Industrial Production Processes Research Articles

Duple Color Image Encryption System Based on 3-D Nonequilateral Arnold Transform for IIoT

The Industrial Internet of Things (IIoT) is to continuously integrate network communication, intelligent analysis and other technologies into every link of the industrial production process, thus greatly improving the manufacturing efficiency. While such systems greatly improve the productivity of the industry, they introduce major safety challenges during the design and operational phases. Therefore, it is necessary to encrypt and protect the information transmitted by the system during the design and runtime stages. This paper focuses on the transmission security of image data in every link of IIoT. Two color images that need to be transmitted can be encrypted into color ciphertext image by using 3D Non-equilateral Arnold Transform (3D-NEAT) and 3D Lorenz System (3D-LS). Different from the traditional algorithm which encrypts one plain image into one ciphertext image, our algorithm encrypts two color images into one color ciphertext image which will cause great confusion to the attacker whom illegally breaks the ciphertext image. First, the proposed method converts two color images with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N\times M$</tex-math></inline-formula> into a 3D bit-level matrix with size <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N\times M\times 48$</tex-math></inline-formula> . Next, 3D-NEAT is applied to permutate the positions of the elements of the resulted 3D bit-level matrix. Then, the permutated 3D bit-level matrix is transformed into three 2D pixel-level images and then diffused by the random diffusion sequences which 3D-LS generates. Finally, the scrambling matrices generated by 3D-LS are used to scramble three diffused 2D pixel-level images and the output is considered as three color components of the encrypted image. The numerical experiments and security analysis show that the proposed image encryption scheme has strong resistance to several known attacks, and yields near-zero correlation and near-eight entropy for the RGB cipher image, and some performance is better than some of the recently proposed image encryption algorithms.

Bioprocess development for the production of xylooligosaccharide prebiotics from agro-industrial lignocellulosic waste

The development of sustainable biorefineries and bioeconomy has been the mandate of most of the governments with major focus on restricting the climate change concerns and finding new strategies to maintain the global food supply chain. Xylooligosaccharides (XOS) are short-chain oligomers which due to their excellent prebiotic potential in the nutraceutical sector has attracted intense research focus in the recent years. The agro-industrial crop and food waste can be utilized for the production of XOS which are derived from hemicellulose fraction (xylan) of the lignocellulosic materials. The extraction of xylan, is traditionally achieved by acidic and alkaline pretreatments which, however, have limited industrial applications. The inclusion of cutting-edge and environmentally beneficial pretreatment methods and technologies such as deep eutectic solvents and green catalysts are preferred. Moreover, the extraction of xylans from biomass using combinatorial pretreatment approaches may help in economizing the whole bioprocess. The current review outlines the factors involved in the xylan extraction and depolymerization processes from different lignocellulosic biomass and the subsequent enzymatic hydrolysis for XOS production. The different types of oligosaccharides and their prebiotic potential for the growth of healthy gut bacteria have also been explained. The introduction of modern molecular technologies has also made it possible to identify enzymes and microorganisms with the desired characteristics for usage in XOS industrial production processes.

ITran: A novel transformer-based approach for industrial anomaly detection and localization

Anomaly detection is currently an essential quality monitoring process in industrial production. It is often affected by factors such as under or over reconstruction of images and unclear criteria for feature distribution evaluation, thus making it challenging to improve detection performance. To solve the above problems, this paper proposes a novel transformer-based approach, Inductive Transformer (ITran) for industrial anomaly detection and localization, which utilizes a multi-layer pyramid structure and multi-level jump connections to extract multi-scale features of the data, putting the anomaly detection into the feature space and achieving more accurate industrial anomaly detection and localization results. It incorporates inductive bias and convolution operations into the Transformer which helps to break the myth of Transformer being “data hungry”. Compared with the common Transformers, ITran significantly reduces the computational cost and memory usage and makes it work well on small datasets. In addition, we basically eliminate the effect of positional embedding on the proposed Transformer model. Sufficient experiments have been conducted to validate global anomaly detection on three datasets MNIST, Fashion-MNST and Cifar-10, as well as local anomaly detection on the industrial datasets MVTec AD, Concrete Crack Image and BTAD. The proposed ITran achieves outstanding results on all the above datasets.

