26 resultados para Manufacturing Execution Systems


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Outsourcing is a common strategy for companies looking for cost savings and improvements in performance. This has been especially prevalent in logistics, where warehousing and transporting are typical targets for outsourcing. However, while the benefits from logistics outsourcing are clear on paper, there are several cases companies fail to reach these benefits. The most commonly cited reasons for this are poor information flow between the company and the third party logistics partner, and a lack of integration between the two partners. Uncertainty stems from lack of information, and it can cripple the whole outsourcing operation. This is where enterprise resource planning (ERP) systems step in, as they can have a significant role in improving the flow of information, and integration, which consequently mitigates uncertainty. The purpose of the study is to examine if ERP systems have an effect on a company's decision to outsource logistics operations. Along the rapid advancements in technology during the past decades, ERP systems have also evolved. Therefore, empirical research on the subject needs constant revision as it can quickly become outdated due to ERP systems having more advanced capabilities every year. The research was conducted using a qualitative single-case study of a Finnish manufacturing firm that had outsourced warehousing and transportation operations in the Swedish market. The empirical data was gathered with use of semi-structured interviews with three employees from the case company that were closely related to the outsourcing operation. The theoretical framework that was used to analyze the empirical data was based on Transaction Cost Economics theory. The results of the study were align with the theoretical framework, in that the ERP system of the case company was seen as an enabler for their logistics outsourcing operation. However, the full theoretical benefits from ERP systems concerning extended enterprise functionality and flexibility were not attained due to the case company having an older version of their ERP system. This emphasizes the importance of having up-to-date technology if you want to overcome the shortcomings of ERP systems in outsourcing situations.

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This study will concentrate on Product Data Management (PDM) systems, and sheet metal design features and classification. In this thesis, PDM is seen as an individual system which handles all product-related data and information. The meaning of relevant data is to take the manufacturing process further with fewer errors. The features of sheet metals are giving more information and value to the designed models. The possibility of implementing PDM and sheet metal features recognition are the core of this study. Their integration should make the design process faster and manufacturing-friendly products easier to design. The triangulation method is the basis for this research. The sections of this triangle are: scientific literature review, interview using the Delphi method and the authors experience and observations. The main key findings of this study are: (1) the area of focus in triangle (the triangle of three different point of views: business, information exchange and technical) depends on the persons background and their role in the company, (2) the classification in the PDM system (and also in the CAD system) should be done using the materials, tools and machines that are in use in the company and (3) the design process has to be more effective because of the increase of industrial production, sheet metal blank production and the designers time spent on actual design and (4) because Design For Manufacture (DFM) integration can be done with CAD-programs, DFM integration with the PDM system should also be possible.

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The objective of this research is to demonstrate the use of Lean Six Sigma methodology in a manufacturing lead time improvement project. Moreover, the goal is to develop working solutions for the target company to improve its manufacturing lead time. The theoretical background is achieved through exploring the literature of Six Sigma, Lean and Lean Six Sigma. The development will be done in collaboration with the related stakeholders, by following the Lean Six Sigma improvement process DMAIC and by analyzing the process data from the target company. The focus of this research is in demonstrating how to use Lean Six Sigma improvement process DMAIC in practice, rather than in comparing Lean Six Sigma to other improvement methodologies. In order to validate the manufacturing systems current state, improvement potential and solutions, statistical tools such as linear regression analysis were used. This ensured that all the decisions were as heavily based on actual data as possible. As a result of this research, a set of solutions were developed and implemented in the target company. These solutions included batch size reduction, bottleneck shift, first-in first-out queuing and shifting a data entry task from production planners to line workers. With the use of these solutions, the target company was able to reduce its manufacturing lead time by over one third.

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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).

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Due to various advantages such as flexibility, scalability and updatability, software intensive systems are increasingly embedded in everyday life. The constantly growing number of functions executed by these systems requires a high level of performance from the underlying platform. The main approach to incrementing performance has been the increase of operating frequency of a chip. However, this has led to the problem of power dissipation, which has shifted the focus of research to parallel and distributed computing. Parallel many-core platforms can provide the required level of computational power along with low power consumption. On the one hand, this enables parallel execution of highly intensive applications. With their computational power, these platforms are likely to be used in various application domains: from home use electronics (e.g., video processing) to complex critical control systems. On the other hand, the utilization of the resources has to be efficient in terms of performance and power consumption. However, the high level of on-chip integration results in the increase of the probability of various faults and creation of hotspots leading to thermal problems. Additionally, radiation, which is frequent in space but becomes an issue also at the ground level, can cause transient faults. This can eventually induce a faulty execution of applications. Therefore, it is crucial to develop methods that enable efficient as well as resilient execution of applications. The main objective of the thesis is to propose an approach to design agentbased systems for many-core platforms in a rigorous manner. When designing such a system, we explore and integrate various dynamic reconfiguration mechanisms into agents functionality. The use of these mechanisms enhances resilience of the underlying platform whilst maintaining performance at an acceptable level. The design of the system proceeds according to a formal refinement approach which allows us to ensure correct behaviour of the system with respect to postulated properties. To enable analysis of the proposed system in terms of area overhead as well as performance, we explore an approach, where the developed rigorous models are transformed into a high-level implementation language. Specifically, we investigate methods for deriving fault-free implementations from these models into, e.g., a hardware description language, namely VHDL.

