Method and system for continuous verification of technological processes using secure sequential hashing and Blockchain-based smart contracts.

Abstract

The invention is intended for managing the technological process of producing a product. The technological result of the present invention lies in verifying a technological process based on the analysis of the steps of that specified technological process. Another technological result of the present invention is ensuring the security of the collected data, characterizing the steps of the technological process, through the use of a decentralized record system. A further result is controlling the quality of the manufactured product through verification of the technological process. Another result is controlling the cost of the manufactured product through verification of the technological process.

Description

Title of the invention: Method and System for Continuous Verification of Technological Processes using Secure Sequential Hashing and Blockchain-Based Smart Contracts. State of the art

[0001] There are many different industries in the modern world, including the chemical and biotechnological industries. These industries play a key role in meeting society's needs, producing a wide range of products, from pharmaceuticals to industrial chemicals. At the same time, ensuring high product quality is a task of crucial importance for any producer.

[0002] Quality control is an integral part of the production process. Errors or violations in the production process can lead to the production and marketing of poor-quality or even dangerous products, which can harm consumer health and the environment, damage the reputation of the manufacturer, and consequently cause material damage to the manufacturer, as well as significantly reduce the competitiveness of the production or manufactured products. Therefore, producers attach great importance to the implementation of strict quality control systems at all stages of production.

[0003] Quality control in production is a multi-level process that includes different stages and verification methods. In the initial production phase, incoming inspection of raw materials and materials used in the production process is carried out. This ensures that the initial components meet the defined specifications and requirements. Continuous operational control is performed during the production process itself. At this stage, technological parameters such as temperature, pressure, speed, pH, and other indicators critical to ensuring the stability and reproducibility of the process are monitored. The monitoring data is recorded and analyzed, allowing for the rapid identification and correction of any deviations. The final stage of quality control is outgoing inspection of the finished product.At this stage, a complete verification of the products' conformity to established requirements concerning physicochemical, microbiological, organoleptic, and other indicators is carried out. Only after successfully passing this inspection can the products be shipped to the consumer.

[0004] Such a multi-stage approach to quality control allows manufacturers to guarantee not only the high quality of their products, but also their conformity to established standards and stated requirements. This means that two different finished products, manufactured in different companies, from different batches of raw materials or at different times, but using the same technology, will have almost identical characteristics. For the consumer or buyer, this means that each subsequent batch will be identical to the previous one, which increases the buyer's confidence in the manufacturer.

[0005] However, quality control is important not only for manufacturers, but also for potential buyers or consumers of the manufactured products. Customers want to receive high-quality products that meet their requirements and expectations. Therefore, they also seek to be able to perform quality control at different stages of the production process.

[0006] Furthermore, when manufactured products are traded on the stock exchange, knowledge of the quality of production processes becomes particularly important. Investors in stock markets are interested in obtaining reliable information on product quality, as this directly affects the value of the company's securities.

[0007] One of the problems faced by manufacturers and buyers is the need for buyers to access information about the production process without disclosing the manufacturer's technical details, algorithms, or know-how. This is essential to protect the manufacturer's intellectual property and preserve its competitive advantages.

[0008] Modern production processes are inconceivable without the widespread use of computer and information technologies in quality control systems. Digital sensors and analyzers collect and transmit enormous amounts of production data in real time. This data is accumulated in unified information systems, where it undergoes in-depth analysis using specialized software.

[0009] Artificial intelligence plays a significant role in modern quality control systems. Machine learning algorithms can identify subtle relationships between production parameters and product quality characteristics, relationships that are imperceptible to human perception. AI-based systems can predict the occurrence of defects, optimize technological processes, and propose corrective actions in real time. The use of AI increases the stability of production processes, reduces the level of defects, and ensures high product quality.

[0010] In turn, these advances provide tools to solve the problem of third-party access to quality control of manufactured products while preserving production secrets within companies. For example, one can consider as such tools and technologies are gaining popularity, such as blockchain and smart contracts.

[0011] These technologies ensure transparency and reliability of information on the production process without disclosing confidential data. This can give customers the ability to control the quality and cost of products at different stages of production, without infringing on the manufacturer's intellectual property rights.

[0012] Known methods and systems, such as those described in US patent 11,985,227 B2, provide a means of securing biotechnology laboratory data using blockchain technology. These systems comprise a central server and several subsystems, each equipped with blockchain databases for storing information and access data. Authorized users can grant or revoke access to the data, and the central server verifies the compatibility and immutability of the blockchain databases.

[0013] Although US patent 11,985,227 B2 provides a method for securing data and managing user access within biotechnology laboratories, it does not offer a mechanism for verifying and validating each step of a technological process. It lacks the integration of sensors for real-time data collection at each stage of the process, the use of sequential hashing to create an immutable string reflecting the complete process flow, and the implementation of smart contracts for automated validation. Furthermore, it does not address the need for process integrity and traceability in various industrial sectors, nor the use of decentralized autonomous organizations to manage processes autonomously.

[0014] Existing methods, such as those described in US 2023 / 0388125 A1, offer systems for secure exchanges of data in the form of assets using tokenization and confidentiality workflows. These systems focus on matching recipient requests with data assets and facilitate transactions between entities through consent and confidentiality mechanisms.

[0015] However, these methods do not meet the need to verify the integrity and conformity of each step of a technological process. They do not provide mechanisms for real-time data collection from the process steps, nor for ensuring process integrity through sequential hashing and validation.

[0016] Existing systems, such as those described in WO 2021 / 130341 A1, offer blockchain-based platforms to improve traceability, efficiency, and fairness in agricultural supply chains. These platforms focus on the connecting consumers with producers, enabling consumers to trace the origin of products and supporting sustainability projects through consumer-facing applications.

[0017] However, these methods do not meet the need to verify the integrity and conformity of internal technological processes in industrial environments. They lack mechanisms for collecting real-time process data using sensors, hashing this data for validation, and ensuring conformity and quality control via blockchain technology.

[0018] Patent JP2020-113280A describes a method and system for recording quality control, production, or regulatory data within a process control system using a distributed ledger maintained by multiple participants. The system detects specific triggering events, such as alarms, errors, leaks, corrective events, process milestones, or corrective actions, within a plant performing a production process via field devices that control industrial processes. When an event is detected, event data, including timestamps, durations, product parameters, and process parameters, are collected. Transactions containing this data are generated and stored in a distributed ledger, whether public or private, accessible to the plant and regulatory authorities.These transactions are then sent to other participants in the distributed ledger network for verification and recording, ensuring data integrity and compliance with regulatory requirements.

[0019] Although patent JP2020-113280A focuses on recording data at specific triggering events and storing it in a distributed ledger for compliance and auditing purposes, it does not address the continuous verification and validation of each step in a technological process. The patent does not specify the use of secure sensors designed to prevent data compromise at the point of collection, nor does it incorporate advanced cryptographic techniques such as sequential hashing that links each step of the process to create a complete chain reflecting the entire process flow. Furthermore, the patent does not use smart contracts to automate validation or advanced hashing methods that prevent reverse engineering of the original data, thus limiting its ability to ensure end-to-end process integrity and security.

[0020] In contrast, the present invention proposes a method for verifying technological processes by continuously collecting data at each stage using secure sensors specifically designed to prevent any data compromise. Each sensor generates data that is hashed sequentially, each hash integrating the data from the current stage and the previous hash. forming a linked chain that accurately reflects the entire process flow. This method uses advanced cryptographic techniques, such as homomorphic or fuzzy hashing, to ensure data confidentiality and integrity, making it impossible to reverse engineer the original data from the hashes. Smart contracts are used to automate the validation of each process step based on predefined criteria, enabling real-time verification and compliance without manual intervention. This approach not only guarantees the integrity and compliance of the entire technological process but also enhances security by preventing unauthorized access or manipulation, thus overcoming the limitations of existing technology described in patent JP2020-113280A. Presentation of the invention

[0021] The invention is intended to control the technological process of producing a product.

[0022] The technological result of the present invention lies in the verification of the technological process based on the analysis of the steps of said technological process.

[0023] Another technological result of the present invention is to ensure the security of the data collected characterizing the steps of the technological process, through the use of a decentralized register of records.

