Improvement Of Industrial Processes Research Articles

Aspects of Spodumene Lithium Extraction Techniques

Lithium (Li), a leading cathode material in rechargeable Li-ion batteries, is vital to modern energy storage technology, establishing it as one of the most impactful and strategical elements. Given the surge in the electric car market, it is crucial to improve lithium recovery from its rich mineral deposits using the most effective extraction technique. In recent years, both industry and academia have shown significant interest in Li recovery from various Li-bearing minerals. Of these, only extraction from spodumene has established a reliable industrial production of Li salts. The current approaches for cracking of the naturally occurring, stable α-spodumene structure into a more open structure—β-spodumene—involve the so-called decrepitation process that takes place at extreme temperatures of ~1100 °C. This conversion is necessary, as β-spodumene is more susceptible to chemical attacks facilitating Li extraction. In the last several decades, many techniques have been demonstrated and patented to process hard-rock mineral spodumene. The objective of this review is to present a thorough analysis of significant findings and the enhancement of process flowsheets over time that can be useful for both research endeavors and industrial process improvements. The review focuses on the following techniques: acid methods, alkali methods, carbonate roasting/autoclaving methods, sulfuric acid roasting/autoclaving methods, chlorinating methods, and mechanochemical activation. Recently, microwaves (MWs), as an energy source, have been employed to transform α-spodumene into β-spodumene. Considering its energy-efficient and short-duration aspects, the review discusses the interaction mechanism of MWs with solids, MW-assisted decrepitation, and Li extraction efficiencies. Finally, the merits and/or disadvantages, challenges, and prospects of the processes are summarized.

Enhanced Smart Industry Wireless Sensor Networks for Smart Factory

Industrial Wireless Sensor Networks are increased in recent years due to provide real-time monitoring, decision-making and controlling. Industrial Wireless Sensor Networks used in many factories such as: food production, aircraft factory and pharmaceutical factory. The aim of this research is to focus on the Industrial Wireless Sensor Networks in smart factory and the challenges that need to be considered in use such as: its location, energy consumptions and security. The research discuss different issues are highlighted the importance of using real-time decision-making to improve the performance of the process and provide service monitoring for industrial process improvement.

DMAIC-v2: A Novel Guide to the Improvement of Industrial Processes

DMAIC-v2: A Novel Guide to the Improvement of Industrial Processes

Particle separation mechanisms in suspension-feeding fishes: key questions and future directions

Key unresolved questions about particle separation mechanisms in suspension-feeding fishes are identified and discussed, focusing on areas with the potential for substantial future discovery. The published hypotheses that are explored have broad applicability to biological filtration and bioinspired improvements in commercial and industrial crossflow microfiltration processes and microfluidics. As the first synthesis of the primary literature on the particle separation mechanisms of marine, estuarine, and freshwater suspension-feeding fishes, the goals are to enable comparisons with invertebrate suspension-feeding processes, stimulate future theoretical and empirical studies, and further the development of biomimetic physical and computational fluid dynamics models. Of the eight particle separation mechanisms in suspension-feeding fishes, six have been proposed within the past twenty years (inertial lift and shear-induced migration, reduction of effective gap size by vortices, cross-step filtration, vortical flow along outer faces of gill raker plates, ricochet filtration, and lateral displacement). The pace of discovery is anticipated to continue accelerating. Multidisciplinary collaboration and integration among biologists and engineers (including chemical, mechanical, biomedical, and filtration engineering) will result in new perspectives to identify patterns and potential unifying mechanisms across the breadth of suspension-feeding fish taxa, morphology, and function.

