Disclosure of Invention
The present disclosure is directed to an engineering contract management method, system, apparatus, and medium for solving the above-described problems.
The technical scheme of the disclosure is as follows:
an engineering contract management method, comprising the following steps:
acquiring engineering contracts, wherein the engineering contracts comprise project subcontestines, and in the engineering contracts and the project subcontestines, the engineering general calculation, the cost occurrence in the contract implementation process, the progress engineering quantity, the unit engineering and visa, the investment and fund payment are associated;
executing project acceptance and check according to nodes of the contract, and executing delivery check and quality check according to the contract by strictly taking the general calculation as a control reference;
Determining whether to correct the engineering contract according to the engineering stage check, and if so, re-acquiring the engineering contract; if not, continuing to execute the sub-project of the next stage, and finishing acceptance;
acquiring contract execution and assessment states, and establishing traceable contract execution evaluation;
and carrying out contract money payment by checking and accepting the contract completion.
As a further optimization scheme of the present disclosure, performing engineering acceptance and assessment by nodes under contract, performing delivery assessment under contract strictly with an approximate calculation as a control reference, specifically includes:
Decomposing and refining the project implementation plan to a month construction plan and/or a day construction plan according to actual needs; according to the actual delivery result of a construction unit, implementing tracking and checking of the completion condition of the whole design plan, including defining alarm days of each stage, defining project general calculation/budget items, and setting project demand date and image progress;
Collecting real-time data of a building construction plan, a construction process and a construction progress to form an electronic data report; the construction plan includes: construction management organization architecture, construction period, equipment, materials, personnel, acceptance, project responsible personnel and quality supervisor, wherein the construction management organization architecture comprises construction management, technical management, quality management and personnel management departments, and manages construction progress, technology, quality and personnel respectively; the construction period comprises the construction period of each project of the building engineering; the equipment, materials and personnel are attached with an inventory; the construction process comprises material preparation, construction flow, construction supervision and quality acceptance; the construction progress comprises a planning progress, an actual progress, an advanced or delayed time, a reason and a daily progress, a week progress and a month progress.
As a further optimization scheme of the present disclosure, collecting real-time data of a construction plan, a construction process, and a construction progress, forming an electronic data report specifically includes:
Configuring a movable communication device at a construction site, wherein the movable communication device is in communication connection with a central server of a construction management system through a communication network; the mobile communication equipment is provided with application program software which is used for receiving instructions of the construction management system to execute a daily Zhou Yuegong project plan and report the workload according to the actual construction process;
the construction site management personnel report the work load of the construction site day, week and month by using the application program software of the movable communication equipment, and the work load adopts the camera video, the construction photo and the milestone photo to report the work progress of the construction site;
Receiving a camera video, a construction photo and a milestone picture through a central server of a construction management system, comparing the image video with a project amount and a project milestone mark set by a project plan, and determining a daily workload completion state of a construction site; automatically generating a daily workload report according to the actual completion amount;
Pushing the week planning task and the month planning task to an application program through a central server system of the construction management system, and determining whether the work site finishes the week and month working amount according to the construction site camera video, the construction photo and the milestone picture contrast and the engineering quantity and the engineering milestone mark set by the engineering planning; and automatically generating a weekly and monthly workload report according to the actual completion amount.
As a further optimization scheme of the present disclosure, acquiring contract execution and assessment states, establishing traceable contract execution evaluation includes:
Acquiring contract execution and examination, wherein the examination content comprises the difference between the construction time and the designed construction time, the difference between man-machine material consumption and contract regulation, and the difference between budget and use expenditure; and determining the evaluation standard of the engineering according to whether the difference is within a specified range or whether the hyperbranched is within a limited range.
