A project management method, system, electronic device and storage medium

Abstract

A project management method, system, electronic device and storage medium, relate to the field of project management. In the method, engineering projects of the same nature are grouped together to form a plurality of project groups, and an access level is set for each project group; information data of the construction site of each engineering project is obtained, the information data including engineering material consumption, labor distribution and equipment operating condition, potential risk factors in project progress and potential cost growth factors are determined according to the information data; a time planning adjustment scheme and a cost planning adjustment scheme are generated according to the potential risk factors and the potential cost growth factors of all engineering projects in the target project group; the time planning adjustment scheme and the cost planning adjustment scheme are sent to the target administrator according to the access level of the target project group. The technical scheme provided by the application improves the scientificity and accuracy of project management and decision-making, and reduces the possibility of potential risks and cost overruns.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of project management, in particular to a management method and system for engineering projects, an electronic device and a storage medium. BACKGROUND

[0002] With the acceleration of urbanization, engineering projects are becoming increasingly complex, and the demand for project management and monitoring is becoming more urgent. Effective project management not only ensures that the project is completed on time, but also effectively controls costs and improves project quality. However, in actual operation, due to factors such as large project size and numerous participants, project management faces many challenges, and how to scientifically and reasonably schedule projects and allocate resources becomes a problem to be solved.

[0003] Currently, in response to the problems existing in engineering project management, the industry generally takes some conventional measures to deal with them. For example, by regularly convening project coordination meetings to summarize information from all parties and promptly identify and solve problems, implementing a site inspection system to keep abreast of the situation at the construction site in order to respond quickly to unexpected situations. Although the above methods have improved the effectiveness of project management to some extent, there are still some shortcomings. In particular, when faced with large-scale and variable engineering projects, the existing management methods are difficult to cover all details comprehensively, resulting in potential risk factors and cost growth factors that cannot be identified and addressed in a timely manner. This not only affects the smooth progress of the project, but also increases unnecessary cost expenditure and reduces overall efficiency.

[0004] Therefore, a more systematic management method is needed that can accurately identify and effectively address these potential problems at an early stage, thereby improving the overall level of project management. SUMMARY

[0005] The present application provides a management method and system for engineering projects, an electronic device and a storage medium, which improves the scientificity and accuracy of project management and decision-making, and reduces the possibility of potential risks and cost overruns.

[0006] In a first aspect of the present application, a management method for engineering projects is provided, applied to an engineering project management platform, the method comprising:

[0007] Grouping engineering projects of the same nature together to form a plurality of project groups, and setting an access level for each project group;

[0008] Obtaining information data of the construction site of each engineering project, the information data including engineering material consumption, labor distribution and equipment operating conditions, determining potential risk factors and potential cost growth factors in project progress according to the information data;

[0009] generate a time schedule adjustment scheme and a cost schedule adjustment scheme according to potential risk factors and potential cost growth factors of all engineering projects in the target project group;

[0010] send the time schedule adjustment scheme and the cost schedule adjustment scheme to a target administrator according to an access level of the target project group.

[0011] Optionally, the determining the potential risk factors and the potential cost growth factors in the project progress according to the information data comprises:

[0012] obtaining cost data and influence data from the information data, the cost data comprising material procurement cost, labor cost, equipment rental cost and subcontractor cost, and the influence data comprising project progress data, quality data and change request data;

[0013] processing the cost data and the influence data to extract cost growth features, the cost growth features comprising material usage rate, labor utilization rate and equipment usage rate;

[0014] reducing dimensions of the cost growth features to obtain principal component features, and inputting the principal component features into a preset unsupervised learning model to obtain the potential cost growth factors.

[0015] Optionally, the determining the potential risk factors and the potential cost growth factors in the project progress according to the information data comprises:

[0016] performing time series analysis on the project progress data to identify progress delay patterns;

[0017] determining quality problems according to the quality data, and determining change frequency according to the change request data;

[0018] inputting the cost growth features, the progress delay patterns, the quality problems and the change frequency into a preset project progress risk prediction model to obtain the potential risk factors.

[0019] Optionally, the generating the time schedule adjustment scheme and the cost schedule adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in the target project group comprises:

[0020] determining priorities of the potential risk factors according to severities and occurrence probabilities of the potential risk factors;

[0021] determining growth amplitude and growth proportion of total project cost according to the potential cost growth factors, and determining influence degrees of the potential cost growth factors according to the growth amplitude and the growth proportion;

[0022] determining an order of generating adjustment schemes according to the priority of the potential risk factors and the influence degree of the potential cost increasing factors;

[0023] generating time schedule adjustment schemes and cost schedule adjustment schemes for all engineering projects in the target project group according to the order.

[0024] Optionally, the determining the priority of the potential risk factors according to the severity and the possibility of occurrence of the potential risk factors comprises:

[0025] assigning a severity score and a possibility score to each potential risk factor, the severity score and the possibility score being based on preset scoring criteria;

[0026] calculating a risk priority index of each potential risk factor according to the severity score and the possibility score;

[0027] ranking all potential risk factors according to the risk priority index to determine the priority of each potential risk factor.

[0028] Optionally, the determining the increasing amplitude and the increasing proportion of the total project cost according to the potential cost increasing factor and determining the influence degree of the potential cost increasing factor according to the increasing amplitude and the increasing proportion comprises:

[0029] predicting an expected increasing contribution of the potential cost increasing factor to the total project cost according to historical data and current trends of the potential cost increasing factor;

[0030] determining the increasing amplitude of the total project cost according to the expected increasing contribution and determining the increasing proportion of the total project cost according to a ratio of the increasing amplitude to the initial budget cost;

[0031] weighting and summing the increasing amplitude and the increasing proportion to obtain an influence factor, and determining the influence degree of the potential cost increasing factor according to the influence factor.

[0032] Optionally, the generating time schedule adjustment schemes and cost schedule adjustment schemes according to potential risk factors and potential cost increasing factors of all engineering projects in the target project group comprises:

[0033] re-evaluating a duration of a critical path according to the potential risk factors, the critical path being a longest sequence of tasks among remaining work of the engineering project;

[0034] analyzing tasks on the critical path, identifying a first target task capable of being executed in parallel, and rearranging a construction sequence of the critical path according to the first target task to reduce the duration;

[0035] evaluate utilization efficiency of existing resources, identify a second target task with utilization efficiency lower than a threshold, and increase resource input for the second target task to reduce the duration.

