Mill Feed Research Articles

Implementation of a first-mill cane-feeding control strategy based on a cane-harvest system

The analysis of the extraction performance of three Colombian sugarcane factories revealed large variations in milling operations. Because more than 70% of the extraction occurs in the first mill, the chute level behavior was evaluated, and the coefficient of variation (CV) values were greater than 55%. This was mainly caused by the control strategy not being capable of mitigating the effect of processing different densities of sugarcane. This variability resulted from the frequent change between manual and mechanically harvested sugarcane. An in-line indicator was designed to determine the type of sugarcane; this was based on the electric current drawn by the cane leveller. In collaboration with factory A, a control strategy was designed that changes the velocity relationship of the conveyor belts depending on the sugarcane harvest type. The control strategy was also applied in the second factory (B), with only a 1.5 m high first-mill chute, which affects feeding stability, but dynamic current protection was added. This was based on PID controllers that manipulate conveyor velocity proportionally, reducing the chance that it would come to a halt, protecting the cane knives and shredder from electrical overload, and providing a more constant mill feed. The evaluation of the new control strategy was compared with the old control loops, increasing the overall extraction of 0.40 and 0.68% for factories A and B, respectively. Better stability was achieved in the first mill chute with a CV of approximately 30%, which was also reflected in the chute levels of the following mills. The new control strategy used the instruments and actuators already installed without any additional investments and can greatly improve the milling performance and, as a result, profitability.

Feed Milling Industries Resilience amid COVID-19 in Ekiti State Nigeria

This study analyzed the resilience strategies for small-scale feed milling industries, learning from the COVID-19 pandemic in Ekiti State, Nigeria. 215 small scale feed mills industries were selected by multistage sampling procedure. Descriptive statistics, gross margin and regression analysis were used for the analysis of data collected. Results revealed that the mean age for the respondents was 40.45 year. In addition, 91.58% of the feed millers were married while 8.42% were single with a mean household size of 6. 13 years was the mean number of years spent in school. With respect to experience, the respondents had 11 years of feed milling experience. Gross margin results indicated that income after COVID-19 is more than during the COVID-19 showing an N168,330.00 significant (p<0.001) difference indicating that COVID-19 had great consequences on the income. The regression result revealed that sex (p<0.001), marital status (p<0.010), household size (p<0.001), education (p<0.001) and experience (p<0.005) were feed mill profitability determining factors in the study area. Constraints faced during COVID-19 are that lockdown due to COVID-19 hindered operational activities of feed mill (65.26%), COVID-19 causes a total increase in the price of inputs (66.32), reduction in the sales of feeds (69.29%), reduction in work force (65.26%), and loss of raw materials through spoilage (66.32%). The study recommended that feed millers should collaborate with local farmers for the supply of materials at lesser price, rather than buying highcost foreign materials.

Distribution of antioxidants and phenolic compounds in flour milling fractions from hard red winter wheat

Mature wheat kernels contain three main parts: endosperm, bran, and germ. Flour milling results in multiple streams that are chemically different; however, the distribution of antioxidants and phenolic compounds has not been well documented in terms of conventional milling by-product streams. In this study, multiple analytical methods were used to investigate antioxidant activity and phenolic compound compositions of hard red winter wheat (whole ground wheat), the parts of a wheat kernel (bran, flour, germ), and wheat by-product streams (mill feed, red dog, shorts) for the first time. For each mill stream, phenolic compounds (total, flavonoid, and anthocyanin contents) were determined and antioxidant activities were evaluated with 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging activity, ferric reducing/antioxidant power (FRAP), and total antioxidant capacity assays. Significant differences (P < 0.05) were observed in phenolic concentrations among fractions of bran, flour, and germ milled from the same kernels and noted that germ accounts for the majority of antioxidant properties, whereas bran contains a substantial portion of phenolic compounds and anthocyanins. Mill feed was high in phenolic content (5.29 mg FAE/g), total antioxidant capacity (866 mg/g), and antioxidant activity (up to 75% DPPH inhibition and 20.26 μmol FeSO4/g). The comprehensive information on distribution of antioxidants and phenolic compounds provides insights for future human consumption of commonly produced co-products from flour milling, and for selecting and using different milling fractions to make foods with improved nutritional properties.

