900 results about "Material consumption" patented technology

The invention relates to the technical field of cost control, in particular to a project cost progress management control method and system, and the method comprises the following steps: collecting attendance equipment material data, combining and calculating resource expenditure density, deducing cost pressure in combination with processes and positions to generate a pressure value sequence, and superposing payment records to calculate daily payment intensity; inputting an abnormal factor algorithm to detect deviation to generate a response fault, analyzing process change to screen a risk section to generate a structural fault, extracting a progress and payment intensity ratio to screen an asynchronous period, constructing a control time axis to analyze a relationship between expenditure density and payment intensity slope, and generating a progress management control result set. Attendance checking, equipment operation and material consumption data are collected to derive cost pressure, abnormal deviation is recognized, risks are early warned, the process and resource change trend is analyzed, the relationship between progress and payment intensity is coordinated, the precision, real-time performance and response efficiency of cost control are improved, and it is guaranteed that a project investment target is smoothly achieved.

The invention relates to the technical field of storage scheduling, in particular to an oryzanol production-oriented intelligent storage cache scheduling method and system. Acquiring batch information of the materials entering the warehousing system; in the material storage process, initial physical feature data of the materials are collected through online sensing equipment; according to the initial physical characteristic data, establishing a mass attenuation model for each material batch, and performing identification based on the mass attenuation model to obtain material attenuation data; production material consumption demands in a future period are periodically obtained, analysis is performed based on material attenuation data and production material consumption data, and potential value loss, task quality matching loss and warehousing operation cost loss of materials are balanced; and generating a storage scheduling strategy which has the minimum comprehensive loss in the period and plans a material batch calling sequence according to a time sequence. According to the invention, the automatic instruction is generated and issued through the storage scheduling strategy to guide material delivery.

The invention discloses an intelligent control system and method for shot blasting equipment based on multi-modal perception, and relates to the technical field of industrial surface treatment.The intelligent control system and method for the shot blasting equipment based on the multi-modal perception have the advantages that a technological parameter self-evolution decision-making mechanism with deep reinforcement learning as a core and real-time feedback of discharging quality as a system is established; the shot blasting process is converted from static experience setting to dynamic model driving, a process parameter optimization model serves as a deep reinforcement learning agent, instant reward functions of processing quality, energy consumption, material consumption and equipment loss are comprehensively considered, and the function guide model pays attention to whether the final quality reaches the standard or not, and also pays attention to the real-time reward functions of the processing quality, the energy consumption, the material consumption and the equipment loss. And meanwhile, the comprehensive economic benefits of the whole process are actively optimized, the quality evaluation and prediction model performs real-time and quantitative analysis on visual images of discharged workpieces, and immediately feeds back results to the decision model, so that the system has the learning ability, and autonomously explores and converges to an optimal process parameter combination for specific workpieces and specific states.

The invention discloses an intelligent control system and control method for a flue gas environment-friendly island, belongs to the technical field of flue gas treatment, and solves the problem of how to improve the working condition adaptability, response speed and prediction precision of the environment-friendly island. According to the technical scheme, through intelligent integrated control over a plurality of subsystems in the denitration, dust removal and desulfurization processes, the working condition adaptability, the response speed and the prediction precision of the environment-friendly island are improved, on the premise that standard emission of pollutants is guaranteed, the comprehensive operation efficiency of all the process links is remarkably improved, energy consumption, material consumption and equipment loss are reduced, and the economic benefit is improved. According to the invention, an edge computing device can be used as an external communication module of a DCS, online robust operation is realized, the method is especially suitable for an environmental protection island SCR system in various flue gas treatment fields, safe, efficient and economical intelligent operation of the flue gas environmental protection island system can be realized on the premise of not changing original control logic, and the system has a wide application prospect. And the method has a wide popularization prospect and a remarkable industrial practical value.

