Informatization management method for building construction

Abstract

The invention discloses an informatization management method for building construction, and relates to the technical field of building informatization management, and the method comprises the steps: carrying out the real-time data collection through employing various sensors installed at a construction site, and a data collection module, extracting the collection data in the same time period from a time series data sequence, and carrying out the data collection through employing a data informatization management module, the method comprises the following steps: respectively calculating a construction efficiency evaluation value XLP, a cost-benefit analysis value CXF and a quality risk prediction value ZL, evaluating the quality risk level of a construction project according to the quality risk prediction value ZL, and comparing the construction efficiency evaluation value XLP with a construction efficiency evaluation value XLPprev of a previous stage and comparing the cost-benefit analysis value CXF with a cost-benefit analysis value CXFprev of the previous stage to obtain the quality risk level of the construction project. According to the method, through optimization and innovation means such as data integration and sharing, scientific evaluation and accurate decision, dynamic adjustment and feedback mechanism and the like, the construction efficiency is improved, the cost risk is reduced, the quality level is improved, and the decision-making ability is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of building information management, and in particular to an information management method for building construction. Background Art

[0002] The information management method of construction is an innovative management method for the construction industry in the context of the information age. It is a new management method based on traditional construction management, combined with modern information technology and data analysis technology. Specifically, it combines modern information technology, data analysis technology and the actual needs of construction management, aiming to improve construction efficiency, reduce costs, improve quality and enhance the scientificity and accuracy of decision-making.

[0003] In the existing technology, data from construction sites are often scattered among various departments and systems, forming data islands, which leads to the inability to share and circulate information in a timely manner. This limits the ability to integrate and analyze data, making it difficult for managers to fully and accurately understand the construction situation. In addition, existing construction management methods often rely on experience judgment and qualitative analysis, and lack scientific and accurate evaluation methods. This leads to the evaluation results of construction efficiency, cost-effectiveness and quality risks being often inaccurate, making it difficult to guide decision-making in the actual construction process. In addition, existing technologies often lack dynamic adjustment and feedback mechanisms, and are unable to adjust construction plans and resource allocations in a timely manner according to the actual situation during the construction process. This leads to problems in the construction process being difficult to discover and solve in a timely manner, affecting construction efficiency and quality. Summary of the invention

[0004] The purpose of the present invention is to provide an information management method for building construction, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution, and the specific implementation steps are as follows:

[0006] Step I: Use various sensors installed at the construction site and data acquisition modules to collect real-time data, and organize the data collected by the sensors in time series to form a time series data sequence;

[0007] Step II, extracting the collected data of the same time period from the time series data sequence;

[0008] Step II: Use the data information management module to calculate the construction efficiency evaluation value XLP, the cost-benefit analysis value CXF, and the quality risk prediction value ZL;

[0009] Step II-I: Evaluate the quality risk level of the construction project based on the quality risk prediction value ZL;

[0010] Step II-II: For the quality risk prediction value ZL and the quality risk prediction value ZL of the previous stage prev The comparison is based on the construction efficiency evaluation value XLP and the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev and formulate corresponding risk control measures;

[0011] Among them, the data information management module includes a unit for quantitatively evaluating construction efficiency, a unit for in-depth analysis of the cost-effectiveness of construction projects, and a unit for predicting potential quality risks.

[0012] Optionally, the sensor includes a quantity sensor, a work time recorder, a mechanical power monitor, a material waste quantity measurer, and a rework quantity measurer, and the sensor is used to collect various data of the construction site in real time;

[0013] The equipment used in the data information management module includes an information platform, which includes a data processing module, an analysis module, and a visualization module, which are used to realize real-time data collection, analysis, sharing and decision support;

[0014] The equipment used by the data acquisition module includes a data acquisition system, and the data acquisition system is used to transmit the data collected by the sensor to the information platform in real time.

[0015] Optionally, the calculation formula for the quantitative evaluation unit of construction efficiency is as follows:

[0016] XLP = YG / SQRT(CL+F);

[0017] YG = [SS × (L + JG) - ST];

[0018] in:

[0019] XLP is the construction efficiency evaluation value;

[0020] YG is the effective workload;

[0021] SS is the total number of people, SS reflects the total number of operators involved in the construction;

[0022] L is the labor time, which reflects the number of hours actually put into work by the construction personnel;

[0023] JG is the mechanical power, JG represents the total power of the construction machinery;

[0024] ST is lost time, including non-productive time of downtime and waiting;

[0025] CL is the amount of material waste, which reflects the amount of material wasted during the construction process;

[0026] F is the rework amount, and F reflects the amount of work that needs to be redone due to quality issues.