[0036] In a second aspect of the present application, a management system of an engineering project is provided, comprising an induction module, an analysis module, an adjustment module, and a display module, wherein:

[0037] The induction module is configured to induce engineering projects with similar properties together to form a plurality of project groups, and set an access level for each project group.

[0038] The analysis module is configured to obtain information data of a construction site of each engineering project, the information data comprising engineering material consumption, labor distribution, and equipment operating status, determine potential risk factors and potential cost growth factors in project progress according to the information data.

[0039] The adjustment module is configured to generate a time planning adjustment scheme and a cost planning adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in a target project group.

[0040] The display module is configured to send the time planning adjustment scheme and the cost planning adjustment scheme to a target administrator according to the access level of the target project group.

[0041] In a third aspect of the present application, an electronic device is provided, comprising a processor, a memory, a user interface, and a network interface, the memory is configured to store instructions, the user interface and the network interface are configured to communicate with other devices, and the processor is configured to execute the instructions stored in the memory to enable the electronic device to perform the method according to any one of the preceding aspects.

[0042] In a fourth aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium stores instructions, when the instructions are executed, the method according to any one of the preceding aspects is performed.

[0043] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0044] 1. Grouping similar engineering projects into multiple project clusters enables centralized management and unified coordination of multiple projects. Compared to traditional single-project management models, this allows for more efficient resource allocation and information sharing, reducing repetitive management work and communication costs. The engineering project management platform automatically acquires information and data from the construction site and generates time and cost planning adjustment schemes based on this data, reducing the time spent on manual analysis and decision-making and improving the timeliness and accuracy of management decisions. Managers no longer need to spend a lot of time manually collecting and analyzing data; instead, they can quickly obtain key information through the platform's automation functions, promptly identify problems, and take measures, making project management more efficient and agile.

[0045] 2. By identifying potential risk factors and cost growth factors in the project schedule based on information and data from the construction site, the project team can proactively identify risk points that may affect project schedule and cost. This early warning mechanism provides the project team with valuable response time, helping to take preventative measures or develop response strategies, reducing the probability and severity of risks. Further analysis of the expected contribution of potential cost growth factors to the total project cost, as well as the severity and likelihood of occurrence of potential risk factors, allows for precise identification of the source and key influencing factors of risks. The project team can then focus on monitoring and managing high-risk factors, concentrating resources on solving the most critical issues, rather than blindly addressing all potential risks, thus improving the accuracy and effectiveness of risk management.

[0046] 3. Based on historical data and current trends of potential cost growth factors, the project team can predict their expected contribution to the total project cost, enabling them to anticipate cost changes and adjust cost planning accordingly. By calculating the growth rate and percentage of the total project cost, and by weighting and summing these factors to obtain the influencing factors, the project team can conduct cost-benefit analyses of different cost control measures and select the optimal solution. This helps to minimize costs and improve the project's economic efficiency while ensuring project quality.

[0047] 4. Re-evaluate the duration of the critical path according to potential risk factors, and identify tasks that can be performed in parallel by analyzing the tasks on the critical path, rearrange the construction sequence, and evaluate the utilization efficiency of existing resources, increase resource input, so as to effectively shorten the length of the critical path. This helps to speed up the project progress, reduce the risk of overall project delay caused by the delay of key tasks, and ensure that the project can be delivered on time or ahead of schedule; regularly track and evaluate the implementation of the time planning adjustment scheme, dynamically adjust according to the actual progress and new risk factors, so that the project progress management has stronger flexibility and adaptability. The project team can adjust the work plan and resource allocation in a timely manner according to the actual situation, continuously optimize the project progress, and better cope with various uncertainties and changes in the project implementation process. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a flowchart of the management method of the engineering project disclosed in the embodiments of the present application;

[0049] Figure 2 is a module schematic diagram of the engineering project management system disclosed in the embodiments of the present application;

[0050] Figure 3 is a structural schematic diagram of an electronic device disclosed in the embodiments of the present application.

[0051] Mark explanation: 201, induction module; 202, analysis module; 203, adjustment module; 204, display module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0052] In order for those skilled in the art to better understand the technical solutions in the specification, the technical solutions in the embodiments of the specification will be described clearly and completely in conjunction with the drawings in the embodiments of the specification. Obviously, the described embodiments are only some of the embodiments of the present application, not all.

[0053] In the description of the embodiments of the present application, the words such as "for example" or "for instance" are used to represent examples, illustrations or descriptions. Any embodiment or design scheme described as "for example" or "for instance" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concept in a specific way.

[0054] In the description of the embodiments of the present application, the term "a plurality of" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first", "second", etc. are used only for the purpose of description and should not be understood as indicating or implying relative importance or implicitly indicating the technical features indicated. Therefore, the features defined with "first", "second", etc. can explicitly or implicitly include one or more of the features. The terms "include", "contain", "have" and their variants mean "include but are not limited to", unless otherwise specifically emphasized.

[0055] The embodiment discloses a management method of an engineering project, applied to an engineering project management platform, Figure 1 is a flowchart of the management method of the engineering project disclosed by the embodiment of the present application, as Figure 1 shown, the method comprises the following steps:

[0056] S101, engineering projects of the same nature are grouped together to form a plurality of project groups, and an access level is set for each project group;

[0057] S102, information data of the construction site of each engineering project is obtained, the information data includes engineering material consumption, labor distribution and equipment operating condition, and potential risk factors and potential cost growth factors in project progress are determined according to the information data;

[0058] S103, a time planning adjustment scheme and a cost planning adjustment scheme are generated according to the potential risk factors and the potential cost growth factors of all engineering projects in the target project group;

[0059] S104, the time planning adjustment scheme and the cost planning adjustment scheme are sent to the target administrator according to the access level of the target project group.

[0060] Engineering projects with similar properties are grouped together to form a plurality of project groups. These project groups can be classified based on project type (such as infrastructure construction, real estate development, technology research and development, etc.), project size, industry characteristics or other relevant criteria. For example, all infrastructure construction projects can be grouped into one group, and all real estate development projects can be grouped into another group. Different access levels are set for each project group to ensure that managers of different levels can access information at corresponding levels. Access levels can be divided into multiple levels, for example:

[0061] Owner: the highest level, can access detailed information and summary data of all project groups, make macro decisions and resource allocation.

[0062] Maintainer: Mid-level access to detailed information of specific project groups, manages and coordinates projects.