The utility model discloses hollow half shaft forming equipment, which belongs to the field of manufacturing of automobile parts and comprises a graded reducing device, a hollow half shaft forming device and a hollow half shaft forming device. The spline cold extrusion device is used for extruding an internal spline on the hollow half shaft blank; the grading hole shrinkage device comprises a first hole shrinkage die, a second hole shrinkage die and a third hole shrinkage die, wherein the first hole shrinkage die is used for extruding the shape of a hollow half shaft on a hollow half shaft blank; the second reducing die is used for reducing and forming the hollow half shaft blank output by the first reducing die to a target diameter; the first reducing die, the second reducing die and the cold extrusion spline device are matched, the cold-rolled steel pipe is used as a hollow half shaft blank for multiple times of reducing forming of the hollow half shaft, material consumption can be reduced, and meanwhile the undesirable phenomena of center hole eccentricity, uneven wall thickness and the like when a special-shaped deep hole is machined in a charge bar can be avoided.

The invention discloses a purchase demand prediction method combined with PMC material management and control, and belongs to the technical field of material management and control data processing, and the method comprises the steps: obtaining a material consumption sequence and corresponding timestamp data, and employing a time sequence decomposition method to separate trend components and seasonal components, and obtaining a consumption rule feature sequence; if the fluctuation amplitude of the consumption rule feature sequence exceeds a preset threshold value, determining the consumption rule feature sequence as a basic demand predicted value sequence; obtaining a market price index sequence, and calculating a correlation coefficient between the basic demand predicted value sequence and the market price index sequence; if the absolute value exceeds a set threshold value, updating a basic demand predicted value sequence through a time sequence model; generating a purchase plan sequence according to the basic demand predicted value sequence and the inventory average value; and generating a final output report. The invention discloses a problem that a current material management and control mode cannot capture key changes in time and is difficult to balance contradictions between inventory and production.

The invention discloses a connecting structure of frameless torque motor flat wire windings, which belongs to the technical field of frameless torque motors, and comprises a stator consisting of a stator core and windings, the stator core comprises stator slots and tooth parts, each phase of winding consists of N sets of two groups of flat wire coils, the width of the flat wire coil is gradually increased from the inner diameter side of the stator to the outer diameter side of the stator, the current direction of the coil accords with regular circulation of positive and negative and positive, each set of coil connecting wire is formed by connecting in the same layer, and compared with a coil with the outer side and the inner side connected with a cross-layer wire, the end space can be reduced, and the end height can be reduced. Compared with a round wire winding, the connection structure of the frameless torque motor flat wire winding has the advantages that the slot fullness rate can be increased, the motor efficiency is high, the stability is improved, the space utilization in a stator slot can be greatly improved through a specific wire connection mode, the space waste in the slot is reduced, the windings are more compact, the overall consumables are less, and the connection and assembly are more convenient.

The invention relates to the technical field of furniture production management, and discloses an intelligent management method and system for furniture production. The method comprises the following steps: collecting production data such as material consumption, equipment operation parameters and process completion time of each process node on a production line in real time; performing multi-dimensional feature extraction on the data to generate a comprehensive feature set containing time sequence, statistical and associated features; dividing continuous production stages according to a characteristic dynamic change rule and distributing identifiers; based on the identifier recombination data, calculating a transition probability matrix between adjacent stages; identifying a potential abnormal stage and generating a mark sequence by analyzing a state jump abnormal mode in the matrix; constructing a quality prediction model in combination with the abnormal mark and the real-time data, and outputting a quality prediction score of each process node; dynamically adjusting a procedure production parameter configuration scheme according to the deviation degree of the score and a preset threshold value; and performing similarity matching on the adjusted scheme and historical optimal configuration, and screening a to-be-verified configuration set to perform a simulation test.

