Search results for: biomethane production

Authors: Iris Vural Gursel, Jonathan Moncada, Ernst Worrell, Andrea Ramirez

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In order to achieve the transition from a fossil to bio-based economy, biomass needs to replace fossil resources in meeting the world’s energy and chemical needs. This calls for development of biorefinery systems allowing cost-efficient conversion of biomass to chemicals. In biorefinery systems, feedstock is converted to key intermediates called platforms which are converted to wide range of marketable products. The C6 sugars platform stands out due to its unique versatility as precursor for multiple valuable products. Among the different potential routes from C6 sugars to bio-based chemicals, 1,3-butadiene and ε-caprolactam appear to be of great interest. Butadiene is an important chemical for the production of synthetic rubbers, while caprolactam is used in production of nylon-6. In this study, ex-ante techno-economic performance of 1,3-butadiene and ε-caprolactam routes from C6 sugars were assessed. The aim is to provide insight from an early stage of development into the potential of these new technologies, and the bottlenecks and key cost-drivers. Two cases for each product line were analyzed to take into consideration the effect of possible changes on the overall performance of both butadiene and caprolactam production. Conceptual process design for the processes was developed using Aspen Plus based on currently available data from laboratory experiments. Then, operating and capital costs were estimated and an economic assessment was carried out using Net Present Value (NPV) as indicator. Finally, sensitivity analyses on processing capacity and prices was done to take into account possible variations. Results indicate that both processes perform similarly from an energy intensity point of view ranging between 34-50 MJ per kg of main product. However, in terms of processing yield (kg of product per kg of C6 sugar), caprolactam shows higher yield by a factor 1.6-3.6 compared to butadiene. For butadiene production, with the economic parameters used in this study, for both cases studied, a negative NPV (-642 and -647 M€) was attained indicating economic infeasibility. For the caprolactam production, one of the cases also showed economic infeasibility (-229 M€), but the case with the higher caprolactam yield resulted in a positive NPV (67 M€). Sensitivity analysis indicated that the economic performance of caprolactam production can be improved with the increase in capacity (higher C6 sugars intake) reflecting benefits of the economies of scale. Furthermore, humins valorization for heat and power production was considered and found to have a positive effect. Butadiene production was found sensitive to the price of feedstock C6 sugars and product butadiene. However, even at 100% variation of the two parameters, butadiene production remained economically infeasible. Overall, the caprolactam production line shows higher economic potential in comparison to that of butadiene. The results are useful in guiding experimental research and providing direction for further development of bio-based chemicals.

Keywords: bio-based chemicals, biorefinery, C6 sugars, economic analysis, process modelling

Procedia PDF Downloads 152

Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an artificial neural network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study includes granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R²), Root mean square error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: national development, granite, profitability assessment, ANN models

Procedia PDF Downloads 101

Authors: M. Kouhirostamkolaei, M. Kouhirostami, M. Sam, J. Woo, A. T. Asutosh, J. Li, C. Kibert

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Construction is one of the most energy consumed activities in the urban environment that results in a significant amount of greenhouse gas emissions around the world. Thus, the impact of the construction industry on global warming is undeniable. Thus, reducing building energy consumption and mitigating carbon production can slow the rate of global warming. The purpose of this study is to determine the amount of energy consumption and carbon dioxide production during the operation phase and the impact of using new shells on energy saving and carbon footprint. Therefore, a residential building with a re-enforced concrete structure is selected in Babolsar, Iran. DesignBuilder software has been used for one year of building operation to calculate the amount of carbon dioxide production and energy consumption in the operation phase of the building. The primary results show the building use 61750 kWh of energy each year. Computer simulation analyzes the effect of changing building shells -using XPS polystyrene and new electrochromic windows- as well as changing the type of lighting on energy consumption reduction and subsequent carbon dioxide production. The results show that the amount of energy and carbon production during building operation has been reduced by approximately 70% by applying the proposed changes. The changes reduce CO₂e to 11345 kg CO₂/yr. The result of this study helps designers and engineers to consider material selection’s process as one of the most important stages of design for improving energy performance of buildings.

