Showing papers in "Procedia Manufacturing in 2018"

TL;DR: In this paper, the authors provide an overview of Industry 4.0 with its applications and identify the challenges and issues occurring with implementation of Industry4.0 and to study the new trends and streams related to Industry 4,0.

TL;DR: An overview of theories and models regarding user acceptance of technology has been provided in this paper, where the existing review will emphasize literature that tries to show how developers and researchers presage the level of admission any information technology will attain.

TL;DR: In this paper, a brief literature review conducted to extend our knowledge about how Industry 4.0 affects business models and to identify business model innovations derived in consequence is presented, where four different ways to innovate the business models based on different degrees of innovation are proposed to embrace the digitalization.

TL;DR: In this article, the authors highlight the benefits of the digitization of logistics process and examine the sustainability impact of digitization in logistics, based on a case study within the FMCG companies and their transport service providers in Turkey.

TL;DR: In this paper, the authors describe the main forms of collaboration of Industry 4.0 in relation to sustainability and point out the advantages provided by the new industry model such as improved product life cycles, manufacturing works in an integrated way with the use of cyber-physical systems allied to the principles of this industry, such as decentralization, virtualization, interoperability, among others.

TL;DR: In this paper, the authors present how the adoption of cyber-physical systems and Industry 4.0 technologies under the teaching factory paradigm will re-shape manufacturing education, addressing the increased need for highly-skilled employees.

TL;DR: This paper develops and investigates a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform, and introduces a knowledge resource center (KRC) built on a cloud server for information intensive applications.

TL;DR: A machine learning method, support vector machine (SVM), is proposed to classify the parts into either ‘good’ or ‘defective’ category and automatically assess the quality of 3D printed parts with the integration of a camera, image processing, and supervised machine learning.

TL;DR: A digital twin framework to support the design, build and control of human-machine cooperation and the case of a manufacturing company with human-robot work teams is presented for developing and validating thedigital twin framework.

TL;DR: This paper aims to present results from six case studies with over two hundred responders from academy and industry about usage and strategies on where and when to implement what xR technology.

TL;DR: In this paper, a review of diamond wire sawing of photovoltaic silicon wafers is presented and compared with the conventional loose abrasive slurry sawing process from a standpoint of sustainable manufacturing.

TL;DR: The ELLI project as discussed by the authors developed a tele-operative material characterization testing cell along with a remote lab for incremental tube forming and a general virtual experimentation lab for mechanical engineering education with a focus on manufacturing technology.

TL;DR: The didactical design of the training program provides a sustainable approach by not only realizing training courses but also includes preparation with management, mid-term coaching and success monitoring after the training.

TL;DR: A concept is presented to evaluate the potential of inspection and maintenance processes in the aviation industry regarding the use of mixed reality systems.

TL;DR: A critical review of the evolution of the advanced coatings deposition process, mainly focused on the Physical Vapour Deposition (PVD) process, particularly in the Magnetron Sputtering technique, is presented in this paper.

TL;DR: The proposed FabRec system decentralizes critical information about the manufacturer and makes it available on a peer-to-peer network composed of fiduciary nodes to ensure transparency and data provenance through a verifiable audit trail.

TL;DR: In this article, the authors summarized the current research status of energy consumption on machine and process levels of additive manufacturing (AM) and highlighted the efforts to quantify the energy flow in AM processes.

TL;DR: This paper addresses the challenges of mutual human-machine learning in factories of the future with the ultimate goal to identify new learning patterns in highly digitalized industrial work scenarios.

TL;DR: It is demonstrated how the integrated models add value to different stages of the lifecycle, allowing for evaluation of performance in the design stage and real-time reflection with the physical asset during its operation.

TL;DR: A method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband is proposed and achieves 98% and 87% recognition accuracy in the half-half and leave-one-out experiments, respectively.

TL;DR: This paper demonstrates automated guided vehicles (AGVs) in a real factory scenario which utilized radio frequency identification (RFID) tags for identification and motion control purposes.

TL;DR: In this article, the authors studied the relationship between 5S evolution and productivity in a local company from Mures County, Romania, which operates in automotive industry for over 10 years, and it is part of an Austrian group.

TL;DR: A previous general assessment algorithm has been implemented to find the optimal and sustainable process parameters levels during machining Inconel 718 with MQL-nano-fluids and it has been found that the assessment algorithm results were in agreement with the physical findings of the conducted experimental results.

TL;DR: A practical learning factory approach with several levels of maturity is presented, focussing on assistance systems as one part of “Industrie 4.0" to illustrate the link between both topics and show the maturity levels of the unification of both topics.

TL;DR: In this article, the authors investigated the influence of laser power and scanning speed on thermal stress related warping distortions and porosity and discussed the implications of the process parameters on the sustainability of the SLM process.

TL;DR: The bearing faults induced in rotating machinery is investigated experimentally using various vibration analysis techniques that are time, frequency and time-frequency domains to lead to the accurate assessment of the failure of rotating machinery, with respect to bearing faults.

TL;DR: In this paper, a conceptual framework for gamification implementation tackling sustainability awareness issues is proposed, where gamification mechanics can contribute to support manufacturing education on Industry 4.0, enabling innovation and sustainability.

TL;DR: In this article, a DT and AR industrial solution is developed as a part of a predictive maintenance framework for the industrial domain, and a proof-of-concept that was developed in special industrial application is presented.

TL;DR: This paper proposes a model for company’s implementation of learning, and discusses how this implies a closer integration with the learning activities to the cyber-physical manufacturing system as a seamless, integrated ICT learning and a hybrid human/machine intelligence model.

TL;DR: A new implementation of a learning factory that uses several technologies included in the Industry 4.0 vision and has a strong experiential learning approach is presented and provides modern design and simulation, prototyping, manufacturing processes, including 3D metal printing resources, and automated assembly and testing systems.