The invention discloses a shared lock catch steel pipe pile cofferdam close to a bridge bearing platform under a high-speed railway line and a construction method, and the shared lock catch steel pipe pile cofferdam close to the bridge bearing platform under the high-speed railway line comprises a first lock catch steel pipe pile, a second lock catch steel pipe pile, a third lock catch steel pipe pile and a fourth lock catch steel pipe pile, the third lock catch steel pipe pile and the fourth lock catch steel pipe pile are connected with the first lock catch steel pipe pile and the second lock catch steel pipe pile. The lock catch steel pipe pile cofferdam is adopted to replace a double-wall steel cofferdam, the problems that the clear distance close to a bridge bearing platform is too small, and no space exists for independently arranging an overwater steel cofferdam are solved, and under the condition that two projects are both control projects and need to be constructed synchronously, a row of shared lock catch steel pipe piles are inserted in the middle to be used in the construction stage of the two bridge bearing platforms at the same time; an independent and separated cofferdam stress system is formed, the condition of synchronous construction of the two newly-built bridges is guaranteed, the using number of the steel pipe pile cofferdams is reduced, and material consumption is reduced.

The invention discloses a connecting structure of frameless torque motor flat wire windings, which belongs to the technical field of frameless torque motors, and comprises a stator consisting of a stator core and windings, the stator core comprises stator slots and tooth parts, each phase of winding consists of N sets of three groups of flat wire coils, the width of the flat wire coil is gradually increased from the inner diameter side of the stator to the outer diameter side of the stator, the connecting line of the first group of coil and the second group of coil of each set of coil is formed by overturning from the inner side of the stator to the outer side of the stator, and the connecting line of the second group of coil and the third group of coil of each set of coil is formed by connecting on the same layer close to the inner side of the stator. Compared with a traditional pear-shaped groove for placing a round wire winding, the connection structure of the frameless torque motor flat wire winding has the advantages that the groove fullness rate can be increased, the motor efficiency is high, the stability is improved, the utilization rate of the space in a stator groove can be greatly improved through a specific connection mode, the waste of the space in the groove is reduced, the windings are more compact, the overall material consumption is less, and the connection and the assembly are more convenient.

This invention belongs to the field of welding fixture technology, specifically a PCB board welding fixture and its welding method; it includes a fixture table; a lifting and suspending assembly is provided on the fixture table; the lifting and suspending assembly includes a lifting square tube, which is connected through to the top of a placement frame, and the two are slidably engaged; the end of the lifting square tube near the fixture table is open and slidably connected to a lifting square column; the end of the lifting square tube away from the fixture table contacts the PCB board; an air storage rectangular frame is located on the top of the fixture table; the placement frame is located inside the air storage rectangular frame; the air storage rectangular frame is provided with a light-touch anti-damage device; it avoids displacement caused by excessively loose clamping and damage caused by excessively tight clamping, while reducing surface damage caused by excessive local pressure, reducing material consumption and production costs, and improving the welding qualification rate and effect of the PCB board, thus reducing the limitations of welding fixtures in application.

The invention discloses an engineering material consumption compliance auditing method and system based on a Transform model, and the method comprises the steps: multi-source data collection: collecting time dimension data, space dimension data, material consumption data and construction risk factor data, which are required by engineering construction, in a manner of combining automatic collection with manual input supplement; based on a Transform model, multi-source data including time dimension data, space dimension data, material consumption data and construction risk factor data in a construction process are acquired, and a space-time attention auditing network including a time attention layer and a space attention layer is constructed, so that construction dynamic change can be captured in real time; the time-space information is fused and is brought into the influence of the risk factor, real-time dynamic auditing is realized, the abnormal material consumption is warned in time, the hysteresis and accuracy defects of a traditional method are effectively solved, and the engineering fine management requirement is met.

The invention provides a truss structure autonomous design system and method based on multiple agents. A layered multi-agent architecture is adopted, a general control agent is taken as a core, and a high-level design intention is analyzed and a plurality of downstream special agents are arranged for cooperative work; the whole design process realizes automatic closed loop through a graph-based workflow engine; the core innovation of the method is a hybrid intelligent optimization algorithm of LLM heuristic exploration and genetic algorithm accurate fine tuning, and the algorithm is driven by an original and quantifiable design quality scoring system to efficiently carry out analysis-diagnosis-optimization iteration so as to cooperatively improve the safety and economy of the design. The design time can be shortened from several hours to several minutes, about 7.0% of material consumption is saved on average, it is ensured that the scheme completely conforms to industry specifications, the design efficiency, economy and reliability are greatly improved, and meanwhile the use threshold of professional design software is remarkably reduced through natural language interaction.