Keywords: construction materials, green construction, energy simulation, carbon footprint, energy saving, concrete structure, designbuilder

Procedia PDF Downloads 198

Authors: Lozano Paul

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Coupled Membrane Separation Technology (CMST), including Cross Flow Microfiltration (CFM) and Reverse Osmosis (RO), are used to concentrate microalgae biomass or/and to extract and concentrate water-soluble metabolites produced during micro-algae production cycle, as well as water recycling. Micro-algae biomass was produced using different feeding mixtures of ingredients: pure chemical origin compounds and natural/ecological water-extracted components from available local plants. Micro-algae was grown either in conventional plastic bags (100L/unit) or in small-scale innovative bioreactors (75L). Biomass was concentrated as CFM retentate using a P19-60 ceramic membrane (0.2μm pore size), and water-soluble micro-algae metabolites left in the CFM filtrate were concentrated by RO. Large volumes of water (micro-algae culture media) of were recycled by the CMTS for another biomass production cycle.

Keywords: extraction, membrane process, microalgae, natural compound

Procedia PDF Downloads 279

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Srinivas Vangari

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With the technological advancements around the globe, artificial intelligence (AI) has boosted supply chain management (SCM) by improving efficiency, sensitivity, and promptness. Artificial intelligence-based SCM provides comprehensive perceptions of consumer behavior in dynamic market situations and trends, foreseeing the accurate demand. It reduces overproduction and stockouts while optimizing production planning and streamlining operations. Consequently, the AI-driven SCM produces a customer-centric supply with resilient and robust operations. Intending to delve into the transformative significance of AI in SCM, this study focuses on improving efficiency in SCM with the integration of AI, understanding the production demand, accurate forecasting, and particular production planning. The study employs a mixed-method approach and expert survey insights to explore the challenges and benefits of AI applications in SCM. Further, a case analysis is incorporated to identify the best practices and potential challenges with the critical success features in AI-driven SCM. Key findings of the study indicate the significant advantages of the AI-integrated SCM, including optimized inventory management, improved transportation and logistics management, cost optimization, and advanced decision-making, positioning AI as a pivotal force in the future of supply chain management.

Keywords: artificial intelligence, supply chain management, accurate forecast, accurate planning of production, understanding demand

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Authors: Chieh Lee

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Today, supply chain managers face extensive disruptions in raw material pricing, transportation block, and quality issue due to product complexity. While digitalization might help managers to mitigate the disruption risk and increase supply chain resilience by sharing information between sellers and buyers through the supply chain, entities are reluctant to build such a system. The main reason is it is not clear what information should be shared and who has access to the stored information. In this research, we propose a smart contract built by blockchain technology. This contract helps both buyer and seller to identify the type of information, the access to the information, and how to trace the information. This contract helps managers control their orders through the supply chain and address any disruption they see fit. Furthermore, with the same smart contract, the supplier can track the production process of an order and increase production efficiency by eliminating waste.

Keywords: blockchain, production process, smart contract, supply chain resilience

Procedia PDF Downloads 79

Authors: M. Nafis Alfarizi, Dinda A. Utami, Arif Hidayat

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Biodiesel is one solution to overcome the use of petroleum fuels. Many alternative feedstocks that can be used among which canola oil. The purpose of this study was to determine the ability of canola oil and KOH for the trans-esterification reaction in biodiesel production. Canola oil has a very high purity that can be used as an alternative feedstock for biodiesel production and expected it will be produced biodiesel with excellent quality. In this case of study, we used trans-esterification process wherein the triglyceride is reacted with an alcohol with KOH as a catalyst, and it will produce biodiesel and glycerol as byproduct and we choose trans-esterification process because canola oil has a 0,445% FFA content. The variables studied in this research include the comparison of canola oil and methanol, temperature, time, and the percent of catalyst used. In this study the method of analysis we use GCMS and FTIR to know what the characteristic in canola oil. Development of canola oil seems to be the perfect solution to produce high-quality biodiesel. The reaction conditions resulted in 97.87% -w methyl ester (biodiesel) product by using a 0.5% wt KOH catalyst with canola and methanol ratio 1:8 at 60°C.