Insights into the effects of ISO 9001:2015 on quality and process improvement in the South African packaging industry: A leadership perspective

Insights into the effects of ISO 9001:2015 on quality and process improvement in the South African packaging industry: A leadership perspective

Ex-ante life cycle assessment of directed energy deposition based additive manufacturing: A comparative gearbox production case study

As new technologies emerge is necessary to assess if they can actually contribute to sustainable improvement of industrial processes. Life Cycle Assessment (LCA) is a valuable tool to determine environmental impacts and compare systems. However, this comparison raises challenges when they have different maturity. This paper performs ex-ante LCA of an additive manufacturing (AM) technology, based on a step-wise approach built with parametrized modelling, allowing fair comparison with its conventional counterpart, for the study case of a gearbox component. Results show that AM technology generates higher impacts than conventional manufacturing (CM) casting process, using baseline values. These impacts can be reduced by 94% with best operating performances from literature, with emissions from 4520 to 264 kg CO2 eq./kg piece, and non-significant difference with CM (demonstrated by Monte Carlo sampling). A 58% weight reduction is necessary for the AM process to improves its environmental sustainability. This research provides eco-design recommendations supporting decision making for further development of new technology.

Optimization and Efficiency Improvement of Robot-based Industrial Production Process

Optimization and Efficiency Improvement of Robot-based Industrial Production Process

Energy Efficiency Process Improvement in the Indian Real Estate Industry

Abstract This study addresses the significant environmental impact of the rapidly expanding Indian real estate sector by examining energy efficiency practices through building information modelling (BIM) simulations. Employing a mixed-method approach, the research combines qualitative data from reputable literature sources and quantitative data collected via a questionnaire survey, chosen for its practicality and effectiveness in reaching a large sample size. The statistical approach involves factor analysis, utilizing the Kaiser–Meyer–Olkin (KMO) test and principal component analysis (PCA) to explore underlying data structures and identify key variables. Findings highlight the importance of boosting BIM adoption, customizing energy efficiency measures to local contexts, fostering industry collaboration, implementing monitoring mechanisms, and investing in research and development. These recommendations aim to guide industry stakeholders, policymakers, and researchers in promoting sustainable development and enhancing energy efficiency in the Indian real estate market.

Design and Implementation of an RFID System for Order Tracking in Smart Manufacturing: A Case Study of a Mechanical Factory

Six Sigma is a well-liked technique for raising productivity and quality of output in industrial processes and process improvement initiatives. In the Six Sigma methodology, abnormalities in the operational process are reviewed and examined using the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle. Corrective action is then taken to reduce bottlenecks to enhance productivity, ensure stable product quality, and create a tightly connected production cycle. This study proposes the use of integrating statistical hypotheses into the DMAIC cycle of the Six Sigma method and proposes the use of Enterprise Resource Planning (ERP) modules to monitor production processes at a major mechanical processing company. Lean tools are also suggested by the author to be used in the analysis phase. The research results show a reduction in the rate of late product delivery to users from 6.28% to 0.02% per month. The lean tool application model, statistical hypotheses, and industry 4.0 system are integrated into the EPR system at the company's improvement department and are considered a model for manufacturing companies to refer to in implementing improvements for their products. Production processes in different companies.

Structural differences of cell walls in earlywood and latewood of Pinus sylvestris and their contribution to biomass recalcitrance.

Scots pine (Pinus sylvestris L.) is an evergreen coniferous tree with wide distribution and good growth performance in a range of habitats. Therefore, wood from P. sylvestris is produced in many managed forests and is frequently used in industry. Despite the importance of pine wood, we still do not fully understand its molecular structure what limits improvements in its processing. One of the basic features leading to variation in wood properties is the presence of earlywood and latewood which form annual growth rings. Here, we characterise biochemical traits that differentiate cell walls of earlywood and latewood in Scots pine. We discover that latewood is less recalcitrant to enzymatic digestion, with galactoglucomannan showing particularly pronounced difference in accessibility. Interestingly, characterisation of lignin reveals a higher proportion of coniferaldehydes in pine latewood and suggests the presence of a different linkage landscape in this wood type. With complementary analysis of wood polysaccharides this enabled us to propose the first detailed molecular model of earlywood and latewood and to conclude that the variation in lignin structure is likely the main determinant of differences in recalcitrance observed between the two wood types in pine. Our discoveries lay the foundation for improvements in industrial processes that use pine wood since we show clear pathways for increasing the efficiency of enzymatic processing of this renewable material. Our work will help guide future breeding of pine trees with desired timber properties and can help link molecular structure of softwood cell walls to function of the different types of xylem in conifers.