A Comprehensive Energy-Saving and Carbon-Negative system (CESCN) includes a Carbon-negative Emissions Device (CED) based on Carbon Capture, Utilization and Storage (CCUS). CED can obtain a carbon emission reduction target from a current Industry 4.2-Green intelligent Manufacturing (14.2-GiM) system, and then collect the material consumption and equipment operation energy consumption data of the CCUS process of CED through a Cyber Physical Agent (CPA) which is the Internet of Things (IoT) component. An intelligent method is used to identify the execution progress of CCUS and improve the automation and intelligent operation of CCUS. The CESCN can effectively reduce the manpower requirements of implementing CCUS and the overall energy consumption of the production line. In addition, it can calculate the amount of the carbon reduction, the amount of the carbon offset and amount of feasible carbon trading according to the amount of carbon fixation.

The application discloses a power transmission line assembled rock anchor rod foundation and a construction method, which optimizes and combines an assembled pole tower foundation and a rock anchor rod foundation to form an assembled rock anchor rod foundation, divides a bearing platform and a main column part into a plurality of prefabricated components according to certain sizes, prefabricates the bearing platform bottom plate, the side plate and the main column in a factory in advance, transports the prefabricated bearing platform prefabricated components and the main column prefabricated components to a construction site for assembly, improves foundation construction quality, reduces on-site concrete maintenance time and material consumption of the pole tower foundation, shortens a construction period, reduces construction cost of the pole tower foundation, reduces environmental problems in the construction process, expands the use range of the anchor rod foundation and the assembled foundation, is beneficial to promoting mechanical construction of power transmission and transformation projects, and has good social and economic benefits and engineering application value.

The invention discloses a mobile platform for DCM construction of a deep soft foundation in a swell sea area. The mobile platform comprises a suction bucket foundation, a track beam, a sliding system and a bearing platform. The suction bucket foundation is positioned below the track beam; the bearing platform is slidably arranged on the track beam through the sliding system, the suction bucket foundation comprises a suction bucket, a pumping and filling device and a buoyancy pile, the suction bucket is of a bucket-shaped structure with a closed upper end and an open lower end, one end of the buoyancy pile is fixedly connected with the suction bucket, and the other end of the buoyancy pile is used for supporting the track beam; water is pumped out of the suction bucket through the pumping and filling device, sinking and penetrating of the suction bucket foundation are achieved, air is inflated into the suction bucket through the pumping and filling device, floating of the suction bucket foundation is achieved, the suction bucket foundation is adopted, the platform foundation is suitable for deep and thick soft soil areas, rapid installation and pulling-out of the platform foundation can be achieved, recycling is achieved, and the material consumption is reduced. The influence of medium and long period surges on DCM equipment construction can be effectively reduced, the operation window is greatly improved, and the construction efficiency is effectively improved.

The invention relates to a power distribution network project material consumption prediction method, and the method is used for predicting the material consumption of a new project having high similarity with a historical project, and comprises the steps: obtaining a new project material receiving table, historical project basic information and historical material receiving information, and carrying out the matching of a historical similar project similar to the new project; determining material subclasses of newly added projects based on material picking conditions of historical similar projects, and carrying out material consumption prediction from a specific material coding dimension according to an expected consumption quantity of the material subclasses; based on the historical work order picking time and the new work order starting time, predicting the material picking time of each material subclass; and obtaining a final material consumption prediction result in combination with the expected consumption quantity of the predicted material coding dimension and the predicted material receiving time. Compared with the prior art, different strategies are adopted for different types of businesses to carry out sub-item prediction, and material consumption prediction with higher fineness and accuracy is obtained.