Keywords: biodiesel, canola oil, KOH, trans-esterification

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Authors: Khalid M. Albarkoly, Kenneth S. Park

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The substantial development of the construction industry has forced the cement industry, its major support, to focus on achieving maximum productivity to meet the growing demand for this material. Statistics indicate that the demand for cement rose from 1.6 billion metric tons (bmt) in 2000 to 4bmt in 2013. This means that the reliability of a production system needs to be at the highest level that can be achieved by good maintenance. This paper studies the extent to which the implementation of RCM is needed as a strategy for increasing the reliability of the production systems component can be increased, thus ensuring continuous productivity. In a case study of four Libyan cement factories, 80 employees were surveyed and 12 top and middle managers interviewed. It is evident that these factories usually breakdown more often than once per month which has led to a decline in productivity, they cannot produce more than 50% of their designed capacity. This has resulted from the poor reliability of their production systems as a result of poor or insufficient maintenance. It has been found that most of the factories’ employees misunderstand maintenance and its importance. The main cause of this problem is the lack of qualified and trained staff, but in addition, it has been found that most employees are not found to be motivated as a result of a lack of management support and interest. In response to these findings, it has been suggested that the RCM strategy should be implemented in the four factories. The paper shows the importance of considering the development of maintenance strategies through the implementation of RCM in these factories. The purpose of it would be to overcome the problems that could reduce the level of reliability of the production systems. This study could be a useful source of information for academic researchers and the industrial organisations which are still experiencing problems in maintenance practices.

Keywords: Libyan cement industry, reliability centred maintenance, maintenance, production, reliability

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Authors: V. Ložar, N. Hadžić, T. Opetuk, R. Keser

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The development of digital twins strongly depends on efficient algorithms and their capability to mirror real-life processes. Nowadays, such efforts are required to establish factories of the future faced with new demands of custom-made production. The ship hull processes face these challenges too. Therefore, it is important to implement design and evaluation approaches based on production system engineering. In this study, the recently developed finite state method is employed to describe the stell hull process as a platform for the implementation of digital twinning technology. The application is justified by comparing the finite state method with the analytical approach. This method is employed to rebuild a model of a real shipyard ship hull process using a combination of serial and splitting lines. The key performance indicators such as the production rate, work in process, probability of starvation, and blockade are calculated and compared to the corresponding results obtained through a simulation approach using the software tool Enterprise dynamics. This study confirms that the finite state method is a suitable tool for digital twinning applications. The conclusion highlights the advantages and disadvantages of methods employed in this context.

Keywords: digital twin, finite state method, production system engineering, shipyard

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Authors: Tulsi Ram Bhusal

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Global climate change is known to have a huge impact on agriculture due to changing in rainfall pattern and elevated air temperature that lead to drought and/or flooding. This systematic study has focused on agriculture in Nepal. The study has shown that the trend of current climatic change is affecting rice production, while the farmers with technological access have tried to adapt to the changing conditions at their level. There is insufficient intervention from the government side in terms of policies and schemes. The lack of sufficient funds is one of the significant reasons in terms of governance. The climatic trends and the way it is affecting the annual riceyieldinNepal has been discussed in this study thoroughly. This study has reviewed published studies and ferred important points regarding the Nepal’s status on rice production. Mainly due to the increasing graph of average temperature and other physical conditions needed for the proper cultivation of ricearechanging due to which there is significant dropofannual rice production. Although from corners of the country, many farmers have attempted to adapt the methods of cultivation to the changing climatic conditions, lack of access to technologies, and fund allocation from the governmental level, it is difficult for the mtobringchanges in rice production by the crown without any institutional help. This systematic study effectively presents the magnitude of the impact on rice cultivation due to climatic changes inrecenttimesinNepal. This review aims to bring the current scenarioofNepal’sricefarming, and it impacts due to changing climate, which can subsequently contribute in devising plans for proper governance, formulating policies, and allocation of funds for the betterment.

Keywords: rice, climate change, rice production, nepal, agriculture

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Authors: Julius Denafas, Irina Kliopova, Gintaras Denafas

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Three opportunities for implementation of industrial ecology principles in the real industrial production of c-Si solar cells and modules are presented in this study. It includes: material flow dematerialisation, product modification and industrial symbiosis. Firstly, it is shown how the collaboration between R&D institutes and industry helps to achieve significant reduction of material consumption by a) refuse from phosphor silicate glass cleaning process and b) shortening of silicon nitride coating production step. Secondly, it was shown how the modification of solar module design can reduce the CO2 footprint for this product and enhance waste prevention. It was achieved by implementing a frameless glass/glass solar module design instead of glass/backsheet with aluminium frame. Such a design change is possible without purchasing new equipment and without loss of main product properties like efficiency, rigidity and longevity. Thirdly, industrial symbiosis in the solar cell production is possible in such case when manufacturing waste (silicon wafer and solar cell breakage) also used solar modules are collected, sorted and supplied as raw-materials to other companies involved in the production chain of c-Si solar cells. The obtained results showed that solar cells produced from recycled silicon can have a comparable electrical parameters like produced from standard, commercial silicon wafers. The above mentioned work was performed at solar cell producer Soli Tek R&D in the frame of H2020 projects CABRISS and Eco-Solar.

