Industrial Mill Research Articles

Recycling Cost formation and Profitability of foods and beverages firm: Evidence from Flour Milling Industries of Nigeria Plc (1991-2021)

Recycling is one of the most viable options to reuse the end of the product in the closed-loop supply chains (CLSC) management. The major focus of this study is to examine the influence of product recycling cost on the profitability of food and beverage firms. This study relied solely on secondary data sourced which was subjected to a mathematical model using regression analysis. It was observed that dependent and the independent variables has a strong positive relationship with r=0.741. The coefficient of determination r2=0.549 shows that 54.9% of the variation in profit can be explained by production cost at 95% level of significant while in the flour mills Nigeria plc, the dependent and the independent variables has a weak positive relationship with r=0.363. The coefficient of determination r2=0.132 shows that 13.2% of the variation in profit can be explained by the production cost at 95% level of significant. Finally in Dangote Nigeria plc, dependent and the independent variables has a weak positive relationship with r=0.174. The coefficient of determination r2=0.030 Shows that 03.0% of the variation in profit can be explained by the production cost at 95% level of significant.

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.).

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling quality is costly and burdensome. Multi-trait genomic selection (MTGS) combines information from genome-wide markers and secondary traits genetically correlated with primary traits to predict breeding values of primary traits on candidate breeding lines. MTGS can improve prediction accuracy and significantly accelerate the rate of genetic gain. In this study, we evaluated different MTGS models that used morphometric grain traits to improve prediction accuracy for primary grain quality traits within the constraints of a breeding program. We evaluated 558 breeding lines from the University of Illinois Oat Breeding Program across 2 years for primary milling traits, test weight, thins, and groat percentage, and secondary grain morphometric traits derived from kernel and groat images. Kernel morphometric traits were genetically correlated with test weight and thins percentage but were uncorrelated with groat percentage. For test weight and thins percentage, the MTGS model that included the kernel morphometric traits in both training and candidate sets outperformed single-trait models by 52% and 59%, respectively. In contrast, MTGS models for groat percentage were not significantly better than the single-trait model. We found that incorporating kernel morphometric traits can improve the genomic selection for test weight and thins percentage.

A Quantitative Assessment of Air Particulate Matter Concentration and Its Correlation with the Climatic Factor of Dinajpur City, Bangladesh

Particulate matter (PM) is the air pollutant that poses the most significant risk to human health compared to other measured criteria pollutants. One of our main goals was to assess the quantities of particulate matter (0.3-10µm) in the Dinajpur municipality's sensitive zones, roads, and residential and commercial buildings. Light scattering particle counters, the Extech VPC-300, were used to measure particulate matter and climatic data at 26 distinct locations in Dinajpur. R 4.2.2 and the data analysis tool in Microsoft Excel were utilized for the statistical analysis. The highest values for PM 0.3, 0.5, 1, 2.5, 5, and 10 µm are 335195, 138118, 37965, 12995, 2087, and 2507 and medium value is accordingly 221304, 71873, 16681, 3393, 361 and 454, respectively. The PM 0.5 μm particle range, which includes 12 samples, is highly concerned and getting closer to the hazardous red polluted zone. Most places of PM 2.5 µm exceed the 2000 particles, which are hazardous for people. The link between climatic variables and particulate matter (PM 0.5-10 µm) significantly correlated with temperature. Humidity and PM (0.3-10 µm) measurements in the study area show a negative correlation. According to observations, factors contributing to the high PM concentration include excessive human movement, combustion byproducts of black smoke, road dust, waste, garbage in every possible place, and rice mill industry emissions.

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.

