CN113298316A

CN113298316A - Intelligent manufacturing framework and method based on block chain, scheduling matching method and model

Info

Publication number: CN113298316A
Application number: CN202110648048.3A
Authority: CN
Inventors: 滕颖蕾; 宋梅; 于非; 王麟琨; 满毅; 张勇; 王小娟; 李蓝林; 郅佳琳; 曹雅丽; 赵杨柳
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2021-06-10
Filing date: 2021-06-10
Publication date: 2021-08-24

Abstract

The invention provides an intelligent manufacturing framework and method, a scheduling matching method and a model based on a block chain. The intelligent manufacturing architecture processes and makes trading decisions on product manufacturing service orders through the platform layer, manufacturing arrangement and control interaction with global benefits are achieved, service is provided for a service requester and a service provider through the application layer, service and control separation is achieved, information of the whole trading process is recorded on the block chain, differential manufacturing services can be responded safely and timely, information safety of the life cycle of the whole product is guaranteed, and efficient and transparent customization on demand is achieved. The scheduling matching method of the platform layer transaction decision is realized by determining scheduled task information and a service provider matched with the task information under the condition that the net profit of a service requester is maximized through a net profit model constructed by taking the net profit of the service requester as a target according to the block size, the time requirement, the reliability requirement and the price requirement.

Description

Intelligent manufacturing framework and method based on block chain, scheduling matching method and model

Technical Field

The invention relates to the technical field of intelligent manufacturing, in particular to an intelligent manufacturing framework based on a block chain, an intelligent manufacturing processing method based on the block chain, a scheduling matching method and a net profit model.

Background

In recent years, the next generation of smart manufacturing, such as industry 4.0, has come to the fore, which facilitates the implementation of flexible manufacturing, revolutionizing global industrial production. Industrial Internet of Things (IIOT) utilizes emerging Internet of Things (IOT) and 5G technologies to provide ubiquitous connectivity and control between physical devices. However, the term "intelligence" is not limited thereto, but it also emphasizes that enterprises create and use information throughout the Product Life Cycle (PLC) in order to achieve environmentally friendly, low cost flexible manufacturing that can quickly respond to changes in enterprise demand.

How to utilize IoT technology to acquire global manufacturing resources with short market lead time and high quality in order to cope with dynamic, increasingly-expanding personalized markets is one of the key issues for future industry development. In fact, due to the fact that raw materials and resources have distributed characteristics in a global range, timeliness and efficiency of traditional customized production are low, in order to solve the timeliness and efficiency problems, a Cloud-Based Manufacturing (CBM) mode for accessing a shared configurable Manufacturing resource pool on demand is provided, and management cost and interaction cost between service providers can be reduced to the maximum extent. However, CBM relies on a third-party trusted intermediary for user interaction, the CBM framework has limited storage capacity and poor scalability, and particularly with exponential growth of customized production, a centralized cloud cannot handle large-scale end-to-end interaction and communication, which hinders large-scale growth of IIOT.

Disclosure of Invention

The invention provides an intelligent manufacturing framework and method, a scheduling matching method and a model based on a block chain, which are used for overcoming the defects of a CBM mode in the prior art, can safely and timely respond to differentiated manufacturing services, ensure the information safety of the life cycle of the whole product and realize efficient and transparent customization as required.

In a first aspect, the present invention provides a blockchain-based intelligent manufacturing architecture, comprising:

the application layer provides an application program interface for information interaction between the service requester and the service provider;

the platform layer is used for maintaining and managing the information of the service requester and the service provider, processing and trading the product manufacturing service order and recording the information of the whole trading process of the product manufacturing service order to the blockchain;

the virtual resource layer abstracts physical resources into virtual resources and provides called resources for maintenance, management, processing, transaction and recording of the platform layer;

the transmission layer provides communication technology support for equipment communication and provides information transmission service for the virtual resource layer;

an infrastructure layer to provide the required infrastructure for completing the product manufacturing service order.

According to the intelligent manufacturing framework based on the block chain, the platform layer comprises:

the maintenance management module is used for maintaining and managing the information of the service requester, the information of the service provider and the information of the product manufacturing service order;

the order processing module is used for abstracting and decomposing the product manufacturing service order to obtain task information corresponding to the product manufacturing service order;

the order transaction module is used for scheduling and matching transaction of the obtained task information to obtain transaction information recorded on the blockchain;

and the transaction issuing module is used for connecting the blocks to the block chain through the generation blocks and recording the information of the whole process from the order generation to the product delivery of the product manufacturing service order to the block chain.

