5 research outputs found

    Simuleringsdriven Utveckling f√∂r √Ėkad Systemtillf√∂rlitlighet

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    The product development process at industrial companies has traditionally focused on hardware-oriented solutions. However, a current trend is to extend business offers to include more service-oriented solutions e.g., functional product business models. A functional product typically includes the four main constituent‚Äôs hardware, software, service support system and management of operation. Availability is one critical property for functional product businesses which the customer and provider must agree upon. Hence, performing simulations for functional product development and operation enables the possibility for functional product availability prediction andincreases the possibilities for business offerings. Functional product availability is a function of reliability and maintainability. Today, many companies measure the strength of the hardware product in terms of durability or life length. However,measuring strength in terms of reliability, which is based on a statistically significant basis, supports the functional product development process. Simulations have generally been used to verify existing solutions; therefore, simulation-driven design strategies have been proposed to more rapidly converge on optimal solutions i.e., simulations are used to drive the development rather than simply verify suggested solutions.Today, measured data or estimated data are often used as input to reliabilityprediction methods e.g., fault tree analysis or Bayesian network. When designing new hardware systems, concepts need to be evaluated by means of reliability, but such data may not exist and prototypes often need to be manufactured, which is expensive and time-consuming. A combination of deterministic and probabilistic simulations can be used to derive needed input data for reliability prediction methods i.e., concepts can be evaluated by means of reliability in early stages of the functional product development process, even before a physical prototype is manufactured. The objective of the work presented in this thesis is to develop a simulation-drivenreliability prediction methodology for product development processes.This methodology shall be applied in early phases of existing product development processes, especially to generate, evaluate and select concepts in terms of reliability, to be used as a decision basis for systems solutions. Further, this methodology takes important variations into account and includes a combination of deterministic and probabilistic simulations.The conducted research is based on theories regarding the functional productdevelopment process, product development methodologies (e.g., stage-gated process), reliability prediction methods (e.g., fault tree analysis), deterministic simulation methods (e.g. rigid body dynamics) and reliability engineering (e.g., probability and reliability theory, distribution functions and Monte Carlo method). The research presented in this thesis followed a 5-step procedure including as-is study, to-be scenario development (simulation-driven methodology and a future functional business situation are described), methodology development, methodology verification (through case studies) and methodology validation (through system testing).Existing reliability methods were evaluated according to suitability in differentdevelopment phases during the as-is study. Fault tree analysis and probabilistic variation mode and effect analysis were found to give accurate results due to use of objective input data. It can be concluded that deterministic simulations (such as rigid body dynamics or welding sequences) can be used to derive input data to be used for probabilistic reliability prediction methods. Probabilistic variation mode and effect analysis can be used to derive a safety factor when designing systems, based on components variation contribution. Hence, a method has been developed based on probabilistic variation mode and effect analysis to derive system reliability. The method uses a distribution function (Normal distribution) and the variation contribution from included components. A method based on deterministic simulations to derive component reliability information has further been developed. This method takes different variations intoaccount and through a series of simulations, input data for system reliability (such as fault tree analysis and Bayesian network) can be derived.A simulation-driven hardware system reliability prediction methodology wasdeveloped, including both deterministic and probabilistic simulation models and methods. The methodology is used to predict hardware system reliability in early phases of the functional product development process and to partly exclude hardware system testing. The methodology takes into account component variations when a limited amount of information exists. The simulation-driven methodology will further be implemented in the company product development process. A case scenario was developed for the simulation-driven mobility function methodology. The methodology manages an increased amount of multidisciplinary interactions to combine deterministic and probabilistic simulation, both in parallel and coupled, within and between the four main constituents. The simulation-driven methodology is primarily focused on mobility functions but is more general and canpartly be used in the simulation-driven methodology for hardware system reliability prediction.Godk√§nd; 2015; 20151021 (jonpav); Nedanst√•ende person kommer att disputera f√∂r avl√§ggande av teknologie doktorsexamen. Namn: Jonas Pavasson √Ąmne: Datorst√∂dd maskinkonstruktion/Computer Aided Design Avhandling: Simulation-Driven Development for Increased System Reliability Opponent: Docent Lars Drugge, Institutionen f√∂r farkost och flyg, Skolan f√∂r teknikvetenskap, KTH, Stockholm Ordf√∂rande: Bitr professor Magnus Karlberg, Avd f√∂r produkt- och produktionsutveckling, Institutionen f√∂r teknikvetenskap och matematik, Lule√• tekniska universitet, Lule√• Tid: Fredag 18 december kl 09.00 Plats: E632, Lule√• tekniska universite