[0024] Another objective is quality control of the manufactured product through verification of the technological process.

[0025] Another objective is to confirm the cost of the quality of the manufactured product by verifying resource consumption.

[0026] This result is achieved through the use of a technological process verification method which collects data on each step of the process, including the resources used; hashes the collected data; validates the steps of the process on the basis of the analysis of the generated hash; and verifies the process on the basis of the analysis of the results of the validation of the steps.

[0027] In another particular case of implementation, the technological process includes at least: the steps of producing the product from the materials obtained, the steps of storing the product and the steps of transferring the product between different stages.

[0028] In another particular implementation case, the product production steps are the chemical production steps.

[0029] In another specific implementation of the process, the data relating to a step in the technological process include at least: the parameters of operation of the equipment used to perform the specified technological process step; the parameters and consumption of materials and energy used at that specified technological process step; and the parameters of the product obtained at the end of that specified technological process step.

[0030] In another particular case of implementation of the process, the data are collected using sensors excluding any compromise of the data at the time of data collection.

[0031] In another particular case of implementation of the process, any compromise of the data collected using a sensor is guaranteed to result in a change in the control data, regardless of the current state of the technological process step.

[0032] In another particular implementation of the method, the sensor with which the data is collected adds information about its state to the collected data, thus influencing the result of the subsequent hashing of the collected data.

[0033] In another particular case of implementation of the method, at least: the sensor state data contain a static encryption key used in the subsequent hashing procedure of the collected data; during the operation of the sensor, an encryption key is generated using a cryptographic hash function, which is used in the subsequent hashing procedure of the collected data.

[0034] In another particular case of implementation of the process, the data on the steps of the technological process are collected sequentially, from the step of the technological process that started to be executed earlier, to the step of the technological process that started later.

[0035] In another particular case of implementation of the method, by hashing data on a step of the technological process, a hash is formed which: identifies the step of the technological process, but does not allow an unambiguous calculation of the data on the basis of which the specified hash was generated.

[0036] In another particular case of implementation of the method, the identification of a technological process step is that the data on a technological process step with a given range of deviations correspond to a certain hash with a collision level not exceeding a given threshold value.

[0037] In another particular implementation of the method, at least one fuzzy or homomorphic hash function is used as a hash function to generate a hash.

[0038] In another particular case of implementation of the process, at least the following are used as homomorphic hash functions: the Rabin hash function, the Pohlig-Hellman hash function or the El-Gamal hash function.

[0039] In another particular case of implementation of the method, a hash for the next step of the technological process is generated on the basis of the data collected concerning the specified step of the technological process and the hash generated for the previous step of the technological process.

[0040] In another particular implementation, the generated hashes are stored sequentially in a decentralized register guaranteeing at least: the execution time of the steps of the technological process; the sequence of steps of the technological process; and the absence of auxiliary steps of the technological process influencing the results of subsequent steps of the technological process.

[0041] In another particular case of implementation of the method, the validation of a step in the technological process is carried out on the basis of an analysis of the accuracy of the constitution of a record in a decentralized registration register.

[0042] In another particular case of implementation of the method, the validation of a step in the technological process is carried out on the basis of the analysis of records concerning the steps in the technological process entered in a decentralized register of records using a pre-generated smart contract.

[0043] In another particular case of implementation of the process, a smart contract is formed from data concerning at least: the operation of sensors which collect data on the steps of the technological process; the hashing method of the collected data; operating parameters of the equipment used to carry out the steps of the technological process; parameters and consumption of materials and energy used at the specified steps of the technological process; parameters of the product obtained at the end of the specified steps of the technological process.

[0044] In another particular case of implementation of the process, the technological process is a decentralized autonomous organization.

[0045] In another particular case of implementation of the process, the validation of a technological process step is carried out on the basis of an analysis of the accuracy of the hash formation of the next technological process step on the basis of the hash of the previous technological process step.

[0046] In another particular case of implementation of the process, the validation of a technological step of the process is considered negative if a violation is detected at least in: the execution time of the technological step of the process; sequence of steps of the technological process; process of generating a hash from the collected data; device of the generated hash; conformity of a decentralized register record generated on the basis of a hash with a pre-generated smart contract.

[0047] In another particular case of implementation of the process, the validation of the technological step of the process is carried out at least: directly, i.e. on the basis of the analysis of a hash generated from data on the specified step of the technological process; indirectly, i.e. on the basis of the analysis of at least one hash generated from data concerning at least one other step of the technological process; using both direct and indirect methods of validation of the steps of the process.

[0048] In another particular case of implementation of the process, the verification of the technological process is carried out by comparing the final hash obtained after analysis of all the steps of the technological process with a hash obtained from data describing at least: material parameters, material consumption and energy used in the technological process; parameters of the product obtained at the end of the technological process.

[0049] In another particular case of implementation of the method, the verification of the technological process is carried out by generating control hashes at each stage of the technological process and comparing them with hashes generated from data collected at the stages of the technological process.

[0050] In another particular case of implementation of the method, the verification of the technological process is considered to be negative if at least the validation of one of the steps of the technological process is negative. Brief description of the figures

[0051] Additional objectives, features and advantages of the present invention will become clear from the following description of the implementation of the invention with reference to the accompanying drawings, in which: - [Fig.1] illustrates the process verification system. - [Fig.2] illustrates the method of verifying the process. - [Fig.3] illustrates the classification system of the manufactured product. - [Fig.4] illustrates the method of classifying the manufactured product. - [Fig. 5] represents an example of a computer system enabling the implementation in the implementation of the present invention. Detailed description of the invention and implementation of the invention.

[0052] The objectives and features of the present invention, and the methods for achieving these objectives and features, will become apparent by reference to examples of embodiments. However, the present invention is not limited to the embodiments described below and can be implemented in various forms. The above description is intended to assist a specialist in the field of technology to fully understand the invention, which is defined solely by the scope of the appended claims.

[0053]

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] [Fig. 1] illustrates the technological process verification system. The technological process validation system consists of a technological process 100, which in turn includes steps 101; data collection tools 110; data collection sensors 115; data hashing tools 120; a decentralized registry of records 125; a tool for validating the steps of the technological process 130; and a technological process verification tool 140. The technological process 100 includes at least: - Steps 101 of product production from the materials obtained. - Steps 101 for product storage. - Steps 101 of product transfer among other steps. In one embodiment of the process, the product production steps are the chemical production steps. In one embodiment of the process, the product production steps are the biochemical production steps. The data collection device 110 is designed to collect data 102 on the steps 101 of the technological process using the data collection sensors 115. In one of the system implementation options, the 102 data points concerning the technological process step 101 are at least: - The operating parameters of the equipment used to perform the specified step of technological process 101. - The parameters of the materials used at the specified stage of the technological process 101. - The consumption of materials and energy used at the specified stage of the technological process 101. - The parameters of the products obtained at the end of the specified step of technological process 101. In another embodiment of the system, the operating parameters of the equipment are at least: - Operating temperature of the equipment. - Pressure in the system. - Electricity consumption. - Operating time in charging mode. - Activation frequency of protection mechanisms. - Level of wear on components. - Raw material supply parameters. - Effectiveness of the control system.

[0060] In another implementation version of the system, the resource consumption parameters for carrying out the technological process are at least: - Operating temperature of the equipment. - Pressure in the system. - Electricity consumption. - Operating time in charging mode. - Raw material supply parameters. - Residual gas parameters. - Process waste parameters. - Conversion rate of resources into final product.

[0061] In another embodiment of the system, the parameters of the materials used in step 101 of the process are at least: - Chemical formula of the materials. - Chemical composition of materials. - Structure of materials. - Quantitative properties of materials, including: • Mass of matter • Volume of matter • Material density - Physical properties of materials, in particular: • Solubility, • Thermal conductivity, • Chemical properties of materials.

[0062] In another embodiment of the system, the parameters of the product obtained at the end of process step 101 are at least: - Chemical composition of the product. - Level of purity (e.g., impurity content). - pH value. - Viscosity. - Melting or boiling point. - Conversion rate of initial reagents. - Level of activity (e.g., catalytic). - Physical form (liquid, solid, gaseous). - Colour and transparency. - Biological activity (e.g., enzymes or drugs).

