Stability Of Production Process Research Articles

Dual Hydrogen Production System: Synergistic Effect of Ru and Ce Over Cu2O Nanotubes Drives Hydrogen Evolution and Formaldehyde Oxidation.

Water splitting for hydrogen production is limited by high cell voltage and low energy conversion efficiencies due to the slow kinetic process of the oxygen evolution reaction (OER). Here, an electrolytic system is constructed in which the cathode and anode co-release H2 at ultra-low input voltage using formaldehyde oxidation reaction (FOR) instead of OER. The prepared RuCe co-doped Cu2O nanotubes on copper foam (RuCe-Cu2O/CF) are used as electrode materials for the HER-FOR system. A current density of 0.8 A cm-2 is achieved at 0.55V, and a stable hydrogen production process is realized at both the cathode and anode. Density functional theory (DFT) studies show that the synergistic effect of Ru and Ce drives: i) the d-band center of RuCe-Cu2O/CF away from the Fermi energy level; ii) the energy barrier for the C─H cracking of the H2C(OH)O* intermediate in FOR is lowered, which promotes the formation of H2 from H*, and iii) ΔGH* tends to 0 (-0.1eV), optimizing the reaction kinetics of HER. This work provides a new design for an efficient catalyst for dual hydrogen production systems from water splitting.

Scaling up production of recombinant human basic fibroblast growth factor in an Escherichia coli BL21(DE3) plysS strain and evaluation of its pro-wound healing efficacy.

Introduction: Human basic fibroblast growth factor (hbFGF) is a highly valuable multifunctional protein that plays a crucial role in various biological processes. In this study, we aim to accomplish the scaling-up production of mature hbFGF (146aa) by implementing a high cell-density fermentation and purification process on a 500-L scale, thereby satisfying the escalating demands for both experimental research and clinical applications. Methods: The hbFGF DNA fragment was cloned into a mpET-3c vector containing a kanamycin resistance gene and then inserted into Escherichia coli BL21 (DE3) plysS strain. To optimize the yield of hbFGF protein, various fermentation parameters were systematically optimized using BOX-Behnken design and further validated in large-scale fermentation (500-L). Additionally, a three-step purification protocol involving CM-Sepharose, heparin affinity, and SP-Sepharose column chromatography was developed to separate and purify the hbFGF protein. Isoelectric focusing electrophoresis, MALDI-TOF/MS analysis, amino acid sequencing, CD spectroscopy, and Western blotting were performed to authenticate its identity. The biological efficacy of purified hbFGF was evaluated using an MTT assay as well as in a diabetic deep second-degree scald model. Results: The engineered strain was successfully constructed, exhibiting high expression of hbFGF and excellent stability. Under the optimized fermentation conditions, an impressive bacterial yield of 46.8 ± 0.3g/L culture with an expression level of hbFGF reaching 28.2% ± 0.2% was achieved in 500-L scale fermentation. Subsequently, during pilot-scale purification, the final yield of purified hbFGF protein was 114.6 ± 5.9mg/L culture with RP-HPLC, SEC-HPLC, and SDS-PAGE purity exceeding 98%. The properties of purified hbFGF including its molecular weight, isoelectric point (pI), amino sequence, and secondary structure were found to be consistent with theoretical values. Furthermore, the purified hbFGF exhibited potent mitogenic activity with a specific value of 1.05 ± 0.94 × 106AU/mg and significantly enhanced wound healing in a deep second-degree scald wound diabetic rat model. Conclusion: This study successfully established a stable and efficient large-scale production process of hbFGF, providing a solid foundation for future industrial production.

