Product Optimization Research Articles

Cost And Product Optimization of Upgrading Light Naphtha Using Pressure Swing Adsorption Method by Aspen Adsorption Simulation

Light naphtha is an organic compound produced from the distillation process that is often sold at a low price because of its poor performance, especially in the value of Research Octane Number (RON). The goal of this study was to improve the quality of naphtha to become a useful fuel with qualifying performance that is High Optimum Mogas Component (HOMC) by using the Pressure Swing Adsorption (PSA) method with the help of Aspen Adsorption simulations to find the most optimal combination of zeolite adsorbents (Beta and 5A) to use in the process. The principle of this quality improvement is to separate the compounds contained in naphtha that have low RON values from those that have high RON values so that the performance of naphtha that has gone through the adsorption process can be maximized. For this study, the RON target from HOMC is 95, while the value of RON for feed light naphtha ranges from 61-65. There are three compounds simulated in this PSA process, n-pentane and n-hexane as compounds that want to be separated because they have low RON values from iso-pentane which has a high RON value. Furthermore, after acquiring the combination of adsorbents that resulted in the products that have the highest RON, the economic potential of all variables was evaluated to get the most optimal process to use. The economic potential is also analyzed to find the profit of the PSA process. The most optimal results are obtained when the adsorbent configuration produces the product with the highest RON and produces high economic potential. The results showed that the most optimal adsorbent combination is to use 30% Zeolite Beta; 70% Zeolite 5A with product results having the highest RON of 84 and economic potential of US$ 114,410,163.92.

Insights into the Key Odorants in Large-Leaf Yellow Tea (Camellia sinensis) by Application of the Sensomics Approach

Large-leaf yellow tea (LYT) is a yellow tea product with a specific aroma characteristic and is enjoyed with increasing enthusiasm in China. However, its key odorants are still unknown. In this study, 46 odorants in the headspace and vacuum-distillate of the tea infusion were identified via aroma extract dilution analysis. Sixteen compounds were newly found in LYT infusion. They were present in the highest flavor dilution factors together with 2-ethyl-3,5-dimethylpyrazine. All odorants were quantitated to evaluate their own odor activity values (OAVs). High OAVs were found for 2-methylbutanal (malty, 210), (E,E)-2,4-heptandienal (fatty/flowery, 170), 2-methylpropanal (malty, 120) and 2,3-diethyl-5-methylpyrazine (earthy/roasty, 110). An aroma recombinate consisting of 17 odorants (all OAVs ≥ 1) in an odorless nonvolatile LYT matrix mimicked the overall aroma of the original infusion, verifying the successful characterization of key aroma components in a LYT beverage. The knowledge of key odorants obtained showed potential for simplifying industrial flavor optimization of the LYT product.

Research on product process design and optimisation model based on IoT intelligent computing

Abstract In this article, some complex parameters of the product and design processes, how to match and optimise the sub-parts of related industrial products and how to improve the quality of the corresponding products and the competitiveness of the product in the international market are discussed in this article. We also build an algorithm based on the particle swarm and XGBoost algorithms, combined with the intelligent computing of the Internet of Things (IoT). We transform some uncertain factors in the process of the industrial product design process through the fuzzy matrix, select the optimal design through the optimised intelligent computing of the IoT scheme and compare the influence of the scheme before and after optimisation on production efficiency. The results show that the method proposed in this article can reduce the time-consumption of optimal solution selection by 42.85%–52.94%. In addition, selecting the optimal solution for each field in a targeted manner can increase the overall production efficiency of the product by about 5%, reaching between 93.6% and 96.5%, which may save raw materials and create more economic value.

The role of excipients in promoting topical and transdermal delivery: Current limitations and future perspectives

Topical and transdermal delivery has historically offered an attractive and non-invasive route for administration of medicines. However, human skin is known to be a remarkably good barrier to the permeation of substances. The majority of dermatological drug products have been reported to only deliver a portion of the total dose applied, often resulting in low drug bio-availability at the site of action inside the skin. This insufficient formulation performance, coupled with the fact that percutaneous delivery is heavily influenced by the innate physicochemical properties of the active, pose limitations on effective treatment and prevention of diseases by using solely topical formulations. Generally, it is known that the rate and the extent of drug delivery to and through the skin is highly dependent on the formulation components. This work highlights the importance of the vehicle for the design of efficacious skin products, discusses current limitations in dermal delivery and explores recent advances for overcoming these challenges. Novel materials with penetration enhancing properties and innovative formulation strategies are also explored, together with future perspectives and outlooks. The emphasis here is on studies focused on passive skin transport because of clinical limitations associated with disrupting the skin barrier by physical methods. This information is believed to aid in the design and optimization of dermatological drug products for topical and transdermal delivery of actives.