[0063] By way of example, consider the process of producing biological drugs, such as antibiotics, in a pharmaceutical factory.

[0064] During process step 101, which includes fermentation, the data acquisition system 102 can monitor the equipment's operating parameters, such as the reactor's operating temperature, which must be maintained between 28 and 32 degrees Celsius for optimal microbial activity. The system pressure is also controlled to prevent excess gas formation and ensure stable conditions for culture growth.

[0065] The parameters of the materials used at this stage include the chemical formula of the nutrient medium containing carbohydrates, amino acids, and vitamins necessary for the growth of microorganisms. Quantitative properties, such as the mass and density of the components used, are essential to achieve the desired nutrient concentration. Physical properties such as solubility also play an important role as they influence the availability of nutrients to the microorganisms.

[0066] In the process of transforming materials into products, various forms of energy are used: mechanical energy for mixing the culture medium; electrical energy for its thermal stabilization, equipment sterilization, and pumping of the media; compression of the gas phase and mass transfer; and thermal energy for inactivating the culture liquid. All forms of energy consumed in the technological process must be taken into account and quantified in order to monitor costs and ensure energy efficiency.

[0067] Measuring and controlling the consumption of materials and energy used in the process are key elements for establishing efficient production.

[0068] At the end of step 101 of the process, the parameters of the product obtained by fermentation include the purity level of the antibiotic, which must be at least 98% to meet pharmaceutical standards. It is also essential to monitor the pH, which must be between 6.5 and 7.5 to ensure product stability. The biological activity of the antibiotic is tested by microorganism susceptibility testing, which allows its effectiveness to be assessed. This data helps to optimize the process and ensures the high quality of the final products.

[0069] In another implementation option, the data 102 are collected using sensors 115, preventing any compromise of the data during collection.

[0070] In another implementation option, data compromise is understood as an unauthorized modification of data, leading to incorrect (different from the true) results of data processing. Furthermore, data compromise may involve the unauthorized provision of access to third-party data (in particular, a data leak), which may lead to the disclosure of quantitative or qualitative details of the technological process.

[0071] For example, in chemical manufacturing, particularly in the production of synthetic polymers, data protection during collection is critically important. Sensors 115 installed on the equipment collect parameters such as temperature, pressure, and the composition of the reactants. These sensors are equipped with encryption and authentication systems to prevent any compromise. Any attempt to alter the operation of the sensors, particularly by modifying the transmitted data or measurements of operating procedures, is recorded and can be detected later, allowing for correction or a production shutdown.

[0072] In another implementation option, the compromise of the data 102 collected using the sensor 115 is guaranteed to lead to a change in the control data which is independent of the current state of the process step 101.

[0073] For example, the data collected by sensor 115 is pre-encrypted (before transmission) using internal keys specific to that sensor. If a sensor is replaced without certification, the encryption keys also change, resulting in a modification of the transmitted data.

[0074] In another implementation of the system, any modification of the control data guarantees an indication of intervention in the operation of sensor 115.

[0075] Consider the example of a chemical production plant where sensors 115 monitor parameters such as the liquid level in the tanks, pressure, and temperature. If one of the sensors begins to give incorrect readings due to interference, such as physical damage or substitution, the system automatically compares the current data with the reference values.

[0076] If discrepancies are detected between the control data and the readings from sensor 115, the system generates an alert and triggers an intervention signal. This can be indicated by a visual warning on the control panel and the sending of notifications to the operators. Thus, changes in the control data not only serve as an indicator of potential interventions, but also allow for a rapid response to potential threats, minimizing the risk of accidents and ensuring the safety of the production process.

[0077] In another embodiment of the system, the sensor 115, used to collect the data 102, adds to this data information about its own state, which influences the result of the subsequent hashing of the collected data 102.

[0078] For example, during the execution of a specific step in a technological process, described by the corresponding data, a flexible hash 0xffl786ad is calculated. This hash lies within a predetermined range, from 0xff100000 to 0xff200000, characteristic of the normal execution of this process. Among other things, the software hash value is influenced by previously known data concerning The operating state of sensors 115, which are hashed with the process data collected by these sensors, is affected. However, if changes have been made to the operation of sensors 115 (including alterations to the transmitted data), this results in a change in their operation, yielding a calculated hash of 0xl25a03fa, outside the predetermined range. This indicates interference with the operation of sensors 115.

[0079] In another embodiment of the system, the data on the status of sensor 115 include at least: - The operating time of sensor 115 for sensors involving a data stream; - The number of data collection and transmission cycles for sensors requiring packet data transmission; - The time spent on the collection, pre-processing and transmission of the collected data; - The volume of data transmitted; - The checksum of the transmitted data; - The operating modes of sensor 115; - The version of the software performing the data preprocessing, for sensors requiring data preprocessing; - The dynamic characteristics of the current state of sensor 115 influencing its operation, such as temperature, pressure, humidity, etc. - The status data from sensor 115 contains a static encryption key used in the subsequent hashing procedure of the collected data 102;

[0080] During the operation of the sensor 115, an encryption key is generated using a cryptographic hash function, which is used in the subsequent hashing procedure of the collected data 102.

[0081] In another implementation variant of the system, the data collection sensors 115 are grouped into an anti-fraud system.

[0082] In another embodiment of the system, the data relating to the steps of the technological process 102 are collected sequentially, from step 101.1, which started to be executed first, to step 101.N, which started to be executed last.

[0083] Let us take an example of chemical production involving the synthesis of a pharmaceutical drug. This process comprises several steps, each with its own parameters and execution times: - Step 101.1: Preparation of Reagents — During this first step, the necessary chemical substances are weighed and mixed. The data information regarding the quantity and quality of the reagents, as well as the quantity and parameters of the energy consumed for this preparation, are recorded. - Step 101.2: Reaction — Once the reactants are prepared, a chemical reaction begins, which may last for some time. During this period, the system collects data on the temperature, pressure, and duration of the reaction, as well as the external energy consumed to carry out this step. - Step 101.3: Product Separation — Once the reaction is complete, the product is separated from the reactant residues and by-products. Data on the yield, product purity, and energy consumed for this separation are also recorded. - Step 101.N: Packaging and Labeling — In the final step, the finished product is packaged and labeled for distribution. The system records data on the number of units packaged and their compliance with standards.

[0084] In this example, the information processing system collects data sequentially for each step of the process, starting with the preparation of the reagents (step 101.1) and ending with the packaging of the finished product (step 101.N). This approach makes it possible to monitor the efficiency of each step, identify bottlenecks in the production process, and ensure that the product conforms to established quality standards.

[0085] The hashing device 120 is intended to hash the data 102 collected by the data collection device 110.

[0086] In one variant of the system implementation, by hashing the data 102 concerning the technological process step 101, a hash 121 is formed, which: - Identifies step 101 of the technological process, - But it prevents the unambiguous calculation of the data from which this 121 hash was formed.

[0087] An example of this type of hashing could be the use of the SHA-256 algorithm to hash data relating to the production stage, such as information on the start and end of the stage, the identifiers of the equipment used, and the product quality parameters. When this data is hashed, a unique 121 hash is obtained, which might, for example, look like: 3alc5e3b8d9e7a4f3c2e6b8d5f8elc2f4a3b9e7ald4f3e2b7c9e8alf6b4c2d3.

[0088] This hashing allows identification of a specific step in the technological process 101, but does not allow recovery of the basic data of the process, because the inverse calculation of the hashing is impossible.

[0089] Furthermore, computed hashes can preserve certain properties of the hashed data. For example, if the data relates to two temperature values ​​and T 2 and that TT 2' are the hashes H and H2 associated with temperatures 7^ and T2 will also satisfy the relationship H±> H2, while making it impossible to recover temperature values ​​from hashes.

