The deposition process of wire and arc additive manufacturing (WAAM) is usually planned based on a bead geometry model (BGM), which represents the relationship between bead geometries (e.g. width, height) and required deposition parameters. However, the actual deposition situation may deviate from the one in which the BGM is built, such as varied heat dissipation conditions, resulting in morphological changes of deposited beads and geometrical errors in the formed parts. In this paper, a novel control mechanism for enhancing the fabrication accuracy of WAAM based on fuzzy-logic inference is proposed. It considers the geometrical errors measured on already deposited layers and deposition context to adjust deposition parameters of beads in the subsequent layer, forming an interlayer closed-loop control (ICLC) mechanism. This paper not only presents the theoretical fundamentals of the ICLC mechanism but also reports the technical details about utilizing this mechanism to control the forming height of multi-layer multi-bead (MLMB) components. A fuzzy-logic inference machine was applied as the core component for calculating speed change of bead deposition based on height error and previously applied change. In terms of validation, the effectiveness of the proposed control mechanism and the implemented controller was investigated through both simulative studies and real-life experiments. The fabricated cuboid blocks showed good accuracy in height with a maximum error of 0.20 mm. The experimental results implied that the proposed ICLC approach facilitates deposition continuity of WAAM, and thus enables process automation for robotic manufacturing.@en

The deposition process of wire and arc additive manufacturing (WAAM) is usually planned based on a bead geometry model (BGM), which represents the relationship between bead geometries (e.g. width, height) and required deposition parameters. However, the actual deposition situation may deviate from the one in which the BGM is built, such as varied heat dissipation conditions, resulting in morphological changes of deposited beads and geometrical errors in the formed parts. In this paper, a novel control mechanism for enhancing the fabrication accuracy of WAAM based on fuzzy-logic inference is proposed. It considers the geometrical errors measured on already deposited layers and deposition context to adjust deposition parameters of beads in the subsequent layer, forming an interlayer closed-loop control (ICLC) mechanism. This paper not only presents the theoretical fundamentals of the ICLC mechanism but also reports the technical details about utilizing this mechanism to control the forming height of multi-layer multi-bead (MLMB) components. A fuzzy-logic inference machine was applied as the core component for calculating speed change of bead deposition based on height error and previously applied change. In terms of validation, the effectiveness of the proposed control mechanism and the implemented controller was investigated through both simulative studies and real-life experiments. The fabricated cuboid blocks showed good accuracy in height with a maximum error of 0.20 mm. The experimental results implied that the proposed ICLC approach facilitates deposition continuity of WAAM, and thus enables process automation for robotic manufacturing.

An approach to repairing surface defects of metal parts is proposed, which includes a combined application of (i) groove machining, (ii) wire and arc additive manufacturing (WAAM), and (iii) finishing machining. The completed analysis revealed that (i) the inclination angle of the groove to be machined is strongly influenced by the manufacturing parameters of the WAAM process, and (ii) the WAAM process models designed for fabricating parts on a flat substrate are not appropriate for filling grooves. To overcome these issues, this research investigated the range of variation of the proper inclination angle of the groove. A mathematical model was developed to determine the manufacturing parameters of WAAM that result in a proper filling of the groove. The effectiveness of the proposed fundamentals was investigated in a case study. The experimental results showed that using the proposed approach and the chosen manufacturing parameters resulted in a complete filling of the machined groove. The fabrication error of the main part of the repaired region before the finishing machining was less than 0.3 mm, while the ‘buy-to-fly’ ratio of the deposited material was 92.1%. The proposed approach for morphological repair lends itself to a computer-aided automatic part repair process.

