Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Design, manufacturing, and testing of a Nb3Sn coil employing Ti alloy as structural material

We describe the design, manufacturing, and testing results of a Nb3Sn superconducting coil in which TiAIV alloys were used instead of stainless steel to reduce the magnetization contribution caused by the heat treatment for the A-15 Nb-3 Sn phase formation that affects the magnetic field homogeneity. Prior to the coil manufacturing several structural materials were studied and evaluated in terms of their mechanical and magnetic properties in as-worked, welded, and heat-treated conditions. The manufacturing process employed the wind-and-react technique followed by vacuum-pressure impregnation(VPI) at 1 MPa atm. The critical steps of the manufacturing process, besides the heat treatment and impregnation, are the wire splicing and joint manufacturing in which copper posts supported by Si3N4 ceramic were used. The coil was tested with and without a background NbTi coil and the results have shown performance exceeding the design quench current confirming the successful coil construction.

Using artificial neural networks for identification of electrical losses in transformers during the manufacturing phase

The paper describes a novel neural model to estimate electrical losses in transformer during the manufacturing phase. The network acts as an identifier of structural features on electrical loss process, so that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through experimental data taking into account core losses, copper losses, resistance, current and temperature. The results obtained in the simulations have shown that the developed technique can be used as an alternative tool to make the analysis of electrical losses on distribution transformer more appropriate regarding to manufacturing process. Thus, this research has led to an improvement on the rational use of energy.

Monitoring the process of densification of 3D and 4D (tridirectional and tetradirectional) carbon/carbon composites

Carbon fiber reinforced carbon composites can be made by iterative liquid impregnation or gas phase carbon deposition routes. In both cases, at the final processing stage the carbon fiber is embedded in carbon matrix which results in unique properties such as low density, high thermal conductivity and thermal shock resistance, low thermal expansion and high modulus, in relation to other refractory materials. In the present study assembled three-directional and four-directional preforms, having 50% volume of pores, were densified by iterative cycles of thermoset resin impregnation followed by pyrolysis under inert atmosphere, until appropriate densities were achieved. The thermoset resin is converted in a carbon matrix during pyrolysis. The iterative manufacturing process of the carbon fiber reinforced carbon composites is evaluated by means of nondestructive techniques based on X-ray computed tomography and electrical resistivity. X-ray computed tomography gives a general mapping view of the filling pores of the preforms which impacts results of the electrical resistivity. After six processing cycles and heat treatments up to 2000?, the final densities of the three-directional and four-directional carbon fiber reinforced carbon composites were 1.16g/cm(3) and an electrical resistivity of approximate to 0.07m. The configuration of preforms, three-directional or four-directional, did not alter the densification profile, in terms of increasing density and reducing porosity during the processing cycles.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.

Die generative Herstellung von Dentalmodellen- eine Rapid Manufacturing Herausforderung

Heutzutage stehen zunehmend – z.B. durch den raschen Fortschritt bei den bildgebenden Verfahren – digitale Datensätze im Dentalbereich zur Verfügung. CAD/CAM-syteme gehören dabei in der Zahntechnik längst zum Stande der Technik. Für die Anwendung derartiger Systeme ist jedoch ein Gipsmodell nötig, welches zum Beginn der Prozesskette vom Zahntechniker mittels eines optischen Scanners digitalisiert wird. Die Weiterentwicklung intraoraler Scanner ermöglicht heutzutage außerdem die Digitalisierung ganzer Kiefer im Patientenmund durch den Zahnarzt. Insbesondere für z.B. die ästhetischen Restaurationen bildet hier das zahntechnische Modell nach wie vor die unersetzliche Arbeitsgrundlage für den Techniker. In der vorliegenden Arbeit wird dazu ein Rapid Manufacturing Verfahren zur Herstellung von Dentalmodellen auf Basis der Stereolithographie vorgestellt. Dabei wird auf die besonderen Anforderungen hinsichtlich Präzision, Robustheit und Wirtschaftlichkeit von generativen Fertigungsverfahren für dentale Applikationen eingegangen und eine neu entwickelte Baustrategie vorgestellt, mittels derer die o.g. Anforderungen erfüllt werden

Super resolution using a modified Spherical Geodesic Waveguide suitable for manufacturing

The previous publications (Miñano et al, 2011) have shown that using a Spherical Geodesic Waveguide (SGW), it can be achieved the super-resolution up to ? /500 close to a set of discrete frequencies. These frequencies are directly connected with the well-known Schumann resonance frequencies of spherical symmetric systems. However, the Spherical Geodesic Waveguide (SGW) has been presented as an ideal system, in which the technological obstacles or manufacturing feasibility and their influence on final results were not taken into account. In order to prove the concept of superresolution experimentally, the Spherical Geodesic Waveguide is modified according to the manufacturing requirements and technological limitations. Each manufacturing process imposes some imperfections which can affect the experimental results. Here, we analyze the influence of the manufacturing limitations on the super-resolution properties of the SGW. Beside the theoretical work, herein, there has been presented the experimental results, as well.