[0090] For example, for the situation described above, hash functions such as BLAKE2 can be used. Suppose that T1 = 75°C and T2 = 50°C. Using this hash function, the hashes and H2 can be respectively: aa456b0e3330a562a5dd3all6271212606ef03c44ela653da44cff5040679ea8d443a96e70edd3f3dc03 and a801ad90736e816c24bfbd3962456510c35ed096ca3d85d7284a4c2c3c6c04af0f04615b0824be4af67c

[0091] For more complex hashes, where not only the "largest" relation that" but also the proportion is preserved, algorithms like Argon2 or PBKDF2 hashes can be used, allowing the creation of hashes that take specific parameters into account. For example, if we want to preserve the ratio of temperatures T1 and T2 such that T1 = 77j / 772, and T2 = 80°C, we can use a hash function that considers not only the temperature but also an additional parameter, such as a coefficient that determines the ratio. By applying Argon2 to the strings representing T1 and T2, taking this coefficient into account, we can obtain H1 = Argon2("Temperature: 80", "Coefficient: 2") and H2 = Argon2("Temperature: 40", "Coefficient: 1"). In this case, the hash H1 will be twice as large as H2, making it impossible to recover the temperatures T1 and T2 from the hashes H1 and H2.

[0092] In another variant of the system implementation, the identification of a step in the technological process 101 is that the data 102 concerning the step in the technological process 101 with a given range of deviations correspond to a certain hash 121 with a collision level not exceeding a given level, the threshold value.

[0093] Hash functions that guarantee the association of input values ​​with a predefined range of output values ​​are called "grouping" or "compression" hash functions. However, most standard hash functions, such as SHA-256 or MD5, do not have these properties, because their output values ​​are distributed over the entire hash space.

[0094] Nevertheless, it is possible to create a hash function possessing these properties, using linear hash functions and modular arithmetic.

[0095] By way of example of such hash functions or hash functions which, after minor modifications, can have the properties described above, one may use: - MurmurHash: This is not a cryptographic hash function, but it is used in various applications, including databases data and distributed systems. It can be used with modular arithmetic to constrain the output value to a specified range; - CityHash: This is another non-cryptographic hashing function developed by Google. Like MurmurHash, it can be adapted to work with limited ranges; - FNV (Fowler-Noll-Vo) Hash: A simple hash function, which can also be used with modular arithmetic to limit values ​​to a given range; - DJB2: A simple hash function developed by Daniel Bernstein, also adaptable for limited ranges, like other non-cryptographic hash functions. - MPHF: The minimum perfect hash function (MPHF) is a specialized function that associates a known set of n unique keys with exactly n unique hash values ​​in a predefined range, usually from 0 to n-1 without any collisions.

[0096] This means that each key has a unique hash value, enabling efficient collision-free searching. The perfect hash function also guarantees collision-free matching but can use a wider range of outputs than the minimal perfect hash. Both types are particularly useful for static key sets, where the input keys are known in advance and do not change, providing precise and efficient access to data without the need for collision resolution strategies, which are common in classical hash functions.

[0097] In another embodiment of the system, at least the following hash functions are used to generate hash 121: - Fuzzy hash function; - Homomorphic hash function.

[0098] A fuzzy hash function is a function that transforms input data (e.g., a file or a string) into a fixed-length hash value, while ensuring that small changes in the input data result in small changes in the hash value. Unlike classical cryptographic hash functions, fuzzy hash functions allow the hash values ​​to be compared to determine the degree of similarity between the input data.

[0099] Thus, a fuzzy hash function not only allows the identification of data, but also the evaluation of their degree of similarity, which makes it useful in tasks related to data processing and analysis, such as digital forensics, duplicate detection and other applications.

[0100] Among the most common fuzzy hash functions, we find at least: - SSDEEP (SpamSum): one of the best-known fuzzy hash functions, used to compare files and identify similar data. It divides a file into blocks and calculates a hash for each block, then combines these hashes to obtain a final hash. SSDEEP can find similar files, even if they have been modified or partially modified. - TLSH (Trend Locality Sensitive Hashing): a fuzzy hash function used to compare files and assess their similarity. It works by analyzing the contents of a file and generating a hash value that reflects its structure. TLSH can be useful for detecting duplicates and similar files in large data collections. - AFL (American Fuzzy Lop): AFL uses fuzzy hash functions for software analysis and testing. It generates test cases based on existing data and uses fuzzy hashing to determine the similarity between the input data and the test cases, allowing it to find vulnerabilities in software.

[0101] A homomorphic hash function is a cryptographic hash function that has the property of allowing operations to be performed on hashed data without revealing the data itself. This means that if two values ​​-¾ and -¾ have their hashes h(x^)eth(x2), you can perform certain operations on the hashes that correspond to operations on the original values, for example: 21(¾)+21(¾) =h(x1 + x2)

[0102] In another variant of the system implementation, the homomorphic hash functions used may include at least: - Rabin's hash function; - The Pollard-Hellman hash function; - The ElGamal hash function.

[0103] Finally, in another variant of the system, the hash 121 for the next step of the technological process 101 is generated from the data 102 collected for that step of the process and the hash 121 generated for the previous step of the technological process 101.

[0104] For example, if data 102 are available for several successive technological processes 101 - [d^], the hashes are calculated successively using the hashes of the previous steps as follows: = H(d^), h2 = H(d2, hl), h3 = H(dy h2),..., hu = H(dn, h^)

[0105] In another implementation variant of the system, quantum cryptography is used to solve problems of data integrity, sensor authentication and anomaly detection in industrial processes: - Use quantum distribution key (QKD) encryption to ensure secure communication between parties guaranteed by the laws of quantum mechanics. - Equip sensors and central processors with QKD functions for the secure exchange of encryption keys used for data transmission. - Detect key interceptions because any attempt alters their quantum state, thus alerting the system to potential security violations. - Scaling up thanks to the latest advances, such as integrated photonic chips for QKD and satellite QKD systems, allows for scalable deployment over large areas and on many devices. - Use quantum digital signatures based on quantum states to create impenetrable signatures for messages in order to identify data. Each sensor can sign its data with a quantum signature, thus guaranteeing the origin and integrity of the data. - Using quantum random number generators (QRNGs) for cryptographic keys used in hashing processes, improving security compared to classical pseudo-random generators, combined with dynamic key generation. - To prevent man-in-the-middle attacks and ensure that the data collected by the sensors remains confidential and protected against any interference. This approach complies with the strict data protection standards required in sectors such as pharmaceutical production and energy. - Use hash functions that are resistant to quantum attacks. - Use quantum sensors to improve measurement accuracy and the reliability of the data, allowing the detection of tiny variations in the data.

[0106] In another embodiment of the system, the generated hashes 121 are recorded sequentially in a decentralized register of records 125, guaranteeing at a minimum: - The execution time of the steps in industrial process 101. - The sequence of steps in the industrial process 101. - The absence of auxiliary steps in the industrial process 101 influencing the results of the following steps.

[0107] In another variant of the system implementation, the decentralized ledger of records is formed using blockchain technology.

[0108] In another embodiment of the system, the decentralized register of records is formed using at least the following technologies: - Directed Acyclic Graph (DAG) technologies: This data structure allows transactions to be recorded as directed acyclic graphs, which can improve processing speed and reduce transaction costs. Examples of DAG usage include IOTA and Hedera Hashgraph. - Decentralized data storage systems: Technologies such as the InterPlanetary File System (IPFS) allow data to be stored in a decentralized manner, offering access via unique addresses, rather than through central servers. - Consensus-based networks: The application of consensus algorithms, such as Practical Byzantine Fault Tolerance (PBFT) or Raft, allows for decentralized management of records without using blockchain, guaranteeing coordination between network nodes. - Systems based on a federative approach: In these systems, several independent nodes can interact with each other while retaining control of their own data and ensuring decentralized management. - Zero-Knowledge Proofs (ZKP) based technologies: These technologies allow information to be verified without disclosing the data itself, which can be useful for ensuring confidentiality in decentralized registries.

[0109] The process step validator 130 is designed to validate the process step 101 on the basis of the analysis of the hash 121, generated by the hashing mechanism 120.

[0110] In another implementation variant of the system, the validation of the industrial process step 101 is carried out on the basis of the analysis of the accuracy of the record in the decentralized register of records 125.