[0027] Optionally, the calculation formula for the in-depth analysis of the construction project cost-effectiveness unit is as follows:

[0028] CXF=[XLP×(ZC-Y)+PBL] / (L+XLP);

[0029] PBL = SQRT[(XLP-XLP prev )×(ES / T)];

[0030] ES = SY-Y;

[0031] in:

[0032] CXF is the cost-benefit analysis value;

[0033] ZC is the total cost, including the cost of materials, labor, and machinery;

[0034] Y is the expected revenue, which reflects the revenue expected to be obtained after the construction is completed;

[0035] PBL is the average rate of change. PBL calculates the square root value of the additional benefit ES brought about by the change in construction efficiency relative to the time period T;

[0036] XLP prev It is the construction efficiency evaluation value of the previous stage;

[0037] ES is the additional benefit, which reflects the additional benefit obtained due to efficiency improvement;

[0038] SY is the actual return;

[0039] T is the time period, which reflects the time period of the current evaluation;

[0040] X is the adjustment factor, which is used to adjust other factors in cost-effectiveness analysis.

[0041] Optionally, the calculation formula for predicting potential quality risk units is as follows:

[0042] ZL=[CXF×(1-QC)-SQRT((CXF-CXF prev )×(QC / QT))]×(1+XLB);

[0043] XLB=(XLP-XLP prev ) / XLP;

[0044] QT=(QXS / ZSL)×100%;

[0045] in:

[0046] ZL is the quality risk prediction value;

[0047] QC is the defect rate, which reflects the proportion of defects in the construction project;

[0048] QXS is the number of defects, and ZSL is the total inspection number;

[0049] CXF prev is the cost-benefit analysis value of the previous stage;

[0050] QT is the additional cost increase, which reflects the cost increase caused by defects, including labor costs, material costs, and equipment costs incurred in repairing defects;

[0051] XLB is the construction efficiency change rate.

[0052] Optionally, the quality risk prediction value ZL is the same as the quality risk prediction value ZL of the previous stage. prev The comparative analysis is as follows:

[0053] If the quality risk prediction value ZL is lower than the quality risk prediction value ZL of the previous stage prev , then the quality risk is considered to be reduced and the current quality control measures should be maintained;

[0054] If the quality risk prediction value ZL is higher than the quality risk prediction value ZL of the previous stage prev , it is considered that the quality risk has increased, and corresponding quality improvement measures should be taken according to the specific reasons.

[0055] Optionally, based on the quality risk prediction value ZL being higher than the quality risk prediction value ZL of the previous stage prev The situation is combined with the construction efficiency evaluation value XLP and the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev The comparative analysis is as follows:

[0056] Construction efficiency evaluation value XLP and construction efficiency evaluation value XLP of the previous stage prev comparative analysis;

[0057] If the construction efficiency evaluation value XLP is lower than the construction efficiency evaluation value XLP of the previous stage prev , it is considered that there are problems with insufficient skills of construction workers, machinery failure, unreasonable material supply and construction process. Appropriate improvement measures should be taken for specific problems, including training of construction workers, repair and replacement of machinery, optimization of material supply process and adjustment of construction process;

[0058] If the construction efficiency evaluation value XLP is higher than the construction efficiency evaluation value XLP of the previous stageprev , it is believed that construction efficiency has been improved and the current construction methods and processes should be maintained;

[0059] Cost-benefit analysis value CXF and cost-benefit analysis value CXF in the previous stage prev comparative analysis;

[0060] If the cost-benefit analysis value CXF is lower than the cost-benefit analysis value CXF of the previous stage prev , it is considered that there is an increase in costs due to a decrease in construction efficiency and a decrease in revenue due to changes in market demand. According to the specific reasons, corresponding cost control strategies and revenue improvement measures are adopted, including optimizing the construction process, reducing material costs, improving construction quality and adjusting sales strategies;

[0061] If the cost-benefit analysis value CXF is higher than the cost-benefit analysis value CXF of the previous stage prev , it is believed that cost-effectiveness has improved and cost-saving measures and profit-enhancing strategies should be maintained.