Keywords: manufacturing, process optimisation, recycling, solar cells, solar modules, waste prevention

Procedia PDF Downloads 142

Authors: Guadalupe Stefanny Aguilar-Moreno, Miguel Angel Aguilar-Mendez, Teodoro Espinosa-Solares

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In the agricultural sector, one of the main emitters of greenhouse gases is manure management, which has been increased considerably in recent years. Biogas is an energy source that can be produced from different organic materials through anaerobic digestion (AD); however, production efficiency is still low. Several techniques have been studied to increase its performance, such as co-digestion, the variation of digestion conditions, and nanomaterials used. Therefore, the aim of this investigation was to evaluate the effect of magnetite nanoparticles (NPs) concentration, synthesized by co-precipitation, on the biogas and methane production in AD using chicken litter as a substrate. Synthesis of NPs was performed according to the co-precipitation method, for which a fractional factorial experimental design 25⁻² with two replications was used. The study factors were concentrations (precursors and passivating), time of sonication and dissolution temperatures, and the response variables were size, hydrodynamic diameter (HD) and zeta potential. Subsequently, the treatment that presented the smallest NPs was chosen for their use on AD. The AD was established in serological bottles with a working volume of 250 mL, incubated at 36 ± 1 °C for 80 days. The treatments consisted of the addition of different concentrations of NPs in the microcosms: chicken litter only (control), 20 mg∙L⁻¹ of NPs + chicken litter, 40 mg∙L⁻¹ of NPs + chicken litter and 60 mg∙L⁻¹ of NPs + chicken litter, all by triplicate. Methane and biogas production were evaluated daily. The smallest HD (49.5 nm) and the most stable NPs (21.22 mV) were obtained with the highest passivating concentration and the lower precursors dissolution temperature, which were the only factors that had a significant effect on the HD. In the transmission electron microscopy performed to these NPs, an average size of 4.2 ± 0.73 nm was observed. The highest biogas and methane production was obtained with the treatment that had 20 mg∙L⁻¹ of NPs, being 29.5 and 73.9%, respectively, higher than the control, while the treatment with the highest concentration of NPs was not statistically different from the control. From the above, it can be concluded that the magnetite NPs promote the biogas and methane production in AD; however, high concentrations may cause inhibitory effects among methanogenic microorganisms.

Keywords: agricultural sector, anaerobic digestion, nanotechnology, waste management

Procedia PDF Downloads 137

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Premrudee Promdet, Fan Cui, Gi Byoung Hwang, Ka Chuen To, Sanjayan Sathasivam, Claire J. Carmalt, Ivan P. Parkin

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A novel single-step fabrication of Cu nanoparticle embedded ZnO (Cu.ZnO) thin films was developed by aerosol-assisted chemical vapor deposition for stable and efficient hydrogen production in Photoelectrochemical (PEC) cell. In this approach, the Cu.ZnO nanoplate thin films were grown by using acetic acid to promote preferential growth and enhance surface active sites, where Cu nanoparticles can be formed under chemical deposition by reduction of Cu salt. Studies using photoluminescence spectroscopy indicate the enhanced photocatalytic performance is attributed to hot electron generated from SPR. The Cu metal in the composite material is functioning as a sensitizer to supply electrons to the semiconductor resulting in enhanced electron density for redox reaction. This work not only describes a way to obtain photoanodes with high photocatalytic activity but also suggests a low-cost route towards production of photocatalysts for hydrogen production. This work also supports a vital need to understand electron transfer between photoexcited semiconductor materials and metals, a requirement for tailoring the properties of semiconductor/metal composites.

