2032 results about "Material consumption" patented technology

The invention discloses a scheduling information management method and system based on fire fighting of a fire fighting truck, and relates to the technical field of intelligent fire fighting scheduling, and the method comprises the steps: receiving fire alarm information, and collecting real-time fire scene data based on a preliminary fire behavior evaluation result; combining the collected real-time fire scene data with historical fire data, and analyzing a fire spreading trend through an AI fire prediction model; according to the fire behavior spreading trend and the equipment state of the fire fighting truck, dynamically allocating fire fighting truck resources, and planning an optimal driving route; the driving state of the fire fighting truck is monitored in real time, dynamic adjustment is performed based on road conditions and equipment information, and task allocation of the fire fighting truck is updated according to the real-time fire scene situation; in the fire extinguishing process, resources are dispatched in real time for supply according to the material consumption condition of the fire fighting truck. By monitoring the material consumption condition of the fire fighting truck in real time, the supply resources are intelligently dispatched, and the continuity and high efficiency of the fire extinguishing action are ensured.

The invention discloses a carbon emission index evaluation method and system based on a full-life-cycle power transmission and transformation project, and the method comprises the steps: S1, collecting data in the full life cycle of the power transmission and transformation project, including material consumption, energy use and equipment operation data in the stages of design, construction, operation, maintenance and demolition; s2, decomposing and optimizing a carbon emission path of each stage by adopting a hierarchical constraint path optimization algorithm; s3, introducing a self-correction energy consumption curve algorithm, and dynamically correcting the carbon emission data according to historical and real-time energy consumption data; s4, monitoring the energy consumption fluctuation in the operation maintenance stage, and automatically correcting the carbon emission deviation caused by the external environment change; s5, integrating hierarchical constraint path optimization and energy consumption curve data, and generating carbon emission assessment; s6, generating a standardized carbon emission evaluation report containing optimization suggestions; and S7, outputting an evaluation report, and supporting low-carbon planning implementation. According to the invention, the carbon emission management and optimization efficiency of the whole life cycle of the power transmission and transformation project is effectively improved.

The invention relates to the technical field of construction project management, in particular to a construction project management system based on cloud computing, which comprises a construction path optimization module, a construction state analysis module, a construction environment monitoring module, a progress plan adjustment module and a green construction optimization module. According to the method, through combination of construction task resource distribution and three-dimensional space information, resource path distribution logic is optimized, material consumption, equipment operation states and key process deviation data are utilized, accurate positioning and prediction of construction dynamic problems are realized, construction interruption is reduced, and equipment and personnel distribution characteristics are extracted based on field image data, so that construction efficiency is improved. The equipment arrangement deviation degree and the potential safety hazard superposition value are quantified, the safety and efficiency of a construction site are improved, and the utilization rate of green construction resources is improved by dynamically adjusting the process time and the resource utilization rate, optimizing the relation between task nodes and factors, improving the flexibility and the response capability of a construction plan and conducting partition modeling energy consumption data and multi-constraint optimization.

The invention relates to the technical field of industrial automation, in particular to an intelligent control method and system for a shoemaking production line, and the method comprises the following steps: based on a shoemaking three-dimensional design model, recognizing size parameters of a plurality of sizes by analyzing the design size and shape of shoes, adjusting the production parameters of the plurality of sizes, and generating multi-size production parameter configuration. According to the method, the production parameters of various sizes are adjusted according to the design model of the shoe, so that the production line flexibly meets the production requirements of multiple sizes of products, production delay and resource waste caused by mismatching of specifications are reduced, the utilization rate of raw materials is increased through real-time image data collection and defect detection, material waste in the cutting process is reduced, and the production efficiency is improved. The system analyzes production parameters and material consumption, predicts material requirements, responds to market changes in real time, optimizes inventory management, reduces the defective product rate in combination with automatic quality monitoring, improves the energy efficiency of a production line by analyzing and optimizing energy consumption, and supports sustainable production and environmental protection.