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Since cellulose is a linear macromolecule it can be used as a material for regenerated cellulose fiber products e.g. in textile fibers or film manufacturing. Cellulose is not thermoformable, thus the manufacturing of these regenerated fibers is mainly possible through dissolution processes preceding the regeneration process. However, the dissolution of cellulose in common solvents is hindered due to inter- and intra-molecular hydrogen bonds in the cellulose chains, and relatively high crystallinity. Interestingly at subzero temperatures relatively dilute sodium hydroxide solutions can be used to dissolve cellulose to a certain extent. The objective of this work was to investigate the possible factors that govern the solubility of cellulose in aqueous NaOH and the solution stability. Cellulose-NaOH solutions have the tendency to form a gel over time and at elevated temperature, which creates challenges for further processing. The main target of this work was to achieve high solubility of cellulose in aqueous NaOH without excessively compromising the solution stability. In the literature survey an overview of the cellulose dissolution is given and possible factors contributing to the solubility and solution properties of cellulose in aqueous NaOH are reviewed. Furthermore, the concept of solution rheology is discussed. In the experimental part the focus was on the characterization of the used materials and properties of the prepared solutions mainly concentrating on cellulose solubility and solution stability.

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In recent years, technological advancements in microelectronics and sensor technologies have revolutionized the field of electrical engineering. New manufacturing techniques have enabled a higher level of integration that has combined sensors and electronics into compact and inexpensive systems. Previously, the challenge in measurements was to understand the operation of the electronics and sensors, but this has now changed. Nowadays, the challenge in measurement instrumentation lies in mastering the whole system, not just the electronics. To address this issue, this doctoral dissertation studies whether it would be beneficial to consider a measurement system as a whole from the physical phenomena to the digital recording device, where each piece of the measurement system affects the system performance, rather than as a system consisting of small independent parts such as a sensor or an amplifier that could be designed separately. The objective of this doctoral dissertation is to describe in depth the development of the measurement system taking into account the challenges caused by the electrical and mechanical requirements and the measurement environment. The work is done as an empirical case study in two example applications that are both intended for scientific studies. The cases are a light sensitive biological sensor used in imaging and a gas electron multiplier detector for particle physics. The study showed that in these two cases there were a number of different parts of the measurement system that interacted with each other. Without considering these interactions, the reliability of the measurement may be compromised, which may lead to wrong conclusions about the measurement. For this reason it is beneficial to conceptualize the measurement system as a whole from the physical phenomena to the digital recording device where each piece of the measurement system affects the system performance. The results work as examples of how a measurement system can be successfully constructed to support a study of sensors and electronics.

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Many-core systems provide a great potential in application performance with the massively parallel structure. Such systems are currently being integrated into most parts of daily life from high-end server farms to desktop systems, laptops and mobile devices. Yet, these systems are facing increasing challenges such as high temperature causing physical damage, high electrical bills both for servers and individual users, unpleasant noise levels due to active cooling and unrealistic battery drainage in mobile devices; factors caused directly by poor energy efficiency. Power management has traditionally been an area of research providing hardware solutions or runtime power management in the operating system in form of frequency governors. Energy awareness in application software is currently non-existent. This means that applications are not involved in the power management decisions, nor does any interface between the applications and the runtime system to provide such facilities exist. Power management in the operating system is therefore performed purely based on indirect implications of software execution, usually referred to as the workload. It often results in over-allocation of resources, hence power waste. This thesis discusses power management strategies in many-core systems in the form of increasing application software awareness of energy efficiency. The presented approach allows meta-data descriptions in the applications and is manifested in two design recommendations: 1) Energy-aware mapping 2) Energy-aware execution which allow the applications to directly influence the power management decisions. The recommendations eliminate over-allocation of resources and increase the energy efficiency of the computing system. Both recommendations are fully supported in a provided interface in combination with a novel power management runtime system called Bricktop. The work presented in this thesis allows both new- and legacy software to execute with the most energy efficient mapping on a many-core CPU and with the most energy efficient performance level. A set of case study examples demonstrate realworld energy savings in a wide range of applications without performance degradation.