Keywords: photocatalysis, photoelectrochemical cell (PEC), aerosol-assisted chemical vapor deposition (AACVD), surface plasmon resonance (SPR)

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Authors: Jonni Guiller Madeira, Angel Sanchez Delgado, Ronney Mancebo Boloy

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The use bioenergy, in recent years, has become a good alternative to reduce the emission of polluting gases. Several Brazilian and foreign companies are doing studies related to waste management as an essential tool in the search for energy efficiency, taking into consideration, also, the ecological aspect. Brazil is one of the largest cassava producers in the world; the cassava sub-products are the food base of millions of Brazilians. The repertoire of results about the ecological impact of the production, by steam reforming, of biohydrogen from cassava wastewater biogas is very limited because, in general, this commodity is more common in underdeveloped countries. This hydrogen, produced from cassava wastewater, appears as an alternative fuel to fossil fuels since this is a low-cost carbon source. This paper evaluates the environmental impact of biohydrogen production, by steam reforming, from cassava wastewater biogas. The ecological efficiency methodology developed by Cardu and Baica was used as a benchmark in this study. The methodology mainly assesses the emissions of equivalent carbon dioxide (CO₂, SOₓ, CH₄ and particulate matter). As a result, some environmental parameters, such as equivalent carbon dioxide emissions, pollutant indicator, and ecological efficiency are evaluated due to the fact that they are important to energy production. The average values of the environmental parameters among different biogas compositions (different concentrations of methane) were calculated, the average pollution indicator was 10.11 kgCO₂e/kgH₂ with an average ecological efficiency of 93.37%. As a conclusion, bioenergy production using biohydrogen from cassava wastewater treatment plant is a good option from the environmental feasibility point of view. This fact can be justified by the determination of environmental parameters and comparison of the environmental parameters of hydrogen production via steam reforming from different types of fuels.

Keywords: biohydrogen, ecological efficiency, cassava, pollution indicator

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Authors: Jagriti Mishra, Vasundhara Chaudhary

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Introduction: The case highlights various issues and challenges faced by Khanna Enterprises while conceptualizing and execution of launching Active Leisure wear in the domestic market, where different steps involved in the range planning and production have been elaborated. Although Khanna Enterprises was an established company which dealt in the production of knitted and woven garments, they took the risk of launching a new concept- Active Leisure wear for Millennials. Methodology: It is based on primary and secondary research where data collection has been done through survey, in-depth interviews and various reports, forecasts, and journals. Findings: The research through primary and secondary data and execution of active leisure wear substantiated the acceptance, not only by the millennials but also by the generation X. There was a demand of bigger sizes as well as more muted colours. Conclusion: The sales data paved the way for future product development in tune with the strengths of Khanna Enterprises.

Keywords: millennials, range planning, production, active leisure wear

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Authors: Rashid S. Mohammad, Shicheng Zhang, Xinzhe Zhao

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In tight oil reservoirs, wettability alteration has generally been considered as an effective way to remove fracturing fluid retention on the surface of the fracture and consequently improved oil production. However, there is a lack of a reliable productivity prediction model to show the relationship between the wettability and oil production in tight oil well. In this paper, a new oil productivity prediction model of immiscible oil-water flow and miscible CO₂-oil flow accounting for wettability is developed. This mathematical model is established by considering two different length scales: nonporous network and propped fractures. CO₂ flow diffuses in the nonporous network and high velocity non-Darcy flow in propped fractures are considered by taking into account the effect of wettability alteration on capillary pressure and relative permeability. A laboratory experiment is also conducted here to validate this model. Laboratory experiments have been designed to compare the water saturation profiles for different contact angle, revealing the fluid retention in rock pores that affects capillary force and relative permeability. Four kinds of brines with different concentrations are selected here to create different contact angles. In water-wet porous media, as the system becomes more oil-wet, water saturation decreases. As a result, oil relative permeability increases. On the other hand, capillary pressure which is the resistance for the oil flow increases as well. The oil production change due to wettability alteration is the result of the comprehensive changes of oil relative permeability and capillary pressure. The results indicate that wettability is a key factor for fracturing fluid retention removal and oil enhancement in tight reservoirs. By incorporating laboratory test into a mathematical model, this work shows the relationship between wettability and oil production is not a simple linear pattern but a parabolic one. Additionally, it can be used for a better understanding of optimization design of fracturing fluids.

Keywords: wettability, relative permeability, fluid retention, oil production, unconventional and tight reservoirs

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Authors: Y. H. Tshela Ntumba, A. Przepiórkowska, M. Prochoń

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Polymeric materials have become an integral part of every aspect of today's industry. They have wide applications, inter alia, in areas such as medicine, food industry and agriculture. In agriculture, for example, they are used for the production of pots, irrigation systems and for soil mulching. The aim of this study was the attempt to produce a biodecomposable agricultural mat, by coating cotton fabric with a blend of carboxylated styrene-butadiene latex (LBSK) containing the enzymatic hydrolyzate of keratin from cattle hair, which would serve as a material for mulching. The production of such material allows the beneficial management of burdensome tannery waste constituted by keratin from cattle hair and at the same time, the production of agricultural mats that much faster undergo decomposition than commonly used polyethylene mats.