[0111] In another embodiment of the system, to ensure the integrity and security of the decentralized register of records 125, the validation mechanism for the steps in the industrial process 130 includes mechanisms for detecting unauthorized access to and modification of records. One of these mechanisms relies on the use of cryptographic methods, such as digital signatures and cryptographic hashes, to verify the authenticity of each record in the register. When a new record is added to the register, It is signed using a private key, which allows its authenticity to be verified using the corresponding public key. If the record is modified, its digital signature becomes invalid, signaling a possible data compromise.

[0112] For example, the system may also include an auditing mechanism, which includes periodic verification of the integrity of all records in the ledger. This process may be automated and include a comparison of the current hash values ​​of the records with the hashes previously recorded at the time the record was created. If inconsistencies are detected, the system initiates an alert and analysis procedure, thus enabling a rapid response to potential security threats and preventing further data corruption.

[0113] Furthermore, to strengthen protection against unauthorized access, the system can use access management mechanisms, such as multi-factor authentication and role-based access control. This ensures that only authorized users can make changes to the register, and that all user actions are logged and can be analyzed if necessary. Thus, the validation mechanism for the steps in the industrial process 130 provides reliable protection of the decentralized register of records 125 against unauthorized access and modifications, thereby strengthening confidence in the data contained in the register.

[0114] In another variant of the system implementation, the validation of the industrial process step 101 is carried out on the basis of the analysis of the records of the industrial process steps 101, entered in the decentralized register of records 125, using a pre-programmed smart contract.

[0115] As an example of implementing the system for validating the steps of industrial process 101 using smart contracts, the supply chain management process can be considered. In this scenario, each step of the goods delivery, from production to delivery to the end consumer, is recorded in the decentralized register of records 125. A smart contract, programmed in advance to check criteria such as adherence to delivery deadlines, product quality, and other parameters, automatically analyzes the records of each step. If all conditions are met, the smart contract confirms the success of the step; otherwise, it generates a non-conformity notification, allowing for a rapid response to any problems encountered.

[0116] In the field of chemical production, smart contracts can be used to automate and validate quality control processes for raw materials and finished products. For example, when chemicals enter the plant, records concerning each carrier and the tests carried out to verify compliance with quality standards are recorded. in the decentralized ledger. The smart contract, programmed to verify these records, can automatically analyze the test results by comparing them to pre-established parameters. If all tests confirm compliance, the smart contract automatically initiates the process of accepting the raw materials and using them in production. In case of non-compliance, the smart contract can block further operations with these raw materials and inform the responsible employees of the need to perform additional checks.

[0117] In the field of biological media production, such as cell cultures or microbial growth media, smart contracts can be used to manage development and testing processes. For example, when creating a new nutrient medium for cells, each step, including the selection of components, their dosage, and the test results, is recorded in the decentralized registry. The smart contract can verify whether all development and testing protocols have been followed and whether the results meet the established criteria. If all conditions are met, the smart contract can approve the transition to the next step, for example, increasing production. In case of non-compliance, the smart contract can initiate repeated tests or block other actions, thereby helping to improve the quality and reliability of the biological media produced.

[0118] In another embodiment of the system, the smart contract is generated on the basis of data concerning at least: - The operation of sensors 115 collecting data 102 on the steps of the industrial process 101; - The hashing method of the collected data 102; - The operating parameters of the equipment used to carry out the steps of the industrial process 101; - The parameters of the materials used at each stage of the industrial process 101; - The consumption of materials and energy at each stage of the industrial process 101; - The characteristics of the product obtained at the end of stage 101 of the industrial process.

[0119] In the context of chemical production, let us take the example of the synthesis process of a pharmaceutical drug, such as an antibiotic. At each stage of this technological process, sensors are used to collect data on the temperature, pressure, and concentration of the reactants. This data is transmitted to the system, where it is processed and hashed using homomorphic cryptography algorithms to ensure its integrity and protection against falsification. As a result, a smart contract is formed, recording all the operating parameters of the equipment, such as the mixing speed and reaction time, as well as the characteristics of the materials used, for example the purity of the reagents and their physico-chemical properties.

[0120] In the final stage of the process, the system also collects data on the final product, including its biological activity and stability. These parameters, along with data from previous stages, are integrated into a smart contract, which can be used to automate quality control and verify compliance with standards. Thus, this system not only ensures the transparency and safety of the production process but also enables real-time audits and monitoring.

[0121] In another variant of the system implementation, the industrial process 100 constitutes a decentralized autonomous organization.

[0122] In the context of chemical production and the manufacture of biological media, a decentralized autonomous organization can be represented as a network of independent laboratories and production facilities, each responsible for a specific step in the technological process. For example, one laboratory might be involved in the synthesis of chemical compounds, while another handles their testing and the optimization of growth conditions for microorganisms. These laboratories can exchange and share data and research results via cloud platforms, enabling them to adapt quickly to changing requirements and improve production processes without requiring centralized management. This approach promotes greater flexibility and efficiency, as each unit can make decisions autonomously based on local conditions and needs.

[0123] In another embodiment of the system, the validation of a step of the industrial process 101 is carried out on the basis of an analysis of the accuracy of the hash formation 121 of the next step of the industrial process 101, as a function of the hash 121 of the previous step of the industrial process.

[0124] For example, the entire technological process comprises several steps from the raw material control step to the manufactured product control step (e.g., the biological environment - bacteria, biologically active substances, etc.). In accordance with standards and the technology map, each step can be described by several sets of data: - data characterizing the raw materials entering the transformation (it should be noted that this is not the initial raw material, but the product of the previous step); - data characterizing the progress of the transformation process of the raw materials received; - data characterizing the product of the transformation of the raw materials received (note that this is not the final product, but the raw material for the next step).

[0125] Based on theoretical data (or the ideal image of the technological process), the permissible ranges of values ​​within which this data can vary are calculated in advance, so that at the end of the process, the product has defined quality parameters. The calculated data are then hashed using homomorphic encryption algorithms, so that ultimately a dataset is obtained that uniquely characterizes the "ideal process" without revealing its details.

[0126] Then, during the execution of the steps of the technological process or after the completion of all the steps, a check is carried out to assess whether the actual encrypted data falls within the range of values ​​of the encrypted "ideal data". The difference between the actual and ideal data is assessed by appropriate comparative methods and a decision is made, in particular on: - if there has been unauthorized intervention in the data collected concerning the steps of the technological process; - if there has been a discrepancy in the execution of the steps of the technological process; - to what extent the detected deviations affected the quality of the final product.

[0127] In another implementation variant of the system, the validation of step 101 of the technological process is considered negative if a violation is detected in at least one of the following elements: - the execution time of step 101 of the technological process; - the order of execution of the steps of the technological process 101; - the method of forming the hash 121 from the collected data 102; - the device used to generate the hash 121; - the conformity of the record generated from hash 121 in the decentralized register of records 125 to the pre-established smart contract.

[0128] For example, in chemical production, during quality control at the synthesis stage, the following sequence of actions can be carried out: - Step execution time: the system can track the time required to complete the reactions and compare it to the defined time parameters. If the time exceeds the norm, this signals a potential problem. - Order of steps: validation can verify that the steps of the synthesis are executed in the correct order (for example, first the addition of reagents, then heating). - Data hashing: the data collected on the reaction parameters (temperature, pressure, concentration of reactants) can be hashed and recorded in the decentralized register to guarantee the immutability of the data. - Smart contract: the smart contract can automatically check the hash's compliance with pre-established conditions (e.g., the permissible limits for each parameter).

[0129] In another example, during the production of biological media at the fermentation process control stage: - Step execution time: the time required for each phase of fermentation can be tracked, and the system can report delays, which may indicate a process malfunction. - Preparation of the medium, inoculation and monitoring of growth to ensure that all steps are carried out in the correct order. - Data hashing: Data concerning temperature, pH, nutrient concentration and other parameters can be hashed and recorded in the log to ensure their integrity. - Smart contract: The smart contract can be used to make automatic decisions based on collected data, for example, to trigger the next phase of the process only after successful validation of the previous phase. - Order of steps: Verification of the sequence of operations, such as preparation of the medium, inoculation and monitoring of growth, to ensure that all steps are carried out in the correct order. - Data hashing: Data concerning temperature, pH, nutrient concentration and other parameters can be hashed and recorded in the log to ensure their integrity.