As a further optimization scheme of the present disclosure, performing engineering acceptance and assessment by deep learning specifically includes:
Acquiring image data of each construction stage from a database, wherein the image data is obtained by shooting from a miniature model of an engineering or the image data of the existing engineering, which is acquired through a network and has the same construction as the construction required by contract construction; the image data is processed in the same proportion, and a database corresponding to the proportion of the actual contract engineering is generated;
Extracting a predetermined amount of data with labels from the database, including image data, wherein the labels are used for identifying the real construction state corresponding to the image data; extracting features capable of reflecting the construction state of the data by extracting features of the data; selecting a corresponding deep learning model according to the characteristics and the targets of engineering data defined by the engineering contract; training the selected deep learning model by using the prepared data and features to obtain a minimized loss function, and training the deep learning model to learn the features and rules of the construction state from the data; after training, adjusting the deep learning model; testing the trained deep learning model, and evaluating the performance and effect of the deep learning model;
collecting image material samples aiming at construction images, photos and milestone pictures at each stage; preparing images and pictures for comparison and uploading at a construction site;
Classifying the construction stage images in the database, respectively performing calibration on the image materials, and marking each key construction mark in the images through different color frames or color marks; forming a sample by using a key construction mark of a color frame or a color mark as a positive sample for algorithm learning; the image without the key construction mark is a negative sample;
Extracting texture features, shape features and spatial relation features of the construction image by using a given algorithm, classifying and training the extracted feature information, and outputting to form a detection model capable of identifying various key construction marks;
autonomous feature learning is carried out based on the calibrated positive and negative samples, model feature parameters are optimized, correction and calibration are carried out according to detection results, the calibrated materials are retrained, and a high-availability analysis model is formed through continuous iteration;
And verifying an intelligent recognition model of the construction workload through field test, performing intelligent recognition on the construction progress, and performing intelligent recognition on the finished or delayed engineering workload.
As a further optimization scheme of the present disclosure, the deep learning model training adopts an improved SSD algorithm to perform target detection, predicts object regions on feature maps of different convolution layers, outputs discretized multi-scale, multi-scale default frame parallel coordinates, and predicts frame coordinate compensation of a series of candidate frames and confidence of each category by using a small convolution kernel; and (5) carrying out frame regression on each position on the whole image by using the local feature map of the multi-scale area.
As a further optimization of the present disclosure, the improved SSD algorithm includes: adopting multi-scale feature map detection, adding a convolution feature layer to the tail end of a truncated basic network, gradually reducing the size of the convolution feature layer to obtain predicted values of multiple scale detection, wherein a detected convolution model is different for each convolution feature layer; the improved SSD algorithm further includes: the convolution predictor of the detection: each added convolution feature layer or an existing convolution feature layer of the alternative underlying network may use a set of convolution filters to produce a fixed prediction set; the improved SSD algorithm, default boxes and aspect ratios, associates a set of default bounding boxes with each feature map unit of the top-level network, the default boxes convolving the feature maps such that the position of each box instance is fixed relative to its corresponding cell; in each feature mapping unit, predicting an offset from a default box shape in the cell, and a per class score for the instance in each box; in feature maps of different resolutions, different default box shapes are used in the plurality of feature maps.
An engineering contract management system comprising a business module, the business module comprising:
the contract input module is used for acquiring engineering contracts, including project subcontestines, taking the engineering contracts as trunks, and correlating the engineering general calculation, cost occurrence, progress engineering quantity, unit engineering, visa, investment and fund payment in the contract implementation process in the engineering contracts and the project subcontestines;
The acceptance checking module is used for executing engineering acceptance and checking according to nodes of the contract, and executing delivery checking and quality acceptance according to the contract by strictly taking the general calculation as a control standard;
The contract correction module is used for determining whether to correct the contract according to the project stage examination, and if yes, the project contract is acquired again; if not, continuing to execute the sub-project of the next stage, and finishing acceptance;
the evaluation module is used for acquiring contract execution and assessment states and establishing traceable contract execution evaluation;
and the payment module is used for carrying out contract money payment by checking and accepting the contract.
An electronic device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
A memory for storing a computer program;
And the processor is used for realizing the engineering contract management method when executing the program stored in the memory.
A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements an engineering contract management method.