In a second aspect, the present invention further provides a blockchain-based intelligent manufacturing processing method applied to the blockchain-based intelligent manufacturing architecture of the first aspect, where the method includes:

receiving a product manufacturing service order submitted by a service requester;

processing the product manufacturing service order to obtain corresponding task information, and putting the task information into a trading pool to queue;

task scheduling and service provider matching are carried out on the task information queued in the transaction pool, transaction information is generated, and the transaction information is recorded on a block chain;

receiving a task acceptance statement which is determined by the service provider to accept the submission of the task according to the transaction information, and recording the task acceptance statement to a block chain;

receiving a task completion statement submitted by the service provider after the task is completed, and recording the task completion statement to a block chain;

receiving a task delivery statement submitted by the service requester after the service provider delivers the product on time and the service requester pays successfully, and recording the task delivery statement on a block chain.

According to the intelligent manufacturing processing method based on the block chain, provided by the invention, the product manufacturing service order is processed to obtain corresponding task information, and the task information is put into a transaction pool to be queued, and the method comprises the following steps:

abstracting the product manufacturing service order, and extracting the order type and the order requirement to obtain a task corresponding to the product manufacturing service order;

decomposing the tasks according to the preset logic of the obtained tasks to obtain a subtask set with a certain logic sequence, and putting the subtask set into a transaction pool to queue; and/or the presence of a gas in the gas,

task scheduling and service provider matching are carried out on the task information queued in the transaction pool, and transaction information is generated, wherein the task scheduling and service provider matching comprise the following steps:

according to the block size, the time requirement, the reliability requirement and the price requirement, aiming at maximizing the net profit of a service requester, task scheduling is carried out on the task information queued in the transaction pool, the task information for carrying out transaction is determined, and a service provider matched with the task information for carrying out transaction is determined according to the received information of the service provider;

and generating transaction information according to the determined task information for performing the transaction and the service provider matched with the task information for performing the transaction.

In a third aspect, the present invention further provides a scheduling matching method, including:

determining scheduled task information and a service provider matched with the task information under the condition that net profits of service requesters are maximized on the basis of a preset net profit model;

wherein the net profit model satisfies the following constraints: the amount of task information scheduled at each time is limited by the size of the block; the time of the service provider for completing the task meets the time requirement in the task information with a certain probability; each scheduled task information is distributed to at most one service provider, and each service provider is matched with at most one scheduled task information; the transaction unit price of the service provider and the reliability of the finished product meet the price requirement and the reliability requirement in the task information;

and generating transaction information according to the scheduled task information and the service provider matched with the task information, and recording the transaction information to the block chain.

According to the scheduling matching method provided by the invention, on the basis of a preset net profit model, under the condition that the net profit of a service requester is maximized, the scheduled task information and a service provider matched with the task information are determined, and the scheduling matching method comprises the following steps:

performing iteration based on a preset net profit model, and determining task information scheduled under the condition that the net profit of the service requester is maximized through a DQN algorithm; and

and determining the service provider matched with the task information under the condition that the net profit of the service requester is maximized through a KM algorithm so as to maximize the long-term net profit of the service requester.

In a fourth aspect, the present invention further provides a net profit model, which implements the scheduling matching method of the third aspect.

According to the net profit model provided by the present invention, the task information includes: the maximum unit price of the task, the time requirement for completing the task, the quantity requirement of the task, the reliability requirement of the task, the transaction fee required by the task uplink and the residence time of the task in the transaction pool which can be accepted by the service requester;

the information of the service provider includes: unit selling price of the service provider, manufacturing efficiency of the service provider and reliability of the service provider;

the time for completing the task comprises: the time when the task information waits for scheduling, the time when the task information generates a block, and the time when the product is actually manufactured.

In a fifth aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the intelligent block chain-based manufacturing processing method according to the second aspect or implements the steps of the scheduling matching method according to the third aspect when executing the program.

In a sixth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the blockchain-based intelligent manufacturing process method according to the second aspect or implements the steps of the schedule matching method according to the third aspect.

The invention provides an intelligent manufacturing framework and a method based on a block chain, a scheduling matching method and a model, wherein the intelligent manufacturing framework is divided into 5 layers from top to bottom, and the 5 layers are application layers in sequence to provide application program interfaces for information interaction between a service requester and a service provider; the platform layer is used for maintaining and managing the information of the service requester and the service provider, processing and trading the product manufacturing service order and recording the information of the whole trading process of the product manufacturing service order to the blockchain; the virtual resource layer abstracts physical resources into virtual resources and provides called resources for maintenance, management, processing, transaction and recording of the platform layer; the transmission layer provides communication technology support for equipment communication and provides information transmission service for the virtual resource layer; an infrastructure layer to provide the required infrastructure for completing the product manufacturing service order. Manufacturing resources and manufacturing capacity are integrated into virtual manufacturing service through a virtual resource layer, so that the delivery time of the service can be shortened, and the manufacturing efficiency and the resource availability can be greatly improved; through the platform layer, order processing and transaction decision making can be realized, manufacturing arrangement and control interaction with global benefits can be realized, and the control layer serving as the whole framework can meet personalized service requirements and realize system-level optimization, such as scalability, privacy, fairness and the like; the application layer provides services for customers and service providers, the service layer of the whole framework focuses on the transparentization of product production, and finally the framework of the embodiment of the invention realizes the separation of service and control. The framework can be applied to IIoT, all information transacted by a customer and a service provider is recorded on a block chain, so that the transaction information is transparent and unchangeable, the safety of the manufacturing data of the whole PLC is guaranteed, the product delivery and the manufacturing are transparent, more users are attracted to participate in the market, and meanwhile, the customer can directly access the production resources through a distributed account book, and the on-demand production is greatly shortened. Distributed and diversified manufacturing resources are shared by using the distrusted blockchain, and various customer services are responded by optimizing resource allocation, so that a flexible manufacturing process is realized.