Robust optimization and data-driven modeling of tissue paper packing considering cargo deformation

This paper considers the container loading problem (CLP) for efficient packing of low density tissue paper products, for which, volume, instead of weight, is the key driver for logistic decision-making. Tissue products are susceptible to deformation during the packing process. However, this aspect is usually overlooked when defining the optimal packing policy. In this work, we take this aspect into account and develop a novel methodology for CLP optimization of tissue paper products. The deformation is modeled as a function of known product characteristics and packing process variables using data-driven models. Several modeling approaches are compared, including those based on variable selection, regularization and projection to latent variables. The data-driven model is then included into a Mixed Integer Non Linear Programming (MINLP) CLP. A worst-case robust optimization approach is considered, resulting in solutions that are robust against data-driven model uncertainty. The methodology is applied to a real case study from a portuguese tissue paper mill concerning the packing of toilet paper rolls in wood shipping pallets. Predicted results show an average gain of 4 to 7% in load density in the worst-case scenario, compared to current practice. The deformation model is validated experimentally on the industrial site, by testing optimal configurations which show gains in load density up to 40%. The methodology can be easily extended to other tissue paper products as well as any low density product showing reversible deformation during packing.

Structural Optimization of the Natural Product: Discovery of Almazoles C–D and Their Derivatives as Novel Antiviral and Anti-phytopathogenic Fungus Agents

Plant diseases seriously affect the growth of crops and the quality and yield of agricultural products. The search for plant-derived pesticide candidates based on natural products is a hot topic of current research. Marine natural products almazoles C-D were efficiently prepared and selected as the lead compounds in this work. Two series of almazole derivatives were designed and synthesized, and their antiviral and fungicidal activities were systematically evaluated. The results of anti-tobacco mosaic virus (anti-TMV) activity showed that almazoles C-D and their derivatives had good anti-TMV activities. Compounds 6, 15, 16a, 16b, 16g, 16l, 16n, 20a, 20d, 20i, and 20n exhibited better anti-TMV activities than the commercial antiviral agent ribavirin. Anti-TMV mechanism studies showed that compound 16b could induce the polymerization of 20S CP (coat protein, CP), thereby affecting the assembly of TMV virus particles. Molecular docking results showed that compounds 15, 16b, and 20n could combine with amino acid residues through hydrogen bonds to achieve an excellent anti-TMV effect. In addition, most of the almazole derivatives were found to have broad-spectrum fungicidal activities against eight kinds of plant pathogens (Fusarium oxysporum f. sp. cucumeris, Cercospora arachidicola Hori, Physalospora piricola, Rhizoctonia cerealis, Alternaria solani, Pyricularia grisea, Phytophthora capsici, and Sclerotinia sclerotiorum). This study provides an important evidence for the research and development of almazole alkaloids containing indole and oxazole structural groups as novel agrochemicals.

An innovative tool for cost control under fragmented scenarios: The container freight index microinsurance

With the impact of the COVID-19 pandemic, global container freights have increased dramatically since the second half of 2020, which has significantly hampered the booking activities of fragmented transportation space for small and medium-sized import and export enterprises (SMIEEs). To provide SMIEEs with an effective tool for controlling shipping costs, we propose the design principles of index microinsurance under fragmented scenarios and design the container freight index microinsurance (CFIM) based on a comprehensive analysis of the term, compensation and share structures. We further establish the pricing model for the CFIM and selection procedure for product optimization, and illustrate the framework with a case study based on the data of the China Containerized Freight Index Europe Service, which demonstrates the good performance of the designed product even under extreme market conditions. The design principles proposed can shed light on the innovation of index microinsurance product that meets fragmented needs and the newly designed CFIM, along with the pricing and optimization procedure, provides practitioners with useful tools for cost control.

