining unit.

3. The production method of freshly squeezed camellia seed oil as claimed in claim 2, wherein The process parameters of the raw material pretreatment unit include raw material moisture content, impurity content and crushing particle size; The process parameters of the pressing unit include pressing pressure, pressing temperature and pressing time; The process parameters of the filtration unit include filtration speed, filter residue residue and filtration accuracy; The process parameters of the refining unit include degumming parameters, deacidification parameters, decolorization parameters and deodorization parameters.

4. The production method of freshly squeezed camellia seed oil as claimed in claim 2, wherein The raw material pretreatment unit further includes a raw material cleaning subunit, and the process parameters of the raw material cleaning subunit include cleaning time, cleaning water temperature and cleaning agent concentration.

5. The production method of freshly squeezed camellia seed oil as claimed in claim 2, wherein The pressing unit further includes a pressing equipment monitoring subunit, and the process parameters of the pressing equipment monitoring subunit include equipment vibration frequency, motor current and pressing chamber pressure fluctuation amplitude.

6. The production method of freshly squeezed camellia seed oil as claimed in claim 3, wherein The degumming parameters include degumming agent dosage, degumming temperature and degumming time; The deacidification parameters include deacidification agent dosage, deacidification temperature and deacidification time; The decolorization parameters include decolorization agent dosage, decolorization temperature, decolorization time and stirring speed; The deodorization parameters include deodorization temperature, deodorization time and vacuum degree.

7. The production method of freshly squeezed camellia seed oil as claimed in claim 1, wherein The guiding process parameter set is determined according to the target oil grade.

8. The production method of freshly squeezed camellia seed oil as claimed in claim 7, wherein The real-time process parameter set and its corresponding guidance process parameter set include process parameters of the same type.

9. The production method of freshly squeezed camellia seed oil as claimed in claim 1, wherein The calculation formula of process quality risk index is: Among them, R represents the process quality risk index, n represents the total number of process parameters that need to be monitored in the process unit, i represents the i-th process parameter, P ia represents the real-time collected value of the i-th process parameter, P ib represents the preset guidance value of the i-th process parameter, w i represents the weight of the i-th process parameter.

10. The method for producing freshly squeezed camellia seed oil according to claim 1, wherein: The process operation compensation strategy includes process parameter adjustment, raw material and semi-finished product processing optimization, production process optimization, emergency plan, and equipment maintenance and calibration.

Images