Drawings

In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.

FIG. 1 is a schematic diagram of a block chain-based intelligent manufacturing architecture provided by the present invention;

FIG. 2 is a schematic flow chart of a blockchain-based intelligent manufacturing process provided by the present invention;

FIG. 3 is a schematic diagram of an application scenario of the intelligent blockchain-based manufacturing process provided by the present invention;

FIG. 4 is a timing diagram illustrating an application scenario of the intelligent blockchain-based manufacturing process of the present invention;

FIG. 5 is a flowchart illustrating a scheduling matching method according to the present invention;

fig. 6 is a schematic structural diagram of an electronic device provided in the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention is described below in connection with fig. 1-3.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a block chain based intelligent manufacturing architecture according to the present invention, and as shown in fig. 1, the block chain based intelligent manufacturing architecture at least includes:

and the application layer provides an application program interface for information interaction between the service requester and the service provider.

In embodiments of the present invention, service requestors may be considered customers, which may include individual customers, and business customers. The customer may register through the application programming interface and submit a product manufacturing service order through the application programming interface after registration. The type of the product manufacturing service order according to the embodiment of the present invention is not limited, and for example, the type of the product manufacturing service order may be a furniture manufacturing type, a medicine manufacturing type, a metal product manufacturing type, or the like. A service provider may be a participant who possesses certain production resources and has the necessary capabilities to service a customer, may be considered a service provider, and may include raw material suppliers, manufacturers, distributors, and retailers. Service providers may register through the application programming interface and periodically update manufacturing resources and service status through the application programming interface after registration. The application program interface may be an application program interface of a World Wide Web (WWW), which may enable direct interaction between a customer and a service provider. Raw material suppliers, manufacturers, distributors, retailers and customers are all stakeholders who together form an "intelligent" supply chain.

And the platform layer is used for maintaining and managing the information of the service requester and the service provider, processing and trading the product manufacturing service order and recording the information of the whole trading process of the product manufacturing service order to the block chain.

Optionally, the platform layer may include: the system comprises a maintenance management module, an order processing module, an order trading module and a trading publishing module. The maintenance management module can maintain and manage the information of the service requester, the information of the service provider and the information of the product manufacturing service order; the order processing module can abstract and decompose the product manufacturing service order to obtain task information corresponding to the product manufacturing service order; the order transaction module can schedule and match transactions on the obtained task information to obtain transaction information recorded on the blockchain; the transaction issuing module can connect the blocks to the block chain through the generation blocks, and record information of the whole process from the order generation to the product delivery of the product manufacturing service order to the block chain. By recording the information of the whole order transaction process to the blockchain, the risk of information tampering is avoided, the production state can be conveniently tracked by a client, and meanwhile, the privacy of the client and a service provider is protected to a certain extent by the anonymity of the blockchain.

Optionally, the product manufacturing Service order may be composed of customer requirements and detailed order description information, the order processing module performs abstraction processing on the product manufacturing Service order, and may extract an order type and an order requirement to obtain a task corresponding to the product manufacturing Service order, where the order type may be a furniture manufacturing type, a metal product manufacturing type, and the like, and the order requirement may be an order size, a product function, a Quality of Service (QoS) requirement, and the like. Since some tasks may include complex subtask logic, such as sequential logic, parallel logic, hybrid logic, etc., where the entire manufacturing service may not be performed by a single service provider, the subtasks may be submitted according to a predetermined logical grouping for ease of processing. The order processing module can decompose the tasks according to the preset logic of the tasks corresponding to the product manufacturing service orders to obtain a subtask set with a certain logic sequence, and the obtained subtask set is placed into a trading pool to be queued.

Alternatively, the order transaction module may generate the order at the decision time, shortly called decision time, based on block size, time requirements, reliability requirements, price requirements, targeting the maximization of net profit for the service requester, task scheduling is carried out on the task information queued in the transaction pool, the task information for carrying out transaction is determined, meanwhile, according to the received information of the service provider, the service provider matched with the task information for transaction is determined, and generates transaction information according to the determined task information for performing transaction and the service provider matched with the task information for performing transaction, so as to generate uplink of task information scheduling and matching results through the transaction information generation block, by defining the parameters of the manufacturing process according to the block size, a dynamic global market can be accommodated, enabling flexible, intelligent and configurable manufacturing.