An up-scaled biotechnological approach for phosphorus-depleted rye bran as animal feed

Side streams from the milling industry offer excellent nutritional properties for animal feed; yet their use is constrained by the elevated phosphorus (P) content, mainly in the form of phytate. Biotechnological P recovery fosters sustainable P management, transforming these streams into P-depleted animal feed through enzymatic hydrolysis. The enzymatic P mobilization not only enables P recovery from milling by-products but also supports the valorization of these streams into P-depleted animal feeds. Our study presents the scalability and applicability of the process and characterizes the resulting P-depleted rye bran as animal feed component. Batch mode investigations were conducted to mobilize P from 100 g to 37.1 kg of rye bran using bioreactors up to 400 L. P reductions of 89% to 92% (reducing from 12.7 gP/kg to 1.41–1.28 gP/kg) were achieved. In addition, High Performance Ion Chromatography (HPIC) analysis showed complete depletion of phytate. The successful recovery of the enzymatically mobilized P from the process wastewater by precipitation as struvite and calcium hydrogen phosphate is presented as well, achieving up to 99% removal efficiency. Our study demonstrates a versatile process that is easily adaptable, allowing for a seamless implementation on a larger scale.Graphical

Evaluation of dry milling characteristics and polyphenolic contents of fourteen conventionally bred colored corn varieties for value-added coproducts recovery

Corn pericarp is a low value cellulosic coproduct. However, colored corn pericarp contains disproportionately higher amounts of polyphenolic compounds such as anthocyanins, flavonoids, flavonols, tannins and phenolic acids, and can be selectively utilized for their economic recovery. Due to the diverse industrial applications of these value-added phytochemicals, colored corn can supplement the lower economic value of conventional yellow dent corn. In this study, dry milling characteristics and polyphenolic contents (anthocyanins, total phenols, and condensed tannins) of fourteen conventionally bred and midwestern US grown colored varieties and their milling coproducts were ascertained and compared with a commercial purple corn. With mean large grits yield of 22.98% (db), colored varieties had a dominant softer endosperm, suitable for wet milling and dry grind industry. The mean starch content of colored varieties was lower than conventional yellow dent corn (∼9.91%, db), and the mean protein content was higher (∼1.70%, db). Although purple corn contained the highest amounts, four experimental varieties had high concentrations of polyphenols. Through HPLC analyses, a diverse mix of various anthocyanin forms, phenolic acids, and flavonoids were identified. The antioxidant potential of polyphenolic extracts from five varieties were evaluated using four different assays, and significant antioxidant activities were observed. Histological analysis was conducted on polyphenol-rich varieties, and most of the pigments were found to be concentrated in pericarp. The pericarp thickness was greatest for the variety containing the maximum polyphenolic compounds. Adapted colored corn varieties can be valorised to recover value-added polyphenolic compounds in line with the circular bioeconomic paradigm.

Adult food and species type influence the nutritional physiology and tolerance of two flour beetles to the extract of Dennettia tripetala (G. Baker)

AbstractTribolium castaneum (Herbst) and Tribolium confusum (Jacquelin du Val) are common and damaging pests of stored grain flours in several homes and flour mill industries worldwide. This study examines how food, species, concentration, and exposure time affect the susceptibility and nutritional physiology of T. castaneum and T. confusum when exposed to partially purified methanolic fruit extract of Dennettia tripetala (G. Baker) and two of its major active compounds (linalool and 2‐phenylnitroethane). Gas chromatography–mass spectrometry was used to evaluate the chemical profile of the partially purified plant extract. Thirty‐two compounds were found in the plant, including established insecticidal and insectifuge compounds such as linalool, cis‐vaccenic acid, 2‐phenylnitroethane, and linoleic acid, among others. The interactions among the factors have a differential impact on the susceptibility and nutritional indices of both Tribolium species to D. tripetala, linalool and 2‐phenylnitroethane. According to LC50 values, linalool and 2‐phenylnitroethane were the most and least toxic to both beetles, respectively. With increasing extract concentrations, all nutritional indices except feeding deterrence decreased. Relative to controls, linalool and 2‐phenylnitroethane evoked the highest and least reduction, respectively, in beetles' nutritional indices. Treated corn discs deterred both species over treated wheat discs, regardless of insecticide type. T. castaneum had a higher overall food consumption than T. confusum. Regardless of insecticide type, the relative growth rate was higher in T. confusum and T. castaneum fed with treated corn and wheat discs, respectively. D. tripetala extract, linalool, and 2‐phenylnitroethane showed higher post‐ingestion toxicity to T. castaneum than T. confusum. This study emphasises the importance of certain intrinsic factors, like beetles' species and cereal food types, when managing Tribolium species with plant‐based insecticides. The various data obtained from this study will help researchers and pesticide manufacturers formulate effective biopesticides from linalool and 2‐phenylnitroethane to control Tribolium species on corn and wheat flours.