[0062] Optionally, the SQRT is an abbreviation for square root, which in mathematics means performing a square root operation on a number;

[0063] In the quantitative evaluation unit for construction efficiency, it is used to calculate the square root of the sum of the material waste CL and the rework F, so as to balance the impact of different scales of resource waste on efficiency evaluation;

[0064] In the in-depth analysis of the construction project cost-effectiveness unit, it is used to calculate the square root value of the difference in construction efficiency change and the additional benefit ES relative to the time period T. This calculation step evaluates the contribution of the construction efficiency change to the additional benefit and takes into account the impact of the time period T;

[0065] In the potential quality risk prediction unit, the cost-effectiveness change difference and the square root value of the defect cost QC relative to the time QT required to handle the defect are calculated. This calculation step evaluates the correlation impact between the cost-effectiveness change and the defect cost.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] 1. The present invention realizes the real-time collection, integration and sharing of construction site data by constructing an information platform of data information management module, which breaks the data silos and enables managers to fully and accurately understand the construction situation, providing strong support for decision-making.

[0068] 2. The present invention uses quantitative evaluation of construction efficiency to carry out quantitative unit, in-depth analysis of construction project cost-benefit unit and prediction of potential quality risk unit to scientifically evaluate the data of the construction site, thereby obtaining the construction efficiency evaluation value XLP, the cost-benefit analysis value CXF and the quality risk prediction value ZL, so as to improve construction efficiency and quality.

[0069] 3. The present invention can timely discover problems and risks in the construction process by real-time monitoring and analyzing the data of the construction site. By comparing the current quality risk prediction value ZL with the previous result, and combining the changes in the construction efficiency evaluation value XLP and the cost-benefit analysis value CXF with the previous result, it can timely discover problems and risks in the construction process, and take corresponding measures to control them, forming a dynamic adjustment and feedback mechanism. This feedback mechanism can timely discover and solve problems, thereby improving construction efficiency and quality level, while reducing cost risks, and providing strong guarantees for the smooth progress of construction projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 The method flow chart of the information management method for this building construction;

[0071] Figure 2 It is a structural diagram of the data information management module of the present invention;

[0072] Figure 3 A flow chart of quality risk prediction based on the information management method for building construction;

[0073] Figure 4 The figure is a flow chart of the in-depth analysis of prediction according to the present invention. DETAILED DESCRIPTION

[0074] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0075] Regarding the information management method of this building construction, it is different from the existing information management method. The existing information management method cannot share and circulate information data in a timely manner, which makes it difficult to fully and accurately understand the construction situation, and lacks scientific and accurate evaluation methods, as well as dynamic adjustment and feedback mechanisms. This algorithm unit solves the problems and shortcomings of existing technologies through optimization and innovation means such as data integration and sharing, scientific evaluation and precise decision-making, and dynamic adjustment and feedback mechanisms, thereby improving construction efficiency, reducing cost risks, improving quality levels and enhancing decision-making capabilities.

[0076] For example, see Figures 1 to 4 This implementation provides an information management method for construction, and the specific implementation steps are as follows:

[0077] Step I: Use various sensors installed at the construction site and data acquisition modules to collect real-time data, and organize the data collected by the sensors in time series to form a time series data sequence;

[0078] Step II, extracting the collected data of the same time period from the time series data sequence;

[0079] Step II: Use the data information management module to calculate the construction efficiency evaluation value XLP, the cost-benefit analysis value CXF, and the quality risk prediction value ZL;

[0080] Step II-I: Evaluate the quality risk level of the construction project based on the quality risk prediction value ZL;

[0081] Step II-II: For the quality risk prediction value ZL and the quality risk prediction value ZL of the previous stage prev The comparison is based on the construction efficiency evaluation value XLP and the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev and formulate corresponding risk control measures;

[0082] The data information management module includes a unit for quantitatively evaluating construction efficiency, a unit for in-depth analysis of construction project cost-effectiveness, and a unit for predicting potential quality risks.

[0083] The sensors include quantity sensors, working time recorders, mechanical power monitors, material waste measurement devices, and rework measurement devices. The sensors are used to collect various data on the construction site in real time.