Enhancing energy recovery and microbial stability in blackwater anaerobic digestion with graphite felt

Maximizing energy recovery from blackwater (toilet wastewater) helps the sustainable development of human society. This study introduces a novel approach by integrating graphite felt in anaerobic baffled reactor for enhanced blackwater treatment under room temperature. During the 382-day operation, incorporating graphite felt effectively mitigated hydrolysis and methanogenesis constraints, resulting in a 1.26 to 3.53-fold increase in methane yield compared to the control. The maximum energy recovery was attained at a hydraulic retention time of 1.59 d and an organic loading rate of 2.68 kg COD/m3reactor/d, with a methane production rate of 371 ± 55 NL CH4/m3reactor/d and a methanization rate of 39.44 ± 5.58 % in graphite felt amended reactor. Our findings revealed that graphite felt augmented the efficiency of microbial and enzymatic interactions with the substrate, and enriched hydrolysis fermentation-associated bacteria for efficient solid matter degradation. Further analysis unveiled that graphite felt strengthened the activity of hydrogenotrophic methanogens and fortified the syntrophic relationship between bacteria and archaea. This led to the promotion of a combined syntrophic acetate oxidation and hydrogenotrophic methanogenesis pathway, which guaranteed a stable and efficient methane production process. Overall, this approach offers a cost-effective and efficient strategy to support sustainable development in less-developed, resource-constrained regions.

Implanting pyrazine ring into g-C3N4 for accelerating photocatalytic hydrogen evolution

It is of great significance to develop an efficient and stable photocatalyst for the photocatalytic decomposition of water to produce hydrogen. Within this paper, an effective and simple strategy was adopted to introduce pyrazine ring into graphite-like carbon nitride framework to realize efficient and stable hydrogen production process. After evaluation, the hydrogen production efficiency of the modified semiconductor material is 3.05 folds higher than the unmodified graphite-like phase carbon nitride, and an excellent stability performance was also achieved. It is proved that the light absorption ability of doped semiconductor composite nanomaterials was enhanced markedly by introducing 2-aminopyrazine into the carbon nitride structure. Meanwhile, the segregation efficiency of photo-induced carriers was obviously accelerated because the amino groups can work as hole trapping agents. Additionally, the introduced amino groups own Lewis alkalinity, which is in favour of the photoreduction. This work expands a new perspective of stable photocatalysts in the water split to produce hydrogen.

Study on induction of Allium sativum L. hairy roots with antibacterial activity against Vibrio

Allium sativum L. has long been used to improve the health of humans and other species due to its antibacterial activity. Applying biotechnology to create a stable and large-scale production process for Allium sativum L., medicinal herbs by hairy root culture technology are essential. However, Allium sativum L. is a monocotyledonous plant, so its ability to induce hairy roots is lower than that of dicotyledonous plants, which requires more research investment. In this study, we succeeded in inducing hairy roots in monocotyledonous plants Allium sativum L, by evaluating parameters impacting hairy root induction such as plant organs, acetosyringone concentration, infection time and co-culture time. The results showed that the optimal procedure for induction of Allium sativum L. hairy roots by Agrobacterium rhizogenes ATCC 15834 was as follows: 10 day old in vitro Allium sativum L. sprouts were wound and soaked in 100 μM acetosyringone solution for 10 min, infection time was 5 minutes, co-culture time was 48 hours cultured on B5 medium (Gamborg B5 medium) having the induction rate of hairy roots reaching 64.4% after 14 days of culture. Allium sativum L. hairy roots had good antibacterial effect against all three strains of Vibrio cholerae, Vibrio parahaemolyticus and Vibrio vulnificus because the MBC/MIC ratios are all less than or equal to 2. Especially, for V. cholerae (MIC = 1.84 mg/ml, MBC = 2.11 mg/ml), hairy roots have antibacterial activity equivalent to tetracycline antibiotics and better than non-infectious roots.

From Corrective to Predictive Maintenance-A Review of Maintenance Approaches for the Power Industry.

Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review shows the evolution of maintenance approaches to support maintenance planning, equipment monitoring and supervision. We present older techniques traditionally used in maintenance tasks and those that rely on IT analytics to automate tasks and perform the inference process for failure detection. We analyze prognostics and health-management techniques in detail, including their requirements, advantages and limitations. The review focuses on the power-generation sector. However, some of the issues addressed are common to other industries. The article also presents concepts and solutions that utilize emerging technologies related to Industry 4.0, touching on prescriptive analysis, Big Data and the Internet of Things. The primary motivation and purpose of the article are to present the existing practices and classic methods used by engineers, as well as modern approaches drawing from Artificial Intelligence and the concept of Industry 4.0. The summary of existing practices and the state of the art in the area of predictive maintenance provides two benefits. On the one hand, it leads to improving processes by matching existing tools and methods. On the other hand, it shows researchers potential directions for further analysis and new developments.