And the virtual resource layer abstracts the physical resources into virtual resources and provides called resources for maintenance, management, processing, transaction and recording of the platform layer.

In the embodiment of the present invention, the physical resources may include computing resources, storage resources, device resources, raw material resources, and the like, and the virtual resource layer may abstract the physical resources of the bottom layer into a virtual resource pool by identifying the physical resources of the bottom layer, so that the upper layer can call the virtual resource pool conveniently.

And the transmission layer provides communication technology support for equipment communication and provides information transmission service for the virtual resource layer.

In the embodiment of the present invention, the transport layer may provide Communication Technology support for Communication between devices, for example, Communication between intelligent devices, for example, the Communication Technology may include Ethernet (Ethernet), Global Positioning System (GPS), Wireless local area network (WiFi), Object connection and embedded Unified Architecture (UA) for Process Control, Time Sensitive Network (TSN), Bluetooth (Bluetooth), Long Term Evolution (LTE) of universal Mobile telecommunications Technology, and 5th Generation Mobile Communication Technology (5G). Meanwhile, the transport layer may also provide a reliable information transfer service for an upper layer.

An infrastructure layer that provides the required infrastructure for completing the product manufacturing service order.

In embodiments of the present invention, the infrastructure layer may provide the required infrastructure for the entire PLC, which may include manufacturing resources and underlying equipment. Wherein the manufacturing resources may provide the necessary raw materials for production. The underlying equipment is used in the production of products and may include control equipment, sensors, actuators, manufacturing equipment, and the like.

The intelligent manufacturing framework based on the block chain is divided into 5 layers from top to bottom, the 5 layers are application layers in sequence, and application program interfaces are provided for information interaction between a service requester and a service provider; the platform layer is used for maintaining and managing the information of the service requester and the service provider, processing and trading the product manufacturing service order and recording the information of the whole trading process of the product manufacturing service order to the blockchain; the virtual resource layer abstracts physical resources into virtual resources and provides called resources for maintenance, management, processing, transaction and recording of the platform layer; the transmission layer provides communication technology support for equipment communication and provides information transmission service for the virtual resource layer; an infrastructure layer to provide the required infrastructure for completing the product manufacturing service order. Manufacturing resources and manufacturing capacity are integrated into virtual manufacturing service through a virtual resource layer, the delivery time of the service can be shortened, and the manufacturing efficiency and the resource availability can be greatly improved; through the platform layer, order processing and transaction decision making can be realized, manufacturing arrangement and control interaction with global benefits can be realized, and the control layer serving as the whole framework can meet personalized service requirements and realize system-level optimization, such as scalability, privacy, fairness and the like; the application layer provides services for customers and service providers, the service layer of the whole framework focuses on the transparentization of product production, and finally the framework of the embodiment of the invention realizes the separation of service and control. The framework can be applied to IIoT, all information transacted by a customer and a service provider is recorded on a block chain, so that the transaction information is transparent and unchangeable, the safety of the manufacturing data of the whole PLC is guaranteed, the product delivery and the manufacturing are transparent, more users are attracted to participate in the market, and meanwhile, the customer can directly access the production resources through a distributed account book, and the on-demand production is greatly shortened. Distributed and diversified manufacturing resources are shared by using the distrusted blockchain, and various customer services are responded by optimizing resource allocation, so that a flexible manufacturing process is realized.

Referring to fig. 2, fig. 2 is a schematic flow chart of a processing method for block chain based intelligent manufacturing according to the present invention, and the method shown in fig. 2 can be applied to the block chain based intelligent manufacturing architecture shown in fig. 1, which is a processing method based on block chain technology for a platform layer in the architecture, and as shown in fig. 2, the processing method for block chain based intelligent manufacturing at least includes:

s201, receiving a product manufacturing service order submitted by a service requester.

In some alternative embodiments, as shown in fig. 3, fig. 3 is a schematic diagram of an application scenario of the intelligent block-chain-based manufacturing processing method provided in the present invention, after receiving a product manufacturing service order submitted by a service requester, the application layer may place the received order into an order pool of the platform layer, and the platform layer may retrieve the product manufacturing service order from the order pool for processing.

S202, the product manufacturing service order is processed to obtain corresponding task information, and the task information is placed into a trading pool to be queued.

In some optional embodiments, as shown in fig. 3, the platform layer may perform abstraction processing on the product manufacturing service order picked from the order pool, extract an order type and an order requirement, and obtain a task corresponding to the product manufacturing service order; and then decomposing the tasks according to the preset logic of the obtained tasks to obtain a subtask set with a certain logic sequence, wherein the subtask set is used as task information and is put into a transaction pool to be queued.

And S203, performing task scheduling and service provider matching on the task information queued in the transaction pool, generating transaction information, and recording the transaction information to the block chain.