A bulk sorting trial of copper ore using a magnetic resonance analyser

Sensor-based bulk ore sorting (BOS) is a technique that may lead to uplift of processing grades by excluding waste as well as an increase in usable resource by sorting material designated as mineralised waste. A magnetic resonance analyser (MRA) was installed on the primary crushed ore feed to the sulphide plant at the Kansanshi copper mine in northwestern Zambia to trial BOS. The conveyor belt operated at 2800tph and carried ore of which greater than 85% by weight of the copper-bearing minerals are chalcopyrite. The MRA was therefore tuned for chalcopyrite’s zero static field magnetic resonance. The analyser achieved a 3σ detection limit of 0.045 wt% copper as chalcopyrite over a 4 s measurement time and standard belt loading, with lower detection thresholds possible if the measurement time increased.A trial of ore diversion was then carried out at the site. Pods of ore measured as less than 0.2 wt% copper as chalcopyrite by the MRA were diverted by a dead box diverter system to form a low-grade stockpile of approximately 10,000 tonnes. A cavity in the mill feed stockpile was arranged and the rejected material fed back through the crusher, past the MRA and directly through the milling circuit to the flotation feed where a Vezin sampler was used to take a sample every 5 min. This sample was then tested for copper grade by the site metallurgical laboratory. The MRA measured a grade of 0.16 wt% copper as chalcopyrite over the test time period and the Vezin samples for the last hour of the trial reported approximately 0.2–0.3 wt% copper despite some mixing with unsorted ore being inevitable. This is as clear a demonstration of bulk ore sorting (BOS) as practically achieveable in the production environment at Kansanshi and, to the author’s knowledge, the first demonstration of BOS on a copper ore stream of at least this throughput.

Induced Ruminal Lactic Acidosis in Sheep Treated with Various Remedial Agents in Libo Kemkem Districts, Northwest Ethiopia.

Grain overload is a ruminant metabolic disorder associated with overingestion or a sudden change to rapidly fermentable concentrate feeds. A randomized clinical trial was carried out in Libo Kemkem districts to investigate vital signs, ruminal fluid, and hematological changes in sheep related to grain overload and to assess the treatment efficacy of various remedial agents in Farta sheep breeds. All sheep were selected by using the simple random process, and categorized into four groups of eight animals groups I, II, and III in which each sheep was given 80 g of wheat flour per kg of body weight then baking soda, Magnalax, and digestive powder were treated successively, but group IV was the negative control group. The current clinical trial explained that all acidotic sheep had statistically significant (p < 0.0002) lower body temperature, rumen motility, protozoa activity, and ruminal fluid pH with 38.48 ± 0.20, 0.5 ± 0.89, 6 (75%), and 5.37 ± 0.34 mean value successively. Nevertheless, there were significant (p < 0.0059) increments in hematological variables including total red blood cell, total white blood cell, packed cell volume, and hemoglobin estimation with 14.05 ± 1.27, 12.71 ± 0.99, 40.78 ± 5.24, and 14.78 ± 1.83 mean value, respectively, before treatment in acidotic sheep. There were also vital sign increments including pulse rate, respiratory rate, skin turgor, and capillary refill time with 123.5 ± 27.1, 73.75 ± 12.71, 3 ± 1.78, and 3.37 ± 1.77 mean values, respectively, before medical treatment in acidotic sheep. Digestive powder was the first drug of choice, followed by Magnalax, and baking soda was ranked at the end based on clinical recovery. The treatment effectiveness illustrated that all treatments could cure the grain overload. Nevertheless, digestive powder is the drug of choice based on the clinical and systemic recovery of the sheep. In addition to this, sheep should be introduced gradually to concentrate rations over 2-3 weeks with a mixture of concentrate in the milled feed containing roughage.

Stress-based approach for predicting and improving large-scale HIG mill performance

As a fine and ultrafine grinding technology, the High Intensity Grinding (HIG) Mill is relatively new and there is opportunity to improve its performance by adjusting operational conditions. A laboratory HIG5 mill is commonly used for HIG mill sizing and scale up, however the clear correlation between the operational variables of laboratory mill to their production level is somewhat lacking. This paper presents a stress-based approach for predicting and improving large-scale HIG mill performance. A total of 27 experimental tests were performed with a HIG5 mill over a range of operational variable set points, including media density, media filling level, feed solid content, mill speed and flow rate. The influence of the variables on product size, mill operating power and specific grinding energy was characterized via multivariable linear regression modelling. Based on theoretical stress analysis and empirical calibration with available survey data, the model derived from laboratory testing was calibrated to predict the operation of the commercial HIG1600 mill. An approach was proposed for determining the effect of operational variables using a HIG5 that can be directly applied to reduce energy consumption at a given mill feed rate and product size target for the production scale mill. Results demonstrated that the stress-based approach integrated with laboratory testing can be used for predicting and improving large-scale HIG mill performance.

