Virtual prototyping and digital twin

The aim of this research is to develop patient-specific 3D mandible models, based on a limited number of measurements taken on the patient. Twenty Computed Tomography scans were used to build the respective 3D cad models of the mandible. Fifteen of these models were given as an input to a Principal Component Analysis software, and eight ‘principal' mandible morphologies were produced. The following step was to identify the most efficient landmarks to ‘weight' these morphologies when building a patient-specific model. Two further mandible computed tomography scans (a ‘normal' mandible and a ‘severely resorbed' one) were used to test the full procedure and to assess its accuracy. The accuracy of the 3D morphed surface resulted to range between 0.025 and 3.235 mm for the ‘normal' mandible and between 0.012 and 1.149 mm for the ‘severely resorbed' one having used eight landmarks to morph a ‘standard' mandible. This work demonstrates how patient-specific models can be obtained registering the position of a limited number of points (on panoramic x-ray or on the physical model), reaching a good accuracy. This allows performing patient-specific planning and numerical simulations even for those cases where a computed tomography scan would not be available. In fact, this procedure can be interfaced with mesh morphing algorithms to automatically build finite element models. The accuracy of the procedure can be further improved, widening the mandibles computed tomography scans database and optimizing landmarks position.

Keywords: Morphing , Patient-specific models , Principal Component Analysis

Eco-design strategies aim to integrate environmental considerations into product design and development. Several regulations, directives and standards have been issued on this topic during last years. In particular, European Directive (2009/125/EC) establishes the eco-design requirements related to domestic and commercial kitchen appliances (e.g. cookers, hobs, grills). The present paper focuses on the virtual product eco-design of domestic induction heating cookers, which are becoming one of the leading cooking systems due to their advantages, e.g. energy efficiency, rapid heating, cleanliness, and user safety. The adoption of numerical analysis tools for the simulation of cooktops use phase, based on thermodynamic modelling, allows to provide useful information regarding the performance of cooking system at each phase of cooking. The paper provides a progress beyond the state-of-art on thermodynamic models for induction hob simulation considering interaction between the cooktop and the pot in the work environment. The goal of the paper is therefore to propose a methodology able to support designers in evaluating heating performances of induction cooking appliances, early in the design phases, through a virtual and multi-physical product model. Thermodynamic performances are determined by measuring several parameters and reproducing the energy consumption test by the mean of a virtual prototyping tool. Results highlight how the proposed model is adherent with the real tests following a specific standard in this sector with a maximum deviation of 3.2% considering the different cooking pot sizes.

Keywords: Design methodology , Eco-design strategies , Virtual Prototyping

In this work the warpage of a power modules ceramic substrates due to temperature variation has been numerically calculated. It has been used a not linear finite element model, which account the experimentally characterized material properties, including the copper elastoplasticity. Model results have been compared with dedicated interferometric measurements to validate the model. As application example, it has been calculated the benefit in terms of temperature warpage realized with a different substrate design option.

The presented work shows the results of investigations with respect to the microstructural evolution and the thermo-mechanical characterization of thick Cu films (20 mm), electrochemical deposited on silicon substrates. Warpage measurements based on Phase-Shift Moir´e principle have been performed considering different temperature profiles. A theoretical explanation has been proposed to justify experimental warpage behavior, also proofed by Differential Scanning Calorimetry (DSC).

Copper wires are nowadays replacing the traditional Au material in wire bonding interconnections, due to lower cost, better thermal/electrical properties and reliability performances. The increased hardness of Cu imposes higher bonding force and ultrasonic power during the wire-bonding process, increasing the risk of stress-induced bondpad damage. The aim of the presented work has been the modeling and characterization of stress and deformations resulting from the ball-bonding phase. A Finite Element Model has been developed and benchmarked with experimental samples obtained by freezing the ball bonding process at different steps, on which the deformations occurred in the bonded copper ball and in the bondpad layers have been measured through Plasma-FIB cross sections.

In the context of reliability of silicon Power Devices, we conducted a study on Power MOS Gate Trench devices. The stress tensor inside the device is characterized through experimental analysis and Finite Element calculation. A test bench is developed to investigate the impact of mechanical stress on the gate leakage current of examined devices.