In some optional embodiments, as shown in fig. 3, the platform layer may perform task scheduling on the task information queued in the transaction pool to determine the task information for performing the transaction, and determine the service provider matching the task information for performing the transaction according to the block size, the time requirement, the reliability requirement, and the price requirement, with the goal of maximizing the net profit of the service requester; and finally, generating transaction information according to the determined task information for performing the transaction and the service provider matched with the task information for performing the transaction, and recording the transaction information to the blockchain to realize the recording of the task content, the scheduling and the matching result to the blockchain.

S204, the receiving service provider determines to receive a task acceptance statement submitted by the task according to the transaction information, and records the task acceptance statement to the block chain.

In some alternative embodiments, as shown in fig. 3, after the service provider obtains the scheduling and matching results from the blockchain, it may choose to accept or not accept the matching results, and record the task acceptance statement to the blockchain through the platform layer in the form of submitting the task acceptance statement to the application layer. Alternatively, the matched service provider may choose to independently complete the task, or may assign a subtask to the collaborative enterprise. Alternatively, to gain more profits, the service provider may prioritize tasks and redistribute subtasks in such a way that new tasks are published on the blockchain according to priority. All characteristics and manufacturing cycles of the service are recorded in a distributed manner on the block chain, so that the whole manufacturing process is monitorable and traceable.

S205, receiving a task completion statement submitted by the service provider after the task is completed, and recording the task completion statement to the block chain.

In some alternative embodiments, as shown in FIG. 3, when a service provider completes a manufacturing task normally by term, a task completion declaration may be submitted to the application layer and recorded onto the blockchain through the platform layer.

S206, receiving the task delivery statement submitted by the service requester after the service provider delivers the product on time and the service requester pays successfully, and recording the task delivery statement to the block chain.

In some alternative embodiments, as shown in FIG. 3, after the service provider delivers the product by deadline and the service requester successfully pays the fee, the service requester may submit a task delivery declaration to the application layer that includes the delivery result and record the task delivery declaration to the blockchain through the platform layer. After completing the entire manufacturing process, the service provider will update the status again, waiting for a match again.

As shown in fig. 4, fig. 4 is a timing diagram of an application scenario of the intelligent manufacturing processing method based on a block chain provided by the present invention, and as can be seen from fig. 4, the arrival of the task is random and time-varying, which also means that the current task volume may exceed the processing capacity of the block chain, and at the same time, the choice of the service provider may affect the timeliness, the transaction price and the reliability of the task, and further affect the profit of the client. Therefore, the invention also provides a net profit model and a scheduling matching method based on the net profit model, which aims at maximizing the benefits of customers, performs task scheduling and supply and demand matching and ensures the efficiency and the manufacturing efficiency of the block chain.

Referring to fig. 5, fig. 5 is a schematic flow chart of a scheduling matching method according to the present invention, and as shown in fig. 5, the scheduling matching method at least includes:

s501, based on a preset net profit model, under the condition that the net profit of a service requester is maximized, determining a service provider with matched scheduled task information and task information.

Wherein the net profit model satisfies the following constraints: the amount of task information scheduled at each time is limited by the size of the block; the time of the service provider for completing the task meets the time requirement in the task information with a certain probability; each scheduled task information is distributed to at most one service provider, and each service provider is matched with at most one scheduled task information; the transaction unit price of the service provider and the reliability of the finished product meet the price requirement and the reliability requirement in the task information.

And S502, generating transaction information according to the scheduled task information and the service provider matched with the task information, and recording the transaction information to the block chain.

In some optional embodiments, the determining may be performed iteratively based on a preset net profit model, and the task information scheduled in the case that the net profit of the service requester is maximized is determined through a Deep Q Network (Deep Q Network, DQN for short); and determining a service provider matched with the task information in the case that the net profit of the service requester is maximized through a Kuhn-Munkras (KM for short) algorithm so as to maximize the long-term net profit of the service requester.

The invention also provides a net profit model for realizing the scheduling matching method.

In some optional embodiments, the task information may include: the maximum unit price of the task, the time requirement for completing the task, the quantity requirement of the task, the reliability requirement of the task, the transaction fee required by the task uplink and the residence time of the task in the transaction pool which can be accepted by the service requester; the service provider's information may include: unit selling price of the service provider, manufacturing efficiency of the service provider and reliability of the service provider; the time to complete the task may include: the time when the task information waits for scheduling, the time when the task information generates a block, and the time when the product is actually manufactured.