Development and validation of a peptide-mapping procedure for a novel C1 esterase inhibitor

Peptide mapping is a key method for studying the primary structure of proteins. With its sensitivity to the slightest changes in the covalent structure of a protein, this method is applicable both to medicinal product identification at the control stage and to production process stability monitoring.The aim of the study was to develop and validate a peptide-mapping procedure for the identification of a novel highly glycosylated recombinant C1 esterase inhibitor.Materials and methods. The authors studied recombinant human C1 esterase inhibitor products and trypsin. The study involved peptide mapping using reverse-phase high-performance liquid chromatography and high-resolution mass spectrometry. The following statistics were calculated to evaluate the results: mean, standard deviation, and coefficient of variation. The validation parameters included specificity, precision, and robustness.Results. The authors tested several variants of sample preparation for tryptic digests, including additional N-glycanase treatment and complete deglycosylation, and established the optimal conditions for sample preparation and chromatographic separation of C1 esterase inhibitor peptides to obtain consistent chromatographic profiles (peptide maps). The authors identified characteristic peaks and the corresponding relative retention time and area ranges. The absolute retention time of the second (characteristic) peak was approximately 16.5–16.9 minutes. The relative retention times were 2.14–2.21 for peak 9, 2.55–2.64 for peak 12, 2.97–3.14 for peak 14, 3.11–3.29 for peak 15, and 6.20–6.63 for peak 28.Conclusions. The authors developed a peptide-mapping procedure for C1 esterase inhibitors and optimised the conditions to achieve an over 18-hour reduction in sample preparation time. This procedure met the established acceptance criteria for specificity, precision, and robustness.

Simulating a Digital Factory and Improving Production Efficiency by Using Virtual Reality Technology

The main goal of every production is an optimally set and stable production process with the lowest possible costs. Such settings can only be achieved through many years of experience or very specific research, which focuses on several critical factors. An example of such factors can be the size and use of available space or the location of the production line and the logistical location of individual production sites, which is individual for each production process. Specific research can be carried out, for example, by means of the TX Plant simulation application, which was used in the present article for the production process of making fiber from pellets. The output of this research is the effective use of the so-called “Digital factory” to make the process in the already created conditions more efficient. This was achieved by the TX Plant simulation application, resulting in a reduced production time and increasing overall productivity. An intuitive interaction with factory equipment is possible with this approach, which allows users to immerse themselves in the virtual factory environment. As a result, a layout’s efficiency of surface use, flow of martial, and ergonomics can be assessed in real time. This paper aims to demonstrate how virtual reality (VR) can be used to simulate a digital factory to aid in decision making and enhance factory efficiency.

Shewhart Control Charts Implementation for Quality and Production Management

Shewhart control charts are suitable for stable but repetitive production processes used for the subsequent identification of random deviations while indicating breached quality limits. They provide information on process variability and, at the same time, make it possible to obtain information on the reliability of monitored processes. The objective of this paper is to assess the quality characteristics of plastic mouldings for the needs of the automotive industry with the application of the control charts method, specifically Shewhart control charts. The Shewhart control charts were applied to evaluate the quality characteristics, or, more specifically, to evaluate the measured width and length of the produced plastic mouldings by statistical analysis. Statistical analyses show that the set parameters are not met in the first two days of the test series. An improvement in the process is observed on the last day of the test series. The process is well set, as confirmed by our verification of the stability of the process. An important condition for setting the control charts is to observe the correct chronological arrangement and regular acquisition of measured values. Solving tasks in the future must be oriented to an evaluation of the capability of the production process of the monitored product. The proposal for future research will be oriented toward the evaluation of this capability via process capability indices that derive continuous data by using the classical method.

