Abstract: Green hydrogen is the most environmental, renewable alternative to produce hydrogen. However, an important challenge to make hydrogen a competitive energy carrier is a constant supply of renewable energy, such as solar, wind and hydropower. Given that the electricity generation potential of these sources vary seasonally and interannually, this paper proposes installing an electrolysis hydrogen production plant in a ship and move the ship to the locations where electricity is cheap, or where the seasonal potential for renewable generation is high. An example of electrolysis ship application is to produce green hydrogen with hydropower from the North region of Brazil and then sail to the Northeast region of Brazil and generate hydrogen using excess electricity from offshore wind power. The electrolysis ship concept is interesting because it has the flexibility to produce green hydrogen using the cheapest renewable electricity available in the market.
Abstract: A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.
Abstract: Most developing nations face energy production and supply problems. This is also the case of Afghanistan whose generating capacity does not meet its energy demand. This is due in part to high security and risk caused by war which deters foreign investments and insufficient internal revenue. To address the issue above, this paper would like to suggest an alternative and affordable way to deal with the energy problem. That is by converting Solid Waste to energy. As a result, this approach tackles the municipal solid waste issue (potential cause of several diseases), contributes to the improvement of the quality of life, local economy, and so on. While addressing the solid waste problem in general, this paper samples specifically one municipality which is District-12, one of the 22 districts of Kabul city. Using geographic information system (GIS) technology, District-12 is divided into nine different zones whose municipal solid waste is respectively collected, processed, and converted into electricity and distributed to the closest area. It is important to mention that GIS has been used to estimate the amount of electricity to be distributed and to optimally position the production plant.
Abstract: Test automation allows performing difficult and time
consuming manual software testing tasks efficiently, quickly and
repeatedly. However, development and maintenance of automated
tests is expensive, so it needs a proper prioritization what to automate
first. This paper describes a simple yet efficient approach for such
prioritization of test cases based on the effort needed for both manual
execution and software test automation. The suggested approach is
very flexible because it allows working with a variety of assessment
methods, and adding or removing new candidates at any time. The
theoretical ideas presented in this article have been successfully
applied in real world situations in several software companies by the
authors and their colleagues including testing of real estate websites,
cryptographic and authentication solutions, OSGi-based middleware
framework that has been applied in various systems for smart homes,
connected cars, production plants, sensors, home appliances, car head
units and engine control units (ECU), vending machines, medical
devices, industry equipment and other devices that either contain or
are connected to an embedded service gateway.
Abstract: Batch production plants provide a wide range of
scheduling problems. In pharmaceutical industries a batch process
is usually described by a recipe, consisting of an ordering of tasks
to produce the desired product. In this research work we focused
on pharmaceutical production processes requiring the culture of
a microorganism population (i.e. bacteria, yeasts or antibiotics).
Several sources of uncertainty may influence the yield of the culture
processes, including (i) low performance and quality of the cultured
microorganism population or (ii) microbial contamination. For
these reasons, robustness is a valuable property for the considered
application context. In particular, a robust schedule will not collapse
immediately when a cell of microorganisms has to be thrown away
due to a microbial contamination. Indeed, a robust schedule should
change locally in small proportions and the overall performance
measure (i.e. makespan, lateness) should change a little if at all.
In this research work we formulated a constraint programming
optimization (COP) model for the robust planning of antibiotics
production. We developed a discrete-time model with a multi-criteria
objective, ordering the different criteria and performing a
lexicographic optimization. A feasible solution of the proposed
COP model is a schedule of a given set of tasks onto available
resources. The schedule has to satisfy tasks precedence constraints,
resource capacity constraints and time constraints. In particular
time constraints model tasks duedates and resource availability
time windows constraints. To improve the schedule robustness, we
modeled the concept of (a, b) super-solutions, where (a, b) are input
parameters of the COP model. An (a, b) super-solution is one in
which if a variables (i.e. the completion times of a culture tasks)
lose their values (i.e. cultures are contaminated), the solution can be
repaired by assigning these variables values with a new values (i.e.
the completion times of a backup culture tasks) and at most b other
variables (i.e. delaying the completion of at most b other tasks).
The efficiency and applicability of the proposed model is
demonstrated by solving instances taken from a real-life
pharmaceutical company. Computational results showed that
the determined super-solutions are near-optimal.
Abstract: Power Regeneration in Refrigeration Plant concept
has been analyzed and has been shown to be capable of saving about
25% power in Cryogenic Plants with the Power Regeneration System
(PRS) running under nominal conditions. The innovative component
Compressor Expander Group (CEG) based on turbomachinery has
been designed and built modifying CETT compressor and expander,
both selected for optimum plant performance. Experiments have
shown the good response of the turbomachines to run with R404a as
working fluid. Power saving up to 12% under PRS derated conditions
(50% loading) has been demonstrated. Such experiments allowed
predicting a power saving up to 25% under CEG full load.