Keywords: agricultural mat, biodecomposition, biodegradation, carboxylated butadiene-styrene latex, cellulosic-elastomeric material, keratin hydrolyzate, mulching, protein hydrolyzate

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Authors: Kamran Taghizadeh

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This study was aimed at evaluating the effect of IMS including occupational health system, environmental management system, and safety and health system on the social responsibility (case study of NISOC`s oil and gas production companies). This study`s objectives include evaluating the IMS situation and its effect on social responsibility in addition of providing appropriate solutions based on the study`s hypotheses as a basis for future. Data collection was carried out by library and field studies as well as a questionnaire. The stratified random method was the sampling method and a sample of 285 employees in addition to the collected data (from the questionnaire) were analyzed by inferential statistics methods using SPSS software. Finally, results of regression and fitted model at a significance level of 5% confirmed all hypotheses meaning that IMS and its items have a significant effect on social responsibility.

Keywords: social responsibility, integrated management, oil and gas production companies, regression

Procedia PDF Downloads 256

Authors: Ana Paula S. Horodenski, Priscila Pelegrini, Salli Baggenstoss

Abstract:

The brewing industry with artisanal concepts seeks to serve a specific market, with diversified production that has been gaining ground in the national environment, also in the Amazon region. This growth is due to the more demanding consumer, with a diversified taste that wants to try new types of beer, enjoying products with new aromas, flavors, as a differential of what is so widely spread through the big industrial brands. Thus, through qualitative research methods, the study aimed to investigate how is the process of managing the production of a craft brewery in a city in the northern State of Mato Grosso (BRAZIL), providing knowledge of production processes and strategies in the industry. With the efficient use of resources, it is possible to obtain the necessary quality and provide better performance and differentiation of the company, besides analyzing the best management model. The research is descriptive with a qualitative approach through a case study. For the data collection, a semi-structured interview was elaborated, composed of the areas: microbrewery characterization, artisan beer production process, and the company supply chain management. Also, production processes were observed during technical visits. With the study, it was verified that the artisan brewery researched develops preventive maintenance strategies with the inputs, machines, and equipment, so that the quality of the product and the production process are achieved. It was observed that the distance from the supplying centers makes the management of processes and the supply chain be carried out with a longer planning time so that the delivery of the final product is satisfactory. The production process of the brewery is composed of machines and equipment that allows the control and quality of the product, which the manager states that for the productive capacity of the industry and its consumer market, the available equipment meets the demand. This study also contributes to highlight one of the challenges for the development of small breweries in front of the market giants, that is, the legislation, which fits the microbreweries as producers of alcoholic beverages. This makes the micro and small business segment to be taxed as a major, who has advantages in purchasing large batches of raw materials and tax incentives because they are large employers and tax pickers. It was possible to observe that the supply chain management system relies on spreadsheets and notes that are done manually, which could be simplified with a computer program to streamline procedures and reduce risks and failures of the manual process. In relation to the control of waste and effluents affected by the industry is outsourced and meets the needs. Finally, the results showed that the industry uses preventive maintenance as a productive strategy, which allows better conditions for the production and quality of artisanal beer. The quality is directly related to the satisfaction of the final consumer, being prized and performed throughout the production process, with the selection of better inputs, the effectiveness of the production processes and the relationship with the commercial partners.

Keywords: artisanal brewery, production management, production processes, supply chain

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Authors: Sezgi Isik, Yasin Urersoy, Gizem Ustunel, Ilkyaz Yalcin

Abstract:

Improvement of the digital tile application, lots of process revolutions have occurred in the tile production. In order to create unique and inimitable designs, all the competitors start to try different applications. Both Europian and domestic ceramic producers focus on the deep and realistic surfaces. In this study, the trend of engoglaze, which is becoming widespread in glaze porcelain tile designs to create the most intensive colours, were investigated. The aim of the study is to develop engoglaze formulation that supports digital ink activation. Thermal expansion coefficient values were determined by a dilatometer. Chemical analyses and sintering behaviors of engoglazes were made by X-ray diffraction and heat microscopy analysis. According to these glaze formulation studies, it has been reported that using engoglaze could easily reduce the digital ink consumption of the design. On the other hand, the advantage of the production cost is gained, and deepness of the design is provided.