The invention belongs to the technical field of clamping, and provides a self-adaptive shape follow-up centering clamp and an automatic clamping method. The self-adaptive shape follow-up centering clamp comprises an end cover, an outer circular ring, a floating shape follow-up positioning cylinder, a driving clamping cylinder, an inner circular ring, a hanging ring, a rib plate and a PLC control system. The automatic clamping method can replace a traditional process ring clamping method, self-adaptive shape follow-up positioning and clamping of the barrel workpiece are achieved, the process ring turning procedure is omitted, and material consumption is reduced. After the outer circular ring, the cylindrical roller bearing and the axis of the lathe spindle in the self-adaptive shape follow-up centering clamp are mounted consistently, it can be guaranteed that the middle barrel section coincides with the axis of the lathe spindle. Shape-following positioning of a blank barrel workpiece is achieved through the floating shape-following positioning cylinder, the barrel workpiece is clamped through the driving clamping cylinder, and it is guaranteed that stress is uniform while the axis of the barrel workpiece does not deviate. The device is achieved based on a PLC control system, the clamping force is quantitatively controlled through feedback adjustment of the oil pressure gauge and the proportional valve, and clamping deformation is reduced.

The invention provides an intelligent construction site real-time monitoring and intelligent scheduling optimization method and system, and relates to the technical field of construction scheduling optimization, and the method comprises the steps: collecting the real-time monitoring data of a construction site, constructing a material consumption thermal distribution diagram, calculating the real-time relative distance between a constructor and equipment, and determining the safety risk level. And determining a material supply sequence and an optimal distribution route based on the thermal gradient and the security risk, generating a scheduling instruction, and ensuring the reliability of the instruction through multi-node voting and smart contract verification. According to the invention, accurate scheduling of construction resources and real-time monitoring of safety risks are realized, and the construction efficiency and safety are improved.

According to the floor support plate, the continuously-bent bottom of a web bar in a combined frame is not transversely bent, manufacturing is easy, material consumption is low, connection with a bottom plate is more stable, force is directly transmitted between the combined frame and a metal bottom plate, the combined frame and the metal bottom plate are jointly stressed, the material properties of the combined frame and the metal bottom plate are brought into play, and the rigidity of the whole structure is higher. The upper chord is of a steel pipe or profile steel or other metal rod piece structures, the strength of the structure can be improved, the steel consumption can be reduced, economical efficiency is better, and the strength, rigidity and overall bearing capacity are higher. Side ribs can be arranged on the side faces of the web ribs according to engineering requirements and act together with the bottom plate. The structural construction requirement of the steel bars in the floor support plate can be met, and the steel bars can not only be combined with metal bottom plates, but also be used for the floor support plate with the requirement of a protective layer. Compared with a traditional truss floor support plate, the steel consumption can be reduced by 8-15%, and the rigidity can be improved by about 10%.

The invention relates to a wafer polishing method and apparatus, a data processing apparatus, a program, and a storage medium. The polishing method comprises the following steps: loading a wafer to be polished; reading in a first polishing formula, and carrying out primary polishing on the wafer according to the first polishing formula; wafer parameters of all the partitions of the wafer are detected, whether the wafer parameters of all the partitions of the wafer reach the standard or not is judged, if yes, the wafer is unloaded, if not, a second polishing formula is obtained through the dynamic adjustment model according to the wafer parameters, and secondary polishing is conducted on the partitions, not reaching the standard, of the wafer based on the second polishing formula. And then returning to detect the wafer parameters of the partitions of the wafer again until the wafer parameters of all the partitions of the wafer are judged to reach the standard, and unloading the polished wafer. According to the method, the reworking function of multi-zone automatic triggering and time-pressure automatic combined adjustment can be achieved in the wafer polishing process, repeated treatment on the whole wafer is avoided, and material consumption and cost are reduced.

The invention discloses a tunnel intelligent primary support construction wet spraying over-consumption analysis method and system, and the method comprises the steps: obtaining spraying track space distribution data through a three-dimensional motion capturing system installed on a spraying unit, and combining a material flow fluctuation curve generated by a dynamic weighing system, constructing a three-dimensional feature tensor comprising a material flow state feature, an injection process feature and an environment interference feature; a theoretical volume of a primary support structure is extracted based on a geological BIM model, surrounding rock back break data obtained by point cloud scanning are fused, a dynamic use amount reference model considering rebound loss is established through fluid mechanics simulation, and a theoretical use amount interval value with a confidence interval is generated. According to the method, the three-dimensional characteristic spectrum and the closed-loop optimization system are constructed by fusing multi-physical-field dynamic data, the problems that dynamic adaptation of geological conditions is not accurate and a multi-factor coupling super-consumption mode cannot be analyzed in wet spraying construction are solved, and dynamic accurate control over the material consumption and explainable diagnosis of super-consumption causes are achieved.