[0084] The equipment used in the data information management module includes an information platform, which includes a data processing module, an analysis module, and a visualization module, which are used to realize real-time data collection, analysis, sharing, and decision support;

[0085] The equipment used in the data acquisition module includes a data acquisition system, which is used to transmit the data collected by the sensor to the information platform in real time.

[0086] In this embodiment, the system forms a system for comprehensively evaluating and managing efficiency, cost and quality risks in the construction process through the mutual cooperation of three algorithm units. Combining the three operation results of XLP, CXF and ZL, they can provide managers with scientific and accurate evaluation results and prediction information, thereby helping them make more informed decisions and improvement measures. XLP is the construction efficiency evaluation value, which is used to evaluate the construction efficiency. By comprehensively considering the factors of the total number of operators SS, labor time L, mechanical power JG and loss ST, the efficiency level of the current construction process is obtained. CXF is the cost-benefit analysis value, which is based on the construction efficiency evaluation value XLP, combined with the total cost ZC, expected benefit Y, and additional benefit ES. The cost-benefit analysis value CXF is calculated based on the factors of the time period T to reflect the economic benefits of the construction project. ZL is the quality risk prediction value, which further considers the quality risk. By combining the cost-benefit analysis value CXF, defect rate QC, defect cost, time required to deal with defects and construction efficiency change rate XLB factors, the potential quality risks in the construction project are predicted. According to the calculation results of ZL and combined with the calculation results of XLP and CXF, it can also affect the calculation of XLP and CXF, so that the three algorithms of this system have high correlation and entanglement, and each plays an important role in the information management method of building construction, and jointly promotes the continuous improvement and development of construction projects through mutual correlation and cyclic influence.

[0087] See also Figures 1 to 4 , the calculation formula for quantitative evaluation of construction efficiency is as follows:

[0088] XLP = YG / SQRT(CL+F);

[0089] YG = [SS × (L + JG) - ST];

[0090] in:

[0091] XLP is the construction efficiency evaluation value;

[0092] YG is the effective workload;

[0093] SS is the total number of people, SS reflects the total number of operators involved in the construction;

[0094] L is the labor time, which reflects the number of hours actually put into work by the construction personnel;

[0095] JG is the mechanical power, JG represents the total power of the construction machinery;

[0096] ST is lost time, including non-productive time of downtime and waiting;

[0097] CL is the amount of material waste, which reflects the amount of material wasted during the construction process;

[0098] F is the rework amount, and F reflects the amount of work that needs to be redone due to quality issues.

[0099] In this embodiment: First, in this algorithm unit, the part "[SS×(L+JG)-ST]" first calculates the product of the total number of operators SS and the sum of the labor time L and the mechanical power JG, and then subtracts the loss time ST, which is actually the product of the effective working time and the mechanical power in the construction process, and then deducts the loss caused by the non-productive time of stopping work and waiting, and finally the effective workload YG can be obtained;

[0100] This embodiment combines the material waste amount CL and the rework amount F into a single measurement value to reflect the degree of resource waste in the construction process, and converts the weighted sum of the material waste amount CL and the rework amount F into a more comparable value through square root operation. This can balance the impact of resource waste of different scales on efficiency evaluation, so that smaller waste amounts can also be properly reflected in the evaluation. In addition, incorporating resource waste into the quantitative evaluation unit of construction efficiency can make the evaluation results more comprehensive and accurate, which helps managers to promptly discover resource waste problems in the construction process and take corresponding measures to improve them, thereby improving construction efficiency.

[0101] This embodiment quantitatively evaluates the construction efficiency and conducts quantitative unitization, so that the manager can reasonably adjust the number of operators, machine configuration and labor time, realize the optimal allocation of resources, reduce waste and improve resource utilization;

[0102] In addition, this embodiment also reduces the amount of material waste CL and the amount of rework F, and quantitatively evaluates the construction efficiency to help improve construction quality and safety, thereby reducing construction delays and cost increases caused by quality problems.