A review on the latest developments in solar dryer technologies for food drying process

Solar drying is a traditional method for removing moisture from food products. Dryers with different dimensions and models are often used for drying food products using solar energy. Indirect Solar Dryer (ISD) was the latest development to dry food products and that ISD with fins inserted Thermal Energy Storage (TES) unit to enhance its performance is not being reviewed in detail yet. So, this review intends to study the features and benefits of ISD with fins inserted TES units for removing moisture from food products. Considerable ISD with fins inserted TES outcomes were reviewed, presented and tabled. An economic analysis of ISD was also presented. The numerical analysis of ISD was reviewed and tabulated using Computational Fluid Dynamics (CFD) for drying food products. It was found that an improvement in increased heat and the performance parameters of moisture removal kinetics of food products on ISD with fins inserted TES units. The payback periods were found to be relatively shorter than the lifespan of the devices. Therefore, this type of ISD is recommended for food products processing industries and farmers. CFD technique can be used to assess the performance of a novel development in food dryer research.

Development of an industrial sustainable process for wax esters production: enzyme immobilization, process optimization, and plant simulation

AbstractBACKGROUNDAs a result of the ban on whaling, there has been a shortage of spermaceti, a natural product with applications in cosmetics and pharmaceuticals. A green and sustainable process for the biocatalytic synthesis of a wax ester mixture analogue to natural spermaceti is presented in this paper.RESULTSImmobilization of Candida antarctica lipase B by covalent binding to Purolite® Lifetech™ ECR8285 allowed for an immobilized derivative with 124.5 mg protein/g support (69.3% protein immobilization yield) that maintains 100% of its enzymatic activity after 12 months of cold storage and presents negligible loses of activity after 9 consecutive reaction cycles. The optimization of the synthesis process in a batch reactor resulted in conditions that, at 70 °C, 350 rpm, and 1.25% w/w of biocatalyst, achieved a conversion of 97% after 1 h of reaction. The simulation of a spermaceti production plant was carried out using the process simulation software aspenONE suite v10. The plant was designed for a continuous operation during 9 h per day, with a reactor of 20.25 L of working volume and a residence time of 1 h. The production of this plant would be 173.25 kg spermaceti/day, with a product purity of 99.55%.CONCLUSIONThe main novelty of this work is the design of a spermaceti production plant, using the most sustainable methodologies and resulting in a product with exceptional characteristics and minimal waste generation. Moreover, a new lipase immobilized derivative is also described. The good values of sustainability indicators point to the viability of its industrial implementation. © 2023 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley &amp; Sons Ltd on behalf of Society of Chemical Industry (SCI).

Regional Comprehensive Economic Partnership (RCEP) on agricultural products

Intra-industry trade plays an important role in the current international economics literature. In 2019, Indonesia's total exports to RCEP member countries reached 61.65% of Indonesia's total exports, and 44% of total exports to RCEP came from the agricultural sector. The purpose of this research is to examine the interdependence of Indonesia and its 14 trading partners in RCEP. This research uses secondary time series data from the trademap, namely the flow of Indonesian agricultural trade with RCEP countries from 2010-2019. The data analysis method in this study is the intra-industry trade index. The results of the study of trade patterns identified through the Indonesia-RCEP Trade Relations (IIT) show that the raw material with the highest average IIT value is processed flour (HS 19). This shows that Indonesia's RCEP trade in flour products (HS 19) is bilateral. In terms of country, Malaysia is a country with the strongest trade relations with Indonesia. The average score of 19.74 between IIT Indonesia and RCEP reflects that the relationship between Indonesian agricultural products and RCEP is still low and classified as inter-industry trade. The low IIT value may be due to the large one-way trade in RCEP, where Indonesia is still the dominant importer. Therefore, it is important for the government to further increase potential commodity exports by encouraging agricultural product processing industries with tax breaks within a certain period.