[0130] In another example, when monitoring the sustainability of processes: - Step execution time: the system can control the time required for processes related to sustainable production (e.g., waste recycling) and report any non-compliance. - Order of steps: validation can verify that all steps, such as collection, recycling and disposal of waste, are carried out in the intended order. - Data hashing: data on the quantity and quality of recycled materials, as well as the energy used for this recycling, can be hashed to ensure transparency and accuracy of information. - Smart contract: the smart contract can automatically regulate the process based on the data collected, for example, increasing the volume of recycling once certain thresholds are reached.

[0131] These examples show how a validation system can be applied to improve the efficiency and reliability of processes in chemical production and the manufacture of biological media, ensuring transparency and quality control at each stage.

[0132] In another implementation variant of the system, the validation of step 101 of the technological process is carried out as follows: - Directly, that is to say on the basis of the analysis of the hash 121, formed from the data 102 of the step of the technological process 101 specified; - Indirectly, that is to say on the basis of the analysis, at least of the hash 121, formed from the data 102 of at least one other step of the technological process 101; - By using both direct and indirect validation of the technological process step.

[0133] The technological process verification system 140 is intended to verify the technological process 100 on the basis of the analysis of the validation results of the steps of the technological process 101, carried out by the validation tool of the steps of the technological process 130.

[0134] In another embodiment of the system, the verification of the technological process 100 is carried out by comparing the final hash 121, obtained after the analysis of all the steps of the technological process 101, with the hash 121, obtained on the basis of the data describing at least: - The parameters of the materials used in the technological process 100; - The consumption of materials and energy used in the technological process 100; - The parameters of the product obtained at the end of the technological process 100.

[0135] In another variant of the system implementation, the verification of the technological process 100 is done by forming control hashes 121 at each step of the technological process 101 and comparing them with the hashes 121, formed from the data collected during the steps of the technological process 101.

[0136] In another implementation variant of the system, the verification of technological process 100 is considered negative if one of the steps of technological process 101 has failed.

[0137] In another embodiment of the system, if the technological process is successfully verified, the final product is considered to conform to the initial requirements (previously defined), that is to say, a product of satisfactory quality, manufactured according to a pre-established technological map.

[0138] In another implementation variant of the system, in the event of failure of the verification of the technological process, at least: - The final product is rejected; - The final product goes through an additional classification system to be reclassified into other product groups (e.g., lower quality products); - An equipment check is carried out to determine the reasons for the failure of the technological process verification.

[0139] [Fig.2] illustrates the method for verifying the technological process. The process verification method includes step 210, which collects data on the process steps, step 220, which hashes the data, step 230, which validates the process steps, and step 240, which verifies the process.

[0140] At step 210, data on each step 101 of the technological process 100 are collected by data acquisition means 110, via at least one data collection sensor 115.

[0141] In one embodiment of the method, the data 102 on the technological process step 101 include at least: - The operating parameters of the equipment used to perform step 101 of the technological process; - The parameters of the materials used in this step of the technological process 101; - The consumption of materials and energy used during this stage of the technological process 101; - The parameters of the product obtained at the end of this step of the technological process 101.

[0142] In another embodiment of the method, in step 210, the data 102 are collected using sensors 115, preventing any compromise of the data during collection.

[0143] In another embodiment of the method, any compromise of the data 102 collected at step 210 via a sensor 115 is guaranteed to result in a change in the control data, regardless of the current state of the technological process step 101.

[0144] In another embodiment of the method, the sensor 115, used to collect the data 102 in step 210, adds information about its state to the collected data 102, thus influencing the result of the hashing of the collected data in step 220.

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153] In another implementation variant of the method, at least: - The data on the state of sensor 115 contains a static encryption key, used in the hashing procedure of the collected data 102; - During the operation of sensor 115, an encryption key is generated using a cryptographic hash function, then used to hash the collected data 102. In another variant of the method implementation, the data from the steps of the technological process 102 are collected sequentially, from the technological process step 101.1, which started earlier, to the technological process step 101.N, which started later. At step 220, the data collected at step 210 on the steps of technological process 101 are hashed using a hashing method 120. In one implementation variant of the method, by hashing the data 102 on a step of the technological process 101, a hash 121 is formed, which: - Identifies step 101 of the technological process, - While making it impossible to uniquely determine the data on which this 121 hash was formed. In another variant of the method implementation, the identification of the technological process step 101 consists of assigning a hash 121 with a collision level below a specified threshold, to data 102 concerning the technological process step 101 within a certain deviation range. In another variant of the implementation of the process, the hash function used to generate hash 121 includes at least: - a fuzzy hash function; - a homomorphic hash function. In another variant of the implementation of the process, the homomorphic hash function used includes at least: - Rabin's hash function; - the Pollard-Hellman hash function; - the El-Gamal hash function. In another variant of the implementation of the process, the hash 121 for the next step of process 101 is generated on the basis of the data 102 collected in step 210 concerning that step of process 101, as well as the hash 121 generated in step 220 for the previous step of process 101. In another variant of the implementation of the process, the hashes 121 generated in step 220 are successively recorded in a decentralized register of records 125 in such a way as to guarantee at least: - the execution time of the steps in process 101; - the execution sequence of the steps of process 101; - the absence of auxiliary steps in process 101 affecting the results of subsequent steps in process 101.

[0154] At step 230, the steps of process 101 are validated on the basis of the analysis of the hash 121 generated at step 220.

[0155] In another variant of the implementation of the process, the validation of the step of the process 101 is carried out on the basis of the analysis of the accuracy of the formation of the record in the decentralized register of records 125.

[0156] In another variant of the implementation of the process, the validation of step 101 of process is carried out on the basis of the analysis of the records of steps 101 of process added to the decentralized register of records 125, using a previously trained smart contract.

[0157] In another variant of the implementation of the method, the smart contract is formed on the basis of data concerning at least: - the operation of the sensors 115 collecting the data 102 on the steps of the process 101; - the hashing method of the collected data 102; - the operating parameters of the equipment used to perform the steps of process 101; - the parameters of the materials used at this stage of process 101; - the consumption of materials and energy used at this stage of process 101; - the parameters of the product obtained at the end of this step of process 101.

[0158] In another variant of the implementation of the process, process 100 is a decentralized autonomous organization.

[0159] In another variant of the implementation of the process, the validation of the step of process 101 is carried out on the basis of an analysis of the accuracy of the formation of the hash 121 of the next step of process 101, based on the hash 121 of the previous step of process 101.

[0160] In another embodiment of the process, the validation of step 101 of the process is considered negative if a violation is detected in at least: - the execution time of step 101 of process; - the execution sequence of the steps of process 101; - the hashing method 121 of the collected data 102; - the hash formation device 121; - the conformity of the record formed on the basis of the hash 121 in the decentralized register of records 125 with the previously formed smart contract.

[0161] In another variant of the implementation of the process, the validation of step 101 of the process is carried out: - directly, that is to say on the basis of the analysis of the hash 121 generated from the data 102 of this step of the process 101; - or indirectly, that is, on the basis of the analysis of the hash 121 generated from the data 102 concerning at least one other step of the process 101; - or by using both direct and indirect methods of validating the process step.

[0162] At step 240, process 100 is verified using process verification tool 140 based on the analysis of the validation results of the process steps 101 carried out in step 230.

[0163] In another embodiment of the process, verification of process 100 is carried out by comparing the final hash 121, obtained after the analysis of steps 101 of process 100 in step 230, with the hash 121 obtained in step 220 based on the data obtained in step 210 and describing at least: - the parameters of the materials used in process 100; - the consumption of materials and energy used in process 100; - the parameters of the product obtained at the end of process 100.

[0164] In another variant of the implementation of the process, the verification of process 100 is carried out by generating control hashes 121 at each step of process 101 and comparing them with the hashes 121 generated at step 220 on the basis of the data collected at step 210 concerning the steps of process 101.

[0165] In another variant of the implementation of the process, the verification of process 100 is considered negative if, at step 230, a negative validation of one of the steps of process 101 is detected.