Adaptive staged remaining useful life prediction of roller in a hot strip mill based on multi-scale LSTM with multi-head attention

Accurate prediction of a roller's remaining useful life (RUL) is significant for a hot strip mill to avoid major safety accidents and substantial economic losses. Since rollers’ degradation processes represent multi-stage characteristics, traditional single-stage models cannot acquire accurate RUL prediction results. Therefore, this paper proposes an adaptive staged RUL prediction method based on multi-scale long short-term memory network with multi-head self-attention (LSTM-MHA). The roller's production data and operation data are fused to construct interpretable health indicators (HI), which can represent the roller's remaining rotatable angle. Then the degradation process is divided into multiple stages and analyzed. The proposed multi-scale LSTM-MHA can adaptively update the model weights based on changes in the roller degradation stages by the multi-scale memory structure. The MHA embedding mechanism filters important temporal information for LSTM units. The trained model can predict the roller's RUL by inputting the current roller's HI. The proposed method is verified on an industrial hot strip mill roller dataset from a well-known steel company. The validation results show that the prediction accuracy of the proposed method is higher than 98.98%. Compared with existing deep learn-based methods, the proposed multi-scale LSTM-MHA method has significant advantages in roller's RUL prediction.

Rolling Eccentric Steel Rings on an Industrial Radial–Axial Ring Rolling Mill

Various industries, including mechanical engineering, utilize steel rings featuring variable cross-sectional profiles, such as eccentric rings. Presently employed methods for producing eccentric rings possess drawbacks like restricted geometries, significant material wastage or uneven microstructures. The radial–axial ring rolling process serves to create seamless rolled steel rings with near-net-shaped cross-sections. A novel technique involves achieving eccentricity by dynamically adjusting the mandrel’s position during the ring rolling process. This method’s fundamental feasibility has previously been showcased using a blend of oil clay and a labor test bench. Transferring the possibility of manufacturing eccentric rings on industrial radial–axial ring rolling mills would expand the product range of ring manufacturers without encountering drawbacks associated with existing manufacturing processes. The objective of this paper is to demonstrate the basic feasibility of the concept of an industrial radial–axial ring rolling mill. In the first step, FEA simulation studies were carried out to develop the rolling strategy and estimate the achievable eccentricity on the institute’s radial–axial ring mill. Subsequently, the rolling strategy was implemented on an industrial ring rolling mill with the help of a unique technology module programmed in C++. Finally, an eccentric ring was ring rolled and compared with the FEA simulation, and the reproducibility was demonstrated to be successful.

Shear strength of soil by using rice husk ash waste for sustainable ground improvement

In the global construction industry, areas characterized by weak and expansive soils are on the rise, necessitating effective solutions for strength enhancement. Addressing this concern, sustainable soil amendments have gained attention, with rice husk ash (RHA) from rice milling industries being a notable focus. Our experimental study aimed to assess the shear strength of this innovative construction material, introducing a unique approach that considers subgrade layers with minimal cement dosage, including upper, bottom, and double layers a novel contribution yet unexplored in existing literature. In addition to conventional mechanical testing, we employed SEM (Scanning Electron Microscopy) and EDS (Energy-Dispersive X-ray Spectroscopy) analyses to comprehensively explore the treated soils' microstructural and elemental composition aspects. Examining sixteen specimen combinations of weak expansive soil-RHA-cement, varying proportions of RHA (2%, 4%, 6%) and cement (2%, 4%, 6%) were mixed to understand their effects on shear strength parameters. Our findings revealed significant shear strength improvement in each subgrade layer, with specimen 6%RHA6%C in the lower subgrade layer exhibiting the highest cohesive strength at 143 kN/m2. Notably, the double layer configuration, specimen 2%RHA6%C, achieved maximum deviatoric stresses of 383 kN/m2. This novel construction material contributes to effective waste management and presents an innovative engineering solution for sustainable ground improvement, offering promising prospects for future geotechnical advancements.

