Showing papers in "CIRP Annals in 2019"

TL;DR: An overview of symbiotic human-robot collaborative assembly is provided and future research directions for voice processing, gesture recognition, haptic interaction, and brainwave perception are highlighted.

TL;DR: Error separation algorithms for removing machine tool errors, which is specially required in on-machine and in-process surface metrology, are overviewed, followed by a discussion on calibration and traceability.

TL;DR: The effectiveness of the machine learning method for on-line detection of defects due to process non-conformities, providing the basis for adaptive SLM process control and part quality assurance is confirmed.

TL;DR: The current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control are dealt with.

TL;DR: In this article, an object-oriented event-driven simulation as a digital twin of a flexible assembly cell coordinated with a robot to perform assembly tasks alongside human is presented, and validated with an industrial case study involving dexterous assembly tasks.

TL;DR: The infrastructure under development for specification standards in AM is presented, and the research on geometrical dimensioning and tolerancing for AM is reviewed, and post-process metrology is covered, including the measurement of surface form, texture and internal features.

TL;DR: Using the test environment of smart factory cells, methodological, technological, operative, and business aspects of developing and operating Digital Twins are investigated and design elements for the development of Digital Twin are derived and presented.

TL;DR: A framework for designing and operating GPNs is introduced, which structures influencing factors, challenges, enablers and outlines the need for decision support systems.

TL;DR: This paper reviews the status and trends of these emerging development technologies such as model-based systems engineering and digital twin as well as software-intensive, data-driven, and service-conscious smart products.

TL;DR: A systematic review of recent advancements related to tooling performance and functionalities, including tool materials, tooling fabrication processes, sensing, and data analytics, including machining, heat treatment, coating, surface texturing, and additive manufacturing are provided.

TL;DR: A novel method for accurately predicting tool wear under varying cutting conditions based on a proposed new meta-learning model which can be easily trained, updated and adapted to new machining tasks of different cutting conditions is presented.

TL;DR: A genetic algorithm is proposed to approach the Assembly Line Balancing Problem (ALBP) in the case of human-robot collaborative work to minimization the assembly line cost.

TL;DR: A data mining approach for predicting different quality parameters of battery cells based on extensive data acquisition over the whole process chain can be used to improve the planning and control of battery production.

TL;DR: An overview on the common classification and characterization of modelling and models in metal forming, as well as a model selection procedure are given and various relevant process limits for metal forming are investigated regarding existing models.

TL;DR: In this paper, an infrared-based set-up is presented to record spatial and temporal variations during printing of an FFF part, with a field of view of 21.7 × 14.9 × 30.2 µm.

TL;DR: In this article, a method to estimate the cutting forces and vibrations at the milling tool from accelerometers mounted on the spindle housing is presented, where the distortion of signal transmission from tool to the accelerometer location is compensated with a Kalman filter.

TL;DR: In this article, the authors present a review of various materials which the medical industry needs to machine, then comments on the advances in the understanding of their specific cutting mechanisms, and highlight the specific functional requirements that need to be considered when machining biocompatible materials and the associated machines and tooling.

TL;DR: This paper presents a new approach to develop digital twins of helicopter dynamic systems using a multibody dynamic formalism, including a new model of bearing and its validation based on bench tests.

TL;DR: In this article, a comparative analysis of the heat transfer rate was made utilizing cooling of a controlled heat source with an integrated temperature sensor, coupled with experimental in-process temperature measurements in cryogenic milling of titanium alloy Ti-6Al-4V (s).

TL;DR: A new optimization method using design of experiment and surrogate model to configure lattice structures in specified 3D hulls to gain both mass and computation efficiency for structure design is proposed.

TL;DR: A hybrid machine learning method is presented that integrates heterogeneous data (structured process parameters and unstructured power profiles and tool wear images) for tool condition prognosis and is validated in milling of H13 steel and Inconel 718.

TL;DR: In this article, the uncertainty of CT surface topography measurements was investigated on Ti6Al4V reference samples fabricated by laser powder bed fusion to improve the understanding of CT-based surface texture characterisation, including the use of new generalised surface texture parameters suited for AM surfaces.

TL;DR: A new method for handling manufacturing and geometrical requirements in the framework of a general Topology Optimisation (TO) strategy in order to obtain multiple load paths or to locally limit the size of the component.

TL;DR: A conceptual framework that utilises blockchain technology principles for managing product development information and processes is proposed with the goal of providing new approaches to extending the functionality of product data management systems.

TL;DR: A generic methodology, suitable for arbitrary part geometries and various ISF processes, for addressing one of the main causes of geometric inaccuracy, i.e., in-process springback is developed.

TL;DR: This paper introduces a novel workflow for providing simulation-based decision support for improving KPIs of high-mix low-volume production systems by reducing the size of the input domain with the application of unsupervised machine learning techniques.

TL;DR: In this paper, a high-intensity X-ray beam was used to quantify the melt pool dynamics during continuous wave laser remelting of a Co-Cr alloy manufactured using selective laser melting, and the results indicated that the keyhole and its characteristic oscillations can suppress large wavelength features on the initial surface.

TL;DR: In this paper, the authors proposed a design of a drill tool with a shape that suppresses burrs and delamination during the drilling of composite materials such as carbon fiber reinforced plastic.

TL;DR: Considering the experimentally determined transfer-function between the force at the TCP and the displacement sensor, it is possible to calculate cutting forces during machining and the virtual quality is compared with CMM measurements.

TL;DR: In this article, a photoelectrochemical mechanical polishing (PECMP) method was proposed for finishing the n-type gallium nitride semiconductor wafers.