[0103] See also Figures 1 to 4 , the calculation formula for in-depth analysis of the cost-effectiveness unit of the construction project is as follows:

[0104] CXF=[XLP×(ZC-Y)+PBL] / (L+XLP);

[0105] PBL = SQRT[(XLP-XLP prev )×(ES / T)];

[0106] ES = SY-Y;

[0107] in:

[0108] CXF is the cost-benefit analysis value;

[0109] ZC is the total cost, including the cost of materials, labor, and machinery;

[0110] Y is the expected revenue, which reflects the revenue expected to be obtained after the construction is completed;

[0111] PBL is the average rate of change. PBL calculates the square root value of the additional benefit ES brought about by the change in construction efficiency relative to the time period T;

[0112] XLP prev It is the construction efficiency evaluation value of the previous stage;

[0113] ES is the additional benefit, which reflects the additional benefit obtained due to efficiency improvement;

[0114] SY is the actual return;

[0115] T is the time period, which reflects the time period of the current evaluation;

[0116] X is the adjustment factor, which is used to adjust other factors in cost-effectiveness analysis.

[0117] In this embodiment, first, “XLP×(ZC-Y)” is used to evaluate the impact of construction efficiency on cost-effectiveness, that is, the higher the construction efficiency, the better the cost-effectiveness, and “SQRT[(XLP-XLP prev )×(ES / T)]” This formula calculates the construction efficiency change (XLP-XLP prev ) and the additional benefit EES, and considers the impact of the time period T to evaluate the economic benefits brought about by the improvement or reduction of construction efficiency. This helps managers understand the direct impact of changes in construction efficiency on the overall economic benefits of the project. The "(L+XLP)" part calculates the sum of the product of labor time L and the construction efficiency evaluation value XLP, which actually considers the comprehensive impact of construction time and construction efficiency on cost-benefit analysis;

[0118] This embodiment helps managers to better control costs, thereby reducing unnecessary expenses and improving the cost-effectiveness of projects by deeply analyzing the total cost ZC and expected benefit Y factors in the cost-effectiveness unit of the construction project;

[0119] In-depth analysis of the additional benefits ES and time period T factors in the cost-effectiveness unit of the construction project encourages managers to obtain more additional benefits ES by improving construction efficiency and shortening construction period, so as to further improve the economic benefits of the project.

[0120] See also Figures 1 to 4 , the calculation formula for predicting potential quality risk units is as follows:

[0121] ZL=[CXF×(1-QC)-SQRT((CXF-CXF prev )×(QC / QT))]×(1+XLB);

[0122] XLB=(XLP-XLP prev ) / XLP;

[0123] QT=(QXS / ZSL)×100%;

[0124] in:

[0125] ZL is the quality risk prediction value;

[0126] QC is the defect rate, which reflects the proportion of defects in the construction project;

[0127] QXS is the number of defects, and ZSL is the total inspection number;

[0128] CXF prev is the cost-benefit analysis value of the previous stage;

[0129] QT is the additional cost increase, which reflects the cost increase caused by defects, including labor costs, material costs, and equipment costs incurred in repairing defects;

[0130] XLB is the construction efficiency change rate.

[0131] In this embodiment, the algorithm unit first calculates the actual cost benefit after deducting the defect cost, and then calculates the actual cost benefit after deducting the defect cost. prev The calculation significance of “(1+XLB)” is the correlation between cost-effectiveness change and defect cost, and the calculation function of “(1+XLB)” is used to adjust the quality risk prediction value, considering the impact of construction efficiency change on quality risk;

[0132] This embodiment predicts potential quality risk units, so that managers can discover potential quality risks in construction projects in advance, and take preventive measures according to the additional cost increase QT problem caused by the defect rate QC to avoid the occurrence of quality problems, thereby reducing construction delays and cost increases caused by quality problems;

[0133] Predict the construction efficiency change rate XLB factor in potential quality risk units, and encourage managers to further reduce quality risks by continuously improving construction methods and processes, improving construction efficiency and quality levels.

[0134] See also Figures 1 to 4 , the quality risk prediction value ZL and the quality risk prediction value ZL of the previous stage prev The comparative analysis is as follows:

[0135] If the quality risk prediction value ZL is lower than the quality risk prediction value ZL of the previous stage prev , then the quality risk is considered to be reduced and the current quality control measures should be maintained;

[0136] If the quality risk prediction value ZL is higher than the quality risk prediction value ZL of the previous stage prev , it is considered that the quality risk has increased, and corresponding quality improvement measures should be taken according to the specific reasons;

[0137] Based on the quality risk prediction value ZL being higher than the quality risk prediction value ZL of the previous stage prev The situation is combined with the construction efficiency evaluation value XLP and the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev The comparative analysis is as follows:

[0138] Construction efficiency evaluation value XLP and construction efficiency evaluation value XLP of the previous stage prev comparative analysis;

[0139] If the construction efficiency evaluation value XLP is lower than the construction efficiency evaluation value XLP of the previous stage prev , it is considered that there are problems with insufficient skills of construction workers, machinery failure, unreasonable material supply and construction process. Appropriate improvement measures should be taken for specific problems, including training of construction workers, repair and replacement of machinery, optimization of material supply process and adjustment of construction process;

[0140] If the construction efficiency evaluation value XLP is higher than the construction efficiency evaluation value XLP of the previous stage prev , it is believed that construction efficiency has been improved and the current construction methods and processes should be maintained;

[0141] Cost-benefit analysis value CXF and cost-benefit analysis value CXF in the previous stage prev comparative analysis;

[0142] If the cost-benefit analysis value CXF is lower than the cost-benefit analysis value CXF of the previous stage prev , it is considered that there is an increase in costs due to a decrease in construction efficiency and a decrease in revenue due to changes in market demand. According to the specific reasons, corresponding cost control strategies and revenue improvement measures are adopted, including optimizing the construction process, reducing material costs, improving construction quality and adjusting sales strategies;

[0143] If the cost-benefit analysis value CXF is higher than the cost-benefit analysis value CXF of the previous stage prev , it is believed that cost-effectiveness has improved and cost-saving measures and profit-enhancing strategies should be maintained.

[0144] In this embodiment, the cyclical influence of the algorithm unit on the quantitative evaluation unit of construction efficiency based on the prediction of potential quality risk unit is mainly reflected in the feedback and adjustment of the quality risk prediction result on the construction efficiency evaluation value. By predicting the potential quality risk unit, the manager can discover the quality risk in advance and take corresponding preventive measures. At the same time, with the improvement of construction efficiency, the construction efficiency evaluation value XLP in the quantitative evaluation unit of construction efficiency will also increase accordingly.

[0145] It is worth noting that in the construction process, quality risk is an important factor that cannot be ignored. By regularly comparing the quality risk prediction value ZL, project managers can discover potential quality problems in a timely manner. This timely identification capability is crucial because it allows managers to take preventive measures before the problem becomes serious. Specifically, when the quality risk prediction value ZL shows that the quality risk increases, managers can immediately start the quality review process to check whether there are problems with construction materials, construction processes and construction personnel. This timely intervention can not only avoid the cost increase caused by quality problems, but also prevent construction delays, thereby ensuring that the project is completed on time and with quality.

[0146] Furthermore, after identifying quality risks, it is crucial to take targeted measures. Specifically, by comparing the changes in the construction efficiency evaluation value XLP and the cost-benefit analysis value CXF, project managers can accurately identify the key factors that affect construction efficiency and cost-effectiveness. If the construction efficiency evaluation value XLP decreases, it means that there are bottlenecks in the construction process and the construction personnel lack skills. Similarly, if the cost-benefit analysis value CXF decreases, it indicates cost overruns and insufficient benefits. Through precise policy implementation, project managers can solve problems more effectively and improve construction efficiency and cost-effectiveness.

[0147] The construction process is a process of continuous improvement. By constantly comparing and feeding back the values ​​of quality risk prediction value ZL, construction efficiency evaluation value XLP and cost-benefit analysis value CXF, project managers can continuously optimize the construction process, improve construction efficiency and quality level, and reduce cost risks.

[0148] In summary, by timely identifying risks, implementing precise policies and making continuous improvements, project managers can more effectively manage the construction process, improve construction efficiency and quality, and reduce cost risks. These beneficial effects not only contribute to the smooth completion of the project, but also provide valuable experience and reference for future construction projects.

[0149] For example 2, please refer to Figures 1 to 4 , SQRT is the abbreviation of square root, which means performing a square root operation on a number in mathematics;

[0150] In the quantitative evaluation unit of construction efficiency, it is used to calculate the square root of the sum of material waste CL and rework F to balance the impact of different scales of resource waste on efficiency evaluation;

[0151] In the unit of in-depth analysis of construction project cost-effectiveness, it is used to calculate the square root value of the difference in construction efficiency change and the additional benefit ES relative to the time period T. This calculation step evaluates the contribution of the change in construction efficiency to the additional benefit and takes into account the impact of the time period T;

[0152] In the unit for predicting potential quality risks, the calculation step is used to calculate the difference in cost-effectiveness changes and the square root value of the defect cost QC relative to the time QT required to handle the defect. This calculation step evaluates the associated impact between cost-effectiveness changes and defect costs.