The net profit model and the scheduling matching method based on the net profit model are explained in detail as follows:

manufacturing tasks and manufacturers, i.e. service providers, may be classified according to the manufacturing content, with all requested manufacturing tasks forming a transaction pool, where different types of subtask sets are queued in different queues waiting to be scheduled. Manufacturers are limited by their type of production and capacity and may not be able to accomplish a complex task by a single manufacturer. In the present invention, it can be assumed that there are enough manufacturers to distribute for one manufacturing task, each manufacturer can only undertake one task at each decision time of generating blocks, each manufacturing task only matches one manufacturer, and the manufacturer decides whether to perform sub-task distribution according to its own manufacturing capability. Based on reliability being the primary consideration, the present invention uses Proof Of Work (POW) as a consensus mechanism. And aiming at the uncontrollable task completion time, the combined design of block chain configuration and manufacturing optimization is carried out, so that the net profit of a client is maximized under the condition of meeting the QoS requirement. Through the joint design, task scheduling and matching decisions are made at the same time, and the block chain efficiency and the manufacturing efficiency can be ensured. Wherein the POW is determined by finding a correct random number nonce field such that the resulting hash value is not greater than the target difficulty value. Miners try many nonces from scratch to meet the difficult goals, which in fact is a course of chance, resulting in randomness in the block generation time.

(1) Description of tasks and manufacturers

Task: at decision time t, assuming that K tasks exist in the transaction pool, defining the task set as

Task k may use a quintuple

Is described, wherein

Representing the maximum unit price of task k that the customer can accept,

indicating the time requirement to complete task k,

indicating the requirements of the number of tasks k,

and

respectively representing the reliability requirement of task k and the transaction fee required for the uplink of task k. In addition, define

The residence time in the transaction pool until the current time is task k. Alternatively, different transaction fees may be set for different commercial values or privacy levels, etc., to better enable on-demand services.

The manufacturer: at decision time t, assuming there are M manufacturers, a set of manufacturers is defined as

For task k, the set of manufacturers that can service it is defined as

The invention uses

Denotes a manufacturer m capable of processing a task k, wherein

Respectively, the unit selling price of the manufacturer m, the manufacturing efficiency (the number of manufacturing tasks completed per unit time) of the manufacturer m, and the reliability of the manufacturer m.

(2) Client profit model

Profitability is the ultimate goal of a customer's participation in the market. Profits are affected by many factors, including production quantity, reliability, timeliness, and cost, etc., and the invention will be described separately below:

the task completion time is as follows: definition of T_kTo accomplish a task^kIs composed of three parts, including block chain latency

(stay time in transaction pool before task k is packed into tiles), blockchain service time

(actual generation time of the block containing task k) and actual manufacturing time

The formula for the task completion time is as follows:

in block chain using common identification mechanism of POW, block chain service time

Is random, which is caused by the randomness of the mineworker's search process for the random number nonce. Suppose that

Are independently and identically distributed (i.i.d.) and follow the following exponential distribution, which is expressed as follows:

G(x)＝1-e^-μx(formula 2)

Where μ is the average block generation rate.

Blockchain latency, which is the total sojourn time of task k in the trading pool, can be modeled using the Markov Decision Process (MDP), which is formulated as follows:

wherein ξ_kIndicating whether task k is selected to be uplinked. That is, when xi_kWhen 1, the transaction containing task k is selected and immediately packed into the current block for distribution. Conversely, when xi_kWhen 0, the transaction containing task k is still waiting in the wait queue for another block generation time T^gene，

Is practically equal to

The manufacturing time depends on both the number of products for the task and the manufacturing efficiency of the manufacturer. Definition of δ_k,mFor matching indices, the actual manufacturing time is calculated as follows:

wherein, delta _k,m1 indicates that task k matches manufacturer m.

The quantity and reliability of finished products are as follows: neglecting the dynamics of the internal and external environments of the enterprise, in the market for supply and demand, each manufacturing task can be successfully completed after being matched. Thus, task k corresponds to a finished product quantity equal to the quantity of the product originally demanded, i.e., the quantity of the finished product

The reliability of the finished product is determined by the selection of both supply and demand parties. In addition, the reliability of the blockchain and the reliability of the communication also have an influence on the final reliability, i.e. the actual reliability R of task k_kCan be expressed as the following equation:

wherein R is^bAnd R^cRespectively representing block chain reliability and communication reliability.

And (3) revenue model: considering the free market, the economic benefit of the customer who issues task k can be expressed as the following formula:

U(Y_k,R_k,T_k)＝R_kY_kpk(T_k) (formula 6)

Wherein, pk (T)_k) Is the pricing of task k in relation to the total time to complete task k.

When the demand curve is stable over time, neglecting the impact of unit cost and product durability on the basis of the pricing model proposed by Robert j_k) Can be expressed as the following equation:

where v is a price sensitive parameter of the demand curve,

is the base price of task k, α represents the impact of product type and market competition on the price-time relationship, t_kRepresenting the time interval, t, between the generation of a task k from its initial assumption and its submission onto the blockchain_k+T_kRepresents the Time To Market (TTM) of task k. Here, the number of the first and second electrodes,

describes the market competitiveness at the time of task k submission, and

indicating market competitiveness when task k is complete. T is_kThe larger the market competition, the lower the pricing required to compensate for the low market share.

The pricing pk (T) is well described_k) Free market characteristics that decline exponentially with increasing time to market.