Validation study on a coarse-grained DEM-CFD simulation in a bead mill

A bead mill is often employed in powder processes. In the bead mill, the bead-particles move rapidly under high shear rate due to the moving structures. The discrete element method (DEM) coupled with the computational fluid dynamics (CFD) has been applied to simulate the bead-particle behavior for the optimization of the bead mill design and operating conditions. However, the existing DEM-CFD method faces essential problems regarding the substantial limit of the number of computational particles, stable calculations, and modeling of rapidly moving structures. To solve these problems, we newly investigate a numerical model combining the coarse-grained DEM-CFD, an implicit algorithm for the drag force term, and a scalar field-based wall boundary in the calculation of a bead mill commonly employed in industrial powder processes. In this study, our proposed model is shown to successfully simulate the macroscopic behavior of the bead-particles through the validation test of the coarse-grained DEM-CFD simulation in the bead mill system. Specifically, the macroscopic characteristics such as the particle location, the particle velocity, and total kinetic energy, are shown to agree well between the original particle system and coarse-grained particle systems. Consequently, this study illustrates the combination of the coarse-grained DEM-CFD, an implicit algorithm for the drag force term, and the scalar field-based wall boundary is essential for simulating the typically industrial bead mill, where an enormous number of bead-particles should be calculated in liquid under high shear rate.

Assessment of the Baking Properties of Rye Flour Based on the Polysaccharide Content and Properties

This study aimed to determine the baking quality of rye flour in terms of the content and properties of its polysaccharides, i.e., starch and pentosans. The study materials were low- and high-extract rye flours produced in industrial mills from the rye grain of two growing seasons (2019 and 2020). The results of the starch content, falling number, amylograph properties, DSC test, content of pentosans, swelling curve test, and laboratory baking test were determined. It was found that the type of flour had a greater impact on the baking quality of rye flour than the year of its production. Research has shown that the most frequently used parameters, such as the falling number and the maximum viscosity of starch paste, are not good indicators for assessing the baking value of currently produced rye flours. From the parameters used for evaluating the properties of the starch–amylolytic complex, the initial and onset temperatures for starch gelatinization were the best indicators for evaluating the baking quality of rye flour. This study revealed a significant correlation between the pentosan content (total, water soluble, and insoluble), swelling curve parameters and quality parameters of rye bread, such as the specific bread volume, bread crumb moisture, and bread crumb hardness. Assessment of the baking value of rye flour based only on the evaluated properties of the starch–amylolytic complex is currently not sufficient to determine the baking quality of rye flour and predict the quality of rye bread. This study on the baking quality of rye flour should be extended to include the assessment of the dough properties related to the pentosan content and the enzymes that degrade these components. It was shown that the properties of rye dough related to the content of pentosan can be characterized based on the swelling curve test as a method that, together with the initial and onset starch gelatinization temperatures, allows better assessment of the baking quality of the commercial rye flour and its suitability for the good-quality rye bread production.