The beneficial effects of the present disclosure are:
The method takes the contract as a tie, connects with the approximate calculation and the cost occurrence in the contract implementation process, and organically connects the progress engineering quantity, the unit engineering, the visa, the investment and the fund payment, thereby forming a strict comprehensive control system taking the approximate calculation as the total control, the contract delivery and the quality acceptance as the process control; decomposing and supervising the engineering contract by utilizing a large engineering integrated management system; the computer system is used for sharing information and raising information value, and providing high-value analysis and decision information for managers and decision makers.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings, wherein it is to be understood that the following detailed description is for the purpose of further illustrating the application only and is not to be construed as limiting the scope of the application, as various insubstantial modifications and adaptations of the application by those skilled in the art can be made in light of the foregoing disclosure.
As shown in fig. 1, an engineering contract management method includes the following steps:
acquiring engineering contracts, wherein the engineering contracts comprise project subcontestines, and in the engineering contracts and the project subcontestines, the engineering general calculation, the cost occurrence in the contract implementation process, the progress engineering quantity, the unit engineering and visa, the investment and fund payment are associated;
executing project acceptance and check according to nodes of the contract, and executing delivery check and quality check according to the contract by strictly taking the general calculation as a control reference;
Determining whether to correct the contract according to the project stage check, if so, re-acquiring the project contract; if not, continuing to execute the sub-project of the next stage, and finishing acceptance;
acquiring contract execution and assessment states, and establishing traceable contract execution evaluation;
and carrying out contract money payment by checking and accepting the contract completion.
In this embodiment, the method specifically includes:
Step 1, inputting engineering contracts, including project subcontract, and associating the engineering general calculation and cost occurrence in the contract implementation process, progress engineering quantity, unit engineering and visa, investment and fund payment in the engineering contracts and the project subcontract.
Contract entry: contract entry personnel: and the method is responsible for inputting basic information of contracts, grading definition of quotation and information of quotation. The general calculation hitching personnel: responsible for hooking of the contract offer single item (BOQ) overview code. Contract approver: after the contract information is input, the input content is checked again, and the contract is approved after the input content is confirmed without errors. After the contract is approved, subsequent operations such as contract change, contract payment and the like can be performed; material equipment hitching personnel: and for the contract requiring the hanging of the material codes, the equipment classification codes and the equipment list, after the contract is input or approved, hanging the material equipment. Budget hitching personnel: if the budget management subsystem is enabled, the financial department budget administrator needs to attach a budget code to the contract before the contract is approved; after contract approval, the attached budget code needs to be modified each year.
And (3) performing information input work such as basic contract information, quotation structure definition, quotation single price and the like on the service module, and completing approval confirmation. The entering of the basic information of the contract comprises the following steps: contract subcontractor, contract bidding coin, definition quotation structure, recording quotation price information, hanging materials/equipment and equipment total list; in the process of inputting the contract, the contract is connected with the general calculation, and the name list of the approver of the input personnel is set.
Step 2: executing project acceptance and check according to nodes of the contract, strictly taking the general calculation as a control reference, and executing delivery check and quality check according to the contract;
In order to better manage the design plan and progress, the project implementation plan is decomposed and refined to a month construction plan or even a day construction plan according to actual needs. And (5) tracking and checking the completion condition of the whole design plan according to the actual delivery result of the construction unit. Including defining alarm days for each stage; project overview/budget details are defined. Setting engineering demand date and image progress.
The business module is connected to the design and construction departments of the building engineering through the local area network, and collects real-time data of the building construction plan, the construction process and the construction progress to form an electronic data report. The construction plan includes: construction management organization architecture, construction period, equipment, materials, personnel, acceptance, project responsible personnel, quality supervisor and the like, wherein the construction management organization architecture comprises departments of construction management, technical management, quality management, personnel management and the like, and the construction progress, the technology, the quality, the personnel and the like are respectively managed. The construction period includes the construction period of each item of the building engineering. The equipment, materials, personnel are accompanied by an inventory. The construction process comprises material preparation, construction flow, construction supervision, quality inspection and acceptance and the like. The construction progress comprises a planning progress, an actual progress, an advanced or delayed time, a reason and a daily progress, a week progress and a month progress.