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Finnish design and consulting companies are delivering robust and cost-efficient steel structures solutions to a large number of manufacturing companies worldwide. Recently introduced EN 1090-2 standard obliges these companies to specify the execution class of steel structures for their customers. This however, requires clarifying, understanding and interpreting the sophisticated procedure of execution class assignment. The objective of this research is to provide a clear explanation and guidance through the process of execution class assignment for a given steel structure and to support the implementation of EN 1090-2 standard in Rejlers Oy, one of Finnish design and consulting companies. This objective is accomplished by creating a guideline for designers that elaborates on the four-step process of the execution class assignment for a steel structure or its part. Steps one to three define the consequence class (projected consequences of structure failure), the service category (hazards associated with the service use exploitation of steel structure) and the production category (manufacturing process peculiarities), based on the ductility class (capacity of structure to withstand deformations) and the behaviour factor (corresponds to structure seismic behaviour). The final step is the execution class assignment taking into account results of previous steps. Main research method is indepth literature review of European standards family for steel structures. Other research approach is a series of interviews of Rejlers Oy representatives and its clients, results of which have been used to evaluate the level of EN 1090-2 awareness. Rejlers Oy will use the developed novel coherent standard implementation guideline to improve its services and to obtain greater customer satisfaction.

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Product Data Management (PDM) systems have been utilized within companies since the 1980s. Mainly the PDM systems have been used by large companies. This thesis presents the premise that small and medium-sized companies can also benefit from utilizing the Product Data Management systems. Furthermore, the starting point for the thesis is that the existing PDM systems are either too expensive or do not properly respond to the requirements SMEs have. The aim of this study is to investigate what kinds of requirements and special features SMEs, operating in Finnish manufacturing industry, have towards Product Data Management. Additionally, the target is to create a conceptual model that could fulfill the specified requirements. The research has been carried out as a qualitative case study, in which the research data was collected from ten Finnish companies operating in manufacturing industry. The research data is formed by interviewing key personnel from the case companies. After this, the data formed from the interviews has been processed to comprise a generic set of information system requirements and the information system concept supporting it. The commercialization of the concept is studied in the thesis from the perspective of system development. The aim was to create a conceptual model, which would be economically feasible for both, a company utilizing the system and for a company developing it. For this reason, the thesis has sought ways to scale the system development effort for multiple simultaneous cases. The main methods found were to utilize platform-based thinking and a way to generalize the system requirements, or in other words abstracting the requirements of an information system. The results of the research highlight the special features Finnish manufacturing SMEs have towards PDM. The most significant of the special features is the usage of project model to manage the order-to-delivery process. This differs significantly from the traditional concepts of Product Data Management presented in the literature. Furthermore, as a research result, this thesis presents a conceptual model of a PDM system, which would be viable for the case companies interviewed during the research. As a by-product, this research presents a synthesized model, found from the literature, to abstract information system requirements. In addition to this, the strategic importance and categorization of information systems within companies has been discussed from the perspective of information system customizations.

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Manufacturing companies have passed from selling uniquely tangible products to adopting a service-oriented approach to generate steady and continuous revenue streams. Nowadays, equipment and machine manufacturers possess technologies to track and analyze product-related data for obtaining relevant information from customers use towards the product after it is sold. The Internet of Things on Industrial environments will allow manufacturers to leverage lifecycle product traceability for innovating towards an information-driven services approach, commonly referred as Smart Services, for achieving improvements in support, maintenance and usage processes. The aim of this study is to conduct a literature review and empirical analysis to present a framework that describes a customer-oriented approach for developing information-driven services leveraged by the Internet of Things in manufacturing companies. The empirical study employed tools for the assessment of customer needs for analyzing the case company in terms of information requirements and digital needs. The literature review supported the empirical analysis with a deep research on product lifecycle traceability and digitalization of product-related services within manufacturing value chains. As well as the role of simulation-based technologies on supporting the Smart Service development process. The results obtained from the case company analysis show that the customers mainly demand information that allow them to monitor machine conditions, machine behavior on different geographical conditions, machine-implement interactions, and resource and energy consumption. Put simply, information outputs that allow them to increase machine productivity for maximizing yields, save time and optimize resources in the most sustainable way. Based on customer needs assessment, this study presents a framework to describe the initial phases of a Smart Service development process, considering the requirements of Smart Engineering methodologies.