Development of Rice By-Products Based Hair Tonic Mixed with Traditional Thai Herbal Extracts: A Sustainable Approach for Hair Care

Previously, byproducts from Thai rice mill industry including crude riceberry oil (CRO) and broken riceberry (BRB) showed antioxidant and tyrosinase-stimulating activities. This work aimed to develop 5 hair tonic formulae by mixing CRO (0.2-1.0%) and BRB (0.4-2.0%) with three Thai traditional herbal ethanolic extracts (2.0%) of Catunaregam tomentosa (CT), Acacia concinna (AC) and Tinospora crispa (TC) in 4:3:3 (v/v). The results showed that formula 5 (F5) containing 2% BRB, 1.0% CRO and 2% herbal extracts exhibited the highest antioxidant activity (DPPH scavenging capacity at 16.6 TEAC mg/g, FRAP value at 1.18 FeSO4 mg/g, and ABTS value at 14.9 TEAC mg/g) and tyrosinase-stimulating activity of 38%. This hair tonic was safe to use based on skin irritation test, and stable over 8-week storage at room temperature. Hence, F5 hair tonic (coded (R)) was tested on 20 subjects divided in 2 groups (older and younger age groups) with 10 individuals each in a randomized, double-blind, placebo-controlled experimental design with split-head method where treatments were conducted as intra-individual trial for 10, 20 and 30 days. The hair tonic coded C (Control without BRB, CRO or herbal extracts) and the commercial hair tonic coded G were tested for comparison. Adverse reactions were not noticed during the study. The hair tonic R was able to reduce hair loss by 48-71% in 2 groups with no significant difference from the commercial hair tonic. In comparison with the efficacy in the reduction of gray hair of the 2 groups at each time interval, the 2experimental (R) hair tonic product was found to be more effective in group 2 (younger age). However, the efficacy in the reduction of gray hair was lower than that in the reduction of hair loss. The experimental hair tonic R was more effective in dandruff reduction in group 1 (older age). The R hair tonic product received a satisfactory score of 6.79±0.32 out of 9.0 (moderate-to-high likeness) with the highest score from the aroma and the lowest score from the opaque color resulting from mixing aqueous herbal extract and oil. This is a sustainable way to add value to byproducts from rice mill industry and Thai traditional herbs as cosmetic elements in the formulation of hair products.

Modification of tetrahedrite Cu12Sb4S13 thermoelectric performance via the combined treatment of mechanochemistry and composite formation

Tetrahedrite Cu12Sb4S13 with its low thermal conductivity represents a flagship in sulphide thermoelectrics. However, to achieve a reasonable figure-of-merit ZT (measure of thermoelectric efficiency), adequate doping or special sample processing is needed. In this work, a different approach (without doping) is illustrated for the two tetrahedrite-containing systems. In the first approach binary composite tetrahedrite Cu12Sb4S13/chalcopyrite CuFeS2 was prepared by mechanochemical leaching with the aim to obtain partly decomposed tetrahedrite. In this approach, the alkaline leaching medium (Na2S + NaOH) was applied to extract Sb from tetrahedrite thus changing its composition. The obtained composite (formed from its own phases in an intrinsic mode) shows low values of ZT = 0.0022@673 K in comparison with the non-treated tetrahedrite where ZT was 0.0090@673 K. In this case the extremely high electric resistivity (6–20 mΩ cm−1) was documented. In the second approach binary composite tetrahedrite Cu12Sb4S13/muscovite KAl2(AlSi3O10)(OH)2 (formed from its own and foreign phases in an extrinsic mode) was prepared by two-step mechanical activation in which combined treatment of industrial vibratory milling and subsequent laboratory planetary milling was applied. The addition of a foreign phase, muscovite, did not give extraordinary thermoelectric performance results. However, the two-step milling process (without the addition of foreign phase) gives the value of ZT = 0.752@673 K which belongs to the highest in the tetrahedrite thermoelectric community. In this case, the two-times increase in specific surface area and the increased amount of tetrahedrite in comparison to famatinite are suspectable for this effect. Both applied non-traditional approaches to synthesize tetrahedrite composites form a platform for potential modification of its thermoelectric performance.