Generally, comfort may be defined as the “level of well-being” perceived by humans in a working environment. The state-of-the-art about the evaluation of comfort/discomfort shows the need for an objective method to evaluate the “effect in the internal body” and “perceived effects” in main systems of comfort perception. Some medical studies show that each human joint has its own natural Rest Posture in which human muscles are completely relaxed or at the minimum strain level. Basing on this assumption, in other studies postural comfort curves for each Degree of Freedom of human upper and lower-limbs joints have been studied and CaMAN software has been developed to have a direct interface with these curves. In this paper, the upper limbs' postural comfort curves have been compared with the results gained by the biomechanics virtual simulation built on ANYBODY Software. A detailed study has been conducted on the upper body muscular activation during upper limbs movement with and without load. Postures have been analysed both by ANYBODY and CaMAN in order to correlate the postural (dis)comfort perception with the calculated muscular activity.

Keywords: ANYBODY software , Human Man Interface simulation , Postural comfort

The pillars of Industry 4.0 require the integration of a modern smart factory, data storage in the Cloud, access to the Cloud for data analytics, and information sharing at the software level for simulation and hardware-in-the-loop (HIL) capabilities. The resulting cyber-physical system (CPS) is often termed the cyber-physical manufacturing system, and it has become crucial to cope with this increased system complexity and to attain the desired performances. However, since a great number of old production systems are based on monolithic architectures with limited external communication ports and reduced local computational capabilities, it is difficult to ensure such production lines are compliant with the Industry 4.0 pillars. A wireless sensor network is one solution for the smart connection of a production line to a CPS elaborating data through cloud computing. The scope of this research work lies in developing a modular software architecture based on the open service gateway initiative framework, which is able to seamlessly integrate both hardware and software wireless sensors, send data into the Cloud for further data analysis and enable both HIL and cloud computing capabilities. The CPS architecture was initially tested using HIL tools before it was deployed within a real manufacturing line for data collection and analysis over a period of two months.

Keywords: Cyber physical system , Industry 4.0 , OSGi framework , Smart factory , Wireless sensor networks

Nowadays, there is an increasing interest in Phase-Change Materials due to their capacity to store latent heat during the phase transition. In the literature, the solid-liquid change is widely applied in cooling applications such as the thermal management of Li-ion batteries. The optimization of the cooling system is one of the solutions to reduce battery aging and increase the battery lifetime. Even if Phase-Change Materials are studied to be used in this context, there is still a lack of suitable solutions to be used in engineering design for a further product commercialization. In this context, the paper proposes a modular approach to support the design of a battery pack considering Phase-Change Materials in the cooling system. The approach shows how a single module of cells can be stacked and how the cooling system of each module can be easily connected to each other. The modularity concept is extended from the electrical configuration to the cooling system. As a test case, a battery module has been analyzed. The battery module has been simulated using a Computer-Aided Engineering tool to analyze the behavior of the temperature profile under loading conditions.

Keywords: Battery cooling , Battery simulations , Battery thermal management , Li-ion batteries , Modular design , Phase-change materials (PCM)

The fourth industrial age takes the manufacturing factory to a new level by introducing smart, extendible, flexible, modular and customized mass production technologies. Production lines or machines need to be integrated at the management level to be industry 4.0 compliant: in this way they can create and optimize a customer-oriented production, while constantly maintaining good performance conditions. In this context, one of the main challenges is the possibility to detect faults as fast as possible, to accurately diagnose those faults which can negatively affect the overall production cycle, and finally address them before it is too late. Due to the great importance that electric motors play in this context, an online smart algorithm for fault detection in electric motors is proposed in this paper. The effectiveness of the proposed method has been validated by applying it on an experimental benchmark, where the results show that the method is accurate and fast in detection of faults.

Keywords: Data Analysis , Fault Detection , Fault Diagnosis , Industry 4.0

Today, the improvement of the product value in consumer goods, such as new services to increase the positive customer experience, is the subject of many research activities. In a context where the product complexity becomes ever greater and the product life-cycle is always shorter, the use of intelligent tools for supporting all phases of the product life-cycle is very important. One of the aspects that is taking interest is to support the consumer in fault management. This analysis are well-known practices in the industrial, automotive fields, etc. but less used for consumer electronics. This paper analizes a Cloud service based on a Machine Learning (ML) approach used to provide fault detection capabilities to household appliances equipped with electric motors and compare the results with on premise ML algorithms provided research tools. The purpose of this paper is to perform a preliminary comparison of ML algorithm performances provided by two software, namely Microsoft Azure (cloud solution) and MATLAB (on premise solution), on a study case. In detail, the vibration data of an asynchronous motor installed in an oven extractor hood for commercial restaurant kitchen have been analyzed. To this end, two classification algorithms have been selected to implement fault diagnosis techniques.