The invention relates to the technical field of intelligent manufacturing and digital service, and discloses an online quotation method and system for 3D printing parts. An online quotation method for 3D printing parts comprises the following steps that S1, order information is obtained, feature parameters are extracted from the order information, and the feature parameters comprise geometric parameters, process parameters and material attribute parameters of to-be-printed parts; s2, the material consumption cost and the printing time cost of the to-be-printed part are calculated according to the feature parameters, and the total cost is obtained by integrating the material consumption cost and the printing time cost; and S3, calculating according to the total cost and a preset gross profit rate to obtain a final quotation. The method can also adapt to different part characteristics and printing requirements, and effectively solves the problems of low efficiency and insufficient standardization of a traditional quotation mode.

The invention discloses a process for preparing synthesis gas by non-catalytic and catalytic coupling of hydrocarbon-containing raw material gas. The process comprises the following steps: (S1) dividing preheated raw material gas into first raw material gas and second raw material gas; (S2) introducing the first raw material gas, water vapor and preheated oxygen into a non-catalytic reactor, and carrying out a non-catalytic conversion reaction to generate first synthesis gas; (S3) introducing the second raw material gas and supplemented water vapor into a pre-catalytic reactor, and carrying out pre-catalytic conversion reaction to generate second synthesis gas; (S4) introducing the first synthesis gas and the second synthesis gas into a catalytic reactor, and carrying out catalytic conversion reaction to prepare third synthesis gas; and (S5) carrying out heat recovery on the prepared third synthesis gas to obtain the synthesis gas. According to the invention, the non-catalytic conversion reaction and the catalytic conversion reaction are coupled, so that the material consumption is greatly reduced, and meanwhile, heat is provided for the catalytic conversion reaction through the non-catalytic conversion reaction, so that the heat is recovered to a great extent.

The invention relates to the field of pressing equipment, and discloses a pull rod pre-pressing type pressing mechanism and a pre-tightening force applying method thereof. The mechanism comprises a fixed plate, a movable plate, a pull rod, a pre-tightening rod, a mold locking unit and a mold moving unit, initial pressure stress is applied to the pull rod through a pre-tightening structure, the tensile stress level of the pull rod in work is reduced, and the safety is improved by combining a double-insurance mechanism of the pull rod and the pre-tightening structure. The pre-tightening force is transmitted to the pull rod through the pre-tightening rods, the pre-tightening nuts and the pre-tightening plates, and the adjacent pre-tightening rods can be combined to optimize the structure. The fatigue life of the pull rod can be remarkably prolonged, crack propagation is restrained, material consumption is reduced, cost is reduced, and meanwhile safety accidents caused by failure of a single component are avoided.

The invention provides a support-free formwork system for a post-cast strip and a construction method, and relates to the technical field of building construction. The support-free formwork system for the post-cast strip and the construction method comprise the following steps that S1, on the basis of BIM model data, a variable density method topological optimization algorithm is adopted for formwork unit design, a lightweight structure of a modular formwork is generated through a parametric modeling technology, and a finite element analysis method is applied to verify the structural strength; and generating a parameterized template layout scheme. Through combination of a variable density method topological optimization algorithm and a parametric modeling technology, lightweight design of a template unit is realized, the material consumption is reduced on the premise of ensuring the structural strength, the design reliability is ensured through verification of a finite element analysis method, and the processing logic breaks through a traditional empirical design mode and has a good application prospect. A heuristic path planning algorithm and a laser positioning system work cooperatively, the three-dimensional assembly precision is improved, the mechanical connection stability is guaranteed through a torque control method, and a space self-locking network is formed.

The invention discloses a double-support rotary full-bore throttle valve and a station switching method. Through the core assembly composed of the actuator, the valve rod, the rotary valve element, the double-end bearing supports and the like, a stress model is optimized into a stable simply supported beam structure from a traditional cantilever beam structure, vibration caused by fluid impact is remarkably restrained, and the operation stability of the whole machine is enhanced. The rotary valve core is integrated with a variable-cross-section throttling molded surface, a large-diameter full-bore flow channel and a cut-off molded surface, so that the equipment not only can realize continuous adjustment of flow and pressure, but also can perform on-line blockage removal and pollution discharge by rotating and switching to a full-bore state under the condition of not closing an upstream valve and a downstream valve, and the maintenance process is greatly simplified. In addition, according to the design, the axial telescopic space is omitted through the rotary motion principle, a valve element sleeve protection structure is omitted through high stability, the equipment size and material consumption are effectively reduced, and the beneficial effects of being high in function integration degree, high in erosion resistance, long in service life and the like are achieved.