The method is operated on a large computer of an engineering management system, a business module is built in the computer to respectively execute each step of the management method and has the functions of machine learning and deep learning, the business module acquires a large number of data analysis reports of engineering actual contract management through a network, automatic project assessment problems and judgment thresholds of engineering risks are built through the machine learning and the deep learning, the management platform automatically issues early warning on possible risks, and intelligent adjustment and optimization are carried out on construction plans and construction progress, such as adjustment of construction period, change of construction procedures, standardization of operation flow and reinforcement of supervision and inspection.
And collecting real-time data of a building construction plan, a construction process and a construction progress to form an electronic data report. The method comprises the following steps:
Step 2.1, configuring movable communication equipment on a construction site, wherein the movable communication equipment is in communication connection with a central server of a construction management system through a communication network; the mobile communication equipment is provided with application program software which is used for receiving instructions of the construction management system to execute a daily Zhou Yuegong project plan and report the workload according to the actual construction process;
Step 2.2, the job site responsible person reports the work load of the construction site day, week and month by using the application program software of the movable communication equipment, and the work adopts a camera video, a construction photo and a milestone picture to report the work progress of the construction site;
Step 2.3, a central server of the construction management system receives the camera video, the construction photo and the milestone picture, compares the image video with the engineering quantity and the engineering milestone mark set by the engineering planning, and determines the daily workload completion state of the construction site; automatically generating a daily workload report according to the actual completion amount;
Step 2.4, the central server system of the construction management system also pushes the week planning task and the month planning task to the application program, and whether the work site finishes the week and month working amount is determined according to the construction site camera video, the construction photo and the milestone picture contrast and the engineering quantity and the engineering milestone mark set by the engineering planning; and automatically generating a weekly and monthly workload report according to the actual completion amount.
The business management module is connected and communicated with each engineering project responsible person through a local area network, and each engineering project responsible person reports the daily progress, the weekly progress and the monthly progress of the project. And the collected data is automatically generated into an electronic data report form by the service module. The electronic data report forms and the daily schedule, the weekly schedule and the monthly schedule report forms of the responsible persons of each engineering project can be displayed in real time at the terminal of the business module and the mobile client of the manager.
In order to monitor the construction process in real time, the camera equipment is allowed to be installed in the construction site, the service module collects real-time video data of the progress and the safety condition of the construction project, and the video data is loaded into the electronic data report as a part of data collection, so that the engineering progress can be known more intuitively. The business module integrates and analyzes the acquired electronic data to form an electronic data analysis report, wherein the electronic data analysis report comprises engineering progress, material use, quality supervision, fund status, reasons and problems of overdue engineering. If the project is not finished as expected or quality and safety problems exist, the anomalies and reasons in the construction plan, the construction process and the construction progress are analyzed and found, such as unqualified materials, nonstandard construction, illegal operation and the like.
The business module automatically evaluates the risk and the reason of the overdue project or the problem generated by the overdue project through machine learning the data analysis report, on the basis, the management platform automatically issues early warning for the possible risk and intelligently adjusts and optimizes the construction plan and the construction progress, such as adjusting the construction period, changing the construction procedure, standardizing the operation flow and enhancing the supervision and inspection.
In order to monitor the construction process in real time, the camera equipment is allowed to be installed in the construction site, the service module collects real-time video data of the progress and the safety condition of the construction project, the video data are converted into data of the progress of the project, and the data are loaded into the electronic data report as a part of data collection, so that the progress of the project can be known more intuitively. The business module integrates and analyzes the acquired electronic data to form an electronic data analysis report, wherein the electronic data analysis report comprises engineering progress, material use, quality supervision, fund status, reasons and problems of overdue engineering. If the project is not finished as expected or quality and safety problems exist, the anomalies and reasons in the construction plan, the construction process and the construction progress are analyzed and found, such as unqualified materials, nonstandard construction, illegal operation and the like.
The business module automatically evaluates the risk and the reason of the overdue project or the problem generated by the overdue project through machine learning the data analysis report, on the basis, the management platform automatically issues early warning for the possible risk and intelligently adjusts and optimizes the construction plan and the construction progress, such as adjusting the construction period, changing the construction procedure, standardizing the operation flow and enhancing the supervision and inspection.
