983 resultados para cell manufacturing
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This research project investigated a bioreactor system capable of high density cell growth intended for use in regenerative medicine and protein production. The bioreactor was based on a drip-perfusion concept and constructed with minimal costs, readily available components, and straightforward processes for usage. This study involved the design, construction, and testing of the bioreactor where the results showed promising three dimensional cell growth within a polymer structure. The accessibility of this equipment and the capability of high density, three dimensional cell growth would be suitable for future research in pharmaceutical drug manufacturing, and human organ and tissue regeneration.
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In this paper, we propose an approach, using Coloured Petri Nets (CPN) for modelling flexible manufacturing systems. We illustrate our methodology for a Flexible Manufacturing Cell (FMC) with three machines and three robots. We also consider the analysis of the FMC for deadlocks using the invariant analysis of CPNs.
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The objective of the current study is to evaluate the fidelity of load cell reading during impact testing in a drop-weight impactor using lumped parameter modeling. For the most common configuration of a moving impactor-load cell system in which dynamic load is transferred from the impactor head to the load cell, a quantitative assessment is made of the possible discrepancy that can result in load cell response. A 3-DOF (degrees-of-freedom) LPM (lumped parameter model) is considered to represent a given impact testing set-up. In this model, a test specimen in the form of a steel hat section similar to front rails of cars is represented by a nonlinear spring while the load cell is assumed to behave in a linear manner due to its high stiffness. Assuming a given load-displacement response obtained in an actual test as the true behavior of the specimen, the numerical solution of the governing differential equations following an implicit time integration scheme is shown to yield an excellent reproduction of the mechanical behavior of the specimen thereby confirming the accuracy of the numerical approach. The spring representing the load cell, however,predicts a response that qualitatively matches the assumed load-displacement response of the test specimen with a perceptibly lower magnitude of load.
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The aim of this paper is to describe the implementation of a new approach for the introduction of so called 'holonic manufacturing' principles into existing production control systems. Such an approach is intended to improve the reconfigurability of the control system to cope with the increasing requirements of production change. A conceptual architecture is described and implemented in a robot assembly cell to demonstrate that this approach can lead to a manufacturing control system which can adapt relatively simply to long-term change. A design methodology and migration strategy for achieving these solutions using conventional hardware is proposed to develop execution level of manufacturing control systems.
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In recent years, a large number of approaches to developing distributed manufacturing systems has been proposed. One of the principles reasons for these development has been to enhance the reconfigurability of a manufacturing operation; allowing it to readily adapt to changes over time. However, to date, there has only been a limited assessment of the resulting reconfigurability properties and hence it remains inconclusive as to whether a distributed manufacturing system design approach does in fact improve reconfigurability. This paper represents part of a study which investigates this issue. It proposes an assessment tool - the so called "Design Structure Matrix" as a means of assessing the modularity of elements in a manufacturing system. (Modularity has been shown to be a key characteristic of a reconfigurable manufacturing system.) The use of the Design Structure Matrix is illustrated in assessing a robot assembly cell designed on distributed manufacturing system principles. Copyright © 2006 IFAC.
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Hardy, N. W., Barnes, D. P., Lee, L. H. (1989). Automatic diagnosis of task faults in flexible manufacturing systems. Robotica, 7 (1):25-35
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The three-dimensional (3D) weaving process offers the ability to tailor the mechanical properties via design of the weave architecture. One repeat of the 3D woven fabric is represented by the unit cell. The model accepts basic weaver and material manufacturer data as inputs in order to calculate the geometric characteristics of the 3D woven unit cell. The specific weave architecture manufactured and subsequently modelled had an angle interlock type binding configuration. The modelled result was shown to have a close approximation compared to the experimentally measured values and highlighted the importance of the representation of the binder tow path.