[0063] Developer: Lower-level access to detailed information of specific projects they are responsible for, handles daily management and execution.

[0064] Obtain information data of each construction site from the project management platform, including but not limited to:

[0065] Engineering material consumption: material procurement cost, material usage, material inventory, etc.

[0066] Labor allocation: labor cost, actual working hours, planned working hours, labor utilization rate, etc.

[0067] Equipment operating status: equipment rental cost, actual equipment operating time, total available equipment time, equipment utilization rate, etc.

[0068] Other influencing data: project progress data, quality data, change request data, etc.

[0069] Perform time series analysis on project schedule data to identify patterns and trends of schedule delays. For example, smooth the schedule data using moving average or exponential smoothing methods to detect outliers and trend changes in the data. Determine quality issues in the project based on quality data. For example, assess the impact of quality issues on project schedule using statistical analysis methods such as ANOVA or correlation analysis. Determine the frequency of change requests based on change request data. For example, assess the impact of changes on project schedule and cost by analyzing the number and type of change requests. Process cost data and impact data to extract cost growth characteristics such as material usage, labor utilization, and equipment usage. Use techniques such as principal component analysis to reduce high-dimensional data to lower dimensions to obtain principal component features, reducing the complexity of the data while retaining the main variation information. Input the principal component features into a pre-set unsupervised learning model (such as K-means clustering algorithm or Gaussian Mixture Model GMM) to train the model and identify patterns and anomalies in the data, discovering potential cost growth factors. Generate time planning adjustment schemes and cost planning adjustment schemes based on potential risk factors and potential cost growth factors of all engineering projects in the target project group. According to the access level of the target project group, send the generated time planning adjustment scheme and cost planning adjustment scheme to the target administrator through the automatic notification system of the engineering project management platform. Notification methods can include email, SMS or platform message. The target administrator is responsible for communicating the adjustment scheme to relevant team members and ensuring the implementation of the scheme. At the same time, establish a monitoring and evaluation mechanism to regularly track and evaluate the implementation of the adjustment scheme, dynamically adjust according to the actual progress and new risk factors to ensure that the project progresses as planned.

[0070] Optionally, the determination of potential risk factors and potential cost growth factors in the project schedule based on the information data comprises:

[0071] Obtain cost data and impact data from the information data, the cost data including material procurement cost, labor cost, equipment rental cost and subcontractor fee, and the impact data including project schedule data, quality data and change request data;

[0072] Process the cost data and the impact data to extract cost growth characteristics, the cost growth characteristics including material usage, labor utilization and equipment usage;

[0073] Dimension reduction is performed on the cost growth characteristics to obtain principal component features, and the principal component features are input into a pre-set unsupervised learning model to obtain potential cost growth factors.

[0074] Material procurement cost: Record the procurement expenses of all materials in the project, including raw materials, parts, and so on. Labor cost: Record the expenses of all labor forces in the project, including workers' wages, welfare, overtime pay, and so on. Equipment rental cost: Record the rental expenses of all equipment in the project, including construction equipment, tools, and so on. Subcontractor cost: Record the expenses of all subcontractors in the project, including the contract amount of subcontracted work, and so on. Project progress data: Record the start time, end time, duration, completion percentage, and so on of each task in the project. Quality data: Record the quality inspection results of each task in the project, including the number of defects, rework times, and so on. Change request data: Record the number, type, impact range, and so on of all change requests in the project. Material usage rate: Calculate the ratio of material procurement cost to total project cost, reflecting the proportion of material cost in total project cost. Labor utilization rate: Calculate the ratio of actual working time to planned working time, reflecting the utilization efficiency of labor force. Equipment usage rate: Calculate the ratio of actual equipment running time to total available equipment time, reflecting the utilization efficiency of equipment. Remove duplicate data, fill in missing values, correct erroneous data, and so on to ensure the quality and completeness of the data. Extract the above cost growth features from the raw data, which can more intuitively reflect the status and potential problems of the project. Use principal component analysis technology to reduce the dimensionality of high-dimensional feature data to a lower dimension, reducing the complexity of the data while retaining the main variation information. The principal component features after dimensionality reduction can be more effectively used for subsequent model training. Select Gaussian mixture model as the unsupervised learning algorithm, which assumes that the data is mixed by multiple Gaussian distributions, which can better handle the complex distribution of data. Expectation-maximization (EM) algorithm: Use the EM algorithm to train the Gaussian mixture model to estimate the parameters (mean, covariance, and mixing weight) of each Gaussian component, thereby performing soft clustering on the data. Input the principal component features after dimensionality reduction into the Gaussian mixture model, and the model outputs the probability of each data point belonging to different Gaussian distributions. By analyzing these probabilities, identify patterns and anomalies in the data and discover potential cost growth factors. Identify abnormal points and patterns in the data through the output of the Gaussian mixture model. For example, some data points may belong to a cluster with high cost growth, and these data points correspond to projects that may have abnormal cost growth at a certain stage. Analyze the characteristics of these abnormal points, such as high material usage rate, low labor utilization rate, frequent equipment failures, and so on, to identify potential cost growth factors. Compare the identified potential cost growth factors with financial data to verify their accuracy. Incorporate these factors into the financial control system and set up an early warning mechanism to notify the financial team and project managers in a timely manner when potential cost growth risks are detected, and take appropriate measures to intervene.

[0075] By obtaining cost data and influence data from information data on the construction site, including material procurement cost, labor cost, equipment rental cost, subcontractor fee, project progress data, quality data, and change request data, potential risk factors and potential cost growth factors in project progress can be identified comprehensively and accurately. Compared with traditional subjective evaluation, this method is more objective and comprehensive, can reduce the interference of human factors, and improve the accuracy of risk identification. The cost data and influence data are processed to extract cost growth characteristics such as material usage rate, labor utilization rate, and equipment usage rate, and principal component features are obtained through dimension reduction technology. This process helps to remove noise and redundant information in the data, highlights key features, and makes potential risk factors and cost growth factors more clearly presented, further improving the accuracy of risk assessment. The principal component features are input into a pre-set unsupervised learning model, such as Gaussian mixture model, which can automatically identify patterns and anomalies in the data and timely discover potential risk factors and cost growth factors. Unsupervised learning model does not require pre-labeled data and can analyze and warn new data in real time, so that the project team can take measures in advance to avoid or mitigate risks. Based on the real-time monitoring function of unsupervised learning model, the project team can track project progress, cost, quality, and risk data in real time, discover potential problems in time, and dynamically adjust project plan and resource allocation according to actual situation. This real-time monitoring and warning mechanism makes project management more proactive and efficient, which can effectively reduce project risks. By predicting the historical data and current trend of potential cost growth factors, the cost change trend can be predicted in advance, and the cost planning can be adjusted in time. For example, if it is predicted that the material price will rise, the price can be locked in advance by negotiating with the supplier, or alternative materials can be found; if there is a trend of increasing labor cost, the work flow can be optimized to improve labor productivity, or reasonable arrangements can be made for overtime and outsourcing, so as to effectively control cost growth and ensure that the total cost of the project is within the budget. The growth amplitude and growth proportion of the total cost of the project are calculated, and the influence factor is obtained by weighted summation of the growth amplitude and growth proportion. The project team can conduct cost-benefit analysis on different cost control measures and choose the optimal solution. This helps to minimize cost and improve economic efficiency of the project under the premise of ensuring project quality.

