Dynamic prediction models and optimization of polyacrylonitrile (PAN) stabilization processes for production of carbon fiber

Thermal stabilization process of polyacrylonitrile (PAN) is the slowest and the most energy-consuming step in carbon fiber production. As such, in industrial production of carbonfiber, this step is considered as amajor bottleneck in the whole process. Stabilization process parameters are usually many in number and highly constrained, leading to high uncertainty. The goal of this paper is to study and analyze the carbon fiber thermal stabilization process through presenting several effective dynamic models for the prediction of the process. The key point with using dynamic models is that using an evolutionary search technique, the heat of reaction can be optimized. The employed components of the study are Levenberg–Marquardt algorithm (LMA)-neural network (LMA-NN), Gauss–Newton (GN)-curve fitting, Taylor polynomial method, and a genetic algorithm. The results show that the procedure can effectively optimize a given PAN fiber heat of reaction based on determining the proper values of heating rampand temperature

Design of experiments and springback prediction for AHSS automotive components with complex geometry

With the drive towards implementing Advanced High Strength Steels (AHSS) in the automotive industry; stamping engineers need to quickly answer questions about forming these strong materials into elaborate shapes.
Commercially available codes have been successfully used to accurately predict formability, thickness and strains in complex parts. However, springback and twisting are still challenging subjects in numerical simulations of AHSS components. Design of Experiments (DOE) has been used in this paper to study the sensitivity of the implicit and explicit numerical results with respect to certain arrays ofuser input parameters in the forming ofan AHSS component. Numerical results were compared to experimental measurements of the parts stamped in an industrial production line. The forming predictions of the implicit and explicit codes were in good agreement with the experimental measurements for the conventional steel grade, while lower accuracies were observed for the springback predictions. The forming
predictions of the complex component with an AHSS material were also in good correlation with the respective experimental measurements. However, much lower accuracies were observed in its springback predictions. The number of integration points through the thickness and tool offset were found to be of significant importance, while coefficient of friction and Young's modulus (modeling input parameters) have no significant effect on the accuracy of the predictions for the complex geometry.

Carbon nanotubes formed in graphite after mechanical grinding and thermal annealing

Multi-walled carbon nanotubes with cylindrical and bamboo-type structures are produced in a graphite sample after mechanical milling at ambient temperature and subsequent thermal annealing up to 1400 °C. The ball milling produces a precursor structure and the thermal annealing activates the nanotube growth. Different nanotubular structures indicate different formation mechanisms: multi-wall cylindrical carbon nanotubes are probably formed upon micropores and the bamboo tubes are produced because of the metal catalysts. A two-dimensional growth governed by surface diffusion is believed to be one important factor for the nanotube growth. A potential industrial production method is demonstrated with advantages of large production quantity and low cost.

Statistical analysis of finite element modeling in sheet metal forming and springback analysis

This work focuses on development of a method to statistically study forming and springback problems of TRansformation Induced Plasticity (TRIP) through an industrial case study. A Design of Experiments (DOE) approach was used to study the sensitivity of predictions to four user input parameters in implicit and explicit sheet metal forming codes. Numerical results were compared to experimental measurements of parts stamped in an industrial production line. The accuracy of forming strain predictions for TRIP steel were comparable with conventional steel, but the springback predictions of TRIP steel were far less accurate. The statistical importance of selected parameters for forming and springback prediction is also discussed. Changes of up to ±10% in Young's modulus and coefficient of friction were found to be insignificant in improving or deteriorating the statistical correlation of springback accuracies.

Determinants of intra-ASEAN exports and imports

Analyses the factors which explain the behaviour of intro-ASEAN exports and imports including the real exchange rate, real income, the industrial production capacity, and other factors; namely foreign direct investment and industrialisation policies, regionalism and emerging new markets.