Keywords: ceramic, engoglaze, digital ink activation, glazed porcelain tile

Procedia PDF Downloads 133

Authors: K. Abdul Halim, E. L. Yong

Abstract:

Palm oil industry is a major revenue earner in Malaysia, despite the growth of the industry is synonymous with a massive production of agro-industrial wastewater. Through the oil extraction processes, palm oil mill effluent (POME) contributes to the largest liquid wastes generated. Due to the high amount of organic compound, POME can cause inland water pollution if discharged untreated into the water course as well as affect the aquatic ecosystem. For more than 20 years, Malaysia adopted the conventional biological treatment known as lagoon system that apply biological treatment. Besides having difficulties in complying with the standard, a large build up area is needed and retention time is higher. Although anaerobic digester is more favorable, this process comes along with enormous volumes of sludge and methane gas, demanding attention from the mill operators. In order to reduce the sludge production, denitrifiers are to be removed first. Sulfate reducing bacteria has shown the capability to inhibit the growth of methanogens. This is expected to substantially reduce both the sludge and methane production in anaerobic digesters. In this paper, the effectiveness of sulfate reducing bacteria in minimizing sludge and methane will be examined.

Keywords: methane reduction, palm oil mill effluent, sludge minimization, sulfate reducing bacteria, sulfate reduction

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Authors: I. Ben Kaddour, S. Larbaoui

Abstract:

Since their first synthesis, the Silicoaluminophosphates materials have proved their efficiency as a good adsorbent and catalyst in several environmental and energetic applications. In this work, the photocatalytic hydrogen production from water splitting reactions has been conducted under visible radiations in the presence of a series of iron and/or titanium-containing microporous silico-alumino-phosphates materials synthesized by hydrothermal method, using triethylamine as an organic structuring agent to obtain the AFI structure type. These photo-catalysts were then characterized by various physicochemical methods to determine their structural, textural and morphological properties such as X-ray diffraction (XRD), Fourier transformed infrared spectroscopy (FTIR), scanning electron microscopy (SEM) coupled with X rays microanalysis, nitrogen adsorption measurements, UV-visible diffuse reflectance spectroscopy (UV-Vis-DRS), and X-rays photoelectron spectroscopy (XPS) and the analysis revealed that these materials have significant photocatalytic properties. The hydrogen production process has been followed by photoelectrochemical characterization (PEC). The results showed that hydrogen is the only gas produced, and the reaction takes place in the conduction band where water is reduced to hydrogen. The electron recombination has also been avoided, as holes are entrapped using hole scavengers. In addition, these catalysts have been shown to remain stable during reuse for up to five cycles.

Keywords: photocatalysis, SAPO-5, hydrothermal synthesis, hydrogen production

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Authors: Sónia Ribeiro, Diana Farinha, Hélia Sales, Rita Pontes, João Nunes

Abstract:

The demand and commitment to sustainability in the agrifood sector introduce news opportunities for new composite materials. Composite materials are emerging as a vital entity for the sustainable development. Polylactic acid (PLA) has been recognized as a potential polymer with attractive characteristics for agrifood sector applications. PLA that can be beneficial for the development of composites, biocomposites, films, porous gels, and so on. The production of PLA from lignocellulosic biomass residues matrix is a key option towards a sustainable and circular bioeconomy and a non-competitive application with feed and food sector. The Flui and BeirInov projects presents news developments in the production of PLA composites to value the Portuguese forest ecosystem, with high amount of lignocellulosic biomass residues and available. A performance production of lactic acid from lignocellulosic biomass undergoes a process of autohydrolysis, saccharification and fermentation, originating a lactic acid fermentation medium with a 72.27g.L-1 was obtained and a final purification of 72%. The high purification PLA from multi lignocellulosic residues representing one economic expensive process, and a new materials and application for the polymers and a combination with others types of composites matrix characteristic is the drive-up for this green market.