Industrial Process Improvement by Automation and Robotics

Automation and robotics have revolutionized industrial processes, making them more efficient, precise, and flexible [...]

Biodegradation and valorization of feather waste using the keratinase-producing bacteria and their application in environmentally hazardous industrial processes

Poultry feathers are widely discarded as waste worldwide and are considered an environmental pollutant and a reservoir of pathogenic bacteria. Therefore, developing sustainable and environmentally friendly methods for managing feather waste is one of the important environmental protection requirements. In this study, we investigated a rapid and eco–friendly method for the degradation and valorization of feather waste using keratinase–producing Pseudomonas geniculata H10, and evaluated the applicability of keratinase in environmentally hazardous chemical processes. Strain H10 completely degraded chicken feathers within 48 h by producing keratinase using them as sources of carbon, nitrogen, and sulfur. The culture contained a total of 402.8 μM amino acids, including 8 essential amino acids, which was higher than the chemical treatment. Keratinase was a serine-type metalloprotease with optimal temperature and pH of 30 °C and 9, respectively, and showed relatively high stability at 10–40 °C and pH 3–10. Keratinase was also able to degrade various insoluble keratins such as duck feathers, wool, human hair, and nails. Furthermore, keratinase exhibited more efficient depilation and wool modification than chemical treatment, as well as novel functionalities such as nematicidal and exfoliating activities. This suggests that strain H10 is a promising candidate for the efficient degradation and valorization of feather waste, as well as the improvement of current industrial processes that use hazardous chemicals.

Growth Kinetics of Autochthonous Lactic Acid Bacteria Isolated from Double Cream Cheese as Potential Starter Culture

Currently, there is a permanent search for native Lactic Acid Bacteria (LAB) to explore and apply their biodiversity in the development and improvement of industrial processes, with studies of growth kinetics and performance factors being a fundamental tool for biotechnological use. The objective of this study was to determine the kinetic parameters of 12 autochthonous strains (Pediococcus pentosaceus (19), Leuconostoc citreum (20), Pediococcus acidilactici (21), Leuconostoc mesenteroides subsp. Mesenteroides (22, 29), Enterococcus faecium (24, 25), Enterococcus faecalis (27), Weissella viridescens (28), Lactococcus lactis (30), Lacticaseibacillus casei (31) and Limosilactobacillus fermentum (32)) isolated from a traditional Colombian cheese Double Cream Cheese to obtain information that allows establishing the ideal conditions of the inoculum, standardizing the production of metabolites and exploring their use as starter cultures. Fermentation was carried out in UHT milk at 120 rpm and 35-37 °C until stationary phase, and samples were taken over time to determine pH and titratable acidity (TTA). Exponential and logistic models were used to fit the growth kinetics data. Validation of both models was carried out with the coefficient of determination R2, obtaining good consistency for both (R2 = 0.925 - R2 = 0.932), with slight variations in the kinetic parameters in all the strains. The genera Pediococcus, Leuconostoc, Lactococcus, and E. faecium (24) had the shortest adaptation phases (0-2 h), being P. acidilactici (21), Leu. mesenteroides (22), W. viridescens (28), and E. faecium (24) presented the lowest pH values and high acidity percentages, which shows their potential to be included in the native LAB starter culture and for technology and suitability aptitude studies to produce double cream cheese using pasteurized milk without losing the qualities of the original product.

Versatile Product Detection via Coupled Assays for Ultrahigh-Throughput Screening of Carbohydrate-Active Enzymes in Microfluidic Droplets.