Research and application of the sintering whole process intelligent manufacturing system

ABSTRACT Stable production processes, high efficiency and good product quality are the main objectives of the sintering industry. Taking the whole sintering production process as the research object, cutting-edge intelligent algorithms and classical sintering theories are applied to establish a sintering batch optimization model, a sinter layer permeability prediction model, a sintering end point optimization control model and a sinter quality prediction and evaluation model respectively, supported by a large amount of historical data, so that the model has reasonably accurate results as well as strong practicality. At the same time, a sintering whole process intelligent manufacturing system based on the above four models is constructed using Java and Python programming languages. The system realizes the functions of real-time analysis of key parameters, intelligent early warning, decision optimization and fault tracing, which provides reasonable line optimization suggestions for field operators, and significantly improves the intelligence and production efficiency of sintering process.

An efficient production planning approach based demand driven MRP under resource constraints

Production plans based on Material Requirement Planning (MRP) frequently fall short in reflecting actual customer demand and coping with demand fluctuations, mainly due to the rising complexity of the production environment and the challenge of making precise predictions. At the same time, MRP is deficient in effective adjustment strategies and has inadequate operability in plan optimization. To address material management challenges in a volatile supply-demand environment, this paper creates a make-to-stock (MTS) material production planning model that is based on customer demand and the demand-driven production planning and control framework. The objective of the model is to optimize material planning output under resource constraints (capacity and storage space constraints) to meet the fluctuating demand of customers. To solve constrained optimization problems, the demand-driven material requirements planning (DDMRP) management concept is integrated with the grey wolf optimization (GWO) algorithm and proposed the DDMRP-GWO algorithm. The proposed DDMRP-GWO algorithm is used to optimize the inventory levels, shortage rates, and production line capacity utilization simultaneously. To validate the effectiveness of the proposed approach, two sets of customer demand data with different levels of volatility are used in experiments. The results demonstrate that the DDMRP-GWO algorithm can optimize the production capacity allocation of different types of parts under the resource constraints, enhance the material supply level, reduce the shortage rate, and maintain a stable production process.

Study on production decline law of fracturing wells in southeast Sulige tight gas field

The main exploitation strategies in southeast Sulige gas field of Ordors Basin are hydraulic fracturing and downhole throttling are mainly adopted. Fractured wells in southeast Sulige gas field have no real stable production process, and the production is constantly decreasing. Fitting effect of adopting one decreasing method to investigate production decline is poor, such as Arps decline, SEPD decline and Duong decline methods. Because of such problems and production characteristics of southeast Sulige, a three-stage decline law study is put forward. The early production decline of gas well belongs to exponential decline, the middle stage belongs to exhaustion decline, and the intermittent exploitation stage belongs to linear decline mode. Most of the production of gas well comes from early and middle production. The study of decline law could provide certain guidance for the evaluation of recoverable reserves and development strategy.

Tapping into Middle Eastern Markets for Soft Drinks Industry of Bangladesh

Though in a relatively infant stage, the soft drink industry of Bangladesh has been thriving. Coupled with high-tech machinery, a stable production process (i.e., aseptic plant) and maintaining international standards have led some companies to export soft drinks to approximately 110 countries. However, despite these achievements, the companies still deal with wavering consumer perception, cultural differences and barriers to enter foreign markets (i.e., the Middle East). Focusing on Akij Food and Beverage Ltd., this case mainly sheds light on how local companies are adapting their strategies to tackle these hurdles: dealing with the fast and fickle consumers, scepticism about quality, changing production lines and even the brand name of products to enter the Middle East markets. The case revisits classical international business topics, such as expansion strategies, culture, communications, global strategic rivalry theory, global supply chain management and distribution networks.