Step 3: determining whether to correct the contract according to the project stage check, if yes, returning to the step 1, and if not, continuing to execute the sub-project of the next stage; and go to step 5;
Step 4: entering contract execution and assessment states, and establishing traceable contract execution evaluation; the engineering contract management method includes the steps of firstly inputting original data required by engineering, then carrying out data extraction, data conversion, data quality inspection and data loading on the original data, carrying out data analysis and storage on the loaded related data, establishing a relational database and a multidimensional database based on the analyzed and stored related data, carrying out classified integration on the relational database and the multidimensional database according to preset rules, and carrying out visual conversion on the classified integrated related data, so as to obtain various different engineering visual data. Through real-time acquisition and online automatic analysis of information data, foreground and background data linkage is realized, site construction conditions are clearly presented, error correction and dynamic adjustment of construction flow are timely carried out according to site actual conditions, and project propulsion is ensured to meet various requirements of contracts.
The examination includes: the difference between the construction time and the designed construction time, the difference between man-machine material consumption and contractual provision, the difference between budget and use expenditure. And determining the evaluation standard of the engineering according to whether the difference is within a specified range or whether the hyperbranched is within a limited range.
And the business module carries out engineering contract modification options under an engineering acceptance project, and the engineering acceptance project carries out acceptance according to the modified contract.
And the business module examines the construction task and transmits the examination result to the material comparison and engineering pattern in the database module.
Step 5: and the contract is completed through acceptance, and payment of contract money or remaining money is performed.
The construction site management based on deep learning further comprises the following steps:
Step S1, preparing a deep-learning material. The image data of each construction stage can be obtained by shooting a miniature model of the project or can be obtained by the network to obtain the image data of the existing project which has the same construction as the construction required by the contract construction; performing the same proportion processing on various image materials to generate an image database corresponding to the proportion scale of the actual contract engineering;
step S2, extracting a predetermined amount of data with labels from the database in step S1, wherein the labels are used for identifying the real construction state corresponding to the image data; extracting a feature capable of reflecting the construction state of each piece of data; selecting an appropriate deep learning model according to the characteristics and the targets of engineering data defined by engineering contracts; training the selected deep learning model by using the prepared data and features to obtain a minimized loss function, wherein the training model learns features and rules of a construction state from the data; after training, the model is adjusted; testing the trained model, and evaluating the performance and effect of the model;
Step S3, collecting video image sample data, and collecting image material samples aiming at construction images, photos and milestone pictures at each stage; preparing images and pictures for comparison and uploading at a construction site;
S4, classifying the construction stage images in the database by manpower, respectively performing calibration on the image materials, and marking each key construction mark in the images by different color frames or color marks; for example: the constructed platform surface or gate slot overflows the road;
Forming a sample by using a key construction mark of a color frame or a color mark as a positive sample for algorithm learning; the image without the key construction mark is a negative sample;
s5, extracting texture features, shape features and spatial relation features of the construction image by using a given algorithm, classifying and training the extracted feature information, and outputting to form a detection model capable of identifying various key construction marks;
S6, performing autonomous feature learning based on the calibrated positive and negative samples, optimizing model feature parameters, correcting and calibrating according to detection results, retraining calibrated materials, and forming a high-availability analysis model through continuous iteration;
And S7, evaluating the model, and intelligently identifying the construction progress by verifying an intelligent identification model of the construction workload through field test. And carrying out intelligent recognition on the finished or delayed engineering quantity.
The video image sample data of the construction progress is collected, and diversification of materials is required to be ensured; the more abundant the material scene of the video image of each type of construction progress, the higher the image quality, the clearer the construction site picture, the more favorable the learning of the algorithm, and the more capable of improving the accuracy of the identification; therefore, if the construction model is built by adopting a 3-dimensional modeling mode, the construction model should be close to an actual construction pattern as much as possible.
The step S6 model training adopts an improved SSD algorithm to detect targets, predicts object areas on feature maps of different convolution layers, outputs discretized multi-scale and multi-proportion default frame parallel coordinates, and simultaneously predicts frame coordinate compensation of a series of candidate frames and confidence of each category by utilizing a small convolution kernel; and (5) carrying out frame regression on each position on the whole image by using the local feature map of the multi-scale area.