[0166] [Fig.3] illustrates a finished product classification system. The system of Finished product classification includes process 100, which is composed of steps 101, process step validation tool 130, process verification tool 140, step comparison tool 310, product comparison tool 320, product classification tool 330, and product price determination tool 340.

[0167] The technological process 100, the means for validating the steps of the technological process 130 and the means for verifying the technological process 140 are described in more detail in [Fig.1] and [Fig.2].

[0168] In one of the system implementation variants, the product may be at least: - a chemical substance (including a mixture) as the final product of chemical production; - a biological medium as the final product of biological production.

[0169] In another implementation variant of the system, a technological roadmap describes the production steps during which the final product will conform to a predefined quality.

[0170] In another implementation variant of the system, during the validation process of a step in the technological process 101, at least the following are determined: - to what extent the technological process step 101 corresponds to the step described in the technological roadmap for the production of the product; - the quality of the product that will be produced if the execution of the steps of the technological process 100 continues.

[0171] In another variant of the system implementation, the quality of the product is determined by its conformity to at least one predefined criterion.

[0172] In another implementation variant of the system, a product quality criterion may be at least: - a range of numerical values, such that if a characteristic of the product is outside this range, the product is considered not to conform to the specified quality, and if it is within this range, the product is considered to conform to the specified quality; - a numerical value, any deviation from which indicates a deviation in the quality of the product; - an enumerative set of characteristics, such that if a characteristic of the product belongs to this set, the product is considered compliant, otherwise it is considered non-compliant.

[0173] In another implementation variant of the system, the product criteria include at least: - physical parameters of the product, such as mass, density, volume, etc.; - chemical parameters of the product, such as acidity, chemical composition, etc.

[0174] The step comparison tool 310 is designed to calculate a correspondence coefficient between a step validated using the technological process step validation tool 130 and a step described in the technological roadmap for the production of the product.

[0175] The step comparison tool 310 is designed to calculate a correspondence coefficient between a step validated using the technological process step validation tool 130 and a step described in the technological roadmap for the production of the product.

[0176] In one embodiment of the system, the conformity coefficient of the validated step with the step according to the product output technology map is a numerical value in a given range, or the minimum value characterizes the step of the technology process, the execution of which produces a result that does not meet any of the predetermined quality criteria of the product, and the maximum value characterizes the step of the technology process, the execution of which produces a result that meets all the predefined quality criteria.

[0177] The product comparison means 320 is designed to calculate a correspondence coefficient between the quality of a product manufactured according to the technological process 100 and the predefined quality.

[0178] In one implementation variant of the technological process verification system, at least the following are determined: - to what extent the technological process corresponds to the process described in the technological roadmap for the production of the product; - the quality of the product that was manufactured.

[0179] The product classification tool 330 is designed to classify a product manufactured according to the technological process 100 based on the quality correspondence coefficient calculated using the product comparison means 320.

[0180] In one implementation variant of the system, when classifying the manufactured product, it is assigned to at least one of the following categories: - product conforms to the specified quality; - product not conforming to the specified quality, but usable; - product does not conform to the specified quality and is unusable.

[0181] The price determination tool 340 is designed to determine, after classification by the product classification tool 330, at least: - the cost of the product; - the application area of ​​the product, this area being chosen from among the application characteristics associated with the required quality of the product in this area.

[0182] [Fig. 4] illustrates a method of classifying the manufactured product. The method of Product classification includes the following steps: step 230, during which the steps of the technological process are validated; step 240, during which the technological process is verified; step 410, during which the conformity coefficients of the technological process step are calculated. step 420, during which the product quality conformity coefficient is calculated, step 430, during which the product is classified according to its quality, step 440, during which the price of the product is determined.

[0183] In step 230, the validation tool for the steps of technological process 130 validates the steps of technological process 101 based on the analysis of a previously established technological roadmap for production. In step 240, the verification tool for technological process 140 verifies technological process 100 based on the validation results of the steps of technological process 101. These steps are detailed in [Fig. 1] and [Fig. 2].

[0184] In one of the implementation variants of the method, the product may be at least: - a chemical substance (including a mixture) as the final product of a chemical production; - a biological medium as the final product of a biological production.

[0185] In one of the implementation variants of the method, the technological roadmap describes the production steps, the execution of which ensures that the manufactured product meets a predefined quality.

[0186] In one of the implementation variants of the method, during the validation of a step in the technological process, at least the following are determined: - to what extent the process step corresponds to that described in the technology roadmap for the production of the product; - the quality of the product that will be manufactured if the execution of the steps in the technological process continues.

[0187] In one of the implementation variants of the method, the quality of the product is determined by its conformity to at least one predefined criterion.

[0188] In one of the implementation variants of the method, a product quality criterion may be at least: - a range of numerical values, such that if a characteristic of the product is outside this range, the product is considered non-compliant, and if it is within this range, it is considered compliant; - a numerical value, any deviation of which indicates a deviation in quality; - an enumerative set of characteristics, such that if a characteristic belongs to this set, the product conforms, otherwise it does not.

[0189] In one of the implementation variants of the method, the criteria include at least: - physical parameters of the product, such as mass, density, volume, etc.; - chemical parameters of the product, such as acidity, chemical composition, etc.

[0190] During step 410, the step comparison tool 310 calculates the conformity coefficient between a validated step 101 and the corresponding step in the technology roadmap.

[0191] In one of the implementation variants of the method, the conformity coefficient of the validated step with the step according to the product release roadmap is a numerical value in a given range: where the minimum value characterizes the step of the technological process, during which the released product will not meet any of the predetermined product quality criteria, and the maximum value characterizes the step of the technological process during which the released product will meet all the criteria of a predetermined product quality.

[0192] During step 420, if successful validation of the technological process 100 is achieved using the product comparison tool 320, the coefficient of conformity of the quality of the product manufactured using the specified technological process 100 with the previously declared quality is calculated.

[0193] In one of the implementation variants of the method, during the verification of the technological process, at least the following are determined: - to what extent the process corresponds to that described in the technology roadmap; - the quality of the manufactured product.

[0194] During step 430, the product classification tool 330 classifies the product manufactured according to the technological process 100, based on the product quality conformity coefficient specified with the previously declared quality.

[0195] In one of the embodiments of the process, when classifying a released product, the product is classified into at least one of the following categories: - product conforms to the specified quality; - product not conforming to the declared quality, but which is adaptable to a use; - Product is non-compliant and unusable.

[0196] During step 440, the pricing tool 340, after classifying the released product in step 430, determines at least: - the cost of the product; - the product's field of application, the latter being selected from the characteristics related to the quality required in that field.

[0197] [Fig.5] illustrates a computer system on which different variants of the systems and the methods described in this document can be implemented. The computer system 20 can be configured to implement the present invention and may be a single computing device or multiple computing devices, such as a desktop computer, a laptop computer, a server, a mainframe computer, an embedded device, and other forms of computing devices.

[0198] As illustrated in [Fig.5], the computer system 20 comprises: a central processor 21, a system memory 22 and a system bus 23 which links the various components of the system, including the memory associated with the central processor 21.

[0199] The system bus 23 is implemented in the form of any bus architecture known in the prior art, including in particular a bus memory or bus memory controller, a peripheral bus and a local bus, capable of interacting with any other bus architecture. Examples of buses include: PCI, ISA, PCI-Express, HyperTransport™, InfiniBand™, Serial ATA, I2C and other suitable connections between computer system components 20.

[0200] The central processor 21 contains one or more processors with one or more cores. The central processor 21 executes one or more sets of machine-readable instructions implementing the methods described in this document. The system memory 22 can be any type of memory used to store data and / or computer programs executed by the central processor 21. This system memory can include read-only memory (ROM) 24 as well as random-access memory (RAM) 25.

[0201] The basic input / output system (BIOS) 26 contains the fundamental procedures enabling the transfer of information between the elements of the computer system 20, in particular during the boot of the operating system from the ROM 24.

[0202] The computer system 20 includes one or more data storage devices, such as one or more removable storage devices 27, one or more non-removable storage devices 28, or a combination of removable and non-removable devices. One or more removable storage devices 27 and / or non-removable storage devices 28 are connected to the system bus 23 via an interface 32.