The invention discloses a power distribution network construction material demand analysis and prediction method, which comprises the following analysis and prediction steps: S1, collecting historical material data of a power distribution network construction project, the historical material data comprising project attribute data and material usage data; s2, preprocessing the material consumption data, including data cleaning, standardization and normalization processing; s3, carrying out dimension reduction processing on the material data based on a principal component analysis method; s4, performing clustering analysis on the material project attributes based on a clustering analysis algorithm; s5, parameters of the extreme learning machine are optimized based on a particle swarm algorithm, the optimized extreme learning machine is adopted to construct a power distribution network construction material demand prediction model, and the number and amount of power distribution network construction material demands are predicted; the system can effectively improve the material management level of a power enterprise, and improves the efficiency and quality of a material demand plan.

The invention provides a resin tower regeneration cycle optimization method based on an AI algorithm. The method comprises the following steps: S1, continuously monitoring the calcium and magnesium ion concentration of salt water at an outlet of a resin tower on line; s2, collecting operation parameters associated with the adsorption process of the resin tower, wherein the operation parameters comprise the salt water double-alkali excess alkali amount, turbidity, pH, ORP, flow, temperature and resin tower pressure difference; s3, constructing a resin adsorption capacity dynamic prediction model and a resin tower outlet calcium and magnesium content dynamic prediction model based on the calcium and magnesium ion concentration monitored in the step S1 and the operation parameters collected in the step S2; and S4, constraint conditions are set through a multi-objective optimization algorithm, a regeneration opportunity decision matrix is generated based on the real-time prediction data of the two dynamic prediction models constructed in the step S3, and the constraint conditions are used for judging whether a resin tower regeneration program is triggered or not. Dynamic optimization of the regeneration period of the resin tower can be realized, the quality of saline water is guaranteed, the regeneration frequency and material consumption are reduced, the production cost of an enterprise is reduced, and the operation efficiency of the resin tower is improved.

The invention provides a material collaborative distribution method in an electric forklift assembly process, and relates to the technical field of intelligent logistics and production management, and the method comprises the steps: obtaining the material demand prediction data of each station through employing a time-phased material consumption prediction model based on the material demand information of an electric forklift assembly station; and in combination with the material storage position information, a cooperative distribution path of multiple distribution vehicles is calculated by adopting an improved ant colony algorithm, the cooperative distribution path is decomposed according to the material distribution emergency degree, a material distribution task sequence is generated, and distribution task adjustment is performed in a task interaction area by adopting a bidirectional matching algorithm. According to the method, distribution path planning and task dynamic adjustment are optimized, and task interaction area resources are fully utilized, so that the problems of insufficient prediction precision, poor path optimization effect and low distribution resource utilization rate in the prior art are effectively solved.

The invention belongs to the technical field of cooling of high-frequency transformers. According to the method, the temperature rise and cooling liquid flow characteristics of an internal winding and an iron core of the transformer are simulated by constructing a multi-physical field simulation model considering the thermophysical property change of a material; establishing a response surface model based on transformer structure parameters, and selecting the outer diameter, the wall thickness, the number of turns and the spacing of a cooling pipe as design variables; an NSGA-II multi-objective optimization algorithm is adopted, and a Pareto optimal solution set is obtained by taking maximum temperature minimization and cooling material consumption minimization as objectives; and typical scheme optimization is realized in combination with an entropy weight-TOPSIS method. According to the invention, the design requirements under different cooling structures and operation conditions can be met, the hot-spot temperature rise is obviously reduced, the cooling efficiency is improved, and good structural safety and manufacturability are achieved.