[0076] Optionally, the determining potential risk factors and potential cost growth factors in project progress according to the information data comprises:

[0077] performing time series analysis on the project progress data to identify progress delay patterns;

[0078] determining quality problems according to the quality data and determining change frequency according to the change request data;

[0079] The cost growth feature, the schedule delay pattern, the quality problem, and the change frequency are input into a pre-set project schedule risk prediction model to obtain potential risk factors.

[0080] Project schedule data is collected from project management platforms or construction site records, including planned start time, planned end time, actual start time, actual end time, completed work quantity, etc. for each task. Time series analysis methods such as moving average, exponential smoothing or ARIMA model are used to analyze project schedule data. These methods can help identify trends, seasonality and periodic changes in project schedule, thus discovering potential schedule delay patterns. Through time series analysis, it can be identified which tasks are often delayed, the average number of days delayed, the frequency of delay, etc. For example, if a task is delayed in multiple stages, it may indicate that there is a systematic problem with the task that needs further analysis and resolution. Collect quality data in the project, including quality inspection reports, defect records, rework records, etc. These data can help identify quality problems in the project. Analyze quality data to determine which quality problems occur frequently and which quality problems have a greater impact on project schedule and cost. For example, if a quality problem leads to multiple reworks, it will have a serious impact on project schedule and cost. Collect change request data in the project, including the number of change requests, the type of change requests, the processing time of change requests, etc. Analyze change request data to determine the frequency and type of change requests. High-frequency change requests may indicate that project requirements are not clear or project management is not well done, and project management processes need to be further optimized. Extract cost growth features from project schedule data, quality data, and change request data, such as material usage rate, labor utilization rate, equipment usage rate, etc. At the same time, extract features such as schedule delay pattern, quality problem, and change frequency. Use pre-set project schedule risk prediction models such as logistic regression model, decision tree model or random forest model to input the extracted features into the model. Through model training, potential risk factors in project schedule are identified. The model can output the risk probability of each risk factor to help the project team prioritize high-risk factors. Analyze the potential risk factors output by the model to determine which factors have the greatest impact on project schedule and cost. For example, if a task has both a schedule delay pattern and a quality problem, it may indicate that the task has significant risks that need to be addressed first.

[0081] By conducting time series analysis on project schedule data, patterns and trends of schedule delays can be identified. This approach can reveal schedule fluctuations at different stages of the project, helping the project team to identify key nodes that may lead to delays in advance. Combining quality data to determine quality issues and change request data to determine change frequency further enriches the assessment dimensions of project schedule risks. Quality problems may lead to rework and delayed delivery, while frequent change requests may disrupt the original project plan, increasing project complexity and uncertainty. By considering these factors comprehensively, the project team can have a more comprehensive understanding of the potential risks facing the project schedule, and thus develop more targeted risk response strategies. Inputting cost growth characteristics, schedule delay patterns, quality problems, and change frequency into a pre-set project schedule risk prediction model can predict potential risk factors in project schedule in advance. This data analysis-based prediction model can use historical project data and current project data to mine potential patterns through machine learning algorithms and other technical means, providing forward-looking intelligence for the project team. The project team can adjust project plans and optimize resource allocation in advance based on the prediction results of the model, proactively addressing potential risks rather than passively responding to problems that have already occurred, thereby improving project controllability and success rate. The above method supports dynamic monitoring and real-time feedback of project schedule. The project team can update project schedule data, quality data, and change request data regularly and re-run the risk prediction model to obtain the latest risk assessment results. This dynamic monitoring mechanism ensures that the project team can capture any changes in the project progress process in a timely manner and adjust management strategies in a timely manner to maintain the smooth progress of the project. By analyzing cost growth characteristics such as material usage rate, labor utilization rate, and equipment usage rate, the project team can more clearly understand the reasons and trends of cost changes. This helps to identify key factors that may cause cost overruns, such as material waste, labor idleness, or low equipment efficiency, so that appropriate measures can be taken for optimization. By combining cost growth characteristics with project schedule risk factors such as schedule delay patterns, quality problems, and change frequency, the project team can more comprehensively consider the mutual influence between cost and schedule when developing project plans and budgets.

[0082] Optionally, the generating a time plan adjustment scheme and a cost plan adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in the target project group comprises:

[0083] determining a priority of the potential risk factor according to a severity and a possibility of occurrence of the potential risk factor;

[0084] determining a growth amplitude and a growth proportion of the total project cost according to the potential cost growth factor, and determining an influence degree of the potential cost growth factor according to the growth amplitude and the growth proportion.

[0085] determining an order of generating adjustment schemes according to the priority of the potential risk factors and the influence degree of the potential cost growth factors;

[0086] generating time planning adjustment schemes and cost planning adjustment schemes of all engineering projects in the target project group according to the order.

