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.

The product development process at industrial companies has traditionally focused on hardware-oriented solutions. Business strategies strive towards more service-oriented solutions e.g., functional product business models. In this paper two case studies are developed and the objective is to highlight important challenges and opportunities by implementing a simulation-driven strategy in functional product development and operation. It can be concluded that challenges and opportunities within simulation-driven functional product development and operation are related to both quality and management of the simulations. With the proposed strategies for validation and coupling of the simulations, some of the challenges within functional product development can be overcome.

Engineering product development has developed considerably over the past decade. In order for industry to keep up with continuously changing requirements, it is necessary to develop new and innovative simulation methods. However, few tools and methods for simulation-driven design have been applied in industrial settings and proven to actually drive the development and selection of the ideal solution. Such tools, based on fundamental equations, are the focus of this paper.In this paper the work is based on two cases of mechanics of materials and structures: welding and rotor dynamical simulations. These two examples of simulation-driven design indicate that a larger design space can be explored and that more possible solutions can be evaluated. Therefore, the approach improves the probability of innovations and finding optimal solutions.A calibrated block dumping approach can be used to increase the efficiency of welding simulations when many simulations are required.

The possibility of predicting the reliability of hardware for both components and systems is important in engineering design. Today, there are several methods for predicting the reliability of hardware systems and for identifying the causes of failure and failure modes, for example, fault tree analysis and failure mode and effect analysis.Many failures are caused by variations resulting in a substantial effect on safety or functional requirements. To identify, to assess and to manage unwanted sources of variation, a method called probabilistic variation mode and effect analysis (VMEA) has been developed. With a prescribed reliability, VMEA can be used to derive safety factors in different applications. However, there are few reports on how to derive the reliability based on probabilistic VMEA, especially for transmission clutch shafts.Hence, the objective of this article was to show how to derive system reliability based on probabilistic VMEA. In particular, wheel loader automatic transmission clutch shaft reliability is investigated to show how different sources of variation affect reliability.In this article, a new method for predicting system reliability based on probabilistic VMEA is proposed. The method is further verified by a case study on a clutch shaft. It is shown that the reliability of the clutch shaft was close to 1.0 and that the most significant variation contribution was due to mean radius of the friction surface and friction of the disc.

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