For simplicity, β is used_kRepresents

Thus, the economic benefit of the customer who issued task k is rewritten as follows:

a cost model: the customer cost consists of two elements, the manufacturing cost (the fee paid to the manufacturer) and the transaction fee (the fee paid to the miners), respectively. Thus, the total cost to complete task k is expressed as the following equation:

wherein λ is the token exchange rate adopted by the blockchain.

By completing task k, the net profit that the customer can achieve is expressed by the following equation:

I_k＝U(Y_k,R_k,T_k)-c_k(formula 10)

Equation 10 characterizes the profitability of the customer with respect to task k. In addition, customer behavior on the manufacturing market can be well organized by reasonable manufacturing task scheduling, manufacturer selection, and controllable block size.

(3) Joint design for blockchain configuration and manufacturing optimization

The invention jointly optimizes the block size, task scheduling and supply-demand matching with the aim of maximizing the client net profit on the block chain.

In a blockchain-based intelligent manufacturing architecture, there is a clear conflict between limited transaction throughput and ever-increasing mass manufacturing. To improve the timeliness and efficiency of the system, two basic principles should be followed in selecting tasks.

First, the number of tasks selected from the transaction pool is limited by the block size, and is expressed by the following formula:

wherein S is_B、S_TAnd s_BRespectively representing block size, transaction size and storage space size reserved for other types of transactions。

Second, since production of manufacturing tasks is real-time, random, each task should be completed within a probabilistic time requirement. Different transaction fees may be set for the manufacture of each product, taking into account the different commercial value and specific requirements of each product. Definition of the invention

The total production time T of task k is the elastic coefficient of the time requirement_kThe probability constraint expressed by the following formula should be satisfied:

wherein epsilon_kRepresenting an arbitrarily small positive number, η_kThe higher the transaction fee is guaranteed, the more time is required.

To maximize the net profit for the customer while considering price and reliability constraints when matching the task with the manufacturer, the present invention designs an optimization problem

The formula is as follows:

wherein constraint C1 ensures that the number of tasks scheduled at a time is limited by the maximum blockchain throughput; c2 ensures that the completion time of task k meets the time requirement with a certain probability; constraints C3 and C4 respectively ensure that each selected task is assigned to at most one manufacturer, each manufacturer matching at most one selected task; constraints C5 and C6 respectively guarantee that the transaction unit price of task k and the reliability of finished products meet the price requirement and the reliability requirement.

It is seen that there are problems

With opportunity constraint C2, which is neitherIt is a convex optimization problem and not a deterministic planning problem. However, the block generation time T^geneAnd service time of a block containing task k

Although uncertain, they are independently co-distributed and all obey equation 2 of exponential Distribution, so the present invention can use the Cumulative Distribution Function (CDF) to convert the opportunistic constraint into a deterministic constraint. Definition of

Due to variable xi_kBecause the probability density function (pdf) of Z cannot be directly deduced, the invention is based on xi_k0 and xi_kThe final C2 can be converted to the following equation, derived separately for 1:

although the original problem becomes a deterministic one, two difficulties remain. First, the actual completion time of a task is related not only to the task schedule, but also to the matching between the task and the manufacturer, and the current task schedule affects the supply and demand matching at the current time, which in turn affects the task schedule at the next time, i.e. the schedule and matching variables of the task are coupled. Second, task scheduling and supply-demand matching not only determine the current output, but also affect the state at the next time, i.e., the scheduling and matching of tasks is time-dependent. In addition, problems arise

Is a mixed integer programming problem. In the invention, considering the high-dimensional perception input brought by the dynamic property of the environment, the DQN algorithm is firstly considered for solving, because the method based on DQN avoids the above difficulties. However, when all variables are solved using DQN, due to the huge motion space S × 2^K*2^(KM)(S represents a block size S_BThe number of selectable values) makes the algorithm very complex. In fact, the Markov block chain latency is only equal to ξ_kRelated to, and_k,mis a typical optimal binary matching problem depending on the set of tasks and manufacturers, so the invention will be δ_k,mSeparate from the time-related problem, a two-stage decision framework is proposed: in the first stage, a typical DQN method is used to solve the selection of block size and manufacturing task, and in the second stage, a popular algorithm for solving weighted maximum matching of bipartite graphs, namely KM algorithm, is used to solve the optimal matching problem between task and manufacturer.

(4) Optimal binary matching based DQN performance optimization framework

The DQN performance optimization algorithm based on optimal binary matching is divided into two stages, the invention firstly expounds the state space, the action space and the reward function in the DQN algorithm in the first stage, then proposes the KM algorithm to solve the supply and demand matching problem in the second stage, and finally reconstructs the original problem.

A. The first stage is as follows: joint optimization of task scheduling and block size

In the first stage, initialization is performed with feasible matches satisfying C2-C6, and block sizes S satisfying C1 and C2 are determined by DQN algorithm_BAnd task selection index xi_kThe value of (c).