The invention relates to the technical field of project cost management, in particular to a hydraulic engineering construction cost control system and method, and the system comprises a material consumption analysis module, an inventory early warning calculation module, a dynamic inventory adjustment module, a replenishment trigger optimization module, and a consumption stability evaluation module. According to the method, the material consumption rate is dynamically monitored, the construction progress and engineering quantity are combined to measure and calculate data, a consumption trend curve is established, the actual use condition is compared, the consumption rate deviation is accurately quantified, real-time evaluation of material use is achieved, the number of supply days is calculated in combination with inventory data, the replenishment period is matched, and the replenishment time is dynamically adjusted; the inventory level is optimized, fund occupation is reduced, the stability is evaluated according to the consumption fluctuation range, the maximum consumption fluctuation value is calculated, the demand is adjusted in combination with replenishment, the inventory early warning threshold value is dynamically corrected, the supply chain breakage risk is reduced, the adaptability of construction material management is improved, and the cost control accuracy is improved.

The invention provides a light wall spraying process based on artificial intelligence, which comprises the following steps of: acquiring key parameters such as spraying thickness, uniformity, material consumption, spraying pressure, environment temperature and humidity and the like in a spraying process in real time through mounted sensor equipment; the data processing module is used for transmitting the data to the data processing module for data cleaning, denoising and format conversion, the spraying process is divided into a plurality of sub-regions, a data set in each sub-region is processed through a self-adaptive distributed generative adversarial network model, the pre-processed data is analyzed by utilizing a self-adaptive distributed generative adversarial network algorithm, and the data is stored in the data processing module. A prediction model of the spraying process is constructed, the prediction model can predict the spraying effect in real time according to the input parameters, feedback signals are generated, and operation parameters of spraying equipment are adjusted through an intelligent optimization algorithm; and closed-loop control is formed, so that the spraying quality is continuously optimized in the construction process, the material waste is reduced, and the construction efficiency is improved.

The invention belongs to the technical field of building project management, and particularly relates to a building curtain wall assembly management technology, in particular to a building engineering project management intelligent system and method. A three-dimensional matrix including component identification, material consumption, a planned entering time window and a material sensitivity label is constructed based on a component entering plan; meanwhile, a construction site space model is established, the occupation state of a three-dimensional matrix simulation material storage yard is loaded in the model according to a component entering plan, and component entering is dynamically optimized by comprehensively considering storage yard space overlapping and meteorological adaptability factors in combination with meteorological prediction data in an assembly time window; prejudgment and adjustment of the assembly plan before implementation are realized, and the change frequency in the actual execution process is effectively reduced, so that the waste of manpower and material resources is remarkably reduced, and the stability and efficiency of a construction organization are improved.

The invention provides a road construction carbon emission monitoring method, which belongs to the technical field of electric digital data processing, and comprises the following steps: establishing a monitoring network through a multi-source sensor, collecting equipment operation, material consumption and construction activity data by using an Internet of Things terminal, and calculating carbon emission in combination with a carbon emission factor database to form a fingerprint spectrum. Edge calculation is adopted to carry out time sequence analysis to recognize abnormal points, a neural unit jump algorithm and a multi-head attention architecture are applied to carry out fine adjustment on a pre-training model, and a jump threshold value is calculated through a specific function. And introducing a distributed gradient descent optimization equation to integrate data of multiple construction sites to protect privacy, and generating a monitoring report including total carbon emission, intensity and emission reduction suggestions. And by adaptively adjusting the monitoring time interval, the carbon emission monitoring precision and efficiency are improved. The pre-training model adopts a multi-layer time convolutional network structure, and the adaptability to a specific construction scene is improved through unsupervised pre-training and supervised fine tuning.