Low-frequency volatility of yen interest rate swap market in relation to macroeconomic risk

Using ‘low-frequency’ volatility extracted from aggregate volatility shocks in interest rate swap (hereafter, IRS) market, this paper investigates whether Japanese yen IRS volatility can be explained by macroeconomic risks. The analysis suggests that this low-frequency yen IRS volatility has strong and positive association with most of the macroeconomic risk proxies (e.g., volatility of consumer price index, industrial production volatility, foreign exchange volatility, slope of the term structure and money supply) with the exception of the unemployment rate, which is negatively related to IRS volatility. This finding is fairly consistent with the argument that the greater the macroeconomic risk the greater is the use of derivative instruments to hedge or speculate. The relationship between the macroeconomic risks and IRS volatility varies slightly across the different swap maturities but is robust to alternative volatility specifications. This linkage between swap market and macroeconomy has practical implications since market makers and hedgers use the swap rate as benchmark for pricing long-term interest rates, corporate bonds and various other securities.

Facile fabrication of polyolefin/carbon nanotube composites via in situ friedel-crafts polyalkylation : structure and properties

Despite major advances in addressing the dispersion of carbon nanotubes (CNTs) in polymers and their interfacial interactions, exploring a facile approach for massively creating them is still fascinating. We interestingly find that the CNT dispersion is considerably improved in polypropylene (PP), and ?19.1 wt % of PP chains were in situ chemically grafted onto CNT surfaces only using a trace of AlCl3 via a one-step melt-blending. Compared with the PP/CNT composite, adding 0.2 wt % of AlCl3 enables an increase in tensile strength and Young's modulus of 30% and 25%, respectively. Moreover, the elongation at break is almost maintained, while adding CNTs alone causes significant decreases. Additionally, 0.2 wt % AlCl3 makes the thermal degradation temperature further improved. These remarkable improvements in properties are mainly attributed to better dispersion of CNTs and enhanced interfacial compatibility. This work opens up an innovative approach for scalable preparation of polyolefin/CNT composites applying to industrial production.

In situ prepared V2O5/graphene hybrid as a superior cathode material for lithium-ion batteries

Developing synthetic methods for graphene based cathode materials, with low cost and in an environmentally friendly way, is necessary for industrial production. Although the precursor of graphene is abundant on the earth, the most common precursor of graphene is graphene oxide (GO), and it needs many steps and reagents for transformation to graphite. The traditional approach for the synthesis of GO needs many chemicals, thus leading to a high cost for production and potentially great amounts of damage to the environment. In this study, we develop a simple wet ball-milling method to construct a V2O5/graphene hybrid structure in which nanometre-sized V2O5 particles/aggregates are well embedded and uniformly dispersed into the crumpled and flexible graphene sheets generated by in situ conversion of bulk graphite. The combination of V2O5 nanoparticles/aggregates and in situ graphene leads the hybrid to exhibit a markedly enhanced discharge capacity, excellent rate capability, and good cycling stability. This study suggests that nanostructured metal oxide electrodes integrated with graphene can address the poor cycling issues of electrode materials that suffer from low electronic and ionic conductivities. This simple wet ball-milling method can potentially be used to prepare various graphene based hybrid electrodes for large scale energy storage applications.

Industrial biotechnology for the production of proteins/enzymes for a sustainable future

Worldwide emergence of Industrial biotechnology (IB) is providing opportunities to produce enzymes/proteins with variety of industrial/therapeutic applications. In transitioning the Australian economy towards a sustainable future, Federal government identified the development of IB pathway which would ensure increased productivity, enhanced sustainability, health, safety and reduced environmental footprint. The presentation will revolve around specific stories that drives Deakin University newest technology platform which applies biology and fermentation in an integrated way to play a crucial role in developing cost-effective technologies for the development of molecules that can benefit pharmaceutical and food industry in regional Victoria and Australia in general. The talk will also highlight specific examples where new products like recombinant rhamnosidase (an enzyme used for the production of flavonoids with health benefits) and ribosome inactivating proteins (detected in medicinal plants which possess RNA N- glycosidase activity that depurinates the major rRNA, thus damaging ribosome in an irreversible manner and arresting protein synthesis) would be made available through bioprocessing.