Response surface optimization of product yields and biofuel quality during fast hydrothermal liquefaction of a highly CO2-tolerant microalgae

The effects of biochemical components and processing variables (e.g., temperatures, solid-liquid ratio, ethanol concentration, and time) during fast hydrothermal liquefaction of a highly CO2-tolerant microalgae (Micractinium sp.) on the product yields and biofuel quality were explored using response surface methodology coupled with central composite design. Results showed that the maximum bio-oil yield (51.4 %) was obtained at 321 °C for 49 min at ethanol concentration of 75 % and solid-liquid ratio of 15.3 %. Among different studied parameters, ethanol concentration showed the highest significant impact on the bio-oil yield due to the low P-value and high F-value in ANOVA analysis. Furthermore, the chemical compositions of bio-oils were determined, which showed that the increase of ethanol concentration in the solvent not only increased the bio-oil yield but also promoted the bio-oil quality by reduction of carboxylic acids and nitrogen-containing compounds with simultaneous enhancement of esters in the bio-oil. The present results show that fast hydrothermal liquefaction is a promising approach to convert the microalgae into high quality biofuels rich in esters.

179P Early proof of concept of safety and clinical activity of clonal neoantigen-reactive T cells (cNeT)

cNeT therapy addresses limitations of TIL therapies including the requirement for high dose lymphodepletion and IL-2 which restricts application to fitter patients, and limited understanding of the active component that limits product optimisation and potency assay development. We have initiated trials evaluating cNeT in advanced, heavily pre-treated patients with NSCLC (CHIRON, NCT04032847) or melanoma (THETIS, NCT03997474) utilising lower dose lymphodepletion and IL-2 (1M IU/m2 sc x10d).

Boosting productivity with tech

Boosting productivity with tech

Research on Application of Artificial Intelligence Teaching Mode Based on Project-based Learning

AI learning emphasizes learning based on real projects. The projects that students need to do must be real, complete, meaningful, and can be completed in a short time. It helps students comprehensively apply various knowledge and skills in the process of exploration and practice, and improve the core quality of AI. This study made a preliminary exploration of the AI teaching mode based on project-based learning. Combined with teaching practice, it summarized the basic links of AI teaching based on project-based learning: based on the situation, ingenious project design, brainstorming, creativity generation, role assignment, each role, activity exploration, engineering design, iterative iteration, product optimization, achievement sharing, and ability improvement. Through these six main links to carry out teaching activities, the artificial intelligence teaching model based on project-based learning has achieved good teaching results.

Long term behavior of dexamethasone-loaded cochlear implants: In vitro & in vivo

The aim of this study was to better understand the long term behavior of silicone-based cochlear implants loaded with dexamethasone: in vitro as well as in vivo (gerbils). This type of local controlled drug delivery systems offers an interesting potential for the treatment of hearing loss. Because very long release periods are targeted (several years/decades), product optimization is highly challenging. Up to now, only little is known on the long term behavior of these systems, including their drug release patterns as well as potential swelling or shrinking upon exposure to aqueous media or living tissue. Different types of cylindrical, cochlear implants were prepared by injection molding, varying their dimensions (being suitable for use in humans or gerbils) and initial drug loading (0, 1 or 10%). Dexamethasone release was monitored in vitro upon exposure to artificial perilymph at 37 °C for >3 years. Optical microscopy, X-ray diffraction and Raman imaging were used to characterize the implants before and after exposure to the release medium in vitro, as well as after 2 years implantation in gerbils. Importantly, in all cases dexamethasone release was reliably controlled during the observation periods. Diffusional mass transport and limited drug solubility effects within the silicone matrices seem to play a major role. Initially, the dexamethasone is homogeneously distributed throughout the polymeric matrices in the form of tiny crystals. Upon exposure to aqueous media or living tissue, limited amounts of water penetrate into the implant, dissolve the drug, which subsequently diffuses out. Surface-near regions are depleted first, resulting in an increase in the apparent drug diffusivity with time. No evidence for noteworthy implant swelling or shrinkage was observed in vitro, nor in vivo. A simplified mathematical model can be used to facilitate drug product optimization, allowing the prediction of the resulting drug release rates during decades as a function of the implant's design.

