1,721,241 research outputs found
Design, control and management of renewable energy plants and technologies
Full text linkNowadays, and even more in the next decades, the availability and easy-access to energy sources represent a crucial asset for the world development and the progress of people and nations. At the same time, the depletion of natural resources, together with the increase of the anthropic activity impact on the Earth ecosystem and climate, force communities and institutions, at all levels, to discuss and actuate different approaches to achieve the social and economic growth, based on the so-called sustainable development pattern. In such a scenario, renewable energy sources, i.e. solar, wind, hydro, biomass, geothermal, etc., certainly play a key role to join progress and attention to the environmental issues.
The present Ph.D. dissertation focuses on such topics investigating strategies, methods and innovative approaches for the effective design, control and management of renewable energy plants and technologies.
Specifically, the energy scenario is investigated from a global point of view proposing studies and optimization models highlighting the relevance and the potential impact of the major energy sources, both renewable and conventional. Such sources represent the elements of a big puzzle, i.e. the energy mix, in which their economic and environmental strengths should be emphasized minimizing the associated negative impacts and weaknesses.
Among renewable sources, solar energy is of primary importance for availability, diffusion and potential impact. The present Ph.D. dissertation particularly investigates such a source presenting models, methods and prototypes to increase its relevance in the energy mix. The fundamentals of solar energy, together with innovative approaches to estimate the solar radiation components, are provided. Furthermore, the pioneering concentrating solar sector is deeply focused presenting the design, development and preliminary field-test of a bi-axial Fresnel solar photovoltaic/thermal (PV/T) concentrating prototype. Possible solar tracking strategies and control algorithms are, then, investigated describing a customized semi-automatic motion control platform, developed in LabViewTM programming environment. Finally, the last section, proposes an effective approach for the design of a solar simulator, the most frequently adopted device in solar optic laboratory tests.
In conclusion, the present Ph.D. dissertation describes effective strategies for the renewable energy spread, considering their performances and their potential impact to achieve the ambitious challenge of a sustainable living planet
Reconfigurable manufacturing systems: Literature review and research trend
No full textThe current manufacturing environment aims at getting an increasing variety of customised, high-quality products in flexible batches. The dynamic market demand, the short product lifecycle and the flexibility need mark the transition from the traditional manufacturing systems to the so-called Next Generation Manufacturing Systems (NGMSs). Reconfigurable Manufacturing Systems (RMSs) are within NGMSs and seem to match to these current market trends. RMSs allow rapid change in structure, hardware and software configuration to adjust, promptly, their production capacity and functionality.
This paper presents a structured and updated systematic review of the literature about RMSs, highlighting the application areas as well as the key methodologies and tools. The review further provides a schematic of RMS research, identifying five emerging and promising research streams ranging from conceptual models to empirical applications. Compared to previous reviews, focusing on specific aspects of the RMS design and management, this study covers multiple areas and topics and it links reconfigurable manufacturing to the upcoming Industry 4.0 fourth industrial revolution. Finally, important issues and new trends in the literature are outlined to stimulate researchers and practitioners in developing studies in this field strongly linked to the Industry 4.0 environment
Decision system to support the practitioners in the wind farm design: A case study for Iran mainland
No full textSelecting wind turbines has traditionally been based on designing a new turbine matching the wind profile of a given site. However, this method of selection has proven time-consuming and uneconomical. A more practical approach would be to select the turbine that best matches the wind characteristics of a specific site among the commercially available ones. The assessment of wind turbines, nevertheless, is a complex process that involves different criteria with different degrees of importance such as, economic, technological, and environmental ones. The object of this study is to identify the evaluation criteria that influence the wind turbine selection and then to provide an effective model based on AHP to evaluate wind turbines when developing a wind farm. Based on the proposed model, using the knowledge and experience of experts in an Iranian renewable energy firm, a case study is carried out. In this case, the importance of the factors and the performance of different wind turbines are identified. Results highlights that the most suitable wind turbine for the case is T-1 with rated power of 2000 kW, and cut-in wind speed of 3.5 m/s. The results should prove practical to other decision makers in selecting the most suitable wind turbines
Hierarchical approach for paced mixed-model assembly line balancing and sequencing with jolly operators
No full textIn order to increase flexibility and reduce costs, several companies adopt mixed-model assembly lines whose output
products are variations of the same basic model with specific and distinctive attributes. Unfortunately, such attributes
typically lead to variations in the task process times. In the case of un-paced buffered assembly lines, these variations
are smoothed by buffers with consequences in terms of work-in-progress, costs, space utilisation and lower productivity
control. To face such weaknesses, some companies adopt paced un-buffered assembly lines where the cycle time is
controlled by the continuous/synchronous moving of the products from the first to the last assembly station. In such
contexts, the possibility of assembling different models with different assembly times can be managed through the use
of supplementary flexible workforce. This article introduces an innovative balancing and sequencing hierarchical
approach for paced mixed-model assembly lines using supplementary flexible workforce called ‘jolly operators’. The
goals are to minimise the number of jolly operators and to limit the occurrence of work-overloads, which typically result
in out-of-the-line assembly completion. The proposed approach is preliminary validated and applied to a case study from
an Italian company assembling industrial air-dryers
Material handling improvement in warehouses for the assembly line parts feeding in case of kitting and in case of different parts categories
No full textThe assembly line parts feeding is a complex problem that strongly involves the logistic activities at the
warehouse. In case of kitting the handling activities within the warehouse are related to the collection of
parts for each kit composition, which is called the Order Picking Problem. Improving the order picking means
to minimize the total travel distance and to minimize the time spent to pick the single part once reach its