Abstract: In times of global warming and the increasing
shortage of resources, sustainable production is becoming more and
more inevitable. Companies cannot only heighten their
competitiveness but also contribute positively to environmental
protection through efficient energy and resource consumption.
Regarding this, technical solutions are often preferred during
production, although organizational and process-related approaches
also offer great potential. This project focuses on reducing resource
usage, with a special emphasis on the human factor. It is the
aspiration to develop a methodology that systematically implements
and embeds suitable and individual measures and methods regarding
resource efficiency throughout the entire production. The measures
and methods established help employees handle resources and energy
more sensitively. With this in mind, this paper also deals with the
difficulties that can occur during the sensitization of employees and
the implementation of these measures and methods. In addition,
recommendations are given on how to avoid such difficulties.
Abstract: Compost manufacturing plants are one of units where
wastewater is produced in significantly large amounts. Wastewater
produced in these plants contains high amounts of substrate (organic
loads) and is classified as stringent waste which creates significant
pollution when discharged into the environment without treatment. A
compost production plant in the one of the Iran-s province treating
200 tons/day of waste is one of the most important environmental
pollutant operations in this zone. The main objectives of this paper
are to investigate the compost wastewater treatability in hybrid
anaerobic reactors with an upflow-downflow arrangement, to
determine the kinetic constants, and eventually to obtain an
appropriate mathematical model. After starting the hybrid anaerobic
reactor of the compost production plant, the average COD removal
rate efficiency was 95%.
Abstract: In this article, the design of a Supply Chain Network
(SCN) consisting of several suppliers, production plants, distribution
centers and retailers, is considered. Demands of retailers are
considered stochastic parameters, so we generate amounts of data via
simulation to extract a few demand scenarios. Then a mixed integer
two-stage programming model is developed to optimize
simultaneously two objectives: (1) minimization the fixed and
variable cost, (2) maximization the service level. A weighting method
is utilized to solve this two objective problem and a numerical
example is made to show the performance of the model.
Abstract: Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.
Abstract: All around the world pulp and paper industries are the
biggest plant production with the environmental pollution as the
biggest challenge facing the pulp manufacturing operations. The
concern among these industries is to produce a high volume of papers
with the high quality standard and of low cost without affecting the
environment. This result obtained from this bleaching study show
that the activation of peroxide was an effective method of reducing
the total applied charge of chlorine dioxide which is harmful to our
environment and also show that softwood and hardwood Kraft pulps
responded linearly to the peroxide treatments. During the bleaching
process the production plant produce chlorines. Under the trial stages
chloride dioxide has been reduced by 3 kg/ton to reduce the
brightness from 65% ISO to 60% ISO of pulp and the dosing point
returned to the E stage charges by pre-treating Kraft pulps with
hydrogen peroxide. The pulp and paper industry has developed
elemental chlorine free (ECF) and totally chlorine free (TCF)
bleaching, in their quest for being environmental friendly, they have
been looking at ways to turn their ECF process into a TCF process
while still being competitive. This prompted the research to
investigate the capability of the hydrogen peroxide as catalyst to
reduce chloride dioxide.
Abstract: This work aims to investigate a potential of
microalgae for utilizing industrial wastewater as a cheap nutrient for
their growth and oil accumulation. Wastewater was collected from
the effluent ponds of agro-industrial factories (cassava and ethanol
production plants). Only 2 microalgal strains were isolated and
identified as Scenedesmus quadricauda and Chlorella sp.. However,
only S. quadricauda was selected to cultivate in various wastewater
concentrations (10%, 20%, 40%, 60%, 80% and 100%). The highest
biomass obtained at 6.6×106 and 6.27×106 cells/ml when 60%
wastewater was used in flask and photo-bioreactor. The cultures gave
the highest lipid content at 18.58 % and 42.86% in cases of S.
quadricauda and S. obliquus. In addition, under salt stress (1.0 M
NaCl), S. obliquus demonstrated the highest lipid content at 50%
which was much more than the case of no NaCl adding. However, the
concentration of NaCl does not affect on lipid accumulation in case
of S. quadricauda.
Abstract: Modeling of a heterogeneous industrial fixed bed
reactor for selective dehydrogenation of heavy paraffin with Pt-Sn-
Al2O3 catalyst has been the subject of current study. By applying
mass balance, momentum balance for appropriate element of reactor
and using pressure drop, rate and deactivation equations, a detailed
model of the reactor has been obtained. Mass balance equations have
been written for five different components. In order to estimate
reactor production by the passage of time, the reactor model which is
a set of partial differential equations, ordinary differential equations
and algebraic equations has been solved numerically.
Paraffins, olefins, dienes, aromatics and hydrogen mole percent as
a function of time and reactor radius have been found by numerical
solution of the model. Results of model have been compared with
industrial reactor data at different operation times. The comparison
successfully confirms validity of proposed model.
Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.