State space: the invention uses the state x of task k_kThe residence time of task k in the transaction pool until the current time

And the status of manufacturer m bearing task k

To indicate the state of decision time t, (t ═ 1,2, …)

The formula is as follows:

state space: in order to maximize the net profit of the customer while effectively coping with dynamic transaction volumes, several parameters of the blockchain and task scheduling need to be adjusted to accommodate the dynamic environment, including the block size S_BAnd task selection index xi_kAnd the matching index delta_k,mIt can be found by the KM algorithm in the second stage, so the action at decision time t is expressed as the following equation:

the reward function: the reward function is defined as the instant profit at each moment under the block size, time requirements of the task and matching constraints. Formally, the reward function at decision time t is expressed as follows:

among them, the constraints C1-C6 are the key to ensure that the selected action is valid. To avoid an invalid situation, the reward for not satisfying the constraint is set to zero.

B. And a second stage: optimal binary matching

In the second phase, the scheduling between the selected task and the available manufacturers is typically the best binary match. Define bipartite graph G (V, E), where V can be divided into two independent sets

And

namely, it is

Wherein

And

respectively representing a selected set of tasks and a set of available manufacturers. To pair

e_k,mE.g. E. Definition of

As a set of weights, edge e_k,mWeight w of_k,mThe net profit that the customer receives when task k is assigned to manufacturer m is expressed by the following formula:

the invention takes the bipartite graph G (V, E) and the weight W as input, and uses the KM algorithm to solve the maximum weight matching, so as to obtain the maximum weight matching G ' (V ', E ') and the matching index delta of G (V, E)_k,m. By task selection index xi_kMatching index delta_k,mAnd equation 17, the value of the reward function can be obtained, which is equal to the sum of the weights of the maximum weight match G ' (V ', E '), i.e.

C. Problem reconstruction and algorithm implementation

The objective function is defined to maximize the long term customer net profit, with future rewards discounted by a discount factor γ ∈ (0, 1), i.e. a decision is made at each decision time to solve the problem of the following formula:

the DQN performance optimization framework based on optimal binary matching is described in detail in algorithm 1 below. By means of a two-stage DQN performance optimization framework,the motion space of DQN is reduced to S.multidot.2^KAnd the complexity of action search is greatly reduced.

According to the net profit model and the scheduling matching method based on the net profit model, the QoS requirement and the dynamic task quantity of a manufacturing task are considered, the time constraint, the reliability and the price constraint of the task and the block size constraint are modeled, the joint optimization of block size, task scheduling and supply and demand matching is performed by taking the benefit of a client as a target, the key problems of efficiency and delay in the real-time block chain manufacturing process are solved, the preference of a rational entity on economic benefit is coordinated, and the whole PLC is promoted; by the optimal binary matching-based DQN performance optimization framework, the maximization problem is solved, the time complexity is reduced, and meanwhile the convergence is improved.

Fig. 6 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 6: a processor (processor)610, a communication Interface (Communications Interface)620, a memory (memory)630 and a communication bus 640, wherein the processor 610, the communication Interface 620 and the memory 630 communicate with each other via the communication bus 640. The processor 610 may invoke logic instructions in the memory 630 to perform a blockchain-based smart manufacturing process method comprising:

Or, executing a scheduling matching method, the method comprising:

In addition, the logic instructions in the memory 630 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

In another aspect, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer being capable of executing the intelligent blockchain-based manufacturing processing method provided by the above methods, the method including:

Or, the scheduling matching method provided by the above methods is executed, and the method includes:

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to execute the method for block-chain-based smart manufacturing processing provided by the above methods, the method comprising:

The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.

Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. An intelligent blockchain-based manufacturing architecture, comprising:

2. The blockchain-based smart manufacturing architecture of claim 1, wherein the platform tier comprises:

3. A blockchain-based smart manufacturing processing method applied to the blockchain-based smart manufacturing architecture of claim 1 or 2, the method comprising:

4. The intelligent blockchain-based manufacturing process method according to claim 3, wherein processing the product manufacturing service order to obtain corresponding task information, and queuing the task information in a transaction pool comprises:

5. A method for scheduling matching, comprising:

6. The schedule matching method according to claim 5, wherein determining the scheduled task information and the service provider matched with the task information in case of maximizing net profit of the service requester based on a preset net profit model comprises:

7. A net profit model implementing the schedule matching method of claim 5 or 6.

8. The net profit model of claim 7, wherein the mission information includes: the maximum unit price of the task, the time requirement for completing the task, the quantity requirement of the task, the reliability requirement of the task, the transaction fee required by the task uplink and the residence time of the task in the transaction pool which can be accepted by the service requester;

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the intelligent blockchain-based manufacturing process method of claim 1 or 4 or implements the steps of the schedule matching method of claim 5 or 6.

10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the blockchain based intelligent manufacturing process method of claim 1 or 4 or implements the steps of the schedule matching method of claim 5 or 6.