[0087] Evaluate the potential impact of each potential risk factor on project schedule and quality. For example, a delay in a critical task may have a significant impact on the delivery date of the entire project, which has a higher severity level. Evaluate the probability of occurrence of each potential risk factor. For example, the instability of a certain supplier's material supply leads to a higher risk of material shortage, which has a higher likelihood of occurrence. Assign a severity score and a likelihood score to each potential risk factor, with a scale of 1 to 10, 1 being the lowest and 10 being the highest. Calculate the risk priority index of each potential risk factor, with the formula: risk priority index = severity score × likelihood score. For example, a potential risk factor has a severity score of 8 and a likelihood score of 6, so its risk priority index is 8 × 6 = 48. Sort all potential risk factors according to their risk priority index, with higher priority index indicating higher priority. According to the historical data and current trends of potential cost growth factors, predict their expected contribution to the overall cost growth of the project. For example, rising material prices, increasing labor costs, or low equipment efficiency may all lead to cost growth. If the material price is expected to rise by 10%, and the material cost accounts for 30% of the total project cost, the expected contribution is 30% × 10% = 3%. Add up the expected contributions of all potential cost growth factors to get the growth amplitude of the total project cost. Calculate the growth proportion of the total project cost, with the formula: growth proportion = growth amplitude / initial budget cost of the project. For example, if the initial budget cost of the project is 1 million yuan, and the growth amplitude is 30,000 yuan, the growth proportion is 3%. According to the growth proportion, divide the potential cost growth factors into three levels: high impact, medium impact, and low impact. Growth proportion greater than or equal to 10% is high impact, growth proportion between 5% and 10% is medium impact, and growth proportion less than 5% is low impact. Create a comprehensive evaluation matrix, with rows corresponding to potential risk factors and columns corresponding to potential cost growth factors. Assign a comprehensive score to each combination of potential risk factors and potential cost growth factors, based on the risk priority index and the cost growth proportion. Sort all combinations of potential risk factors and potential cost growth factors according to the comprehensive score to determine the order of generating adjustment plans. Prioritize the combinations with the highest comprehensive score to ensure that the project team addresses the most impactful issues first. Re-evaluate the duration of the critical path based on potential risk factors, which is the longest sequence of tasks remaining in the engineering project. Analyze the tasks on the critical path and identify tasks that can be executed in parallel, rearrange the construction sequence to reduce the duration. Evaluate the utilization efficiency of existing resources and identify tasks with utilization efficiency below the threshold, increase resource input for these tasks to reduce the duration. Develop specific action steps, timelines, and responsible persons for each critical task to ensure that the project progresses as planned.Specific cost control measures are developed for high-impact potential cost growth factors, such as negotiating lower procurement costs, improving labor efficiency, optimizing equipment usage plans, etc. According to the impact degree and occurrence probability of potential cost growth factors, the amount of risk buffer fund is determined to deal with possible additional costs in the future, ensuring that the total project cost is controlled within the budget. Regularly review and update the cost planning adjustment scheme, dynamically adjust according to the actual situation, and ensure that the cost control is within the budget.

[0088] By evaluating the severity and occurrence probability of potential risk factors, the priority of each risk factor is determined, and the project team can more clearly identify which risks need to be prioritized and handled. This method makes risk management more scientific and systematic, avoiding the uncertainty of decision-making based on experience or intuition. Determine the growth amplitude and proportion of potential cost growth factors to the total project cost, and its impact degree, so that the project team can quantify the specific impact of risks on project cost. This quantitative analysis helps to more accurately assess the potential impact of risks, so as to develop more targeted countermeasures. According to the priority of potential risk factors and the impact degree of potential cost growth factors, the order of generating adjustment schemes is determined to ensure that the project team can handle each risk factor in order of importance and urgency. This sequential scheme generation method improves the efficiency and effectiveness of project adjustment, avoiding waste of resources and duplication of work. Sequentially generate time planning adjustment schemes and cost planning adjustment schemes for all engineering projects in the target project group, so that time and cost management can be carried out in coordination. The project team can consider progress and cost factors at the same time to develop a comprehensive adjustment scheme that meets time requirements and is within budget, improving the overall coordination and consistency of project management. By identifying and evaluating potential risk factors in advance, the project team can develop countermeasures in advance rather than reacting hastily after the risk occurs. This forward-looking risk management approach helps to reduce the risk of project delays and cost overruns, improving the success rate and delivery quality of the project.

[0089] Optionally, the priority of each potential risk factor is determined according to the severity and occurrence probability of the potential risk factor, including:

[0090] Each potential risk factor is assigned a severity score and an occurrence probability score, both based on pre-set scoring criteria;

[0091] According to the severity score and the occurrence probability score, a risk priority index of each potential risk factor is calculated;

[0092] According to the risk priority index, all potential risk factors are sorted to determine the priority of each potential risk factor.

[0093] Evaluate the impact of each potential risk factor on project objectives (e.g., schedule, cost, quality, etc.) if it occurs. Generally, scoring can be done according to the following criteria:

[0094] High severity: This risk, if it occurs, will have a significant impact on critical project objectives, potentially causing the project to be unable to continue or resulting in significant financial loss. Scoring can be set to 9-10.

[0095] Medium severity: This risk, if it occurs, will have some impact on certain project objectives, but will not cause significant loss to the entire project. Scoring can be set to 5-8.

[0096] Low severity: This risk, if it occurs, has little impact on the project and can be ignored. Scoring can be set to 1-4.

[0097] Evaluate the probability of each potential risk factor occurring. Generally, scoring can be done according to the following criteria:

[0098] High probability: This risk is almost certain to occur and cannot be avoided or reduced. Scoring can be set to 9-10.

[0099] Medium probability: This risk has a certain degree of possibility of occurring and requires appropriate preventive measures. Scoring can be set to 5-8.

[0100] Low probability: This risk has a small chance of occurring and can be ignored. Scoring can be set to 1-4.

[0101] Risk Priority Number (RPN): By multiplying the severity score (S) and the probability score (O), the risk priority number (RPN) of each potential risk factor is calculated. The formula is: RPN=S×O. For example, if the severity score of a certain risk factor is 7 and the probability score is 3, then its RPN is: RPN=7×3=21. The larger the RPN value, the higher the priority of the risk factor, which needs to be given priority and handled. All potential risk factors are ranked according to RPN value from high to low. The risk factor with the highest RPN value has the highest priority and needs to be handled first; the risk factor with the lowest RPN value has the lowest priority and can be handled later. The specific steps are as follows:

[0102] High priority: Risk factors with RPN values between 81 and 100 need to be immediately managed and controlled.

[0103] Medium priority: Risk factors with RPN values between 36 and 80 need to be continuously monitored during project execution and appropriate preventive measures need to be taken.

[0104] Low priority: Risk factors with RPN values between 1-35, which can be checked regularly but do not require immediate action.