Tensile performance and viscoelastic properties of rubber nanocomposites filled with silica nanoparticles: A molecular dynamics simulation study

Understanding the relationship between the macro-properties and microstructure of rubber and rubber nanocomposites (RNCs) is crucial for the design and optimization of relevant rubber composite products. Herein, we explore the mechanical and viscoelastic properties of rubber and RNCs filled with silica nanoparticles by using atomistic molecular dynamics simulation. It is found that increasing cross-linking density can greatly enhance the tensile performance of pure rubber, and reduce the permanent deformation and hysteresis loss. The addition of silica nanoparticles causes significant changes in the static distribution, movement, and bond orientation, and the Tg of RNCs increases by more than 6% when the volume fraction of NPs reaches 10%. At fixed volume fraction of NPs, decreasing the NP size can further enhance the mechanical properties of RNCs, and the maximum tensile stress can increase by 50%. In addition, cross-linking in the RNCs can improve the viscoelastic properties, and more highly crosslinked RNCs present larger storage modulus and loss modulus, and smaller loss angle. This work gives an in-depth understanding of the effect of microstructure on the mechanical properties of RNCs.

Incorporating a choice-based diffusion model into a bi-objective multi-generation product optimization problem under consignment stock policy

Rapid changes and evolution in technological innovation have spilled over many industries and compelled firms to release new products periodically. The advent of new products intensifies the importance of analyzing sales data trends and finding the most profitable portfolio that can no longer be ignored in production planning. The topic of diffusion processes has evoked considerable interest from academics and practitioners to forecast sales patterns of two or three competitive generations. However, there is still a lack of in-depth discussion on the effects of core determinants on customers' preferences and choices. This paper bridges the gaps in the literature by conceptualizing the interaction effects among current and new products on diffusion processes that could affect supply chain operations. Specifically, the Bass diffusion model (BDM) is modified to estimate market volume, advertisement effects, and sales data trends, then combined with a choice model to examine how consumers' propensities affect the choice probability of alternatives. The proposed choice-based diffusion model is incorporated into a supply chain problem for joint planning on a production-location-inventory problem concerning the economic and social aspects of designing multi-generation production lines. The model formulation is a bi-objective mixed-integer nonlinear problem with a computation burden. Thus an outer approximation-based algorithm is proposed to reduce computational complexity and combined with an augmented ε-constraint to generate efficient Pareto sets. The model is validated by conducting a case study in Iran and compared to other established models. The computational results demonstrate the proposed model outperforms the expert forecasts, and there are no significant differences between the total sales estimated by the proposed model and the actual sales. The manager is advised to adopt a conscious policy for adoption engagement under supply constraints. It should price the products in a way be more tightly aligned with customers’ desirability and overcome the supply constraints by increasing production or storage capacities.

Comparative study on the synergistic reinforcement of lignin between carbon black/lignin and silica/lignin hybrid filled natural rubber composites

When the content of carbon black (CB)/silica is constant, the combination of lignin and CB/silica offers obvious advantages over previously reported partial replacement of carbon black/silica by lignin. Considering the distinction between CB/lignin and silica/lignin interactions, the effects of lignin concentration on the vulcanization behavior, crosslink density, filler dispersion, and physical and mechanical properties of the NR composites were investigated. The results showed that the incorporated lignin extended the scorch time (ts1) and optimum vulcanization time (tc90) of the sulfur-cured NR/CB/lignin compounds. The addition of lignin was beneficial for reducing the networking of CB. Although the moduli at 100% and 300% elongation decreased, the NR/CB/lignin composites still exhibited good tensile strength and elongation at break, especially with the addition of lignin at less than 30 phr. For the silica-filled NR composites, the extent of vulcanization of the NR/silica/lignin compounds slightly increased, and the vulcanization rate showed little change. The introduction of lignin plays a significant role in the reinforcement effect of silica-filled NR composites. The strengthened interaction between silica/lignin and NR and the improved filler dispersion significantly contributed to improved reinforcement. However, severe filler networking was observed when the lignin concentration was too high (up to 50 phr), resulting in decreased tensile strength. It is worth mentioning that due to significant reinforcement and the little changes in the hardness of the silica-filled NR vulcanizates by the addition of lignin, the combination of lignin and silica becomes more practical and potential for the formulation optimization of industrial rubber products.