PELATIHAN PENGGUNAAN E-DRAW MAX UNTUK MEMBUAT DESAIN SISTEM

Edraw Max is a 2D business technical diagram software that helps create flowcharts, organization charts, mind maps, network diagrams, floor plans, workflow diagrams, business charts and Engineering diagrams, flowcharts, graphs and mappings, besides E- Draw Max is also a vector-based diagramming software, which is usually used to make it easier to make a design. One of them is the design of a production process system in a factory that can use this application. In this training, the E-Draw Max tools will focus on making Data Flow Diagrams (DFD), which are useful for describing the flow of the created system, which consists of Context Diagrams, Level Diagrams, and Level n Diagrams. Data Flow Diagram (DFD) is a diagram that describes the flow of data from a process or information system. In DFD, there is information related to the input and output of each of these processes. DFD also has various functions, such as conveying system design, describing systems, and designing models. This training was held at the ITS NU Pekalongan Institute of Computer Technology. The purpose of this training is to help ITS NU Pekalongan S1 Computer Technology students in making system designs, specifically designing Data Flow Diagrams (DFD) using E-Draw Max tools to make it easier for students to make the flow of the system made in this case DFD on production process in Industry.

Production Strategy and Technology Innovation under Different Carbon Emission Polices

Given that the production process in the manufacturing industry is a significant contributor to carbon emissions, many governments have implemented carbon emission-related policies to incentivize manufacturers to optimize their production process or invest in green production technology, with the aim of reducing their carbon footprint. Therefore, it is necessary to determine the effectiveness of carbon policies considering manufacturers always tend to prioritize economic profits in their actual operations. We compare the effects of three different carbon emission policies—carbon tax, cap-and-trade, and intensity target—on manufacturers’ production strategies and technology innovation investments, which include production and carbon emission quantities, price of goods and emission permit, and technological innovation of the production improvement and the emission abatement. The study results show that the intensity target policy increases the carbon market price and decreases the carbon emission rate. For the manufacturers with higher (lower) initial emission intensity, intensity target policy induces them to decrease (increase) production quantities and carbon emission quantities. For the technology innovation choice, cap-and-trade induces more incentive on production improvement technology innovation for manufacturers with lower initial emission intensity and carbon emission abatement technology innovation for manufacturers with higher level initial emission intensity.

Engineering chitin deacetylase AsCDA for improving the catalytic efficiency towards crystalline chitin

Chitin deacetylase (CDA) catalyzing the deacetylation of crystal chitin is a crucial step in the biosynthesis of chitosan, and also a scientific problem to be solved, which restricts the high-value utilization of chitin resources. This study aims to improve the catalytic efficiency of AsCDA from Acinetobacter schindleri MCDA01 by a semi-rational design using alanine scanning mutagenesis and saturation mutagenesis. The quadruple mutant M11 displayed a 2.31 and 1.73-fold improvement in kcat/Km and specific activity over AsCDA, which can remove 68 % of the acetyl groups from α-chitin. Furthermore, structural analysis suggested that additional hydrogen bonds, contributing the flexibility of amino acids and increasing the negative charge in M11 increased the catalytic efficiency. The microstructure changes of α-chitin pretreated by the mutant M11 were observed and evaluated using 13C CP/MAS NMR spectroscopy, FT-IR spectroscopy, XRD and SEM, and the results showed that M11 more efficiently catalyzed the release of acetyl groups from α-chitin. This study would provide a theoretical basis for the molecular modification of CDAs and accelerate the process of industrial production of chitosan by CDAs.

CFD-DPM data-driven GWO-SVR for fast prediction of nitrate decomposition in blast furnaces with nozzle arrangement optimization