Keywords: polylactic acid, lignocellulosic biomass, agrifood, composite materials

Procedia PDF Downloads 75

Authors: Liuhui Zhu, Peng Zeng

Abstract:

The rural revitalization strategy means to take the country and the city on the same level, and achieve urban-rural integration and comprehensive development of rural areas. Beijing-Tianjin-Hebei rural areas have always been the weak links in the region, with prominently uneven development between urban and rural areas. The rural areas need to join the overall regional synergy. Based on the analysis of the characteristics and problems of rural development in the region from the perspective of production-living-ecology space, the paper proposes the township as the basic unit for rural revitalization according to the overall requirements of the rural revitalization strategy. The basic unit helps to realize resource arrangement, functional organization, and collaborative governance organized by the production-living-ecology spatial network. The paper summarizes the planning strategies for the basic unit. Through spatial cognition and spatial reconstruction, the three space is networked through the base, nodes, and connections to improve the comprehensive value of rural areas and achieve the multiple goals of rural revitalization.

Keywords: rural revitalization, Beijing-Tianjin-Hebei region, township level, production-living-ecology spatial network

Procedia PDF Downloads 195

Authors: St. Subaedah, A. Takdir, Netty, D. Hidrawati

Abstract:

Maize development at the rainfed lowland after rice is often confronted with the occurrence of drought stress at the time of entering the generative phase, which will cause be hampered crop production. Consequently, in the utilization of the rainfed lowland areas optimally, an effort that can be done using the varieties of early maturity to minimize crop failures due to its short rainy season. The aim of this research was evaluating the potential yield of genotypes of candidates of maize early maturity in the rainfed lowland areas. The study was conducted during May to August 2016 at South Sulawesi, Indonesia. The study used randomized block design to compare 12 treatments and consists of 8 genotypes namely CH1, CH2, CH3, CH4, CH5, CH6, CH7, CH8 and the use of four varieties, namely Bima 3, Bima 7, Lamuru and Gumarang. The results showed that genotype of CH2, CH3, CH5, CH 6, CH7 and CH8 harvesting has less than 90 days. There are two genotypes namely genotypes of CH7 and CH8 that have a fairly high production respectively of 7.16 tons / ha and 8.11 tons/ ha and significantly not different from the superior varieties Bima3.

Keywords: evaluation, early maturity, maize, yield potential

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Authors: Joelle Penniston, E. B. Gueguim-Kana

Abstract:

Biohydrogen has been identified as a promising alternative to the use of non-renewable fossil reserves, owing to its sustainability and non-polluting nature. pH is considered as a key parameter in fermentative biohydrogen production processes, due to its effect on the hydrogenase activity, metabolic activity as well as substrate hydrolysis. The present study assesses the influence of regulating pH on dark fermentative biohydrogen production. Four experimental hydrogen production schemes were evaluated. Two were implemented using suspended cells under regulated pH growth conditions (Sus_R) and suspended and non-regulated pH (Sus_N). The two others regimes consisted of alginate immobilized cells under pH regulated growth conditions (Imm_R) and immobilized and non-pH regulated conditions (Imm_N). All experiments were carried out at 37.5°C with glucose as sole source of carbon. Sus_R showed a lag time of 5 hours and a peak hydrogen fraction of 36% and a glucose degradation of 37%, compared to Sus_N which showed a peak hydrogen fraction of 44% and complete glucose degradation. Both suspended culture systems showed a higher peak biohydrogen fraction compared to the immobilized cell system. Imm_R experiments showed a lag phase of 8 hours, a peak biohydrogen fraction of 35%, while Imm_N showed a lag phase of 5 hours, a peak biohydrogen fraction of 22%. 100% glucose degradation was observed in both pH regulated and non-regulated processes. This study showed that biohydrogen production in batch mode with suspended cells in a non-regulated pH environment results in a partial degradation of substrate, with lower yield. This scheme has been the culture mode of choice for most reported studies in biohydrogen research. The relatively lower slope in pH trend of the non-regulated pH experiment with immobilized cells (Imm_N) compared to Sus_N revealed that that immobilized systems have a better buffering capacity compared to suspended systems, which allows for the extended production of biohydrogen even under non-regulated pH conditions. However, alginate immobilized cultures in flask systems showed some drawbacks associated to high rate of gas production that leads to increased buoyancy of the immobilization beads. This ultimately impedes the release of gas out of the flask.

Keywords: biohydrogen, sustainability, suspended, immobilized

Procedia PDF Downloads 342

Authors: Bokkasam Sasidhar, Ibrahim Aljasser

Abstract:

The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

Procedia PDF Downloads 402