EFFICIENT USE OF ELECTRIC ENERGY WHEN OPERATING A BALL MILL WITH A CONSTANT ROTATION SPEED

Link for citation: Zakamaldin A.A., Perevoshchikov F.V., Shilin A.A. Efficient use of electric energy when operating a ball mill with a constant rotation speed. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 9, рр. 115-127. In Rus. The relevance. Ball mills are widely used in industry for grinding bulk materials, as well as in the last stages of ore crushing, where the required optimal particle sizes are achieved for enrichment. Although ball mills have a relatively simple design and cover extensive research, the industry is still struggling with the very low energy efficiency of the grinding process. As the retrofitting heavy equipment is the costliest approach, process optimization through control system is the most suitable for energy consumption reduction. As a rule, the feed rate is the main control variable for a mill with a constant rotation speed. Due to insufficient information content, outdated methods of analysis and control of the internal dynamics of the mill, control systems keep the target value of feed rate at a deliberately low level in order not to overload the mill. This article provides an explanation of how, in such a case, an increase in mill feed rate could affect the energy efficiency of grinding. The main aim: study of energy efficient modes of operation of stations; verification of models and confirmation of experimental data: the relationship between door loading and power consumption indicators; construction of buildings for energy efficient control of ball towers. Objects: the process of grinding in a ball tower with a constant rotation speed. Methods: mathematical description of the behavior of the electromechanical part of a machine that consumes current and works on a load in the form of spherical furniture; simulation modeling of the operation of the door electric drive; statistical analysis of production indicators. Results. The paper demonstrate the tendency to increase electricity consumption with a decrease in feed rate and vice versa, respectively for ball mills with a synchronous drive of 2500 kW based on modeling and experimental data. Increase in feed rate in the range of 10–40 t/h, there is a drop in active power by 0,48–1,57 %. The values of the specific power consumption of ~5–8 kWh/t during the grinding of apatite ore were obtained. An increase in productivity by 5 t/h on average leads to a decrease in the specific power consumption by 0,12 kWh/t. It is necessary to increase productivity in the operation of ball mills only after integrating measuring instruments into the control system of the mill, which allow an accurate assessment of the state of loading of the mill drum.

Research on the multi-physical coupling characteristics of the machine tool and milling process based on the systematically integrated model

Good machine tool precision and a stable milling process are important foundations for obtaining high-quality qualified parts. During the machining process, the machine tool and the milling process will impact each other, and further jointly affect the motion accuracy as well as part quality. This paper makes a deep analysis of the machine tool and milling process from a new perspective, which regards the machine tool and milling process as a coupled entirety, and studies the interaction between them from a systematic perspective. By establishing a systematically integrated model of the ball screw feed system and milling process, the multi-physical simulation of the whole system is realized with the consideration of multi-source harmonics. The electrical-magnetic-mechanical-kinematic coupling characteristics between the machine tool and the milling process are investigated based on the established model and experiments. The research results show that the servo system and the milling process are two major harmonic sources in the system that generate low-medium frequency and medium-high frequency harmonics, respectively. As the machining process progresses, these harmonics will be transmitted and coupled through the servo motor, mechanical structure, and feedback signals, leading to the fluctuation in the motion of the worktable and the influences on the surface quality of the final part. A type of part surface defect that can only be explained by integrated analysis of the whole system is also demonstrated. The research work indicates that the machine tool and milling process is an integrated system with strong coupling characteristics. It's of great significance to study them from a systematic perspective.

Controlling Salmonella: strategies for feed, the farm, and the processing plant

Controlling Salmonella in poultry is an ongoing food safety measure and while significant progress has been made, there is a need to continue to evaluate different strategies that include understanding Salmonella-poultry interaction, Salmonella-microbiota interactions, Salmonella genetics and response to adverse conditions, and preharvest and postharvest parameters that enable persistence. The purpose of this symposium is to discuss different strategies to consider from feed milling to the farm to the processing environment. This Poultry Science Association symposium paper is divided into 5 different sections that covers 1) immunological aspects of Salmonella control, 2) application of Salmonella genetics for targeted control strategies in poultry production, 3) improving poultry feed hygienics: utilizing feed manufacture techniques and equipment to improve feed hygienics, 4) practical on farm interventions for controlling Salmonella-what works and what may not work, and 5) monitoring and mitigating Salmonella in poultry. These topics elucidate the critical need to establish control strategies that will improve poultry gut health and limit conditions that exposes Salmonella to stress causing alterations to virulence and pathogenicity both at preharvest and postharvest poultry production. This information is relevant to the poultry industry's continued efforts to ensure food safety poultry production.

