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The critical role that numerical simulation plays in additive manufacturing has stimulated research on the effectiveness and potential applications of mesh-free, particle-based discretisation techniques. These methods excel at handling fluid flows and are viable alternatives to the mesh-based techniques typically used in commercial simulation software. In this paper, we review recent advances in developing computational models for metal additive manufacturing (MAM) processes using particle methods, in the theoretical understanding of the fundamental mechanisms that control such processes at the powder (or melt pool) scale, and in the predictability of physics-based modelling approaches. The paper explores the applicability and performance of particle-based methods in simulating powder bed fusion, directed energy deposition, and binder jetting processes. Since the progress of MAM relies on systematic material-process-structure realisations which are often impossible to sense or observe experimentally, developing efficient particle-based and multiscale simulation tools can be essential to achieving this objective through in-situ process control and optimisation. [ABSTRACT FROM AUTHOR]

We present a model that deals with continuous space and functional regions in the form of overlapping, interacting, and constantly changing contact fields associated with the individual actors in a labor market. Simulations illustrate the results of the model, presenting individual histories of firms and workers. The model demonstrates the importance of the relative location of the firm and the employee in terms of the effort needed to construct functional contact fields. Firms and workers located at either the boundary of the region or in isolated interior positions endure two locational effects: the reduced ability to gather information and to recruit workers due to a truncated or low-density contact field. In addition to locational effects, acquired skill levels and accumulated tenure with a firm influence the behavior of the workers. Also each firm adopts a production process that reflects a desired level of profit obtainable from a specific class of labor. Firm behavior is assumed to be a function of stress arising in response to a perceived suboptimal profit position relative to other firms. The aggregation of the individual histories of many firms and workers is used to describe the macro-scale evolution of the spatial pattern of functional contact fields and adopted production processes. The paper concludes with a discussion of the model's limitations and suggested directions for further development. [ABSTRACT FROM AUTHOR]

Many modern industrial processes are capable of generating rich and complex data records that do not readily permit the use of traditional statistical process-control techniques. For example, a "single observation" from a process might consist of n pairs of (x, y) data that can be described as y = f(x) when the process is in control. Such data structures or relationships between y and x are called profiles. Examples of profiles include calibration curves in chemical processing, oxide thickness across wafer surfaces in semiconductor manufacturing, and radar signals of military targets. In this paper, a semiparametric wavelet method is proposed for monitoring for changes in sequences of nonlinear profiles. Based on a likelihood ratio test involving a changepoint model, the method uses the spatial-adaptivity properties of wavelets to accurately detect profile changes taking nearly limitless functional forms. The method is used to differentiate between different radar profiles and its performance is assessed with Monte Carlo simulation. The results presented indicate the method can quickly detect a wide variety of changes from a given, in-control profile. [ABSTRACT FROM AUTHOR]

OVERVIEW: Every new product development (NPD) team learns a unique set of lessons in solving the many problems that arise in a typical project, and it is important to ensure that these lessons are shared. Since much of the learning is tacit in nature, it is difficult to articulate, to capture, and to disseminate. Therefore, managers face a Challenge in trying to stimulate project-to-project learning. Many companies hold post-project reviews (PPRs)--meetings at the end of projects to determine the lessons learned and document them for the future. However, discussing a project, noting down the lessons learned, and entering them into a database is not sufficient. Our research at five leading German companies shows that written reports fail to convey much of the key learning from NPD teams and so managers need to focus on stimulating individual learning and running PPRs in specific ways to generate and transfer tacit knowledge. Managers also need to integrate PPRs with other mechanisms, such as mentoring schemes and knowledge brokering, to stimulate the flow of lessons learned and tacit knowledge. [ABSTRACT FROM AUTHOR]