In the industrial production process, it is important to improve the productivity of blast furnaces in response to the worldwide call for energy saving and emission reduction. In this study, a data-driven method using computational fluid dynamics (CFD) is developed for the rapid prediction of nitrate decomposition in a blast furnace. The method includes the creation of a CFD database, for which nozzle arrangement patterns, relative distances, spray cone angles and temperatures are simulated and collected. Support vector regression (SVR) hyperparameters are optimized using genetic algorithm (GA), particle swarm optimization (PSO), and gray wolf optimizer (GWO). Machine learning interpretability methods shapley additive explanations (SHAP) and partial dependence plots (PDP) are used to analyze the impact of features on prediction results. The results show that the hybrid GWO-SVR model has a better performance, with the degree of fit (R2) improving from 0.7752 to 0.9719. When the distance is taken around 0.58, increasing the temperature and cone angle is more favorable to improve the decomposition rate of the blast furnace. SHAP method shows that only the arrangement 2 and 4 have a positive effect on improving the decomposition rate. The response time for accurate prediction of nitrate decomposition rate is 259200 times shorter than that of industrial-scale CFD simulations. The method is also used to determine the best combination of solutions. This cross-disciplinary approach provides a time-saving and cost-effective tool for improving the response of blast furnace productivity to changes in nozzle arrangement.

Multiple steady states and metabolic switches in continuous cultures of HEK293: Experimental evidences and metabolomics

The optimization of the production process in the biotechnology industry needs a deep understanding of the metabolic patterns developed in the bioreactors. In particular, the possibility to induce changes between different metabolic states in these cultures has opened a new path to reach this optimization. The goal is to drift the culture toward a metabolic state of maximum productivity. In this work we experimentally explore and analyze this path using a HEK293 cell line, transfected to produce the HER1 glycoprotein, cultured in continuous mode. We first show that this cell culture exhibits steady state multiplicity, i.e., different cell densities and protein concentrations for the same experimental parameters. We also demonstrate that the switch between these steady states can be triggered manipulating the dilution rate in the bioreactor. Furthermore, we present an extensive metabolic characterization of the steady states measuring metabolic concentrations through Liquid Chromatographic-Mass Spectrometry (LC-MS). The data obtained is processed using Principal Component Analysis (PCA), unveiling a correspondence between the culture multiplicity and the existence of distinctive metabolic states. Our results support the idea that different stationary states, although obtained for the same experimental parameters, are consistent with major metabolic readjustments in the culture. Finally, the comparison of the different steady states demonstrates that, in this case, the state with reduced lactate production benefits volumetric productivity.

How Can We Control Precision in the ECM Process?

Electrochemical machining (ECM) technology has witnessed several research and development breakthroughs since its introduction in early 1900s. The ECM process serves as one of the key production processes in aerospace, die-moulds, tooling and automotive industries. Over time, the demands on precision have increased and this has resulted in several developments focusing specifically on improving precision in ECM processing. However, the existing review papers have not extensively focused on the methods and parameters controlling precision in the ECM process. Therefore, this article reviews the aspects of precision of ECM processes. This article will serve as a quick-read reference for researchers/engineers looking for precision ECM. An attempt is made to answer the main question posed by industry and academia “How can we control precision in the ECM process”?

Realizing of ZSM-5 microspheres with enhanced catalytic properties prepared from iron ore tailings via solid-phase conversion method.

The comprehensive utilization of iron ore tailings (IOTs) not only resolved environmental problems but also brought huge economic benefits. In this study, the synthetic route presented herein provides a novel method for the synthesis of ZSM-5 microspheres from IOTs. The effects of Si/Al molar ratios and the pH of the precursor solution on the formation of zeolite was evaluated by various analytical methods. The catalytic performance of the catalyst prepared by the solid-phase conversion method (denoted as MP-ZSM-5) was evaluated by methanol-to-propylene (MTP) reaction. Compared with the zeolite catalyst that synthesized via the conventional hydrothermal method (denoted as HM-ZSM-5), MP-ZSM-5 not only prolongs catalytic lifetime from 18.7 to 36.0h but also has higher selectivity for propylene by MP-ZSM-5 (43.7%) than that for HM-ZSM-5 (38.6%). In addition, Kissinger-Akahira-Sunose (KAS) model is applied to the TG result to study the template removal process kinetics. The average activation energy values required for the removal of CTAB and TPABr are 201.11 ± 13.42 and 326.88 ± 16.91kJ∙mol-1, respectively. Furthermore, this result is well coupled with the model-free kinetic algorithms to determine the conversion and isoconversion of the TPABr and CTAB decomposition in ZSM-5, which serves as important guidelines for the industrial production process.