Ddetermination of bond work index of Bagega gold mineral deposit of Zamfara State, Nigeria

The study determined the bond work index of Begaga gold mineral deposit of Zamfara State Nigeria using Berry and Bruce modified bond method. Sample of gold mineral was sourced using random sampling method. Reference mineral (Granite) of known weight and work index of 15.13Kwh/ton was ground for thirty minutes at a particular speed and power consumed was determined from the power rating of the ball mill. An identical weight of Bagega gold mineral whose work index was to be determined was ground in the same ball mill under same condition as that of reference mineral. Size analysis of the ball mill under same condition as that of the reference mineral was performed. Size analysis of the ball mill feed and discharge for both ores was carried out and 80% passing particle size of the ball mill feed and discharge for the two ores were estimated mathematically using correlation approach. The work index of the Bagega gold mineral was determined by equating the power consumed in the two indexes of the ore. It was found to be approximately 14.24Kwh/ton which is within the acceptable range of 10 - 15.14Kwh/ton indicated in literatures as standard work index range of gold. This value of the work index means that 14.25Kilowatts hour of energy is required to reduced one tonne of the gold ore from 80% passing particle size of 1117.32μm to 80% passing particle size of 800.00μm, it should serve as the work index of Bagega gold.

The process of the mill feed flow along a curved acting face of a vibration mill screen

The process of the mill feed flow along a curved acting face of a vibration mill screen

Analyzing process parameters for industrial grinding circuit based on machine learning method

The grinding and classification processes are systematic engineering that must comprehensively consider the influence of several factors to ensure good grinding fineness. Based on the machine learning method, this study analyzed the full process parameters (i.e., ball mill power, fresh ore feed rate, hydrocyclone feed pump power, hydrocyclone pressure, mill feed water flow rate, dilution water flow rate, and sump level) for industrial grinding circuit. The collected real data (42,101 records) were employed to train and test the extreme gradient-boosting (XGBoost) regression model. The XGBoost model’s prediction ability and accuracy were evaluated and analyzed. The validated model was employed to evaluate the relative importance and influence mechanisms of process parameters. It was found that hydrocyclone feed pump power, dilution water flow rate, hydrocyclone pressure, and mill feed water flow rate significantly affected the grinding fineness, which were consistent with the actual operation of grinding circuit.

A conceptual strategy for effective bulk ore sorting of copper porphyries: Exploiting the synergy between two sensor technologies

Bulk ore sorting is a preconcentration technique that may address the operational and environmental challenges of extracting low-grade ore deposits, such as copper porphyries. The technique allows for the early detection and diversion of sub-economic material by sensor-diverter systems before milling, thereby improving mill feed quality and reducing environmental impact. Grade heterogeneity in ore and sensor capability to measure grade accurately are prerequisites to applying bulk ore sorting. The technical synergy between the responses of multiple bulk ore sorting technologies can aid in taking full advantage of the grade heterogeneity existing in sorter feed while providing accurate and precise grade measurements. This study is aimed at quantitatively demonstrating the potential benefits of a conceptual strategy of integrating the responses from two sensor technologies for bulk ore sorting of copper porphyry deposits. Results show that a more significant enhancement in the Net Smelter Return (NSR) of the ore can be achieved by the simultaneous employment of the magnetic resonance (MR) and prompt gamma neutron activation analysis (PGNAA) sensors compared to the bulk ore sorting scenarios in which the sensor technologies are utilized separately. Results are encouraging and can prompt the collaboration of sensor manufacturers and mining companies to prove the actual value of the presented concept by performing on-site trials.