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 a battery piece grid line preparation method and device, and aims to reduce material consumption through a transfer printing technology and realize stable and efficient preparation of small-size battery piece grid lines. The method comprises the steps that conductive paste transfer printing layers corresponding to the front face and the back face of a battery piece are manufactured on a transfer printing substrate, and grid line pattern grooves are formed in the transfer printing layers; the grooves are uniformly filled with conductive paste, the conductive paste transfer printing layers on the front face and the back face are accurately attached to the corresponding faces of the battery piece, and synchronous transfer printing of the grid line patterns on the front face and the back face of the battery piece is achieved by applying appropriate pressure and temperature at the same time from top to bottom. By adopting the technical scheme of simultaneous upper and lower transfer printing, the force distribution is effectively balanced, the problem of subfissure of the battery piece is avoided, and the tight fitting degree of the grid line and the surface of the battery piece and the current collection efficiency are remarkably improved. In addition, the invention further provides a battery piece grid line preparation device, the whole preparation process of the battery piece grid line can be completed in one piece of complete machine equipment, and the integration degree of a production line is improved.

The present invention discloses a fully automatic laser processing production line for unwinding and cutting aluminum veneer, comprising a support seat, on which are arranged from left to right an unwinder, a leveler, a shearing machine, a conveyor belt, an automatic material storage, a pre-marking mechanism, a laser cutting device and a sorting and conveying device; an aluminum material roll is installed on the unwinder, and the aluminum material roll is supported by a roll support device arranged on the left side of the unwinder; a material guiding platform is arranged on the right side of the unwinder between the left side of the leveler. This fully automatic laser processing production line for unwinding and cutting aluminum veneer can realize full automation from raw materials to finished parts, and can be used for various coil raw materials. By using laser cutting, the system can automatically and continuously cut out various workpieces, realize better utilization of various raw materials, achieve minimum material consumption, make workpiece costs lower, improve production capacity, greatly improve production efficiency, reduce time and labor costs, and make operation and management more convenient.

The present invention relates to the technical field of concrete construction, and in particular to a concrete environmental impact assessment method based on a life cycle approach. The method comprises the steps of: determining a concrete type on the basis of a construction environment and design requirements of a project; analyzing each stage of concrete engineering in a functional unit, and determining an evaluation range thereof; establishing a region-specific concrete life cycle database; performing inventory analysis on an evaluation range of a concrete life cycle; after the inventory analysis, using component inventories of full-life-cycle concrete to establish indicators on the basis of environmental policies of a construction region, so as to perform an environmental impact assessment; and finally, analyzing and evaluating various energy indicators of the concrete, and guiding the establishment of a subsequent project construction plan. In the assessment method, a full-life-cycle assessment is performed on concrete, the degrees of environmental impact caused by different construction processes in concrete engineering are objectively and holistically assessed, and evaluation and improvement schemes are proposed for the concrete construction, thereby reducing the energy and material consumption in concrete engineering construction.

The present application relates to a multiphase reactor. The multiphase reactor comprises: a reactor housing in which a reaction cavity is formed, wherein the reactor housing is provided with a second material inlet pipe and first material inlet pipes communicated with the reaction cavity, and the first material inlet pipes are used for conveying a first material to the reaction cavity; a gas distributor located in the reaction cavity, wherein the second material inlet pipe is communicated with the gas distributor, and a second material conveyed by the second material inlet pipe is conveyed to the reaction cavity by means of the gas distributor; and flow guide cylinders located in the reaction cavity, wherein a plurality of ventilation parts are arranged on each flow guide cylinder in the circumferential direction of the reactor housing, and the flow guide cylinders are used for axial drainage and radial cutting in the reaction cavity. The present application solves the technical problems that the reaction efficiency is affected and the material consumption is increased due to uneven distribution of a temperature field and a reaction field in multiphase reactors.

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 embodiment of the invention provides a production process collaborative management and control method, a management and control system and a computer program product, and belongs to the field of automatic control. Comprising the following steps: according to order information and production process information of a plurality of orders, determining resource demand information and a predicted production cycle of each order and a predicted production sequence priority among the plurality of orders; according to the above information, the equipment capacity, the production material information and the inventory information, adjusting the production sequence among the plurality of orders to obtain the actual production sequence among the plurality of orders; obtaining actual production data corresponding to the current production order according to the actual production sequence among the plurality of orders, the equipment operation state in the actual production process and the material consumption data; and adjusting the current production order strategy in real time according to the actual production data corresponding to the current production order and the material inventory data and inventory of the current production order product. According to the invention, cooperative control of production links can be realized, so that the efficiency of the production links is improved.

