Showing papers in "CIRP Annals in 2018"

TL;DR: In order to improve the accuracy and efficiency of PHM, digital twin (DT), an emerging technology to achieve physical–virtual convergence, is proposed for complex equipment.

TL;DR: In this article, the authors present an overview of various process steps in the overall product life cycle of composite materials parts manufacturing. But they focus on the composite part properties and economical production.

TL;DR: Deep learning is investigated as a data driven technique for continuous human motion analysis and future HRC needs prediction, leading to improved robot planning and control in accomplishing a shared task.

TL;DR: In this paper, an investigation into the 3D printing of multiple metallic materials including 316L stainless steel, In718 nickel alloy and Cu10Sn copper alloy within a single build-up process using a specially designed multiple material selective laser melting (SLM) system combining powder-bed with point by point powder dispensing and selective material removal, for the first time.

TL;DR: In this paper, the authors give an overview of different methods, which are established to produce bore holes with demanding aspects related to diameter, length-to-diameter-ratio, bore hole quality, workpiece materials and complex internal contours.

TL;DR: A prescriptive deviation modelling method coupled with machine learning techniques is proposed to address the modelling of shape deviations in additive manufacturing.

TL;DR: Flexibility in forming is reviewed from the viewpoints of process, material, manufacturing environment, new process combinations and machine–system–software interactions.

TL;DR: A data-driven adaptive planning and control approach that uses simulation-based optimization to determine most suitable dispatching rules in real-time under varying conditions is proposed and evaluated.

TL;DR: This paper shows the successful implementation of a reinforcement learning-based adaptive control system for order dispatching in the semiconductor industry and a performance comparison of the learning- based control system with the traditionally used rule-based system shows remarkable results.

TL;DR: This paper analyzes and discusses convergence and underlying science and engineering of well proven natural strategies of surface textures and their effective synthetic implementation in engineered products.

TL;DR: This work proposes a method to analyse and enhance industrial workplaces using immersive virtual reality, which allows the tracking of multiple users virtually performing assembly tasks inside a CAVE system and the visualization of KPIs for supporting decision making by production engineers.

TL;DR: A comprehensive review of lightweight structure applications and the challenges and opportunities they present in a life cycle engineering context with a focus on eco-effectiveness is provided.

TL;DR: The method of Weighted Least Squares (WLSQ) is introduced for adaptive parameter updates, to handle the diverse sample rates of the measured errors by on-machine probing.

TL;DR: This paper reports a design method for a resilient architecture of a cyber-physical production system that can deal with disturbances and failures in a discrete-event process.

TL;DR: A deep learning-based approach to improve the effectiveness and efficiency of mapping CNs to DPs is proposed and the results show that the proposed approach can meet customer needs with high efficiency.

TL;DR: A digital simulation and compensation model for blade machining operations is presented and stiffness of the blade at the cutting zone is updated as the metal is removed without re-meshing using a computationally efficient sub-structuring technique.

TL;DR: In this article, a direct method for joining aluminum alloy and polybutylene terephthalate through metal surface roughening using abrasive micro-blasting and insert molding is presented.

TL;DR: In this paper, the influence of the substrate temperature and the line building sequence on the formation of the built structure and the generation of spatter particles was experimentally investigated, and it was shown that the substrate's temperature has a measurable effect on droplet formation and spatter particle generation.

TL;DR: In this paper, the authors present a reconsideration of value creation in production from various aspects of value viewpoints in several disciplines such as production engineering, social sciences, and human sciences.

TL;DR: The effectiveness of the proposed data analytics methodology is validated through an experimental campaign of CFRP composite drilling, using a setup that reproduces as faithfully as possible the real industrial operations, in order to acquire a suitable dataset of sensor signals.

TL;DR: An approach to controlling an industrial robot using human brainwaves as a means of communication is introduced and an industrial case study is carried out to assist the operator in coordinating a collaborative assembly task of a car engine manifold.

TL;DR: Alternative methods of support with the robot are explained and experimental results show that the robot’s support improves the static and dynamic response of the process, so dimensional errors are minimized and surface quality is improved.

TL;DR: In this article, the effect of gamma prime (γ′) phase on Ni-based superalloys was investigated and it was shown that with the increase of γ′ fraction the grain plastic deformation significantly decreased, while specific cutting energy can switch from low to high values influenced by the real cutting temperature.

TL;DR: Current applications of feeling machine tools and developments of monitoring and compensation systems for tool deflection, including a method to integrate strain sensors within rigid machine tool structures is introduced.

TL;DR: In this article, a geometry scalable predictive model across micro-scale laser scan, mesoscale layer hatch, and macro-scale part build-up was developed to fast predict residual stress in different scanning strategies.

TL;DR: In this paper, the technical feasibility of selective mechanical delamination through milling and cleaving was experimentally studied and the achievable material recovery results are compared to current practices in end-of-life treatment, demonstrating a substantial potential to improve resource preservation.

TL;DR: In this paper, the machining process of Zr-BMG using a transparent sapphire tool with direct laser assistance was discussed, and the effects of machining speed and laser power on the material deformation mechanism were investigated.

TL;DR: This research develops an approach to link as-planned (ISO 6983) to as-fabricated (MTConnect) product data using dynamic time warping to enable the designer to make a more optimal decision from the perspective of the product lifecycle that would have otherwise been challenging to identify.

TL;DR: In this article, the electroplastic effect on AA1050 aluminium alloy sheets was investigated with the aim of decoupling the electro-plastic and thermal behaviour due to Joule effect in electrical-assisted forming.

TL;DR: This work presents the achievable upper and lower capability bounds by introducing so-called stabilizability diagrams of a hypothetical variable pitch milling cutter that is tuned continuously along the stability boundaries.