A new paradigm: cloud agile manufacturing

Cloud Agile Manufacturing is a new paradigm proposed in this article. The main objective of Cloud Agile Manufacturing is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

Cloud agile manufacturing

This paper proposes a new manufacturing paradigm, we call Cloud Agile Manufacturing, and whose principal objective is to offer industrial production systems as a service. Thus users can access any functionality available in the cloud of manufacturing (process design, production, management, business integration, factories virtualization, etc.) without knowledge — or at least without having to be experts — in managing the required resources. The proposal takes advantage of many of the benefits that can offer technologies and models like: Business Process Management (BPM), Cloud Computing, Service Oriented Architectures (SOA) and Ontologies. To develop the proposal has been taken as a starting point the Semantic Industrial Machinery as a Service (SIMaaS) proposed in previous work. This proposal facilitates the effective integration of industrial machinery in a computing environment, offering it as a network service. The work also includes an analysis of the benefits and disadvantages of the proposal.

Knowledge acquisition in international strategic alliances among Malaysian manufacturing firms

This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

Evolving forms of manufacturing strategy development:evidence and implications

This paper outlines, using evidence from several case studies, the use of alternative forms of manufacturing strategy processes. Our investigation shows that the manufacturing strategy development practices of manufacturers are evolving in many directions; we found several alternatives to the formal top-down planning process. Manufacturers use one or more of the following alternatives with or without the top-down manufacturing strategy process: a coherent pattern of actions; manufacturing/process improvement programs; or the pursuit of core manufacturing capabilities. It appears that the various manufacturing strategy development processes may be tied to the strategic role of manufacturing in a company. This paper offers a framework that captures the relationship between the strategic role of manufacturing and the process of manufacturing strategy development. An in-depth case from a UK company illustrates the evolving forms of manufacturing strategy development processes.

Capability development in Chinese manufacturing:a quasi-biotic perspective of knowledge evolution

A quasi-biotic model of knowledge evolution has been applied to manufacturing technology capability development which includes product design and development and manufacturing process/workflow improvement. The concepts of “knowledge genes” and “knowledge body” are introduced to explain the evolution of technological capability. It is shown that knowledge development within the enterprise happens as a result of interactions between an enterprise’s internal knowledge and that acquired from external sources catalysed by: (a) internal mechanisms, recources and incentives, and (b) actions and policies of external agencies. A matrix specifying factors contributing to knowledge development and types of manufacturing capabilities (product design, equipment development or use, and workflow) is developed to explain technological knowledge development. The case studies of Tianjin Pipe Corporation (TPCO) and Tianjin Tianduan Press Co. are presented to illustrate the application of the matrix.

Expansion, harvest and cryopreservation of human mesenchymal stem cells in a serum-free microcarrier process

Human mesenchymal stem cell (hMSC) therapies are currently progressing through clinical development, driving the need for consistent, and cost effective manufacturing processes to meet the lot-sizes required for commercial production. The use of animal-derived serum is common in hMSC culture but has many drawbacks such as limited supply, lot-to-lot variability, increased regulatory burden, possibility of pathogen transmission, and reduced scope for process optimization. These constraints may impact the development of a consistent large-scale process and therefore must be addressed. The aim of this work was therefore to run a pilot study in the systematic development of serum-free hMSC manufacturing process. Human bone-marrow derived hMSCs were expanded on fibronectin-coated, non-porous plastic microcarriers in 100mL stirred spinner flasks at a density of 3×10⁵cells.mL^-1 in serum-free medium. The hMSCs were successfully harvested by our recently-developed technique using animal-free enzymatic cell detachment accompanied by agitation followed by filtration to separate the hMSCs from microcarriers, with a post-harvest viability of 99.63±0.03%. The hMSCs were found to be in accordance with the ISCT characterization criteria and maintained hMSC outgrowth and colony-forming potential. The hMSCs were held in suspension post-harvest to simulate a typical pooling time for a scaled expansion process and cryopreserved in a serum-free vehicle solution using a controlled-rate freezing process. Post-thaw viability was 75.8±1.4% with a similar 3h attachment efficiency also observed, indicating successful hMSC recovery, and attachment. This approach therefore demonstrates that once an hMSC line and appropriate medium have been selected for production, multiple unit operations can be integrated to generate an animal component-free hMSC production process from expansion through to cryopreservation.

Research on rework strategies for reconfigurable manufacturing system considering mission reliability

Rework strategies that involve different checking points as well as rework times can be applied into reconfigurable manufacturing system (RMS) with certain constraints, and effective rework strategy can significantly improve the mission reliability of manufacturing process. The mission reliability of process is a measurement of production ability of RMS, which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. To quantitatively characterize the mission reliability and basic reliability of RMS under different rework strategies, rework model of RMS was established based on the method of Logistic regression. Firstly, the functional relationship between capability and work load of manufacturing process was studied through statistically analyzing a large number of historical data obtained in actual machining processes. Secondly, the output, mission reliability and unit cost in different rework paths were calculated and taken as the decision variables based on different input quantities and the rework model mentioned above. Thirdly, optimal rework strategies for different input quantities were determined by calculating the weighted decision values and analyzing advantages and disadvantages of each rework strategy. At last, case application were demonstrated to prove the efficiency of the proposed method.

Research on reliability evaluation of reconfigurable manufacturing system

It is a crucial task to evaluate the reliability of manufacturing process in product development process. Process reliability is a measurement of production ability of reconfigurable manufacturing system (RMS), which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. An integration framework of manufacturing process reliability evaluation is presented together with product development process. A mathematical model and algorithm based on universal generating function (UGF) is developed for calculating the reliability of manufacturing process with respect to task intensity and process capacity, which are both independent random variables. The rework strategies of RMS are analyzed under different task intensity based on process reliability is presented, and the optimization of rework strategies based on process reliability is discussed afterwards.