Deployment of XRF Sensors Underground: An Opportunity for Grade Monitoring or Bulk Ore Sorting in Cave Mines

Ore grades are monitored regularly in cave mines through drawpoint sampling. Automating grade monitoring through deploying X-ray fluorescence (XRF) sensors on the buckets of production loaders has been proposed as an alternative approach to address the issues around the traditional practice of drawpoint sampling. Bucket-mounted sensors can also be employed for bulk ore sorting underground. This study is aimed at evaluating the deployment of XRF sensors on production loaders as an opportunity for grade monitoring or bulk ore sorting in caving operations. The mill feed grade prediction performances of the drawpoint sampling program and mine planning software were assessed for the Cadia East panel cave mine. The results showed that the drawpoint samples underestimated the mill feed quality during a 10-month investigation period. The cave portions with bulk ore sorting potential were linked to the extraction level layout to estimate the number of drawpoints where sensors could be situated for diverting ore and waste. Samples obtained from the mine were tested to evaluate the ability of a lab-scale proxy of a bucket-mounted XRF sensor system to measure copper and gold grades. R-squared values of 0.84 and 0.68 were achieved between the predicted and measured copper and gold grades of the samples, respectively. Sensor test results are promising in revealing the potential to utilize XRF sensors underground. Future test work is encouraged to further validate the applicability of XRF sensors in an underground mining environment.

Acoustic Sensing and Supervised Machine Learning for In Situ Classification of Semi-Autogenous (SAG) Mill Feed Size Fractions Using Different Feature Extraction Techniques

The harsh and hostile internal environment of semi-autogenous (SAG) mills renders real-time monitoring of some critical variables practically unmeasured. Typically, feed size fractions are known to cause mill fluctuations and impede the consistent processing behaviour of ores. There is, therefore, the need for continuous monitoring of mill parameters for optimal operation. In this paper, an acoustic-based sensing method is employed to estimate, in real time, a snapshot of the different feed size fractions presented to a laboratory-scale SAG mill. Employing the MATLAB 2020b programme, the mill acoustic signal is processed using various transform techniques such as power spectral density estimate (PSDE) by Welch’s method, discrete wavelet transform (DWT), wavelet packet transform (WPT), empirical mode decomposition (EMD), and variational mode decomposition (VMD). Different fractional bandpowers are obtained from the PSDE spectrum, while the statistical root mean square values are further extracted from DWT, WPT, EMD, and VMD as feature vectors. The features are used as input features in different machine-learning classification algorithms for different mill feed size fractions predictions. The various transform techniques and feed size fraction predictions are evaluated using the various performance indicators obtained from the confusion matrix such as accuracy, precision, sensitivity and F1 score. The study showed that the acoustic signal feature extraction techniques used in conjunction with the Support Vector Machine (SVM), linear discriminant analysis (LDA), and ensemble with subclass discriminant machine learning algorithms demonstrated improved performance for predicting feed size variations.

Fractal approach of particle size distribution description of ball milling products: effects of ore type, feed and particle size

ABSTRACT Samples used for this study include chalcopyrite and ilmenite ores. Feed size was divided into two fractions of (+2.38 −4) and (+2 −2.38) millimeters, from which different feeds with different weight and size percent values were fed to mill at three feeds of 750, 1000, and 1250 gr. Particle size distribution (PSD) resulting from grinding operation was investigated through fractal approach to calculate fractal dimension of PSD of products. Fractal dimensions for PSD of products were equal (2.41–2.63) and (2.49–2.60) for chalcopyrite and ilmenite ores, respectively. Fractal dimensions of products are increased by increasing weight of particles for fraction of (+2.38 −4) millimeters in mill feed. This can be attributed to increased coarseness of feed particles, leading to increased dispersion of the products’ PSD. Fractal dimension of products would be reduced with an increase in feed weight, which can be due to lower grinding rate of particles and, consequently, lower production of fine particles. Fractal dimensions obtained for chalcopyrite products were bigger than those of ilmenite once. Fractal dimension has a direct relationship with feed size and an inverse relationship with feed.

Study on the Mechanism of Burr Formation by Simulation and Experiment in Ultrasonic Vibration-Assisted Micromilling

Due to the strong plasticity of Inconel 718 and the significant size effect of micromachining, a large number of burrs will be produced in traditional processing. The addition of ultrasonic vibration during machining can reduce the burr problem. The mechanism of burr generation in traditional micromilling (TMM) and ultrasonic vibration-assisted micromilling (UVAMM) was analyzed by simulation, and verified by corresponding experiments. It is found that applying high-frequency ultrasonic vibration in the milling feed direction can reduce cutting temperature and cutting force, improve chip breaking ability, and reduce burr formation. When the cutting thickness will reach the minimum cutting thickness hmin, the chip will start to form. When A/ƒz > 1/2, the tracks of the two tool heads start to cut, and the chips are not continuous. Some of the best burr suppression effects were achieved under conditions of low cutting speed (Vc), feed per tooth (ƒz), and large amplitude (A). When A is 6 μm, the size and quantity of burr is the smallest. When ƒz reaches 6 μm, large continuous burrs appear at the top of the groove. The experimental results further confirm the accuracy of the simulation results and provide parameter reference.