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INTRODUCTION: Dendritic cells (DCs) are the most important antigen-presenting cell population for activating antitumor T-cell responses; therefore, they offer a unique opportunity for specific targeting of tumors. AREAS COVERED: We will discuss the critical factors for the enhancement of DC vaccine efficacy: different DC subsets, types of in vitro DC manufacturing protocol, types of tumor antigen to be loaded and finally different adjuvants for activating them. We will cover potential combinatorial strategies with immunomodulatory therapies: depleting T-regulatory (Treg) cells, blocking VEGF and blocking inhibitory signals. Furthermore, recommendations to incorporate these criteria into DC-based tumor immunotherapy will be suggested. EXPERT OPINION: Monocyte-derived DCs are the most widely used DC subset in the clinic, whereas Langerhans cells and plasmacytoid DCs are two emerging DC subsets that are highly effective in eliciting cytotoxic T lymphocyte responses. Depending on the type of tumor antigens selected for loading DCs, it is important to optimize a protocol that will generate highly potent DCs. The future aim of DC-based immunotherapy is to combine it with one or more immunomodulatory therapies, for example, Treg cell depletion, VEGF blockage and T-cell checkpoint blockage, to elicit the most optimal antitumor immunity to induce long-term remission or even cure cancer patients.
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Intelligent viewing systems are required if efficient and productive teleoperation is to be applied to dynamic manufacturing environments. These systems must automatically provide remote views to an operator which assist in the completion of the task. This assistance increases the productivity of the teleoperation task if the robot controller is responsive to the unpredictable dynamic evolution of the workcell. Behavioral controllers can be utilized to give reactive 'intelligence.' The inherent complex structure of current systems, however, places considerable time overheads on any redesign of the emergent behavior. In industry, where the remote environment and task frequently change, this continual redesign process becomes inefficient. We introduce a novel behavioral controller, based on an 'ego-behavior' architecture, to command an active camera (a camera mounted on a robot) within a remote workcell. Using this ego-behavioral architecture the responses from individual behaviors are rapidly combined to produce an 'intelligent' responsive viewing system. The architecture is single-layered, each behavior being autonomous with no explicit knowledge of the number, description or activity of other behaviors present (if any). This lack of imposed structure decreases the development time as it allows each behavior to be designed and tested independently before insertion into the architecture. The fusion mechanism for the behaviors provides the ability for each behavior to compete and/or co-operate with other behaviors for full or partial control of the viewing active camera. Each behavior continually reassesses this degree of competition or co-operation by measuring its own success in controlling the active camera against pre-defined constraints. The ego-behavioral architecture is demonstrated through simulation and experimentation.
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Sponge cakes have traditionally been manufactured using multistage mixing methods to enhance potential foam formation by the eggs. Today, use of all-in (single-stage) mixing methods is superseding multistage methods for large-scale batter preparation to reduce costs and production time. In this study, multistage and all-in mixing procedures and three final high-speed mixing times (3, 5, and 15 min) for sponge cake production were tested to optimize a mixing method for pilot-scale research. Mixing for 3 min produced batters with higher relative density values than did longer mixing times. These batters generated well-aerated cakes with high volume and low hardness. In contrast, after 5 and 15 min of high-speed mixing, batters with lower relative density and higher viscosity values were produced. Although higher bubble incorporation and retention were observed, longer mixing times produced better developed gluten networks, which stiffened the batters and inhibited bubble expansion during mixing. As a result, these batters did not expand properly and produced cakes with low volume, dense crumb, and high hardness values. Results for all-in mixing were similar to those for the multistage mixing procedure in terms of the physical properties of batters and cakes (i.e., relative density, elastic moduli, volume, total cell area, hardness, etc.). These results suggest the all-in mixing procedure with a final high-speed mixing time of 3 min is an appropriate mixing method for pilot-scale sponge cake production. The advantages of this method are reduced energy costs and production time.
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In this work, lipolysis, proteolysis and viscosity of ultra-high temperature (UHT) milk containing different somatic cell counts (SCC) were investigated. UHT milks were analysed on days 8, 30, 60, 90 and 120 of storage. Lipolysis as measured by free fatty acids increase, casein degradation and viscosity of UHT milk were not affected by SCC but increased during storage. A negative relationship was observed between SCC and casein as a percentage of true protein on the 120th day of storage, hence indicating that high SCC increases the proteolysis of UHT milk by the end of its shelf life.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This article describes the application of an Artificial Intelligence Planner in a robotized assembly cell that can be integrated to a Flexible Manufacturing System. The objective is to allow different products to be automatically assembled in a single production line with no pre-established assembly plans. The planner function is to generate action plans to the robot, in real time, from two input information: the initial state (disposition of parts of the product in line) and the final state (configuration of the assembled product). Copyright © 2007 IFAC.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)