The improved SSD algorithm adopts multi-scale feature map detection, a convolution feature layer is added to the tail end of a truncated basic network, the size of the convolution feature layer is gradually reduced, predicted values of multi-scale detection are obtained, and a detected convolution model is different for each convolution feature layer; the improved SSD algorithm, the detected convolution predictor: each added convolution feature layer or an existing convolution feature layer of the alternative underlying network may use a set of convolution filters to produce a fixed prediction set;
the improved SSD algorithm, default box and aspect ratio: associating a set of default bounding boxes with each feature map unit of the top-level network, the default boxes convolving the feature map such that the position of each box instance is fixed relative to its corresponding cell; in each feature mapping unit, an offset is predicted relative to the default box shape in the cell, and each class score for the instance in each box.
In the feature diagrams with different resolutions; using different default box shapes in the multiple feature maps, the possible output box shape space can be effectively discretized.
As shown in fig. 2, an embodiment of the present disclosure provides an engineering contract management system including:
the contract input module is used for acquiring engineering contracts, including project subcontestines, taking the engineering contracts as trunks, and correlating the engineering general calculation, cost occurrence, progress engineering quantity, unit engineering, visa, investment and fund payment in the contract implementation process in the engineering contracts and the project subcontestines;
The acceptance checking module is used for executing engineering acceptance and checking according to nodes of the contract, and executing delivery checking and quality acceptance according to the contract by strictly taking the general calculation as a control standard;
The contract correction module is used for determining whether to correct the contract according to the project stage examination, and if yes, the project contract is acquired again; if not, continuing to execute the sub-project of the next stage, and finishing acceptance;
the evaluation module is used for acquiring contract execution and assessment states and establishing traceable contract execution evaluation;
and the payment module is used for carrying out contract money payment by checking and accepting the contract.
The implementation process of the functions and roles of each module in the system is specifically shown in the implementation process of the corresponding steps in the method, and is not repeated here.
For system embodiments, reference is made to the description of method embodiments for the relevant points, since they essentially correspond to the method embodiments. The system embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the disclosed solution. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
In the above embodiment, any of the plurality of modules may be combined in one module to be implemented, or any of the plurality of modules may be split into a plurality of modules. Or at least some of the functionality of one or more of the modules may be combined with, and implemented in, at least some of the functionality of other modules. At least one of all of the modules may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or as hardware or firmware in any other reasonable manner of integrating or packaging the circuits, or as any one of or a suitable combination of three of software, hardware, and firmware. Or at least one of all of the modules may be at least partially implemented as computer program modules that, when executed, perform the corresponding functions.
Referring to fig. 3, an electronic device provided by an embodiment of the present disclosure includes a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, where the processor 1110, the communication interface 1120, and the memory 1130 perform communication with each other through the communication bus 1140;
a memory 1130 for storing a computer program;
The processor 1110 is configured to implement the following engineering contract management method when executing the program stored in the memory 1130.
The communication bus 1140 may be a peripheral component interconnect (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The communication bus 1140 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface 1120 is used for communication between the electronic device and other devices described above.
The memory 1130 may include random access memory (Random Access Memory, RAM) or non-volatile memory (nonvolatile memory), such as at least one disk memory. Optionally, the memory 1130 may also be at least one storage device located remotely from the processor 1110.
The processor 1110 may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), etc.; but may also be a digital signal processor (DIGITAL SIGNAL Processing, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components.
Embodiments of the present disclosure also provide a computer-readable storage medium. The computer-readable storage medium stores thereon a computer program which, when executed by a processor, implements the engineering contract management method as described above.
The computer-readable storage medium may be embodied in the apparatus/means described in the above embodiments; or may exist alone without being assembled into the apparatus/device. The above-described computer-readable storage medium carries one or more programs that, when executed, implement the engineering contract management method according to the embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The foregoing examples have expressed only a few embodiments of the present disclosure, which are described in more detail and detail, but are not to be construed as limiting the scope of the present disclosure. It should be noted that variations and modifications can be made by those skilled in the art without departing from the spirit of the disclosure, which are within the scope of the disclosure.