[0203] In one of the implementation variants, the removable storage devices 27 and the corresponding computer-readable storage media constitute non-volatile modules for storing computer instructions, data structures, software modules and other data of the computer system 20. The system memory 22, the removable storage devices 27 and the non-removable storage devices 28 can use various machine-readable information media.

[0204] Examples of machine-readable information storage media include: machine-type memories such as cache memory, SRAM, DRAM, Z-RAM (capacitorless), thyristor memory (T-RAM), eDRAM, EDO RAM, DDR RAM, EEPROM, NRAM, RRAM, SONOS, PRAM; flash memory or other memory technologies, such as SSDs or USB flash drives; magnetic cassettes, magnetic tapes and magnetic disks, such as hard drives or floppy disks; optical media, such as CD-ROMs or DVDs; and all other media that can be used to store the necessary data and accessed by the computer system 20.

[0205] The system memory 22, removable storage devices 27 and non-removable storage devices 28 present in the computer system 20 are used to store the operating system 35, applications 37, other software modules 38 and software data 39.

[0206] The computer system 20 includes a peripheral interface 46 for transmitting data from input devices 40, such as a keyboard, mouse, stylus, gamepad, voice input device, touch device or other peripherals, such as a printer or scanner, via one or more input / output ports, such as a serial port, parallel port, universal serial bus (USB) or other peripheral interface.

[0207] A display device 47, such as one or more integrated monitors, projectors, or screens, is also connected to the system bus 23 via an output interface 48, such as a video adapter. In addition to the display devices 47, the computer system 20 is equipped with other output devices (not shown in [Fig. 5]), such as loudspeakers and other audiovisual devices.

[0208] The computer system 20 can operate in a networked environment using a connection with one or more remote computers 49. The remote computer (or computers) 49 can be a personal computer or a server containing most or all of the components mentioned earlier in the description of the computer system 20 illustrated in [Fig.5].

[0209] The network environment may also include other devices, such as routers, network stations, or other network nodes. The computer system 20 may integrate one or more network interfaces 51 or network adapters to communicate with remote computers 49 via one or more networks, such as a local area network (LAN) 50, a wide area network (WAN), an intranet, or the Internet.

[0210] Examples of network interfaces 51 include Ethernet, Frame Relay, SONET interfaces, as well as wireless interfaces.

[0211] Variants of the present invention may constitute a system, a method or an information carrier, or a machine-readable information carrier.

[0212] A computer-readable storage medium is a tangible device that retains and stores software code in the form of machine-readable instructions or data structures accessible by the central processing unit 21 of the system Information technology 20. This machine-readable information medium can be electronic, magnetic, optical, electromagnetic, semiconductor, or a suitable combination of these technologies.

[0213] For example, such a machine-readable storage medium may include random access memory (RAM), read-only memory (ROM), EEPROM, read-only compact disc (CD-ROM), digital multipurpose disc (DVD), flash memory, hard disk drive, portable floppy disk, memory card, floppy disk or even a mechanically coded device, such as punched cards or embossed structures containing recorded instructions.

[0214] The system and method of the present invention can be described in terms of a tool. The term "tool", as used in this document, refers to a concrete device, component or set of components, made of hardware, for example using an application-specific integrated circuit (ASIC) or an FPGA, or in the form of a combination of hardware and software, for example using a microprocessor system and a set of machine-readable instructions to implement the functionality of the tool, which, when executed, transform the microprocessor system into a device for a specific purpose.

[0215] The tool can also be implemented as a combination of these two components, with some functions being performed exclusively by instruments, while other functions are implemented by a combination of instruments and software. In some embodiments, part or even all of the means can be implemented on the central processor 21 of the computer system 20. Therefore, each tool can be implemented in various suitable configurations and should not be limited to a specific embodiment presented in this document.

[0216] In conclusion, it should be noted that the information provided in the description is merely an example and does not limit the scope of the present invention as defined in the claims. It is obvious to a specialist in the field that, during the development of any practical implementation of the present invention, it will be necessary to make numerous decisions specific to the embodiment in order to achieve particular objectives, these objectives varying from case to case. It is understood that such development efforts may be complex and demanding, but that they nevertheless fall within the ordinary skills of those with common knowledge in this field, based on the present disclosure of the invention.

Claims

Demands

1. A method for validating a technological process, wherein said method is implemented on a computer device whose processor executes the following steps: a. Collect data on each step of the technological process; b. Chop the collected data; c. Validate the steps of the technological process based on the analysis of the generated hash; d. Verify the technological process based on the analysis of the results of the validation of the process steps.

2. A method according to claim 1, wherein at least the following are used as data on the technological process step: a. Operating parameters of the equipment used to perform the specified step of the technological process; b. Parameters of the materials used at the specified stage of the technological process; c. Consumption of materials and energy used at the specified stage of the technological process; d. Product parameters obtained at the end of the specified step of the technological process.

3. A method according to claim 1, wherein the data is collected using sensors that preclude data compromise at the data collection stage, wherein the compromise of the data collected using a sensor is guaranteed to lead to a modification of the control data that does not depend on the current state of the technological process stage, in particular because the sensor that collected this data adds data about its state to the collected data, which affects the result of the subsequent hashing of the collected data, with at least:

4.

5.

6. a. The sensor's state data contains a static encryption key used in the subsequent hashing procedure of the collected data; b. During sensor operation, an encryption key is generated using a cryptographic hash function, which is used in the subsequent hashing procedure of the collected data. A method according to claim 1, wherein, by hashing data on the technological process step, a hash is formed which: a. Identifies a technological process step, the identification of a technological process step consisting in the fact that the data on a technological process step with a given range of deviations correspond to a certain hash with a collision level not exceeding a given threshold value, and at least the following is used as a hash function to generate a hash: i. Fuzzy hash function, ii. Homomorphic hash function; b. But at the same time, it does not allow an unambiguous calculation of the data on the basis of which the specified hash was generated. A method according to claim 1, wherein the hash for the next step of the technological process is generated on the basis of the data collected concerning the specified step of the technological process and the hash generated for the previous step of the technological process. A method according to any one of claims 1 to 5, characterized in that the generated hashes are stored sequentially in a decentralized register of records so as to guarantee at least: a. Execution time of the technological steps of the process; b. Sequence of steps in the technological process; c. The absence of auxiliary steps in the technological process that affect the results of subsequent steps in the technological process; and the validation of a technological process step is performed on the basis of an analysis of the accuracy of the formation of a record in a decentralized registry, in particular on the basis of an analysis of records concerning the steps of a technological process entered in a decentralized registry of records, using a pre-generated smart contract, where a smart contract is formed on the basis of data on at least approximately: a. Operation of sensors that collect data on the stages of the technological process; b. Method for hashing the collected data; c. Operating parameters of the equipment used to carry out the steps of the technological process; d. Parameter ah and consumption of materials and energy used at the specified stages of the technological process; e. Product parameters obtained at the end of the specified steps of the technological process.

7. A method according to any one of claims 1 to 6, wherein the validation of a step in the technological process is considered negative if a violation is detected in at least: a. Execution time of a step in the technological process; b. Sequence of steps in the technological process; c. Method for generating a hash from the collected data; d. Device for generating the hash; e. Compliance of a decentralized ledger record generated on the basis of a hash with a pre-generated smart contract.

8.

9.

10. A method according to any one of the preceding claims, wherein the validation of the process step is carried out at least: a. Directly, that is, on the basis of the analysis of a hash generated from data on the specified stage of the technological process; b. Indirectly, that is, on the basis of the analysis of at least one hash generated from data concerning at least one other stage of the technological process; c. By using direct and indirect methods of validating the steps in the process. A method according to any one of the preceding claims, wherein the verification of the technological process is carried out by comparing the final hash obtained after analysis of all the steps of the technological process with a hash obtained from data describing at least: a. Parameters and consumption of materials and energy used in the process; b. Product parameters obtained at the end of the technological process. A method according to any one of the preceding claims, wherein the verification of the technological process is carried out by generating control hashes at each stage of the technological process and comparing them with hashes generated on the basis of data collected at the stages of the technological process, while the verification of the technological process is considered to be negative if it is negative for at least one of the stages of the technological process.

Images