[0105] By assigning severity scores and likelihood scores to each potential risk factor based on pre-defined scoring criteria, the objectivity and consistency of risk assessment are ensured. This standardized approach avoids inconsistencies in assessment results due to subjective judgments by different assessors, improving the reliability and comparability of risk assessment. For example, using the same set of scoring criteria for all project team members to assess risks ensures that risk assessment results are comparable across different projects, facilitating unified management and coordination at the project portfolio level. Converting the severity and likelihood of risk factors into specific score values achieves quantification of risk assessment. This quantitative approach makes the size and urgency of risks more intuitive and explicit, facilitating understanding and communication among project teams. Compared to traditional qualitative descriptions, quantitative scoring can more accurately reflect the relative importance of risks, helping project teams quickly identify key risks among numerous risk factors. Sorting all potential risk factors according to the risk priority index allows project teams to clearly identify which risks need to be prioritized. This approach helps optimize resource allocation, ensuring that limited resources such as time, money, and manpower are prioritized for risk factors that have the greatest impact on the project. For example, more resources can be allocated for monitoring and responding to the highest priority risk factors, while simpler measures or temporary shelving can be taken for lower priority risk factors. After determining the priority of each potential risk factor, project teams can develop more targeted risk management strategies. For high-priority risk factors, detailed response plans can be developed, including preventive measures and emergency measures; for medium-priority risk factors, regular monitoring and evaluation can be conducted to respond promptly when risks occur; for low-priority risk factors, more relaxed management strategies can be adopted to reduce unnecessary workload. Based on the results of quantitative scoring and priority sorting, project decision-makers can make more scientific project plans and adjustments. This data-driven decision-making approach reduces the interference of subjective factors, improving the accuracy and reliability of decisions. Project teams can regularly reassess the severity and likelihood of potential risk factors based on project progress and new information, updating risk priority indices and priority rankings. This dynamic adjustment mechanism ensures that project teams can respond to changes in the project environment in a timely manner, continuously optimize risk management strategies, and improve overall project management.

[0106] Optionally, the method further comprises:

[0107] predicting an expected growth contribution of the potential cost growth factor to the total project cost based on historical data and current trends of the potential cost growth factor;

[0108] determining a growth magnitude of the total project cost based on the expected growth contribution and determining a growth proportion of the total project cost based on a ratio of the growth magnitude to an initial budget cost;

[0109] performing a weighted sum of the growth magnitude and the growth proportion to obtain an impact factor and determining an impact degree of the potential cost growth factor based on the impact factor.

[0110] Collect historical data for each potential cost growth factor, such as historical price fluctuations of material procurement costs, historical changes in labor costs, historical usage of equipment rental costs, etc. These data can come from past project records, market reports, or industry databases. Analyze current market trends, economic environment, policy changes, etc. to predict the future trend of cost changes. For example, if the current market material prices continue to rise, it can be predicted that future material procurement costs will continue to increase. Use statistical analysis or machine learning models (such as linear regression, time series analysis, neural networks, etc.) to predict the expected growth contribution of each potential cost growth factor to the total cost of the project based on historical data and current trends. For example, if the material price has risen by 10% in the past year and the current market trend indicates that this upward trend will continue, it can be predicted that future material procurement costs will increase by a certain percentage. Specific calculation: assuming the expected growth contribution of a certain potential cost growth factor (such as material procurement cost) is 100,000 yuan, which means that during the remaining period of the project, this factor is expected to increase the total cost of the project by 100,000 yuan. Add the expected growth contribution of all potential cost growth factors to get the growth amplitude of the total cost of the project. For example, if the expected growth contribution of three potential cost growth factors is 100,000 yuan, 50,000 yuan and 30,000 yuan respectively, then the growth amplitude of the total cost of the project is 180,000 yuan. Determine the growth proportion of the total cost of the project by comparing the growth amplitude with the initial budget cost of the project. For example, if the initial budget cost of the project is 1,000,000 yuan and the growth amplitude is 180,000 yuan, then the growth proportion is 18%. According to the experience of project management and cost control, allocate weights to the growth amplitude and the growth proportion. For example, it can be considered that the weight of the growth amplitude is 0.6 and the weight of the growth proportion is 0.4, these weights can be adjusted according to the characteristics and management requirements of the project. Weighted sum of growth amplitude and growth proportion to get impact factor. For example, if the growth amplitude is 180,000 yuan and the growth proportion is 18%, the weights are 0.6 and 0.4 respectively, then the impact factor is: impact factor = (18 × 0.6) + (18 × 0.4) = 18. According to the size of the impact factor, divide the potential cost growth factors into high impact, medium impact and low impact three levels. For example, you can set the high impact threshold to 20 and the medium impact threshold to 10, the specific threshold can be set according to the historical data of the project and industry standards. The impact factor greater than or equal to 20 is a high impact factor, the impact factor greater than or equal to 10 and less than 20 is a medium impact factor, and the impact factor less than 10 is a low impact factor.

[0111] By calculating the expected growth contribution, growth amplitude, and growth proportion, the impact of potential cost growth factors is quantified, enabling the project team to more intuitively understand the specific impact of each factor on the total project cost. According to the impact factor, the project team can prioritize factors with high impact factors, develop more targeted cost control measures, and optimize resource allocation. Regularly reassess the expected growth contribution and impact factor of potential cost growth factors, dynamically adjust according to project progress and market changes, and ensure the timeliness and effectiveness of cost control strategies. Provide scientific data support for project decision-makers, help them develop reasonable project budgets and cost control plans, and improve the economic benefits and success rate of projects.

[0112] Optionally, the generating the time planning adjustment scheme and the cost planning adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in the target project group comprises:

[0113] Reassessing the duration of the critical path according to the potential risk factors, the critical path being the longest sequence of tasks in the remaining work of the engineering project;

[0114] Analyzing the tasks on the critical path, identifying a first target task that can be executed in parallel, and rearranging the construction sequence of the critical path according to the first target task to reduce the duration;

[0115] Evaluating the utilization efficiency of existing resources, identifying a second target task with utilization efficiency below a threshold, and increasing resource input for the second target task to reduce the duration.

