Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

Predictive Maintenance in Industry 4.0

In the context of Industry 4.0, the manufacturing-related processes have shifted from conventional processes within one organization to collaborative processes cross different organizations, for example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. The development and application of the Internet of things, i.e. smart devices and sensors increases the availability and collection of diverse data. With new technologies, such as advanced data analytics and cloud computing provide new opportunities for flexible collaborations as well as effective optimizing manufacturing-related processes, e.g. predictive maintenance. Predictive maintenance provides a detailed examination of the detection, location and diagnosis of faults in related machinery using various analyses. RAMI4.0 is a framework for thinking about the various efforts that constitute Industry 4.0. It spans the entire product life cycle & value stream axis, hierarchical structure axis and functional classification axis. The Industrial Data Space (now International Data Space) is a virtual data space using standards and common governance models to facilitate the secure exchange and easy linkage of data in business ecosystems. It thereby provides a basis for creating and using smart services and innovative business processes, while at the same time ensuring digital sovereignty of data owners. This paper looks at how to support predictive maintenance in the context of Industry 4.0. Especially, applying RAMI4.0 architecture supports the predictive maintenance using the FIWARE framework, which leads to deal with data exchanging among different organizations with different security requirements as well as modularizing of related functions

POSTRUM: Developing good posture in trumpet players through directional haptic feedback

The literature of brass pedagogy has identified the typical posture problems found in trumpet players and arrived at a consensus regarding optimal body alignment. The suggestion is that poor posture may not only hinder performance but also lead to longterm injuries. This is supported by a growing body of evidence from fields as diverse as biomechanics and pervasive healthcare. After a review of the literature, we focus on the design process used to develop Postrum; a wearable system for trumpet players that uses real-time haptic feedback to encourage better posture. In response to the multifaceted nature of the activity, the design process combines two aspects from different fields: the ‘sketching in hardware’ approach developed by Moussette and Dore in the context of Interaction Design (IxD), and sensing technologies from the New Interfaces for Musical Expression (NIME) field. We follow this with a brief overview of the Postrum system. This includes a 3D camera, custom software that compares the posture of the player to an idealized model, and two vibrotactile arrays mounted on the torso. Three different types of problem can be detected, their categories based on the literature. If player posture deviates from the ideal, haptic feedback is applied. Directional pulses used to indicate the corrective action needed. Finally, we offer some remarks about our experiences in relation to player engagement and performance, discuss emerging design issues, and outline implications for what Hochenbaum and Kapur term the ‘practice room of the future.

APLIKASI SISTEM PERINGATAN TABRAKAN PADA KAPAL BERBASIS DATA GPS MENGGUNAKAN LOGIKA FUZZY

Automatic Identification System (AIS)  is an important equipment in ship for giving ship’s information to other ships or harbour. Unfortunately, there is still no ship collision warning system included in AIS. Hence, an application of ship collision early warning system based on Global Positioning System (GPS) data is proposed in this paper. Here, the zero-order sugeno fuzzy logic is used to process the ships speed and position data. The output of this warning system are recommended ships speed and heading direction to prevent the ship collision based on IMO (International Maritime Organization) regulation. The object used is a ship prototype equiped with GPS. The testing is held in four position of the ship prototype againts static object. The positions are -45o, -25o, 25o dan 45o. The testing results yield 100% accuracy to the IMO regulation of the head on situations case

Imaging of Magnetic Nanoparticles using Magnetoelectric Sensors

Imaging of magnetic nanoparticles offers a variety of promising medical applications for therapeutics and diagnostics. Using magnetic nanoparticles as tracer material for imaging allows for the non-invasive detection of spatial distributions of nanoparticles that can give information about diseases or can be used in preventive medicine. Imaging biodistributions of magnetically labeled cells offers applicability for tissue engineering, as a means to monitor cell growth within artificial scaffolds non-destructively. In the presented work, the capabilities of an imaging system for magnetic nanoparticles via magnetoelectric sensors are investigated. The investigated technique, called Magnetic Particle Mapping, is based on the detection of the nonlinear magnetic response of magnetic nanoparticles. A resonant magnetoelectric sensor is used for frequency selective measurements of the nanoparticles magnetic response. Extensive modeling was performed that enabled proper imaging of magnetic nanoparticle distributions. Fundamental limitations of the imaging system were derived to describe resolution in correspondence to signal-to-noise ratios. Incorporation of additional parameters in the imaging system for the data analysis resulted in an algorithm for a more robust reconstruction of spatial particle distributions, increasing its imaging capabilities. Experimental investigations of the imaging system show the capabilities for imaging of cell densities using magnetically labeled cells. Furthermore, resolution limitations were investigated and differentiation of different particle types in imaging was shown, referred to as ”colored” imaging. The imaging of biodistributions of magnetically labeled cells thus enable exciting perspectives on further research and possible applications in tissue engineering

High Voltage Optical Fibre Sensor for Use in Wire Relay Electrical Protection Systems

The last few decades have a wide spread use of optical fibre sensors in many applications. Optical fibre sensors have significant benefits over existing conventional sensors such as; high immunity to electromagnetic interference, the ability to transmit signal over long distance at high bandwidth, high resolution, usage in hazardous environments and no need for isolation when working at high voltages. The measurement of high voltages is essential for electrical power systems as it is used as a source of electrical information for Relay Protection Systems (RPS) and load management systems. Electrical Power Systems need to be protected from faults. Faults can range from short circuits, voltage dips, surges, transients etc. The Optical High Voltage sensor developed is based on the principle that the Lead Zirconate Titanate (PZT) electrostriction displacement changes when a voltage is applied to it. The displacement causes the fibre (FBG) which is bonded to the PZT material to have a resultant change in the wavelength. An optical fibre sensor prototype has been developed and evaluated that measures up to 250 V DC. Simulation using ANSYS software has been used to demonstrate the operational capability of the sensor up to 300kV AC. This sensor overcomes some of the challenges of conventional sensors issues like electromagnetic interference, signal transmission, resolution etc. R BASHOUR 2 A novel optical fibre high voltage based on the Kerr effect has been demonstrated. The The Kerr effect was determined using Optsim (R-Soft) software and Maxwell software was used to model an optical Kerr Cell. Maxwell software is an electromagnetic/electric field software used for simulating, analysing, designing 2D and 3D electromagnetic materials and devices. It uses highly accurate Finite Element techniques to solve time varying, static, frequency domain electric and electromagnetic fields. A Relay Protection System on electrical networks was discussed in detail. Keywords: Fibre Bragg Grating, Fibre Optics Sensors, Piezoelectricity, Kerr effect, Relay Protection Systems.N/