Enzyme discovery and directed evolution are the two major contemporary approaches for the improvement of industrial processes by biocatalysis in various fields. Customization of catalysts for improvement of single enzyme reactions or de novo reaction development is often complex and tedious. The success of screening campaigns relies on the fraction of sequence space that can be sampled, whether for evolving a particular enzyme or screening metagenomes. Ultrahigh-throughput screening (uHTS) based on in vitro compartmentalization in water-in-oil emulsion of picoliter droplets generated in microfluidic systems allows screening rates >1 kHz (or >107 per day). Screening for carbohydrate-active enzymes (CAZymes) catalyzing biotechnologically valuable reactions in this format presents an additional challenge because the released carbohydrates are difficult to monitor in high throughput. Activated substrates with large optically active hydrophobic leaving groups provide a generic optical readout, but the molecular recognition properties of sugars will be altered by the incorporation of such fluoro- or chromophores and their typically higher reactivity, as leaving groups with lowered pKa values compared to native substrates make the observation of promiscuous reactions more likely. To overcome these issues, we designed microdroplet assays in which optically inactive carbohydrate products are made visible by specific cascades: the primary reaction of an unlabeled substrate leads to an optical signal downstream. Successfully implementing such assays at the picoliter droplet scale allowed us to detect glucose, xylose, glucuronic acid, and arabinose as final products of complex oligosaccharide degradation by glycoside hydrolases by absorbance measurements. Enabling the use of uHTS for screening CAZyme reactions that have been thus far elusive will chart a route toward faster and easier development of specific and efficient biocatalysts for biovalorization, directing enzyme discovery by challenging catalysts for reaction with natural rather than model substrates.

Perspectives of linear motors in electrical engineering

The use of electric linear motion machines is one of the main directions of scientific research in the more advanced drive systems development. The relevance of this direction is due to a wide range of tasks that are set for electric drive systems and the complexity of their designs resulting from various kinematic chains. One of the advantages of using linear electric motors is their ability to compete successfully with other types of drives in many branches of technology, such as automation, instrumentation, robotics, medical technology, etc. The absence of a converter and the ability to perform different types of movement makes linear motors attractive for various applications. One of the promising tasks is the implementation of the translational movement of the mechanism working body using a linear electric motor. This provides new opportunities for the development and improvement of various industrial and technological processes.

Real-time energy flow mapping: A VSM-based proposal for energy efficiency

Rising energy costs and the current concern about sustainability issues directly impact the competitiveness and survival of organizations, promoting the search for continuous improvement in industrial production processes. The present study, by identifying the absence in the literature of models based on Value Stream Mapping and integrated with Industry 4.0 technologies that promote better energy efficiency practices in industrial processes, proposes a new Lean Management model called Real-time Energy Flow Mapping. This innovative model, provide capabilities to a visual, digital and sustainable management system of all energy behavior in machines and equipment using fully parameterizable metrics and rules. Also, estimulating stakeholders with the ability to predict and monitor energy costs, as well as identify possible problems due to changes in the behavior of energy consumption in machines, thus helping managers to make decisions faster and more dynamically. As a result, the literature search turned up 17 Value Stream Mapping based models with a focus on energy efficiency, along with 31 metrics grouped on energy, environmental and production processes. After discussions by the Focus Groups, 16 resulting metrics were submitted to expert panel, in which the least relevant were discarded and the 13 most relevant classified using Fuzzy Delphi. An analysis to verify the interrelationships between the metrics is performed using the Fuzzy DEMATEL, being finally applied in the proposed model. A case study of the model was carried out, submitting it operationally at the LabFaber 4.0, empirically validating the study. The Real Time Energy Flow Map fills the gap in the literature on Value Stream Mapping models to improve energy efficiency, monitoring energy consumption through dynamic mapping of the energy flow of production processes, identifying the area with increased potential for energy savings through changes in operating behavior that reduce overall energy consumption and environmental impacts.

Hot air drying of red beet: Process and product quality monitoring by digital images and near infrared spectroscopy

The use of nondestructive techniques that can guarantee in situ monitoring of the quality of food products during drying processes can promote improvements in industrial processes. In this context, digital imaging and near infrared spectroscopy can play an important role. Red beet moisture content, betalain content, shrinkage, and color were measured during drying. The digital images showed changes in color, which intensified with increasing temperature and correlated with betalain content through multivariate linear regression (R2 of 0.90). In addition, sample shrinkage was identified by digital images. The volumetric shrinkage increased proportionally to the drying air temperature, with a shrinkage of 85.4 ± 0.3% at 70 °C. Spectral data were obtained by a low-cost portable near infrared spectrometer. Partial least square regression was used to predict the product moisture content () and total betalain content () during drying. These tools can be used for the in situ control of red beet drying.