Reduction of fuel consumption in an industrial glass melting furnace

Reduction of fuel consumption in glass melting furnaces can cut the cost of production, and tackle the global warming. This paper presents three independent solutions to reduce the fuel consumption in industrial glass melting furnaces. The solutions include air preheating, raw material preheating, and improving the insulation of combustion space refractory. Energy balance equations are derived and used to identify the effects of each solution. The results indicate that the three solutions reduce the fuel consumption by 9.5%, 17%, and 34%, respectively.

Modeling and simulation for large scale production systems

Computer modeling and simulation provide a foundation upon which industrial processes and systems can be transformed and innovation dramatically accelerated. Computer modeling and simulation is also an indispensable tool of the information age, used extensively in design, analysis, operations, decision-making, optimization, and education and training. Manufacturing, production and design relies upon simulation to develop efficient production systems and factories that produce quality products. Simulation in industry has yet to meet its full potential. The development of models is very time consuming, particularly for geometries of complex engineering systems such as manufacturing plants, automobiles, aircraft and ships. Computer simulation allows scientists and engineers to understand and predict three-dimensional and time-dependent phenomena in science and engineering discipline. This talk will focus on challenges associated with modeling and simulation in the manufacturing sector and through a number of case studies highlight the benefits gained through the use of such technologies.

Production of high fructose syrup from asparagus inulin using immobilized exoinulinase from Kluyveromyces marxianus YS-1

Extracellular exoinulinase from Kluyveromyces marxianus YS-1, which hydrolyzes inulin into fructose, was immobilized on Duolite A568 after partial puriWcation by ethanol precipitation and gel exclusion chromatography on Sephadex G-100. Optimum temperature of immobilized enzyme was 55 °C, which was 5 °C higher than the free enzyme and optimal pH was 5.5. Immobilized biocatalyst retained more than 90% of its original activity after incubation at 60 °C for 3 h, whereas in free form its activity was reduced to 10% under same conditions, showing a signiWcant improvement in the thermal stability of the biocatalyst after immobilization. Apparent Km values for inulin, raYnose and sucrose were found to be 3.75, 28.5 and 30.7 mM, respectively. Activation energy (Ea) of the immobilized biocatalyst was found to be 46.8 kJ/mol. Metal ions like Co2+ and Mn2+ enhanced the activity, whereas Hg2+ and Ag2+ were found to be potent inhibitors even at lower concentrations of 1 mM. Immobilized biocatalyst was eVectively used in batch preparation of high fructose syrup from Asparagus racemosus raw inulin and pure inulin, which
yielded 39.2 and 40.2 g/L of fructose in 4 h; it was 85.5 and 92.6% of total reducing sugars produced, respectively.

An industrial organisation economic supply chain approach for the construction industry : a review

Understanding industries in terms of the concepts of chains, clusters and networks is becoming increasingly important in economies around the world. Supply chain management for an individual organization is an
emerging field of research in the construction management discipline, but less attention has been devoted to investigating the nature of the construction supply chains and their industrial organizational economic environment. This selected review of construction and mainstream management supply chain literature is organized around four themes; distribution, production, strategic procurement management and industrial
organization economics, and highlights the need to develop an industrial organization economic supply chain framework for construction. The merging of the supply chain concept with the industrial organization model
as a methodology for understanding firm conduct and industry structure and performance is an important contribution to both construction supply chain and construction economic theory. Much of the industrial organization supply chain literature has tended to focus upon manufacturing industries, where typically firms are permanent organizations. This raises issues as to the differences between industries founded upon temporary compared with permanent organizations. There is potential for the development of an industrial organization methodology applicable to the project based industry. Ultimately industrial organization research seeks to have direct implications for industry performance and government policies.

Extending robust industrial optimisation using simulation and reinforcement learning

Traditional optimisation methods are incapable of capturing the complexity of today's dynamic manufacturing systems. A new methodology, integrating simulation models and intelligent learning agents, was successfully applied to identify solutions to a fundamental scheduling problem. The robustness of this approach was then demonstrated through a series of real-world industrial applications.