On the variant pairing in transformation product of high strength low alloy steel depending on cooling rate

• Transformation product depending on cooling rate was understood from the perspective of crystallography. • Ideal variant pairing occurred at nose temperature of bainite transformation curve induced more HAGBs. • Large driving force and local carbon enrichment contributed to an ideal variant pairing in transformation product. Crystallographic features of transformation product were investigated in a high strength low alloy steel as a function of the cooling rate. The results showed that phase transformation occurring at the nose temperature of bainite transformation curve was most likely to obtain the highest density of high angle grain boundaries and fraction of V1/V2 variant pair. This was attributed to the ideal variant pairing in the transformation product triggered by the relatively large driving force and local carbon enrichment in the latter-transformed austenite. These findings would be instructive for the optimization of transformation product in low alloy steels via controlling the cooling rate.

Discussion of digital transition impact in Facility Management of buildings

As buildings have various subsystems and numerous components, managing them is challenging. The management of buildings should be efficient during their life cycle, with a sustainable way of considering the new challenges of the Europe Union (EU): resilience and digital transition. Facility management (FM) contributes to achieving these goals, involving multidisciplinary activities and relying on different technologies. The recent concern about an effective digital transition in FM offers an excellent opportunity to improve facility information management in existing buildings through robust data analysis, machine learning, and simulation tools, such as interoperable building information modelling (BIM) platforms. Within this scenario, gathering and structuring in-service information for FM is crucial to boost digital transition in buildings management. This paper discusses the approaches with potential and higher impact in FM and the related steps that should be considered regarding product data template, data collection, and optimisation models.

Optimization of co-production air separation unit based on MILP under multi-product deterministic demand

• The proxy model describes the production space of ASUs.; • Propose multi-product optimization scheduling under deterministic demand for co-production ASU; • Minimize oxygen emission based on avoiding frequent starting and stopping of ASU; • Verify the feasibility of the model by comparing a single product optimization. Optimizing gas distribution is one of the most important energy management issues in process industries such as metallurgy and the chemical industry. The air separation unit (ASU) is characterized by the simultaneous production of multiple products (oxygen, nitrogen, liquid oxygen, liquid nitrogen and liquid argon) and the mutual restriction of each product. The existing single-product scheduling models are not applicable to the actual process and the multi-product scheduling models are only for production processes and usually do not consider constraints such as ASU start/stop. Therefore, for the production as well as the transmission and storage processes of the co-production air separation system, the paper developed a MILP model, which uses a proxy model to express the production space of ASUs. This model minimizes oxygen emission based on avoiding frequent startup and shutdown of ASU, which uses the start-stop and load regulation of ASU, the start-stop of liquefier, and vaporizer as means, and considers device operating constraints. We verified the feasibility of the method by combining actual cases application and analyzing the result of the influence of single product optimization results on the balance of other products.

CHARACTERIZATION AND IDENTIFICATION OF Xanthomonas spp. ISOLATED FROM INFECTED Brassicaceae AND SELECTION OF POTENTIAL XANTHAN GUM PRODUCER

Xanthomonas spp. synthesize a complex exopolysaccharide called xanthan gum, which has significant commercial value. Xanthomonas-infected vegetables exhibiting typical spot symptoms were used in this study. Isolation was done by streaking the sample suspension on the Yeast Malt agar. A colony that resembled Xanthomonas spp. was purified before a simple phenotypic test and identified using BIOLOG and 16 rRNA sequencing. The screening was done based on their performance by fermentation in a shake flask, under controlled conditions. The yield and viscosity of xanthan gum produced from each bacterium were compared to Xanthomonas campestris PV. campestris strain ATCC33913. There were 411 wild types of Xanthomonas spp. successfully isolated and ten strains were selected for xanthan gum evaluation. The results showed, the xanthan production (g/L) varied from (1.57 - 8.24) with the yield of xanthan from 0.64 to 4.71 g/g biomass. Strain C206 produced the highest xanthan gum concentration (8.24±0.20 g/L) compared to others and the control strain, ATCC 33913 (2.27±0.10g/L). The highest yield of xanthan 4.71±0.18 (g/g biomass) was produced by strain C298 followed by strain C279 with 3.88±0.04 (g/g biomass). From our investigation, the production and yield of xanthan gum and the viscosity of the polymers were significantly dependent on the bacterial strain. Based on the stable viscosity and yield of xanthan produced, X. campestris C279 was selected for further studies on product optimization.

Study on Marketing Strategy Optimization of Fresh Agricultural Products under Community Group Purchase Mode

Study on Marketing Strategy Optimization of Fresh Agricultural Products under Community Group Purchase Mode