Efficiency of serum application for prevention and treatment of cattle

The possibility of using serum against pasteurellosis, salmonellosis, escherichiosis, parainfluenza type 3, and infectious bovine rhinotracheitis has been investigated and proven. The stability of production processes in the manufacture of the drug is shown. It has been established that the use of serum in treatment or prevention enhances specific immunity and contributed to the safety of animal population. Serum against pasteurellosis, salmonellosis, escherichiosis, parainfluenza type 3, and infectious bovine rhinotracheitis is a solution for injection. The search for new drugs for the prevention and treatment of farm animals is an urgent task. For veterinary medicinal products, not only high immunogenicity and active protection against diseases are fundamental importance, but also low cost. Only with the economically affordable and sufficiently efficient sera, the possibility of preventing the spread of diseases is realized. Considering the economic component variety of polyvalent antigens for serum production is is significantly reduced. The possibility of using serum against pasteurellosis, salmonellosis, escherichiosis, parainfluenza type 3, and infectious bovine rhinotracheitis has been investigated and proven. The serum is safe, has preventive and therapeutic properties. Medicinal product, namely, Serum against pasteurellosis, salmonellosis, escherichiosis, parainfluenza type 3, infectious bovine rhinotracheitis is registered by the The Federal Service for Veterinary and Phytosanitary Supervision in Register of medicinal products for veterinary use, registered in the Russian Federation. Number of the registered certificate of the medicinal product for veterinary use 02-1-35.13-2309 №ПВР - 1-1.5/02079.

The Effect of High Silicon and Molybdenum Content on the Mechanical Properties and Microstructure of Gray Cast Iron

This paper presents an overview of the current knowledge concerning SiMo ductile cast iron begins by describing the standard type of ductile cast iron before proceding to description of its microstructures. The paper then presents its chemical composition and the significant influence of individual elements on technological and mechanical properties. The research section focuses the influence of the addition of Si and Mo to the matrix of gray iron. After casting, stepped samples were carried out on the microstructure along with UTS tensile strength tests. The research presented in the article is a preliminary step towards the goal of obtaining a stable production process for silico-molybdenum cast iron.

Preparation of Recombinant Human Collagen III Protein Hydrogels with Sustained Release of Extracellular Vesicles for Skin Wound Healing.

Existing treatment methods encounter difficulties in effectively promoting skin wound healing, making this a serious challenge for clinical treatment. Extracellular vesicles (EVs) secreted by stem cells have been proven to contribute to the regeneration and repair of wound tissue, but they cannot be targeted and sustained, which seriously limits their current therapeutic potential. The recombinant human collagen III protein (rhCol III) has the advantages of good water solubility, an absence of hidden viral dangers, a low rejection rate and a stable production process. In order to achieve a site-specific sustained release of EVs, we prepared a rhCol III hydrogel by cross-linking with transglutaminase (TGase) from Streptomyces mobaraensis, which has a uniform pore size and good biocompatibility. The release profile of the rhCol III-EVs hydrogel confirmed that the rhCol III hydrogel could slowly release EVs into the external environment. Herein, the rhCol III-EVs hydrogel effectively promoted macrophage changing from type M1 to type M2, the migration ability of L929 cells and the angiogenesis of human umbilical vein endothelial cells (HUVECs). Furthermore, the rhCol III-EVs hydrogel is shown to promote wound healing by inhibiting the inflammatory response and promoting cell proliferation and angiogenesis in a diabetic rat skin injury model. The reported results indicate that the rhCol III-EVs hydrogel could be used as a new biological material for EV delivery, and has a significant application value in skin wound healing.

Integrated Offsite Logistics Scheduling Approach for High-Rise Modular Building Projects

By maximizing offsite work and minimizing onsite activities, modular construction has become increasingly popular in high-rise, high-density cities. For successfully delivering high-rise modular buildings, a key issue is the effective scheduling of offsite logistics, consisting of module manufacturing, transportation, and storage. This paper proposes an integrated offsite logistics scheduling approach for high-rise modular building projects that addresses project-specific constraints and uncertainties, based on the stochastic Petri net (SPN) method. The proposed approach supports multi-criteria decision-making, that considers completion time, total cost, storage capacity utilization, and production process stability under what-if scenarios. Its efficacy and novelty for offsite logistics scheduling were demonstrated through a real-life project case study. The results indicate the need to (1) strengthen suppliers’ demand responsiveness by shortening module production time; (2) enhance manufacturing flexibility by increasing factory storage utilization; (3) improve supply chain synchronization; and (4) capitalize on the government’s role in offsite logistics enhancement. The findings methodologically innovate offsite logistics scheduling, and practically support contractors and module suppliers in successfully delivering high-rise modular building projects in high-density cities.