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Robotic wire and arc additive manufacturing (WAAM) systems are required to provide predictable and efficient operations to fabricate solid metallic parts with high morphological fidelity and geometric accuracy. Since the metallic parts are fabricated based on a layer-by-layer principle, the interactions between the neighboring beads and layers strongly influence the geometric accuracy of the fabricated part. The layers-overlapping process has been studied and a traditional layers-overlapping model (T-LOM) has been published in the literature. This paper proposes a layers-overlapping strategy (LOS), based on which a revised layers-overlapping model (R-LOM) was proposed for the fabrication of multi-layer multi-bead (MLMB) components with homogeneous layers. A mathematical model for layers-overlapping is presented, which considers the material shortage areas at the edges of the layers. This is important since the material shortage areas result in a situation that the component width is smaller than the expected value. In addition, they will be accumulated when multiple layers are overlapped through normal unidirectional parallel (NUP) paths. The proposed LOS addresses two aspects: (i) the deposition amount of the first bead and the last bead in the lap layers should be increased and (ii) the deposition position of the first bead and the last bead in the lap layers should be moved towards the edges with a given offset distance. Validation experiments were designed and conducted to test the proposed concepts and models. The experimental results indicated that (i) the R-LOM enables the MLMB components to achieve the expected width and (ii) for components deposited with NUP paths, the R-LOM eliminates the effect of accumulation of material shortage areas on the first bead and increases the surface flatness.

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Mathematical modelling of the shape-forming process of multi-layer multi-bead parts dealing with (i) a single layer, (ii) inclination angles and (iii) various slopes, is carried out. In the layers-overlapping model, material shortage areas are generated at the edges of layers. To solve the problem, the deposition amount of beads at the edges of the second and above layers should be modified, in association with the parameters applied to fabricate the slope. Various basic inclined components were deposited to validate the proposed mathematical formulation. Findings from the basic experiments were: (i) depositing additional material to compensate for the material shortage areas is necessary for realizing the designed geometries of the layers, (ii) depositing the bead at the layer edges alongside an already-deposited neighboring bead enables a better shape-forming in the case of negative slopes and (iii) the deposition order of beads in a layer has little influence on the shape formation of positive slopes. A complex part was also fabricated as a case study to validate the model and findings in the real-life context. Practical issues with regard to using the model and the solutions to the issues were discussed.

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Wire and arc additive manufacturing (WAAM) is a competitive technology for fabricating metallic parts with complex structure and geometry. It enables the fabrication of multi-layer multi-bead (MLMB) parts. The basis of planning the deposition paths is the beads overlapping model (BOM). The existing overlapping models consider only the geometric area of adjacent beads, but ignore the spreading of the melted weld beads. The objective of the research was to develop an enhanced BOM (E.BOM) for WAAM, which takes the spreading of the weld beads into consideration. A deposited bead spreads to the already deposited neighboring bead and as a consequence, its center point deviates from the center point of the fed (to be melted) wire. Experiments were designed to explore the relationships between the geometries of the beads, and the offset distance between the center of a weld bead and the center of the fed wire. An artificial neural network was used to predict the offset distance of a certain weld bead based on the results of the experiments. In addition, a reasoning algorithm was implemented to calculate the optimal distance between the centers of adjacent deposition paths in order to achieve a planned center distance between adjacent beads. This enables the control of the actual center distance of the adjacent beads according to an expected value. The E.BOM has been tested by validation experiments. On the one hand, it improves the surface flatness of layers of MLMB parts produced by WAAM. On the other hand, it prevents formation of defects inside the parts.

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There are many real life processes whose smart control requires processing context information. Though the issue of processing varying context information has been addressed in the literature, domain independent solutions that can support reasoning and decision making according to time-varying process scenarios in multiple application fields are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations, and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix. The time-dependent changes in the context information are computed based on a dynamic context information management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. The paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning platform for informing cyber physical systems.@en

Informing cyber-physical systems (I-CPSs) are designed to accomplish sensing, reasoning and informing activities in dynamic context. In order to simplify and accelerate the design and implementation process of multiple context-aware ICPSs, we are developing an information sensing, computing and actuating (SCA) platform that can be used as a central module of these systems. This paper presents the concept of a SCA platform. The functionality of the platform includes development of context-dependent strategies to adapt the sensing, reasoning and informing behaviors of the platform to various dynamic contexts. There are four constituents of the platform: (1) a generic kernel, (2) built-in elements, (3) add-on components, and (4) system interfaces. The paper also discusses both the internal and external integration mechanism of the SCA platform, which can be customized according to the needs of specific I-CPS applications by extending the generic kernel with various functional built-in elements and add-on components. The feasibility and applicability of the platform have been tested through a case study: an indoor fire evacuation guiding system. The proposed platform provides a useful package of functionalities, alleviates the burden of developers, and speeds up the development of applications specific context-aware I-CPS.@en