Management strategy to mitigate voltage sags effects of a multi-motors system using ADALINE algorithm and cascade sliding mode control

Multi-motor systems (MMS) find widespread use in various industrial applications, including plastic, paper, textiles, and steel rolling mills, where synchronized speeds are crucial for optimal operation. However, a significant limitation of these systems is their susceptibility to voltage sags, resulting in speed and synchronization loss, along with peak currents and torques during voltage recovery. This paper presents a comprehensive multi-motors management strategy aimed at attenuating the adverse effects of voltage sags. The proposed technique is based on principles that involve recovering the system’s kinetic energy and leveraging the current reversibility of the converters. The control scheme comprises two main strategies: an adaptive linear neuron or later adaptive linear element (ADALINE)-based voltage sag detection algorithm utilizing least mean square (LMS) adaptation for rapid convergence using artificial neural networks, and a control scheme incorporating sliding mode speed controllers and indirect rotor field-oriented control (IRFOC). Additionally, a logic-based strategy for voltage sag attenuation completes the control framework. The effectiveness and efficiency of the proposed strategy are demonstrated through simulation results obtained using MATLAB/Simulink/SimPowerSystems.

Eichhornia crassipes Leaves as a Waste-derived Bio-Sorbent to Remove Organics and Nutrients from Rice Mill Wastewater

The increased rate of population growth resulted in the increased number of rice mill industries to fulfill the demand for rice. The rice mill wastewater contains a high load of organics and nutrients. Therefore, the direct discharge of wastewater into the environment may degrade the quality of the environment as well as causes adverse effects on human health. Among various methods to treat waste effluent, bio-sorption is a cheap and environmentally sound approach. Eichhornia crassipes is a noxious weed that spreads rapidly. Most of the tanks in Vavuniya are polluted by E. crassipes and it needs a sustainable solution. This study uses the leaves of E. crassipes to produce waste-derived bio-sorbent to treat rice mill wastewater. The wastewater was collected from one of the rice mills in the Vavuniya town area. The adsorption isotherm and adsorption kinetics experiments were conducted to find out the removal efficiencies of COD, nitrate, and phosphate from wastewater. The effect of the dosage of bio-sorbent (1-6 g/L) and the contact time (30-180 min) with the wastewater was studied to determine the optimum dosage and optimum contact time. The bio-sorbent showed maximum removal efficiencies of COD (54.5%), nitrates (58.1%), and phosphates (29.5%) at the optimum dosage of 4 g/L at 120 min. Based on the t-test, E. crassipes leaves significantly reduce COD, nitrate, and phosphate (p-value<0.05). However, COD and nitrate showed higher removal rates than phosphate. Further, long-term column studies should be conducted to apply the above technique in wastewater treatment plants in treating the rice mill wastewater in the real world. This study emphasizes that E. crassipes leaves have the potential to remove contaminants from wastewater as well as this would also help to minimize the spread of the weed to safeguard the environment. 
 Keywords: Eichhornia crassipes, Bio-sorption, Vavuniya tank, Water quality

Comparison of Approaches to Predict Grinding in An Industrial Rod Mill Operating at Low Fillings

ABSTRACT Several approaches have been proposed over the years that may be used to predict the performance of industrial rod mills. Unfortunately, studies that allow comparing the accuracy in their predictions are very scarce. The work compares four methods for predicting size reduction in an industrial rod mill. These were the Bond work index method (BW) and the Callcott–Lynch (CL) model, both originally proposed for rod mills, besides the Herbst–Fuerstenau (HF) and the Austin–Klimpel–Luckie (AKL) models, first proposed for ball mills, but here adapted and applied to rod milling. A total of 10 industrial surveys were conducted of the industrial mill in dry grinding of coke breeze, covering operation under a variety of conditions, all of which at lower fillings than commonly used in industry (<15%). Since most conditions surveyed were not within the typical operating range for rod mills, simulations using the Discrete Element Method were used to predict the mill power, used as input in both BW and HF models. At first, the fidelity of methods that allow predicting full-scale mill performance solely from bench-scale information, namely BW, HF, and AKL, is compared. Results showed that they all presented high biases in their estimates of product fineness, with AKL predicting finer products whereas BW and HF predicting coarser products. Using then data from a single industrial survey for model calibration (base case), in addition to the bench-scale test results, a comparison of the four approaches became possible. Taking the absolute deviations between measured and predicted P 80 values, it became evident that the HF provided the highest fidelity in the predictions, with mean deviations of 12.8%, AKL with 15.3%, with both BW and CL presenting deviations above 18%. The work thus shows that size-mass balance models that rely on fitting most model parameters from bench-scale tests (HF and AKL) can provide predictions with good confidence when data from an industrial base case are additionally used in fine-tuning the model, even when applied to describing rod milling under unusually low fillings.