[0116] The critical path is the longest sequence of tasks in a project from start to finish, and any delay in tasks on the critical path will cause the entire project to be delayed. Tasks on the critical path are often referred to as critical tasks. The duration of the critical path is re-evaluated based on potential risk factors. Potential risk factors may include material supply delays, labor shortages, equipment failures, etc., which can all affect the completion time of critical tasks. By re-evaluating, the project completion time can be more accurately predicted, and potential risk points that may cause delays can be discovered in advance. Analyze the tasks on the critical path and identify the first target task that can be performed in parallel. Parallel tasks are tasks that can be performed simultaneously within the same time period. By reasonably arranging the execution order of these tasks, the total duration of the critical path can be shortened. Assuming that there are tasks A, B and C on the critical path, tasks B and C can be performed in parallel. By adjusting the start time of tasks B and C to synchronize with the end time of task A, the total duration of the critical path can be reduced. According to the identified parallel tasks, the construction sequence of the critical path is rearranged. This adjustment can optimize the dependency relationship of tasks, reduce waiting time and idle time, and improve overall construction efficiency. Project management software or Gantt charts can be used to visualize and adjust task sequences to ensure that the adjusted plan is clear and feasible. Resource utilization efficiency refers to the efficiency of resources such as labor, equipment, and materials in a project. Inefficient resource utilization can lead to task delays and cost increases. By analyzing data such as task completion, resource usage time, and idle time, the efficiency of existing resources can be evaluated. Resource utilization indicators such as equipment utilization rate = actual operating time / total available time can be used to quantify resource utilization efficiency. Identify the second target task whose utilization efficiency is below the threshold. The threshold can be set based on historical data of the project and industry standards. For example, if the equipment utilization rate is less than 80%, it is considered that the utilization efficiency of the equipment is low. Assuming that in a certain project, the utilization rate of equipment D is only 60%, which is lower than the set threshold of 80%, indicating that the utilization efficiency of equipment D is low. Increase resource input for the second target task whose utilization efficiency is below the threshold to reduce the duration of the task. Increasing resources can include increasing labor, extending working hours, increasing the number of equipment, etc. For equipment D, you can increase a same type of equipment or extend the operating time of the equipment to improve the utilization efficiency of the equipment and reduce the duration of the task, thereby shortening the total duration of the critical path.

[0117] The embodiment also discloses a management system of an engineering project, Figure 2 The embodiment discloses a management system of an engineering project, Figure 2 As shown in the figure, the system comprises an induction module 201, an analysis module 202, an adjustment module 203 and a display module 204, wherein:

[0118] The induction module 201 is configured to induce engineering projects with similar properties into a plurality of project groups, and set an access level for each project group;

[0119] The analysis module 202 is configured to obtain information data of a construction site of each engineering project, the information data including engineering material consumption, labor allocation, and equipment operating status, determine potential risk factors and potential cost growth factors in project progress according to the information data;

[0120] The adjustment module 203 is configured to generate a time planning adjustment scheme and a cost planning adjustment scheme according to potential risk factors and potential cost growth factors of all engineering projects in a target project group;

[0121] The display module 204 is configured to send the time planning adjustment scheme and the cost planning adjustment scheme to a target administrator according to an access level of the target project group.

[0122] Optionally, the analysis module 202 is configured to:

[0123] obtain cost data and influence data from the information data, the cost data including material procurement cost, labor cost, equipment rental cost, and subcontractor fee, and the influence data including project progress data, quality data, and change request data;

[0124] process the cost data and the influence data to extract cost growth features, the cost growth features including material usage rate, labor utilization rate, and equipment usage rate;

[0125] reduce dimensions of the cost growth features to obtain principal component features, and input the principal component features into a preset unsupervised learning model to obtain potential cost growth factors.

[0126] Optionally, the analysis module 202 is configured to:

[0127] perform time series analysis on the project progress data to identify progress delay patterns;

[0128] determine quality problems according to the quality data, and determine change frequency according to the change request data;

[0129] input the cost growth features, the progress delay patterns, the quality problems, and the change frequency into a preset project progress risk prediction model to obtain potential risk factors.

[0130] Optionally, the adjustment module 203 is configured to:

[0131] determine a priority of the potential risk factors according to a severity and a possibility of occurrence of the potential risk factors;

[0132] determining a growth amplitude of the total project cost and a growth proportion of the total project cost according to the potential cost growth factor, and determining an influence degree of the potential cost growth factor according to the growth amplitude and the growth proportion;

[0133] determining an order of generating adjustment schemes according to the priority of the potential risk factor and the influence degree of the potential cost growth factor;

[0134] generating time planning adjustment schemes and cost planning adjustment schemes of all engineering projects in the target project group according to the order.

[0135] Optionally, the adjustment module 203 is configured to:

[0136] assigning a severity score and a possibility score to each potential risk factor, the severity score and the possibility score being based on preset scoring standards;

[0137] calculating a risk priority index of each potential risk factor according to the severity score and the possibility score;

[0138] sorting all potential risk factors according to the risk priority index to determine the priority of each potential risk factor.

[0139] Optionally, the adjustment module 203 is configured to:

[0140] predicting an expected growth contribution of the potential cost growth factor to the total project cost according to historical data and current trends of the potential cost growth factor;

[0141] determining a growth amplitude of the total project cost according to the expected growth contribution, and determining a growth proportion of the total project cost according to a ratio of the growth amplitude to an initial budget cost;

[0142] performing weighted summation on the growth amplitude and the growth proportion to obtain an influence factor, and determining the influence degree of the potential cost growth factor according to the influence factor.

[0143] Optionally, the adjustment module 203 is configured to:

[0144] re-evaluating a duration of a critical path according to the potential risk factor, the critical path being a longest sequence of tasks in remaining work of the engineering project;

[0145] analyzing tasks on the critical path, identifying a first target task capable of being executed in parallel, and rearranging a construction order of the critical path according to the first target task to reduce the duration;

[0146] Evaluate the utilization efficiency of the existing resources, identify a second target task with a utilization efficiency lower than a threshold, and increase resource input for the second target task to reduce the duration.

[0147] It should be noted that the device provided in the above examples is only exemplified by the above division of functional modules when implementing its functions. In actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions. In addition, the device and method embodiments provided in the above examples belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be described here.

[0148] The embodiment also discloses an electronic device, which refers to Figure 3 The electronic device can include at least one processor 301, at least one communication bus 302, a user interface 303, a network interface 304, and at least one memory 305.

[0149] The communication bus 302 is used to realize the connection and communication between the components.

[0150] The user interface 303 can include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 can also include a standard wired interface and a wireless interface.

[0151] The network interface 304 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0152] The processor 301 can include one or more processing cores. The processor 301 connects various parts within the server through various interfaces and lines, performs various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Alternatively, the processor 301 can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 301 can integrate a combination of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes operating systems, user interfaces, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; and the modem is used for processing wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor 301, but can be realized by a separate chip.

