Energy and raw material consumption analysis of powder bed fusion: case study: CNC machining and laser additive manufacturing

Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

Press forming of paperboard – advancement of converting tools and process control

Press forming is nowadays one of the most common industrial methods in use for producing deeper trays from paperboard. Demands for material properties like recyclability and sustainability have increased also in the packaging industry, but there are still limitations related to the formability of paperboard. A majority of recent studies have focused on material development, but the potential of the package manufacturing process can also be improved by the development of tooling and process control. In this study, advanced converting tools (die cutting tools and the press forming mould) are created for production scale paperboard tray manufacturing. Also monitoring methods that enable the production of paperboard trays with enhanced quality, and can be utilized in process control are developed. The principles for tray blank preparation, including creasing pattern and die cutting tool design are introduced. The mould heating arrangement and determination of mould clearance are investigated to improve the quality of the press formed trays. The effect of the spring back of the tray walls on the tray dimensions can be managed by adjusting the heat-related process parameters and estimating it at the mould design stage. This enables production speed optimization as the process parameters can be adjusted more freely. Real-time monitoring of pressing force by using multiple force sensors embedded in the mould structure can be utilized in the evaluation of material characteristics on a modified production machinery. Comprehensive process control can be achieved with a combination of measurement of the outer dimensions of the trays and pressing force monitoring. The control method enables detection of defects and tracking changes in the material properties. The optimized converting tools provide a basis for effective operation of the control system.

Monitoring Directed Energy Deposition Processes in Additive Manufacturing

The purpose of this study is to find out how laser based Directed Energy Deposition processes can benefit from different types of monitoring. DED is a type of additive manufacturing process, where parts are manufactured in layers by using metallic powder or metallic wire. DED processes can be used to manufacture parts that are not possible to manufacture with conventional manufacturing processes, when adding new geometries to existing parts or when wanting to minimize the scrap material that would result from machining the part. The aim of this study is to find out why laser based DED-processes are monitored, how they are monitored and what devices are used for monitoring. This study has been done in the form of a literature review. During the manufacturing process, the DED-process is highly sensitive to different disturbances such as fluctuations in laser absorption, powder feed rate, temperature, humidity or the reflectivity of the melt pool. These fluctuations can cause fluctuations in the size of the melt pool or its temperature. The variations in the size of the melt pool have an effect on the thickness of individual layers, which have a direct impact on the final surface quality and dimensional accuracy of the parts. By collecting data from these fluctuations and adjusting the laser power in real-time, the size of the melt pool and its temperature can be kept within a specified range that leads to significant improvements in the manufacturing quality. The main areas of monitoring can be divided into the monitoring of the powder feed rate, the temperature of the melt pool, the height of the melt pool and the geometry of the melt pool. Monitoring the powder feed rate is important when depositing different material compositions. Monitoring the temperature of the melt pool can give information about the microstructure and mechanical properties of the part. Monitoring the height and the geometry of the melt pool is an important factor in achieving the desired dimensional accuracy of the part. By combining multiple different monitoring devices, the amount of fluctuations that can be controlled will be increased. In addition, by combining additive manufacturing with machining, the benefits of both processes could be utilized.

Assessment of virtual design and manufacturing techniques for fibre reinforced composite materials

Virtual tools are commonly used nowadays to optimize product design and manufacturing process of fibre reinforced composite materials. The present work focuses on two areas of interest to forecast the part performance and the production process particularities. The first part proposes a multi-physical optimization tool to support the concept stage of a composite part. The strategy is based on the strategic handling of information and, through a single control parameter, is able to evaluate the effects of design variations throughout all these steps in parallel. The second part targets the resin infusion process and the impact of thermal effects. The numerical and experimental approach allowed the identificationof improvement opportunities regarding the implementation of algorithms in commercially available simulation software.

Cluster analysis for multivariable process control

This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.

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.