    Tillförlitlighetsprediktering i tidiga faser av Funktionell Produktutveckling

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    A trend among industrial companies is to change business strategies from hardware-oriented to more service-oriented solutions, e.g. functional product business models. Functional products are typically constituted by hardware together with a service support system. For functional product businesses, availability is one critical property upon which the customer and provider must agree. Hence, during functional product development and operation, it is important to enable simulations of functional product availability, which is a function of reliability and maintainability. To more rapidly converge on optimal solutions, simulation-driven design strategies have further been proposed by several researchers. In these strategies, the simulations are used to drive the development rather than simply verify suggested solutions. Measured data or estimated data are often used as input to reliability prediction methods such as fault tree analysis and failure mode and effect analysis. However, when designing new systems, reliability input data may not exist and, hence, prototypes are often manufactured and tested, which requires a significant amount of time.The objective of the work presented in this thesis is to develop a simulation-driven methodology for how to predict hardware reliability, as a part of functional product availability.This methodology shall be applied at early concept stages of the functional product development process, where limited component reliability information exists.The conducted research is based on theories regarding product development methodologies, reliability prediction methods and deterministic simulation methods (e.g. rigid body dynamics). The research presented in this thesis followed a 5-step procedure including as-is study, to-be scenario development (where a future functional business situation is described), method development, method verification (through case studies) and method validation.During the as-is study, existing reliability methods were evaluated according tosuitability in different development stages. Fault tree analysis and probabilistic variation mode and effect analysis were found to give accurate results (since objective input data are used). However, those methods would need further development in order to be used for reliability prediction at early concept stages. Traditional probabilistic variation mode and effect analysis did not result in reliability in terms of a probabilistic quantity. Therefore, the probabilistic variation mode and effect analysis method was further developed and verified through a case study which can be used for probabilistic measures.A method based on deterministic simulations to derive component reliabilityinformation has been further developed. This method takes different variations into account and through a series of simulations, input data for system reliability (such as fault tree analysis and probabilistic variation mode and effect analysis) can be derived.Hence, by combining deterministic and probabilistic simulations, hardware system reliability can be predicted, even when limited component reliability information exists. This hardware reliability prediction method is a critical part of a simulation-driven methodology to be used at early stages of functional product developmentGodk√§nd; 2012; 20120926 (jonpav); LICENTIATSEMINARIUM √Ąmne: Datorst√∂dd maskinkonstruktion/Computer Aided Design Examinator: Docent Magnus Karlberg, Institutionen f√∂r teknikvetenskap och matematik, Lule√• tekniska universitet Diskutant: Doktor Rikard M√§ki, Volvo Construction Equipment AB, Technical Center, Eskilstuna Tid: Fredag den 21 december 2012 kl 09.00 Plats: E231, Lule√• tekniska universitetFastelaboratoriet - VINNEX

    A new welding modeling approach in simulation driven design

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    This thesis is a part of a larger project involving the Faste Laboratory at Luleå University of Technology and the Wingquist Laboratory at Chalmers University of Technology. The interaction between simulation driven design and variation simulations is the main focus of this project. Computational welding mechanics has been developed during the last 30 years and can today be used to predict the outcome of real welding processes e.g. deformations and residual stresses. Hence, these types of simulations are starting to be used as a part of the product development process. The aim is to show that it is possible to perform simulation driven design on welded products in such a way that traditional physical testing can be reduced or even excluded. This thesis was divided into two parts. The aim of the first part was to show that VrWeld, a welding simulation software developed by Goldak Technologies, can perform accurate welding simulations and provide reliable results. This is done by running NeT’s Round Robin Benchmark which consists of a single weld bead on a stainless steel plate. The results from VrWeld were compared to simulation results and residual stress measurements from other Round Robin participants. The second part of the thesis is a case study of a rear axle bridge from a Volvo wheel loader. The deformations caused by welding during manufacturing were measured and compared with simulation results. An alternative welding sequence was simulated to show the possibilities of including these simulations in a simulation driven design process. The results show that it is possible to perform welding simulations in VrWeld for both residual stress analyses and deformation analyses, with the same or better accuracy as other simulation softwares. The results also indicate good opportunities to implement such simulation tools in a simulation driven design process.Validerat; 20101217 (root

    System reliability estimation with input data from deterministic simulations

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    The possibility of estimating reliability of hardware, both for components and systems, is important in engineering design, since many failures result in substantial impact on safety or functional requirements. Existing reliability estimation methods require measured or estimated input data which can be difficult to retrieve. The objective of this paper is therefore to derive a simulation-driven method, including variation management, for combining deterministic simulations with Fault Tree Analysis, to estimate system reliability when measured data is not available. The research work started with a literature survey followed by description of a typical as-is situation and definition of a to-be scenario. Then, a simulation-driven method was derived and verified by a case study. In particular, the system used for the case study was modeled and simulated as a transient dynamical system to derive information about loads on components. It was found that deterministic simulations can be used to produce relevant input data for fault tree analysis. The derived simulation-driven system reliability estimation method includes variation management and can be used for evaluation of concepts in the early stages of product development when limited measurement data is availableGodkänd; 2012; 20130117 (ysko)Fastelaboratoriet - VINNEX

    A method to improve efficiency in welding simulations for simulaton driven design

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    Welding is one of the most commonly used methods of joining metal pieces. In product development it is often desirable to predict residual stresses and distortions to verify that e.g., alignment tolerances, strength demands, fatigue requirements, stress corrosion cracking, etc. are fulfilled. The objective of this paper is to derive a strategy to improve the efficiency of welding simulations aiming at a (future) simulation-driven design methodology. In this paper, a weld bead deposition technique called block dumping has been applied to improve the efficiency. The proposed strategy is divided into seven steps, where the first four steps are verified by two welding simulation cases (a benchmark problem for a single weld bead-on-plate specimen and a T-welded structure). This study shows that by use of the block dumping technique, the computation time can be reduced by as much as 93% compared to moving heat source, still with acceptable accuracy of the model.Godkänd; 2010; 20101029 (andpah)Fastelaboratoriet - VINNEX
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