Unleashing the potentials of digital twinning in the production of composite aircraft components

The aircraft industry is continuously challenged to deliver more complex products in order to meet increasingly stricter regulations and growing customer demands, to provide better quality products in larger quantities, and to pay more attention to reusability and circularity issues. At the same time, the industry needs to work with lower costs, shorter lead and production times, less waste, delay, energy consumption, and emissions, and reduce its dependence on non-renewable materials. To keep up with these challenges, the industry automates and continuously innovates as much as is possible. The increasing use of composites in aircraft and aircraft components adds the extra challenge of rapidly bringing innovative manufacturing processes to the factory floor. Aircraft product design, analysis, testing, and production are increasingly being digitized and automated, and consequently involve, and produce, more and more data. Digital twinning is an important enabler for mastering and exploiting this ever-growing plethora of data. In this paper we discuss the potentials of digital twinning in innovative production processes in the aircraft industry, and describe first-hand results and experiences in developing and using digital twinning in the production of composite aircraft components, illustrated by concrete example applications.

Ways to increase the efficiency of industrial production of combined feed

This paper aims at finding a solution to the main problem of feed production: increasing the efficiency of the production process while improving the quality of products. The article aims to develop an adequate mathematical model of the technological process of combined feed industrial production. The authors have developed the theoretical background for describing this process on the basis of flow models within the framework of the original “three effects” concept, a stochastic model has been created taking into account the preservation of the exergy balance of the technological system. The main research tool is the apparatus of system analysis and the theory of random processes. An engineering-mathematical calculation of the parameters of the constructed model was performed, verification of the stochastic model of the technological process of preparing compound feeds in laboratory conditions was carried out. As a result of the research, the authors established the possibility of controlling the stochastic feed flow in all subsystems of the production technological system, outlined ways to solve the problem of increasing the efficiency of feed production by reducing energy costs and improving the output product granulometric composition.

IMPACT OF TOBACCO EXCISE ON SECTORAL OUTPUT AND GROSS INCOME OF INDONESIA : AN APPLICATION OF INPUT OUTPUT ANALYSIS

(Excise on Tobacco Products (CHT) as the largest contributor to the Indonesian economy when compared to other excisable goods reaches 96% so it is considered quite effective to improve the country's economy. CHT has increased every year with the aim of controlling the negative impact of cigarette consumption and relaxing the success of the High Risk Excise Control (PBHT) in eradicating illegal cigarettes. This study aims to analyze the impact of the CHT increase on sectoral output and Gross Domestic Product. The method of analysis in this study is Input-Output using the 2010 IO table (updated in 2019). The classification of the Input Output table is 185 sectors and aggregated into 21 sectors. The analysis in this study is multiplier analysis, distribution and linkage. The result is that the increase in CHT on the tobacco product processing industry has no impact on the national economy as a whole, so it is better for the CHT increase regulation to remain in effect. The government must supervise related parties in the production of the cigarette industry so that fraud does not occur if the CHT increase is still in effect.

CFD simulation and optimization of turning different waste gases into energy in an industrial steam methane reformer

BackgroundOne of the most important processes of industrial hydrogen production is steam methane reforming (SMR). However, the biggest drawback of steam reformer processes is high energy consumption. In methanol production units, 40% of the energy consumed in the steam reformer is provided by methane burning. The best solution to reduce the consumption of methane gas is to use the waste gases of the units. InnovationTo boost the thermal performance of the furnace, as well as the reduction in natural gas utilization, the effects of the kinds of fuel in an industrial unit are investigated. Furthermore, the waste gas is studied to whether it can be used as fuel in an SMR or not. SignificanceCFD is one of the most powerful tools for simulation of the industrial by which a new unit can be set up or the performance of the old units can be developed. Additionally, the effect of diverse parameters on industrial processes can be examined, and the optimal operating conditions of the industrial unit can be found. MethodsIn this study for five different cases of fuel, the furnace of an industrial SMR unit, at the operating conditions, was simulated using Computational Fluid Dynamics, (CFD) and the results were validated by the industrial data. Moreover, regarding the higher thermal efficiency of the furnace and the lower consumption of natural gas, two cases called design, and the suggested modes, were investigated and suggested mode was proposed as the most suitable fuel. FindingBased on the results, removing purge gas and adding waste gases with lower hydrogen content are recommended. Compared with the operational fuel, the suggested mode decreases the flue gas temperature by 11.78 K and increases the temperature of the first row of the reformer tubes by about 4.17 K, while declining the natural gas molar flow rate by 32%. A 64% reduction in hydrogen content of the suggested mode leads to an increase 10% flame length and 14% enhancement of adsorbed radiative heat flux. Moreover, in the suggested mode it is possible to recycle the purge gas to the methanol synthesis reactor and enhance the methanol production to 1% which is 50 ton/day.