The invention discloses a building project material ordering optimization method and system considering supply interruption. The optimization method comprises the steps of obtaining a construction plan and material consumption; based on the construction plan and the material consumption, predicting a material demand within a preset time; obtaining a preliminary material ordering plan according to the material demand; obtaining an optimal material purchasing channel, and performing risk assessment according to the optimal material purchasing channel and the preliminary material ordering plan to obtain a supply risk; and obtaining an optimal material ordering plan according to the supply risk. According to the method, factors such as project progress, construction plans and material consumption are comprehensively considered, material demands in a certain period in the future are predicted, a material ordering plan is made according to a prediction result, the purchasing time, the purchasing quantity and the purchasing channels of materials are reasonably arranged, and the situation of material shortage or excessive purchasing is avoided.

The invention provides a risk monitoring method and system based on power grid material supply chain operation. The supply chain management efficiency is remarkably improved through an intelligent risk identification process. The method comprises the following steps: firstly, acquiring power grid material consumption data from a historical database, and calculating the consumption speed and consumption of various materials according to a bill of materials; and key monitoring materials are screened out through the preset consumption monitoring threshold value, so that tedious data processing on all the materials is avoided. And for the screened monitored materials, the system further collects storage, production and logistics data of the screened monitored materials, and evaluates the risk degree by using a pre-trained supply chain risk identification model. And when the material supply chain risk degree exceeds a preset threshold value, defining the material as a supply risk material. The accurate risk monitoring method not only reduces the calculation overhead of data processing, but also can identify potential supply chain risks in time, and provides a more efficient and intelligent solution for power grid material management.

The invention belongs to the technical field of geological engineering, and particularly relates to a confined aquifer drilling drainage depressurization enhanced grouting method which comprises the steps that the grouting transformation range is determined; a grouting drill hole and a pressure reducing hole are constructed, and the slurry diffusion radius of the grouting drill hole is determined through the pressure reducing hole; determining the positions of other pressure reducing holes according to the slurry diffusion radius; grouting is started to be conducted in the grouting drill hole; after grouting is completed, the pressure reducing holes are treated; and repeating the processes until the transformation is finished. The grouting hole is formed in the center of the grouting transformation area, and the pressure reducing holes are formed in the periphery of the grouting hole, so that the water pressure of the aquifer is effectively reduced, the diffusion range of grout is remarkably expanded, and the grout is promoted to more uniformly permeate and fill cracks of the aquifer. The grouting efficiency is improved, material consumption is remarkably reduced, and the grouting method has high economic benefits and is particularly suitable for mine water prevention and control engineering under complex geological conditions. The grouting effect is greatly improved, and the technical scheme is efficient and economical.

The invention discloses a decorating part and a manufacturing method thereof and a vehicle, the decorating part comprises a shading layer and a texture layer which are stacked, the texture layer comprises a light-transmitting base body and short carbon fibers, the short carbon fibers are randomly distributed in the light-transmitting base body, the decorating part further comprises a supporting framework, and the supporting framework is connected to the face, opposite to the texture layer, of the shading layer. The randomly distributed short carbon fibers are adopted as the texture layer, so that the decorating part can present forging textures of the short carbon fibers, the texture layer has the characteristics of short forming period, good toughness and small carbon fiber material consumption, and the manufacturing cost of the decorating part can be reduced; meanwhile, by means of the multi-layer structure, the middle texture layer can present high fiber stereoscopic impression and high permeability, and the attractiveness of the decorating part is improved; the multi-layer structure can be recycled in a classified mode, the recycling value of the decorating part is improved, and finally the purposes of energy conservation and emission reduction can be achieved.

The invention relates to the technical field of data analysis, in particular to a building structure analysis method and device. Obtaining building structure design data corresponding to multiple candidate designs of the target building; the building structure design data comprises a building structure type, a structure material type, a structure material size, a structure material consumption and structure node data; for each candidate design, according to the building structure design data, analyzing the structure safety level and the carbon emission standard level of the target building; aiming at each candidate design, based on the structure safety level and the carbon emission standard level, carrying out design scoring on the candidate design; and determining the candidate design with the highest design score as a final building structure design scheme of the target building. By acquiring and analyzing multi-dimensional data of building structure design, comprehensive evaluation of the safety level and the carbon emission standard level of a target building structure is realized, design scoring is performed based on an evaluation result, and an optimal building structure scheme is determined.

