Industry 4.0: A bibliometric analysis and detailed overview

Industry 4.0 (I4.0) and Circular Economy (CE) are undoubtedly two of the most debated topics of the last decades. Progressively, they gained the interest of policymakers, practitioners and scholars...

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2019.1680896

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

The increasing awareness of customers toward climate change effects, the high demand instability affecting several industrial sectors, and the fast automation and digitalization of production systems are forcing companies to re-think their business strategies and models in view of both the Circular Economy (CE) and Industry 4.0 (I4.0) paradigms. Some studies have already assessed the relations between CE and I4.0, their benefits, and barriers. However, a practical demonstration of their potential impact in real contexts is still lacking. The aim of this paper is to present a laboratory application case showing how I4.0-based technologies can support CE practices by virtually testing a waste from electrical and electronic equipment (WEEE) disassembly plant configuration through a set of dedicated simulation tools. Our results highlight that service-oriented, event-driven processing and information models can support the integration of smart and digital solutions in current CE practices at the factory level.

Integrating Virtual Reality and Digital Twin in Circular Economy Practices: A Laboratory Application Case

Wire arc additive manufacturing is currently rising as the main focus of research groups around the world. This is directly visible in the huge number of new papers published in recent years concerning a lot of different topics. This review is intended to give a proper summary of the international state of research in the area of wire arc additive manufacturing. The addressed topics in this review include but are not limited to materials (e.g., steels, aluminum, copper and titanium), the processes and methods of WAAM, process surveillance and the path planning and modeling of WAAM. The consolidation of the findings of various authors into a unified picture is a core aspect of this review. Furthermore, it intends to identify areas in which work is missing and how different topics can be synergetically combined. A critical evaluation of the presented research with a focus on commonly known mechanisms in welding research and without a focus on additive manufacturing will complete the review.

The Current State of Research of Wire Arc Additive Manufacturing (WAAM): A Review

Exploring the influence of industry 4.0 technologies on the circular economy

Current mode effects on weld bead geometry and heat affected zone in pulsed wire arc additive manufacturing of Ti-6-4 and Inconel 718

Emerging through an industry-academia collaboration between the University of Sheffield and VBC Instrument Engineering Ltd, a proposed robotic solution for remanufacturing of jet engine compressor blades is under ongoing development, producing the first tangible results for evaluation. Having successfully overcome concept adaptation, funding mechanisms, design processes, with research and development trials, the stage of concept optimization and end-user application has commenced. A variety of new challenges is emerging, with multiple parameters requiring control and intelligence. An interlinked collaboration between operational controllers, Quality Assurance (QA) and Quality Control (QC) systems, databases, safety and monitoring systems, is creating a complex network, transforming the traditional manual re-manufacturing method to an advanced intelligent modern smart-factory. Incorporating machine vision systems for characterization, inspection and fault detection, alongside advanced real-time sensor data acquisition for monitoring and evaluating the welding process, a huge amount of valuable industrial data is produced. Information regarding each individual blade is combined with data acquired from the system, embedding data analytics and the concept of “Internet of Things” (IoT) into the aerospace re-manufacturing industry. The aim of this paper is to give a first insight into the challenges of the development of an Industry 4.0 prototype system and an evaluation of first results of the operational prototype.

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Intelligent sensing for robotic re-manufacturing in aerospace — An industry 4.0 design based prototype

The desire for smart “lights out factories” which can autonomously produce components for high value manufacturing industries is described by the Industry 4.0 solution. This manufacturing methodology is appropriate for newly designed components, which take advantage of modern materials, robotic and automation processes, but not necessarily applicable to overhaul and repair. The aerospace overhaul and repair industry remains heavily dependent on human engineering skills to develop repair and re-manufacturing techniques for complex components of high value.

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Transfer Analysis of Human Engineering Skills for Adaptive Robotic Additive Manufacturing in the Aerospace Repair and Overhaul Industry

Ensuring critical welded joint quality and repeatability is largely dependent on robust, well-designed Welding Procedure Specifications (WPS). Highly skilled manual welding engineers automatically recognise many imperfections, adjusting their responses according to inputs from vision, smell and sounds made during the welding process. Unfortunately, exceptional human ability does not guarantee performance when less predictable influences occur during welding processes. Human error and materials imperfections can result in defective welds for critical applications, commonly attributed to material surface impurities and contamination. Fault detection is problematic; the only finite method of weld testing is destructive testing which is not applicable to final product verification. Quality assurance and control is used to guarantee the welding process repeatability by production of a Procedure Qualification Record. This often-lengthy approval process restricts welding technology and materials application advancement. An alternative method of testing is the detection of flaws and defects in real-time to allow immediate process corrections. Development of real time welding evaluation instrumentation requires welding process parameters measurements combined with high-speed data processing. This real time monitoring and evaluation produces a weld defect fingerprint used to determine quality. We aim to highlight variations found in welding process quality using real-time monitoring and assess if it is within the acceptable standards for nuclear applications. To achieve this, we first must understand the human welding engineer using data taken from a series of manual weld trials. The trials use a common welding operation found in nuclear reactor pressure vessels. Reference data comparisons are made using identical trials with robotic welding equipment. Trial comparison results indicate that real time evaluation of welding processes detects flaws in weld quality. We then demonstrate how applications of welding process parameters are exceptionally effective methods for the control of robotic welding applications.

Advanced Real-Time Weld Monitoring Evaluation Demonstrated with Comparisons of Manual and Robotic TIG Welding Used in Critical Nuclear Industry Fabrication

Industry 4.0, the scheme that drives the fourth industrial revolution, has been, since its conception, reshaping the manufacturing industry. To advance current industrial chains into the smart factories of the future, cyber-physical systems are monitored and communicate with each other to ensure transparent interoperability, giving birth to the emerging field of industrial informatics. To enable the repair and recycling of high value jet engine compressor blades, additive manufacturing is utilized. The complex geometries and asymmetrical wear of the blades require robotic welding systems to be trained by experienced human welding engineers in order to be able to adapt to differing components. Demonstrated in this paper, process monitoring and industrial informatics are introduced to the adaption of Welding Procedure Specifications (WPS) utilized by a developing robotic system for the additive remanufacturing of aeroengine components. Using a novel variant of Gas Tungsten Arc Welding (GTAW), the robotic welding system under development is a product of an industry-academia collaboration between the Enabling Sciences for Intelligent Manufacturing Group (ESIM) of the University of Sheffield and VBC Instrument Engineering Ltd.

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Process monitoring and industrial informatics for online optimization of Welding Procedure Specifications (WPS) in Gas Tungsten Arc Welding (GTAW) – Industry 4.0 for robotic additive remanufacturing of aeroengine components

Michalis Benakis

Papers

Current mode effects on weld bead geometry and heat affected zone in pulsed wire arc additive manufacturing of Ti-6-4 and Inconel 718

Intelligent sensing for robotic re-manufacturing in aerospace — An industry 4.0 design based prototype

Transfer Analysis of Human Engineering Skills for Adaptive Robotic Additive Manufacturing in the Aerospace Repair and Overhaul Industry

Advanced Real-Time Weld Monitoring Evaluation Demonstrated with Comparisons of Manual and Robotic TIG Welding Used in Critical Nuclear Industry Fabrication

Process monitoring and industrial informatics for online optimization of Welding Procedure Specifications (WPS) in Gas Tungsten Arc Welding (GTAW) – Industry 4.0 for robotic additive remanufacturing of aeroengine components