Robust Surveillance Schemes Based on Proportional Hazard Model for Monitoring Reliability Data

Product reliability is a crucial component of the industrial production process. Several statistical process control techniques have been successfully employed in industrial manufacturing processes to observe changes in reliability-related quality variables. These methods, however, are only applicable to single-stage processes. In reality, manufacturing processes consist of several stages, and the quality variable of the previous stages influences the quality of the present stage. This interdependence between the stages of a multistage process is an important characteristic that must be taken into account in process monitoring. In addition, sometimes datasets contain outliers and consequently, the analysis produces biased results. This study discusses the issue of monitoring reliability data with outliers. To this end, a proportional hazard model has been assumed to model the relationship between the significant quality variables of a two-stage dependent manufacturing process. Robust regression technique known as the M-estimation has been implemented to lessen the effect of outliers present in the dataset corresponding to reliability-related quality characteristics in the second stage of the process assuming Nadarajah and Haghighi distribution. The three monitoring approaches, namely, one lower-sided cumulative sum and two one-sided exponentially weighted moving average control charts have been designed to effectively monitor the two-stage dependent process. Using Monte Carlo simulations, the efficiency of the suggested monitoring schemes has been examined. Finally, two real-world examples of the proposed control approaches are provided in the study.

Toward More Sustainable Hydraulic Binders: Controlling Calcium Sulfate Phase Selection via Specific Additives

Bassanite (calcium sulfate hemihydrate) is one of the most extensively used inorganic binders in construction applications. Current industrial processes for the large-scale production of the mineral rely almost exclusively on the thermal dehydration of gypsum (calcium sulfate dihydrate), which consumes considerable amounts of energy. Here, we show that phase-pure bassanite can be obtained in high quantities by spontaneous precipitation from supersaturated solutions at moderate temperatures, where gypsum usually forms as a predominant solid phase. Key to control over phase selection is the presence of specific additives during crystallization, which carry functional groups for binding onto calcium sulfate surfaces as well as additional moieties that withdraw water in the local microenvironment. Some of the investigated additives allowed bassanite to be recovered in large amounts at temperatures as low as 40 °C and added concentrations of only 0.1 M or even less. The concepts described in this work pave the way toward alternative approaches, enabling a less energy-intensive and thus more sustainable production of bassanite for use in construction and other applied systems.

Solid-State Fermentation: Applications and Future Perspectives for Biostimulant and Biopesticides Production.

With the expansion of the green products market and the worldwide policies and strategies directed toward a green revolution and ecological transition, the demand for innovative approaches is always on the rise. Among the sustainable agricultural approaches, microbial-based products are emerging over time as effective and feasible alternatives to agrochemicals. However, the production, formulation, and commercialization of some products can be challenging. Among the main challenges are the industrial production processes that ensure the quality of the product and its cost on the market. In the context of a circular economy, solid-state fermentation (SSF) might represent a smart approach to obtaining valuable products from waste and by-products. SSF enables the growth of various microorganisms on solid surfaces in the absence or near absence of free-flowing water. It is a valuable and practical method and is used in the food, pharmaceutical, energy, and chemical industries. Nevertheless, the application of this technology in the production of formulations useful in agriculture is still limited. This review summarizes the literature dealing with SSF agricultural applications and the future perspective of its use in sustainable agriculture. The survey showed good potential for SSF to produce biostimulants and biopesticides useful in agriculture.