The invention provides a device and method for testing the fracture toughness of a Charpy-like impact sample in a low-temperature environment, and the device comprises an environment box system which is used for providing a low-temperature test environment; the frame system is located in the environment box system, the sample is located in the frame system, a boss is arranged at the bottom of the frame system, and the bottom end of the boss is an arc surface; the loading system comprises a pressure head and a lower guide rod, the lower guide rod is upwards inserted into the environment box system, the pressure head is downwards inserted into the frame system, the boss is located above the lower guide rod, the sample is located below the pressure head, and a notch of the sample is located on a connecting line of the pressure head and the center of the bottom end of the boss; and the measuring system is used for measuring test data. A low-temperature test environment is provided through the low-temperature test box, the purpose of testing the fracture toughness of the Charpy-like impact sample in the low-temperature environment can be achieved, and the device has the advantages that clamping is convenient in the test process, automatic centering is achieved, and the test error is small; meanwhile, test material consumption is reduced, and cost is reduced.

The invention discloses a lightweight honeycomb structure shoe mold printing method based on an SLM process, and the method specifically comprises the following steps: S1, building a three-dimensional model of a shoe mold, and carrying out honeycomb embedding on the three-dimensional model of the shoe mold to obtain a lightweight three-dimensional shoe mold model; s2, the lightweight three-dimensional shoe mold model is uploaded to Msgics software for slicing processing and scanning strategy planning, and the lightweight three-dimensional shoe mold model is uploaded to SLM forming equipment; s3, after parameter setting is carried out on the SLM forming equipment, entity printing of the three-dimensional shoe mold model is carried out according to a scanning strategy; the invention relates to the technical field of additive manufacturing. According to the light-weight honeycomb structure shoe mold printing method based on the SLM process, through arrangement of honeycomb holes, the material consumption is reduced, meanwhile, light-weight design of the shoe mold is achieved, through edge enhancement design of the honeycomb structure, the bearing performance, the elastic modulus and the yield strength of the shoe mold are effectively improved, and the printing quality of the shoe mold is improved. And the high-efficiency preparation targets of light weight, high performance and low cost of the shoe mold are achieved.

The replaceable environment-friendly face cream tank comprises a bottle body, an inner container arranged in the bottle body and an outer cover detachably connected with an opening of the bottle body, the bottle body is provided with a containing cavity for containing the inner container, a bottle opening is formed in the top of the containing cavity, the inner container is of an integrated structure with the same material as the bottle body, and the opening of the inner container is connected with the bottle opening through a clamping structure. A gasket is arranged on the top of an inner cavity of the outer cover and completely covers an opening of the inner container after the outer cover is matched with the bottle body. The inner container is made of the same material as the bottle body and adopts the plastic uptake structure, so that the material consumption is low, the production cost is reduced, the whole recycling is convenient, and the environmental protection property is improved; the clamping structure of the inner container and the bottle body facilitates replacement of the inner container and is more environment-friendly.

The invention discloses a Fe-Beta molecular sieve for N2O catalytic decomposition and a preparation method of the Fe-Beta molecular sieve. According to the method, chitosan and metal Fe < 3 + > ions are complexed to form a chitosan Fe < 3 + > complex, and then the complex, a silicon source, an aluminum source and a template agent are used as raw materials to prepare the Fe-Beta molecular sieve in one step through a hydrothermal method. Hydroxyl, amino and other groups rich in a chitosan molecular chain can effectively complex metal Fe < 3 + > ions to form a stable chitosan Fe < 3 + > complex, and the stable chitosan Fe < 3 + > complex is used as a Fe source to realize uniform dispersion of Fe species in the molecular sieve and effectively reduce formation of FexOy clusters and Fe2O3 nanoparticles, so that the N2O decomposition catalytic performance of the Fe-Beta molecular sieve is improved. Inorganic alkali metal ions are not introduced, so that a large amount of ammonia-nitrogen wastewater generated in a subsequent tedious ammonium exchange process can be avoided, the synthesis period is effectively shortened, and energy consumption, material consumption and environmental pollution are reduced.