The Oil:Water Ratio in the Vertical Centrifuge Separator and Its Influence in Phenolic Compounds in the Virgin Olive Oil and the Olive Mill Wastewater (Alpechín)

The use of the vertical centrifuge in the olive oil production process is generally assumed to be habitual and necessary for the elimination of both the vegetation water and the small olive pulp particles that are not eliminated during solid–liquid separation (horizontal centrifugation). Trials were carried out with different oil:water ratios to study the influence of this variable on both the quality parameters of the olive oils obtained and the loss of oil with the olive wastewater. The trials were carried out at the industrial mill level with oil:water ratios between 0.6 and 5.5. While no differences were observed in the quality parameters of the oils obtained, correct adjustment of the oil:water flow rates reduced the loss of phenols present in the oils by around 30%. In addition, the results show a direct relationship between the soluble effluent and the conductivity of the olive mill wastewater (alpechín) with the loss of oil in the effluent. This work proves that both oil quality and the competitiveness of the olive oil value chain can be increased with energy savings, water consumption reduction, and environmental sustainability.

Analysis of business feasibility on rice milling business in Porsea district of Toba Samosir regency

The consistent growth in grain production, particularly rice, in Toba Samosir has led to the emergence of numerous rice milling businesses in the region. This is due to the significant potential for further expansion in grain production in the district, making it an attractive area for such ventures. Nevertheless, the rice milling industry in the Porsea sub-district has various intricate challenges, including funding, technological advancements, marketing strategies, and access to market intelligence. This study aims to ascertain the characteristics of the rice milling industry and determine the firm’s financial viability. The methodology employed in this study involves doing a feasibility analysis utilizing the metrics of Net Present Value, Internal Rate of Return, and Net Benefit Cost Ratio. The objective is determine the viability of rice milling activities in the Porsea sub-district. The findings indicated that the mean annual income of the rice milling industry in Porsea amounted to 147,439,448 IDR. The Porsea rice milling business has met the necessary criteria for consideration, with a Net Present Value (NPV) of IDR 658,682,140, a Net Benefit-to-Cost ratio (Net B/C) of 1.2, and an Internal Rate of Return (IRR) of 46.29%. These figures suggest that most regional rice milling firms are financially feasible.

Intelligent process control system for predicting operating conditions of slag grinding machines: a data mining approach for improved efficiency and energy savings

This study develops an intelligent data-driven approach for optimising slag grinding systems. Slag grinding exhibits complex nonlinear dynamics that challenge control. The proposed system monitors key operating parameters to assess machine health and automate control adjustments. Operating data are collected, and features linked to health status are identified using data mining techniques. Cluster analysis categorises historical data into healthy/unhealthy modes to build a condition library. Real-time data are then evaluated against this library. A predictive model forecasts future trend. The system was implemented in an industrial slag mill. Results demonstrated reduced vibration and energy use versus manual control. Validation confirmed improved accuracy in predicting mill responses. Significant energy savings were achieved annually through optimised control. The system enhances safety by automating adjustments while minimising costs and environmental impacts. Data-driven strategies overcome the limitations of traditional methods, representing an advance for intelligent management of industrial processes. Benefits were confirmed through rigorous factory implementation and performance monitoring.