position. Typically to a certain kit belong different parts categories: small parts (SP), large parts but pickable
by an operator (PLP), large parts not pickable by an operator but only using a proper equipment (NPLP)
typically stored in different warehouse facilities (i.e. racks, shelves, ground). A two-level approach is proposed
that determines the locations of parts in the warehouse. Once assigned to each part a proper stock keeping
unit in the warehouse and the related SP, PLP, NPLP attribute the first step clusters parts into part families
depending on in which zone/kit of the assembly line they are used. The general output of this phase is a
different dimension of each SP, PLP, NPLP families are generated for each cluster. In the second step an
optimization model is proposed to determine the optimal location of parts minimizing the total picking
distance with the aim of storing the same cluster in the same aisle, considering the typical constrain that in
the warehouse each isle is composed by all the three warehouse facilities to store SP, PLP, NPLP with a fixed
dimension for each one and equal for all the isles. The applied algorithm can easily be modified to be used
with different configurations and for parts with different categorization. A case study from a harvesting
producer company is detailed reported demonstrating the applicability and the practical implication of the
research
Multi-objective design of multi-modal fresh food distribution networks
No full textThis paper presents a methodology to jointly minimise the operating
cost, the carbon footprint and the delivery time in the design of multi-modal
fresh food distribution networks. A tri-objective linear programming model
optimises such criteria overcoming the widely adopted methodologies focused
on the network cost minimisation, only. A practical selection rule supports the
final network structure definition, leading to an effective trade-off among the
three objective functions. The market demand supply, the producer capacity
limits and the food quality decrease during shipment, i.e., perishability, limit
the feasibility region. The paper applies the proposed model to an industrial
case study dealing with the distribution of fruits and vegetables from a
set of Italian producers to multiple European retailers through a multi-modal
(truck, train and air) distribution network. The case study key results suggest
the possibility to reduce the CO2 emissions without relevant cost increase
Stochastic timed Petri nets to dynamically design and simulate industrial production processes
No full textStochastic timed Petri nets are among the most effective languages to model event driven uncertain processes. Their adoption in the industrial sector is even more diffuse and of potential help for the practitioners. This paper presents a stepwise approach to support the dynamic design and simulation of manufacturing and assembly production processes. An industrial application from the white good sector, based on a semi-automatic assembly line is, further, discussed demonstrating the approach flexibility and the modelling language key strengths. The stochastic timed Petri net model for such a scenario is described together with the simulation outcomes of interest for the assembly line design and the production and maintenance activity scheduling
Food distribution optimization considering the produce perishability
No full textDespite the past and recent literature widely investigates effective strategies and innovative approaches for the design and optimization of industrial supply chains, lower attention is paid to the agriculture sector, even if it represents an high value market in which high quality and low costs are key issues to compete. Aim of this paper is to propose an optimization model to support the logistic managers and practitioners in the design of an agriculture supply chain. The model includes some cost drivers and constraints specific of the agricultural sector, making it different from any other market area, e.g. the produce perishability characteristics, the temperature-controlled shipping requirements, the quality decrease through the supply chain, from farm to fork, etc. The best shipment conditions, minimizing the global network cost, subject to defined produce quality profiles are assessed and compared in this paper.
The proposed model is validated and applied to a realistic case study for the fresh produce distribution in the European area. Results highlight that the most convenient shipment strategies depend on the combination of both the produce shelf life and its production cost. The lower the perishability and expensiveness, the higher the convenience to distribute such a produce through an intermodal freight, e.g. truck & trail, is. Furthermore, for the discussed case study, a reduction of the global network cost of about 10% without a relevant increase of the produces discharged due to a loss of quality occurs and represents a relevant outcome of the analysis fully described in this paper
Artificial neural network optimisation for monthly average daily global solar radiation prediction
No full textThe availability of reliable climatologic data is essential for multiple purposes in a wide set of anthropic activities and operative sectors. Frequently direct measures present spatial and temporal lacks so that predictive approaches become of interest. This paper focuses on the prediction of the Monthly Average Daily Global Solar Radiation (MADGSR) over Italy using Artificial Neural Networks (ANNs). Data from 45 locations compose the multi-location ANN training and testing sets. For each location, 13 input parameters are considered, including the geographical coordinates and the monthly values for the most frequently adopted climatologic parameters. A subset of 17 locations is used for ANN training, while the testing step is against data from the remaining 28 locations. Furthermore, the Automatic Relevance Determination method (ARD) is used to point out the most relevant input for the accurate MADGSR prediction. The ANN best configuration includes 7 parameters, only, i.e. Top of Atmosphere (TOA) radiation, day length, number of rainy days and average rainfall, latitude and altitude. The correlation performances, expressed through statistical indicators as the Mean Absolute Percentage Error (MAPE), range between 1.67% and 4.25%, depending on the number and type of the chosen input, representing a good solution compared to the current standards
Optimal design of AS/RS storage systems with three-class-based assignment strategy under single and dual command operations
No full textThis paper presents an extension of the analytical
models already proposed by the literature to compute the expected
travel time of automated storage and retrieval systems
(AS/RS) in three-class-based storage (3-CBS) rectangular-intime
(RIT) storage systems. The authors determined the analytical
closed form of the mean travel time for both the singlecommand
(SC) and the dual-command (DC) cycles varying
the warehouse shape factor and the ABC turnover curve. The
performances obtained by the adoption of the proposed analytical
travel time model under different configurations of the
warehousing system, i.e., shape, dimension of the classes, and
ABC curve, are evaluated and compared. Finally, the optimal
boundary limits for the 3-CBS AS/RS, considering both the
SC and the DC cycles, are fixed presenting the percentage
saving of such configurations toward the common random
assignment policy
- …