[0153] The memory 305 can include a random access memory (RAM) and a read-only memory (ROM). Alternatively, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 305 can alternatively be at least one storage device located away from the aforementioned processor 301. As shown in the figure, the memory 305 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of the management method of the engineering project. Figure 3 As shown in the figure, the memory 305 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of the management method of the engineering project.

[0154] In Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an interface for the user to input, and obtain data input by the user; and the processor 301 can be used to invoke an application program stored in the memory 305 and storing the management method of the engineering project, which, when executed by one or more processors 301, causes the electronic device to perform the method of one or more of the above-described embodiments.

[0155] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all described as a series of action combinations, but those skilled in the art should know that the present application is not limited to the order of the actions described, because according to the present application, certain steps can be performed in other order or at the same time. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0156] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0157] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic. The division of the units is only a logical function division. There can be another division manner for actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different parts can be indirect couplings or communication connections through some interfaces, devices or units, and can be electrical or other forms.

[0158] The units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0159] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present alone, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0160] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a memory 305 and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned memory 305 includes: a U disk, a mobile hard disk, a magnetic or optical disk and various media that can store program codes.

[0161] The above-described are only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the disclosure. The present application is intended to cover any variations, uses or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include common knowledge or conventional technical means in the art that are not described in the present disclosure. The scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method of managing an engineering project, characterized by, The method is applied to an engineering project management platform and comprises the following steps: Grouping engineering projects with similar properties to form a plurality of project groups, and setting an access level for each project group; Obtaining information data of a construction site of each engineering project, the information data comprising engineering material consumption, labor distribution and equipment operating conditions, determining potential risk factors and potential cost growth factors in project progress based on the information data; Generating a time planning adjustment scheme and a cost planning adjustment scheme based on the potential risk factors and the potential cost growth factors of all engineering projects in a target project group; Sending the time planning adjustment scheme and the cost planning adjustment scheme to a target administrator according to the access level of the target project group, The method of generating a time planning adjustment scheme and a cost planning adjustment scheme based on the potential risk factors and the potential cost growth factors of all engineering projects in a target project group comprises the following steps: Determining a priority of the potential risk factors based on a severity and a possibility of occurrence of the potential risk factors; Determining a growth amplitude and a growth proportion of a total project cost based on the potential cost growth factors, and determining an influence degree of the potential cost growth factors based on the growth amplitude and the growth proportion; Determining a sequence of generating adjustment schemes based on the priority of the potential risk factors and the influence degree of the potential cost growth factors; Generating the time planning adjustment scheme and the cost planning adjustment scheme of all engineering projects in the target project group in sequence according to the sequence, The method of determining a priority of the potential risk factors based on a severity and a possibility of occurrence of the potential risk factors comprises the following steps: Assigning a severity score and a possibility score to each potential risk factor, the severity score and the possibility score being based on preset scoring standards; Calculating a risk priority index of each potential risk factor based on the severity score and the possibility score; Determining a priority of each potential risk factor based on a sequence of all potential risk factors.

2. The method of claim 1, wherein The method of determining potential risk factors and potential cost growth factors in project progress based on information data comprises the following steps: Obtaining cost data and influence data from the information data, the cost data comprising material procurement cost, labor cost, equipment rental cost and subcontractor fees, and the influence data comprising project progress data, quality data and change request data; Processing the cost data and the influence data to extract cost growth features, the cost growth features comprising material usage rate, labor utilization rate and equipment usage rate; Reducing dimensions of the cost growth features to obtain principal component features, and inputting the principal component features into a preset unsupervised learning model to obtain potential cost growth factors.

3. The method of claim 2, wherein The method of determining potential risk factors and potential cost growth factors in project progress based on information data comprises the following steps: Performing time series analysis on the project progress data to identify progress delay patterns; Determining quality problems based on the quality data, and determining change frequency based on the change request data; inputting the cost growth feature, the schedule delay pattern, the quality problem, and the change frequency into a preset project schedule risk prediction model to obtain a potential risk factor.

4. The method of claim 1, wherein determining a growth amplitude of the total project cost and a growth proportion of the total project cost according to the potential cost growth factor, and determining an influence degree of the potential cost growth factor according to the growth amplitude and the growth proportion includes: predicting an expected growth contribution of the potential cost growth factor to the total project cost according to historical data and current trends of the potential cost growth factor; determining a growth amplitude of the total project cost according to the expected growth contribution, and determining a growth proportion of the total project cost according to a ratio of the growth amplitude to an initial budget cost; performing a weighted summation of the growth amplitude and the growth proportion to obtain an influence factor, and determining the influence degree of the potential cost growth factor according to the influence factor.

5. The method of claim 1, wherein generating a time planning adjustment scheme and a cost planning adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in a target project group includes: re-evaluating a duration of a critical path according to the potential risk factors, the critical path being a longest sequence of tasks in remaining work of the engineering project; analyzing tasks on the critical path, identifying a first target task capable of being executed in parallel, and rearranging a construction sequence of the critical path according to the first target task to reduce the duration; evaluating utilization efficiency of existing resources, identifying a second target task having a utilization efficiency lower than a threshold, and increasing resource input to the second target task to reduce the duration.

6. A management system for an engineering project, characterized by comprising an induction module, an analysis module, an adjustment module, and a display module, and performing the method of any one of claims 1-5, wherein: the induction module is configured to induce engineering projects of the same nature together to form a plurality of project groups, and set an access level for each project group; the analysis module is configured to obtain information data of a construction site of each engineering project, the information data including engineering material consumption, labor allocation, and equipment operating conditions, and determine potential risk factors in project schedule and potential cost growth factors according to the information data; the adjustment module is configured to generate a time planning adjustment scheme and a cost planning adjustment scheme according to the potential risk factors and the potential cost growth factors of all engineering projects in a target project group; the display module is configured to send the time planning adjustment scheme and the cost planning adjustment scheme to a target administrator according to the access level of the target project group.

7. An electronic device, comprising: comprising a processor, a memory, a user interface, and a network interface, the memory being configured to store instructions, the user interface and the network interface both being configured to communicate with other devices, and the processor being configured to execute the instructions stored in the memory to cause the electronic device to perform the method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, the computer-readable storage medium stores instructions that, when executed, perform the method of any one of claims 1-5.

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