Intelligent prediction and early warning of abnormal conditions for fluid catalytic cracking process

Fluid catalytic cracking (FCC) is a key unit in the petrochemical production process with frequently encountered abnormal conditions and great safety challenge due to its complex and harsh production environment. The prediction and early warning of abnormal conditions in FCC process is able to improve the safety and stability of production process and avoid the occurrence of severe accidents. In this paper, a data-driven and knowledge-based fusion approach (DL-SDG) is proposed for prediction and early warning of abnormal conditions in FCC process. Firstly, the key variable is identified as prediction target of the process through the calculation of centrality in complex network. Secondly, Spearman ranking correlation coefficient is used for the selection of feature variables to reduce the input data dimension and improve the prediction accuracy of the deep learning (DL) model. Then, the long short-term memory network with attention mechanism and convolution layer is applied to predict the future trend of the key variable. Finally, the signed directed graph (SDG) model deduces the propagation path of abnormal conditions based on the predicted results of key variable to facilitate handling the anomaly in time. The proposed method was successfully applied to a typical FCC unit in a petrochemical enterprise with an excellent performance.

Towards monitoring of a cricket production using instance segmentation

A growing world population requires sufficient food to sustain itself. Therefore, increasingly more resources are required to produce the food. Insects are a viable food and feed alternative since their production requires only a fraction of the resources that conventional livestock needs. For the efficient production of insects, automation technology is needed. An automatic monitoring of the insects’ growth ensures stable production processes and a high product quality. The use of a camera with image processing using neural networks makes it possible to detect insects, measure their features such as shape and colour and enables to derive their age, size, and health. In this paper, instance segmentation using mask scoring regional convolutional neural network (Mask Scoring R-CNN) shows good results in detecting house crickets (Acheta domesticus). A dataset is created consisting of six images, showing 1,022 insect instances, of a real-world cricket production facility to train and test the algorithm. Furthermore, image augmentation by cropping, flipping and rotating is applied to the set to solve the problem of limited data. By combining the augmentations, 288 different trainings are compared to find the best augmentation strategy. The evaluation of the algorithm uses two variations of the F1-score: one variation to estimate the capabilities of producing qualitative segmentation masks and another to estimate the detection capabilities. For the estimation of the detection capabilities, a rule termed ‘centre over ground truth’ is developed. The results show that the presented method is suitable for monitoring a cricket production facility with a recall of 76.6% and a precision of 96.2%.

Algorithm for control and forecasting of the functional stability of complex information-technical systems

The characteristics of the behavior of complex technical systems that realize the property of functional stability of these systems were studied. One of the possible statements of the problems of planning the operation of complex technical systems arising within the functional-parametric direction of risk theory is considered. It is shown that on the basis of the developed algorithms of the minimax assessment of the technical condition using the idea of ellipsoidal assessment, it is possible to implement a guaranteeing strategy for managing the risks of unauthorized influences. The proposed approach allows forecasting even with a small number of parameter measurements, does not require information about the stochastic properties of measurement errors and other obstacles, and has adaptive properties. The conditions for ensuring the functional stability of the technological process are given and practical recommendations for applying these conditions for decision-making in the practical implementation of production processes are described. Ensuring the functional stability of production processes is one of the most important tasks today. Currently, many different methods have been proposed to ensure a high level of functional stability, but this problem requires constant improvement and development of new approaches. In order to improve and develop methods of organizing production processes that ensure the functional stability of technological processes thanks to the implementation of an individual strategy for the operation of technical systems, an approach to the formation of an operation management strategy that ensures the functional stability of the relevant systems is proposed. An individual strategy for planning the operation of technical systems was studied, depending on their actual state, taking into account the features of this specific system. The proposed approach is advisable to use when planning the functionally stable operation of complex technical systems of responsible purpose, the failure of which is associated with significant material losses or catastrophic consequences.