Understanding HMF inhibition on yeast growth coupled with ethanol production for the improvement of bio-based industrial processes

Inhibitory compounds generated from biomass hydrolysis affect the production of biofuels. HMF is a furan derivative inhibitor and influences the ethanol yield by inhibiting enzymes such as alcohol dehydrogenase, aldehyde dehydrogenase and glycolysis. The most striking effect of HMF on the organisms is that it interferes with the microbial growth and is considered as the most potent inhibitor in bioethanol production. In this study, HMF inhibition within yeast cells is investigated by both computational (COBRA) and experimental approaches. The active subsystems in the medium with and without HMF and the coupling types of the reactions are determined to get an insight on how to improve bioethanol production by strain engineering techniques. While extracellular transport subsystem is prominent in term of flexibility, post transcriptional regulation is outstanding among transcriptional to metabolic regulation types. The strategies to increase biomass and ethanol simultaneously with gene/reaction deletion methods are discussed, and ethanol production can be increased by 17% up to 33.35 mmol gDW−1hr−1 with several reaction deletions. The genome scale metabolic model and the complementary experiment given here shed light on the biofuel management in the bio-based industry for future.

Comparison of Chemical and Mechanical Surface Treatments on Metallic Precision Spheres for Using as Optical Reference Artifacts.

The improvement of industrial manufacturing processes requires measurement procedures and part inspection tasks to be faster and faster while remaining effective. In this sense, the capabilities of noncontact measuring systems are of great help, not only because of the great amount of data they provide but also for the ease of the integration of these systems as well as their automation, minimising the impact on the industry. This work presents a comparative study on the influence of two surface treatments performed on low-cost, high-precision metallic spheres on the suitability of these spheres to be used as artefacts for the calibration of optical sensors, specifically laser triangulation sensors. The first surface treatment is sandblasting (a mechanical process), whose effect has been studied and presented in previous work. The second treatment focused on in this paper is acid etching (a chemical process). The comparison has been performed by evaluating the same metrological characteristics on two identical groups of spheres of similar type (diameter and accuracy), each of which was subjected to a different treatment. It was necessary to obtain the reference values of the metrological parameters with high accuracy, which involved measuring the spheres with a coordinate measuring machine (CMM) by contact probing. Likewise, spheres were scanned by a laser triangulation sensor mounted on the same CMM. The results derived from both the contact and laser measurements and before and after treating the surfaces were used to compare four parameters: point density, sphere diameter, sphere form deviation, and standard deviation of the best-fit sphere to the corresponding point cloud. This research has revealed that acid etching produces better optical qualities on the surfaces than the mirror-like original ones, thus enhancing the laser sensor capturing ability. However, such chemical etching has affected the metrological characteristics of the spheres to a greater extent than that produced by sandblasting. This difference is due to the variability of the chemical etching, caused by the high aggressiveness of the acid, which makes the process very sensitive to the time of exposure to the acid and the orientations of the spheres in the bath.

Improvement of industrial processes in Colombia. Case study: Cocoa pressing process in a chocolate factory

This work explored an industrial-scale cocoa liquor pressing process used to obtain two standard fat-reduced cocoa powders with 12% and 16% wt. fat, respectively. A novel methodology was developed to sample and characterize fat content in cocoa cakes as released from the press before the powdering. Cocoa liquors with ~ 53% wt. fat, and with solids containing maximum ~1% wt. of particle below mesh 200 were pressed at 90 °C, and up to 550 bar following a specific time-pressure profile. Fat content in samples was measured with a pulsed nuclear magnetic resonance spectrometer. Experiments enabled to evaluate the variability of fat content of products from different batches, in different cakes from a batch, and within the cakes, verifying large average deviations (~ 5% wt.). By using a Kernel canonical correlation analysis with a Kriging interpolation approach, it was possible to map the fat content profile within the cakes, enabling to identify suitable sampling areas in the cakes for consistent and more accurate measurements of fat content in the product. Finally, the developed methodology was used to characterize different pressing batches at the industrial facility, and to correlate the required processing time for a specific fat content in the liquor.