Evaluation of logistic regression and support vector machine approaches for XRF based particle sorting for a copper ore

The study is aimed at particle sorting at the Copper Mountain Mine using XRF. Possible applications include the rejection of barren material from mill feed, the rejection of pebbles in the SABC circuit or the recovery of valuable material from low grade stockpiles. It is recognized that XRF is a surface measurement that can detect copper but depending on several operational conditions, such as the orientation of the particle or mineral texture, the sensor spot may not see the copper. However, XRF also provides information about the concentrations of a range of elements in minerals that are associated with copper mineralization which can improve sorting. The study described herein is aimed at improving XRF sensor-based sorting by the introduction of logistics regression (LR)- and support vector machine (SVM)-based machine learning approaches. To solve the collinearity and dimensionality issues in the input variables, the authors propose a combined approach of principal component analysis (PCA) and stepwise regression to extract the significant features. The combined PCA and stepwise regression approach is novel and has shown to be very effective for dimensionality reduction of the XRF spectrum data. By applying the ROC and AUC), the LR and SVM models are compared. Results showed that the LR model with the AUC of 0.847 outperforms the SVM with kernel functions with respect to classification accuracy; especially for data sets with a small number of features. The improved classification accuracy should benefit the economic performance of the particle sorting system.

Life Cycle Environmental Impact Assessment of Aquaculture Products in the Gaza Strip, Palestine

This study used the life cycle assessment (LCA) approach to evaluate the environmental impacts resulting from aquaculture ponds and associated activities. The assessment focused on eutrophication, acidification, global warming, energy use, and local nutrient emissions. Two farms, Fish Fresh and Al-Bahar, were analyzed to determine the contribution of different components in fish farming systems to various impact categories. Data on fish feed, onsite electricity, feed milling electricity, fuel intensity, water input, and fish production were meticulously collected through a comprehensive questionnaire and insightful interviews conducted over a one-year period in 2020. Furthermore, valuable information was diligently gathered regarding the nitrogen and phosphorus emissions in aquaculture ponds, with a focus on feed inputs. Environmental indicators were evaluated using a functional unit of 1 ton and 1 kg of live fish weight. Results reveled that global warming impacts varied between the two farms, with feed production being the primary contributor, accounting for 74.73% and 76.30% of total emissions, respectively. Acidifying emissions were mainly generated through fish production, accounting for 74.8% and 76.3% of the total for Fish Fresh and Al-Bahar farms, respectively. Eutrophication was primarily driven by fish production, while feed production and transportation operations also made noticeable contributions. The average emissions per kilogram of fresh fish were higher for the Fish Fresh farm compared to Al-Bahar in terms of global warming, acidification, and eutrophication. Energy consumption and water dependence also varied between the farms. These findings emphasize the importance of considering environmental impacts throughout the life cycle of fish farming in the Gaza Strip.

Effects of cryogenic gas jet cooling on milling surface roughness and tool life for GH4169 alloy additive manufacturing parts

Hybrid additive and subtractive manufacturing is development in metal additive manufacturing techniques, wherein the dry cutting cooling method for subtractive cutting is one of the key technologies. To improve the milling performance of GH4169 alloy (namely Inconel 718 nickel-based superalloy) additive manufacturing parts, a dry cutting cooling method with a cryogenic gas jet and its effects on the cutting performance were investigated in this study. The theoretical model of the cryogenic gas jet flow was established, and the geometric characteristics, motion characteristics, and temperature distribution of the jet flow were analyzed. Meanwhile, considering the design of the nozzle outlet, the jet flow core length with a single nozzle and jet flow field envelope effect on the cooling heat transfer process with multiple nozzles were analyzed using a finite element simulation. Then, milling experiments on GH4169 alloy additive manufacturing parts with different cryogenic gas jet flow parameters were carried out. To reduce tool wear and the machined surface roughness of various parts, the jet flow parameters were optimized using the response surface analysis method. The effects of the milling feed direction on the tool wear and machined surface roughness were investigated. Furthermore, the tool wear morphologies were observed under different continuous milling times. The chemical compositions of the worn zone and tool wear mechanism were analyzed. The results show that cryogenic gas jet cooling can significantly improve the tool life and machined surface roughness of parts for GH4169 alloy additive-manufacturing-part milling, and the continuous cutting time within the tool wear allowance can reach approximately 50 min.