[0153] In this embodiment, the quantitative evaluation of construction efficiency is performed by using a square root operation, which can make the impact of different scales of resource waste on efficiency evaluation more balanced, thereby improving the accuracy of the evaluation. The result after the square root is used as the denominator and divided by the effective workload, which can more intuitively reflect the degree of resource waste in the construction process.

[0154] In-depth analysis of the cost-effectiveness of construction projects. By calculating the square root value between the change in construction efficiency and the additional income, the economic benefits brought about by the improvement or reduction of construction efficiency can be evaluated. The square root operation can balance the impact of efficiency changes of different scales on the results, making the evaluation results more robust and reliable. By dividing the additional income by the time period and calculating the square root value, it can reflect the continuous impact of changes in construction efficiency on the economic benefits of the project over a long period of time.

[0155] The potential quality risk prediction unit can reflect the potential quality risks in the construction project by calculating the square root value between the cost-benefit change and the defect cost. The square root operation can balance the impact of benefit changes and cost increases of different scales on the results, making the evaluation results more accurate and reliable. In addition, the calculation results can provide decision-making support for managers, helping them understand the potential quality risks in the construction project and take corresponding measures to reduce the risks.

[0156] In summary, the calculation purpose and significance of SQRT in quantitative evaluation of construction efficiency in units one, two and three are different, but they all aim to improve the accuracy, reliability and robustness of the evaluation, thereby providing strong support for efficiency, cost and quality risk management in the construction process.

[0157] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The information management method for building construction is characterized by: The specific implementation steps are as follows: Step I: Use various sensors installed at the construction site and data acquisition modules to collect real-time data, and organize the data collected by the sensors in time series to form a time series data sequence; Step II, extracting the collected data of the same time period from the time series data sequence; Step II: Use the data information management module to calculate the construction efficiency evaluation value XLP, the cost-benefit analysis value CXF, and the quality risk prediction value ZL; Step II-I: Evaluate the quality risk level of the construction project based on the quality risk prediction value ZL; Step II-II: For the quality risk prediction value ZL and the quality risk prediction value ZL of the previous stage prev and combined the construction efficiency evaluation value XLP with the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev and formulate corresponding risk control measures; Among them, the data information management module includes a unit for quantitatively evaluating construction efficiency, a unit for in-depth analysis of the cost-effectiveness of construction projects, and a unit for predicting potential quality risks.

2. The information management method for building construction according to claim 1 is characterized in that: The sensors include quantity sensors, work time recorders, mechanical power monitors, material waste quantity measuring instruments, and rework quantity measuring instruments; The equipment used by the data information management module includes an information platform, which includes a data processing module, an analysis module, and a visualization module; The equipment used by the data acquisition module includes a data acquisition system, and the data acquisition system is used to transmit the data collected by the sensor to the information platform in real time.

3. The information management method for building construction according to claim 2 is characterized in that: The calculation formula for the quantitative evaluation unit of construction efficiency is as follows: XLP = YG / SQRT(CL+F); YG = [SS × (L + JG) - ST]; in: XLP is the construction efficiency evaluation value; YG is the effective workload; SS is the total number of people, SS reflects the total number of operators involved in the construction; L is the labor time, which reflects the number of hours actually put into work by the construction personnel; JG is the mechanical power, JG represents the total power of the construction machinery; ST is lost time, including non-productive time of downtime and waiting; CL is the amount of material waste, which reflects the amount of material wasted during the construction process; F is the rework amount, and F reflects the amount of work that needs to be redone due to quality issues.

4. The information management method for building construction according to claim 3 is characterized in that: The calculation formula for the in-depth analysis of the cost-effectiveness unit of the construction project is as follows: CXF=[XLP×(ZC-Y)+PBL] / (L+XLP); PBL=SQRT[(XLP-XLP prev )×(ES / T)]; ES = SY-Y; in: CXF is the cost-benefit analysis value; ZC is the total cost, including the cost of materials, labor, and machinery; Y is the expected revenue, which reflects the expected revenue after the construction is completed; PBL is the average rate of change. PBL calculates the square root value of the additional benefit ES brought about by the change in construction efficiency relative to the time period T; XLP prev It is the construction efficiency evaluation value of the previous stage; ES is the additional benefit, which reflects the additional benefit obtained due to efficiency improvement; SY is the actual return; T is the time period, which reflects the time period of the current evaluation.