The invention discloses an automatic ceramic glazing control system and method fusing machine vision and track planning, and relates to the technical field of ceramic production automation, and the method comprises the steps: obtaining basic information and glazing demand information of to-be-glazed ceramic; according to the automatic ceramic glazing control system and method fusing machine vision and trajectory planning, three-dimensional data are obtained by shooting ceramic images from multiple angles and scanning, the three-dimensional features of surface profiles, textures and tiny defects can be accurately captured, even pits and protrusions can be recognized, and when a glazing path is planned, the glazing quality is greatly improved. The angle of the nozzle can be adjusted in real time according to the surface morphology of the ceramic to ensure that glaze is sprayed perpendicular to an arc-shaped surface and a special-shaped surface, and meanwhile, the moving speed of the nozzle and the glaze output quantity are matched to avoid material consumption deviation per unit area; the glazing thickness uniformity and the coverage area precision are improved through mutual cooperation, the problems that coating of special-shaped ceramics is missed, and the thickness fluctuation of curved-surface products is large are solved, and the percent of pass of complex ceramic products is remarkably improved.

The invention discloses a method for generating a metal 3D printing supporting structure, and relates to the technical field of additive manufacturing. The method comprises the steps that geometric analysis is conducted on a three-dimensional model of a to-be-printed part, and areas needing to be supported are recognized and classified into a strong supporting area, a weak supporting area and a transition supporting area; different laser scanning parameters are configured for different supporting areas, a supporting main body adopts low-energy density parameters to form a porous structure, a contact interface adopts discrete dot matrix scanning to form weak connection, and a transition layer with gradually-changed parameters is arranged between the supporting main body and the contact interface; a composite supporting structure composed of hexagonal honeycomb units and vertical thin walls is generated; in the printing process, high-frequency micro-vibration is applied to the support to improve powder fluidity, and sweep-frequency vibration is applied to the interface layer to weaken interface bonding; thermal cycle treatment is carried out after printing, and interface automatic cracking is achieved through the difference of thermal expansion coefficients; and finally, support falling is accelerated through resonance frequency vibration. Through the synergistic effect of the scanning parameter gradient, the structure optimization design and the vibration auxiliary technology, the removability of the support is remarkably improved, the material consumption is reduced, and the surface quality of the part is improved.

The invention belongs to the technical field of bridge construction, and particularly relates to a design method for a temporary pushing buttress based on reinforcement learning. The method comprises the following steps that reinforcement learning modeling is carried out, and a temporary buttress design agent is constructed; constructing a finite element simulation environment for simulating the structural response of the buttress scheme; training a temporary buttress design agent by adopting a depth deterministic strategy gradient algorithm; and strategy network deployment: deploying the trained temporary buttress design agent model to an engineering design platform, and realizing automatic generation of a pushing temporary buttress design scheme in an actual scene. According to the method, the intelligent and dynamic temporary buttress design optimization is realized by constructing the multi-target reinforcement learning framework including buttress stability, material consumption and girder deformation and combining with the depth deterministic strategy gradient algorithm to train the intelligent body capable of automatically carrying out temporary buttress design under different environment constraints; and the design efficiency of the temporary buttress is obviously improved.

The invention discloses a material demand prediction method based on an ARIMA model and an LSTM model, and the method comprises the steps: constructing a time-serialized material demand data set, and carrying out the data preprocessing; time sequence analysis is carried out, linear trend modeling is carried out by using an ARIMA model, a preliminary prediction value is obtained, and a prediction residual error is calculated; constructing an LSTM neural network to perform nonlinear feature learning on the residual error, predicting a future residual error value, determining an optimal model by using an LSTM model evaluation index, and predicting future annual material consumption by using the optimal model; determining a calculation range of an annual purchase quantity, and establishing an annual recommendation purchase model; calculating an annual purchase quantity recommendation value of a plurality of years in the future, and forming an annual purchase schedule; and setting an early warning inventory value, and monitoring the inventory in real time. Compared with a traditional method depending on a single model, the method can more comprehensively capture tendency and volatility in material demands, and adapts to changes of material consumption modes in complex construction scenes.