5. The information management method for building construction according to claim 4 is characterized in that: The calculation formula for predicting potential quality risk units is as follows: ZL=[CXF×(1-QC)-SQRT((CXF-CXF prev )×(QC / QT))]×(1+XLB); XLB=(XLP-XLP prev ) / XLP; QT=(QXS / ZSL)×100%; in: ZL is the quality risk prediction value; QC is the defect rate, which reflects the proportion of defects in the construction project; QXS is the number of defects, and ZSL is the total inspection number; CXF prev is the cost-benefit analysis value of the previous stage; QT is the additional cost increase, which reflects the cost increase caused by defects, including labor costs, material costs, and equipment costs incurred in repairing defects; XLB is the construction efficiency change rate.

6. The information management method for building construction according to claim 5 is characterized in that: The quality risk prediction value ZL is the same as the quality risk prediction value ZL of the previous stage. prev The comparative analysis is as follows: If the quality risk prediction value ZL is lower than the quality risk prediction value ZL of the previous stage prev , then the quality risk is considered to be reduced and the current quality control measures should be maintained; If the quality risk prediction value ZL is higher than the quality risk prediction value ZL of the previous stage prev , it is considered that the quality risk has increased, and corresponding quality improvement measures should be taken according to the specific reasons.

7. The information management method for building construction according to claim 6 is characterized in that: Based on the fact that the quality risk prediction value ZL is higher than the quality risk prediction value ZL of the previous stage prev The situation is combined with the construction efficiency evaluation value XLP and the construction efficiency evaluation value XLP of the previous stage. prev Comparison of the cost-benefit analysis value CXF and the cost-benefit analysis value CXF in the previous stage prev The comparative analysis is as follows: Construction efficiency evaluation value XLP and construction efficiency evaluation value XLP of the previous stage prev comparative analysis; If the construction efficiency evaluation value XLP is lower than the construction efficiency evaluation value XLP of the previous stage prev , it is considered that there are problems with insufficient skills of construction workers, machinery failure, unreasonable material supply and construction process. Appropriate improvement measures should be taken for specific problems, including training of construction workers, repair and replacement of machinery, optimization of material supply process and adjustment of construction process; If the construction efficiency evaluation value XLP is higher than the construction efficiency evaluation value XLP of the previous stage prev , it is believed that construction efficiency has been improved and the current construction methods and processes should be maintained; Cost-benefit analysis value CXF and cost-benefit analysis value CXF in the previous stage prev comparative analysis; If the cost-benefit analysis value CXF is lower than the cost-benefit analysis value CXF of the previous stage prev , it is considered that there is an increase in costs due to a decrease in construction efficiency and a decrease in revenue due to changes in market demand. According to the specific reasons, corresponding cost control strategies and revenue improvement measures are adopted, including optimizing the construction process, reducing material costs, improving construction quality and adjusting sales strategies; If the cost-benefit analysis value CXF is higher than the cost-benefit analysis value CXF of the previous stage prev , it is believed that cost-effectiveness has improved and cost-saving measures and profit-enhancing strategies should be maintained.

8. The information management method for building construction according to claim 5 is characterized by: SQRT is the abbreviation of square root, which means performing a square root operation on a number in mathematics; In the quantitative evaluation unit for construction efficiency, it is used to calculate the square root of the sum of the material waste CL and the rework F, so as to balance the impact of different scales of resource waste on efficiency evaluation; In the in-depth analysis of the construction project cost-effectiveness unit, it is used to calculate the square root value of the difference in construction efficiency change and the additional benefit ES relative to the time period T. This calculation step evaluates the contribution of the construction efficiency change to the additional benefit and takes into account the impact of the time period T; In the potential quality risk prediction unit, the cost-effectiveness change difference and the square root value of the defect cost QC relative to the time QT required to handle the defect are calculated. This calculation step evaluates the correlation impact between the cost-effectiveness change and the defect cost.

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