Keywords: Artificial Intelligence , Fault Diagnosis , Machine Learning as a Service

A robust machine health state recognition tool is a pillar for condition-based maintenance and Deep Learning approach finds its natural application in such a context. This paper investigates the recognition of machine failures by image classification through a convolutional neural network in a condition-based maintenance environment. The case study involves a refrigerator for large retail establishments. Experimental measures, while the machine is approaching failure, are difficult to be collected, especially in the quantity needed for training and testing the neural network. For this reason, a digital twin of the asset has been created to simulate the behavior of the machine and generate as many data as needed: physically-based models of the machine and failure modes have been included and the simulated behavior has been tuned by using experimental data. Finally, it has been employed to generate signals that, translated into images, test the suitability of the neural network.

Keywords: Condition based maintenance , Digital twin , Image classification , Neural network

Additive Manufacturing based on Powder Bed Fusion processes enables the construction of end-use functional metal components, making it feasible to design several level of geometrical complexity. Nevertheless, the printing process leads to material and shape defects, residual stress and induced distortions on final components that mainly are caused by the high thermal gradients associated to the intense and nonuniform power energy sources used to selectively melt metal powders. In this paper, techniques to reduce or prevent these effects are summarized. The more broadly Design for Additive Manufacturing approach based on the use on CAD platforms for product-process design is the backbone upon this research is based on. Specifically, the work presents a design method to predict drawbacks and improve the industrialization subphase. Laser-based Powder Bed Fusion technique is considered and the implementation and validation of the Selective Laser Melting process simulation is performed in order to support the method. Two case studies are presented. The former demonstrates the simulation implementation feasibility through a CAD platform. The latter validates the simulation results compared to experimental data for further method application.

Keywords: CAD platforms , design for additive manufacturing , industrialization , powder bed fusion , process simulation , selective laser melting

Use of Additive Manufacturing provides great potentials to settings focused on high performance products. It allows feasibility of sundry innovative features to completely rethink geometries and shapes and it leads to embrace new design approaches. The enhanced design freedom can be exploited to optimize products, using techniques such as topology optimization. The study of methods for development of optimized components to be produced by AM becomes therefore fundamental. A framework for the methodological approach to operations to be carried out from the concept model to the printed component has been analyzed and it is clear that issues and research efforts relapse both the global level of the workflow and the local level of singular tasks to be performed. Problems related to management of Design for Additive Manufacturing workflow can be solved with holistic approach, through the use of computer aided integrated tools. The aim of this work is to test the effectiveness at local level of such tools with respect to operations for both design and industrialization optimization, working on an automotive case study. In particular, specific tools for topology optimization, product simulation, printing preparation and process simulation are taken as reference and results obtained with an integrated CAD platform are discussed.

Keywords: CAD based integrated platform , Design for Additive Manufactruing , High performance automotive components , Powder Bed Fusion

The aim of this paper is to analyze some critical issues in the Design for Additive Manufacturing workflow and evaluate the introduction of CAD platforms as backbone tools to shorten product development time and raise its efficiency. It is focused on the design of components to be printed by Powder Bed Fusion metal Additive Manufacturing. Even though the use of additive technologies firmly joins a CAD mathematical model and the actually printed component, the workflow from the concept to the definitive job may result in many sequential steps which have complex and slow relationships. Currently, at the state of art for the production of components specifically designed to be produced by additive manufacturing, there are issues both with the adoption of STL as interchange files and the not reversible sequence of tasks. For example, if a problem occurs in the part re-design during component industrialization, usually one must restart the work from the beginning. Thus, an improvement of the design workflow that could shorten time to product and improve both product performances and process quality and reliability, is necessary. In particular, the use of CAD platforms that integrates CAD and CAE tools has been investigated. An automotive case study, originally made by traditional subtractive technology (CNC milling), has been re-designed with topology optimization in order to be printed by Selective Laser Melting process with benefit of weight reduction. Design and industrialization tasks have been tested with respect to the selected integrated CAD platform, and potential improvements have been evaluated.

Keywords: Automotive , CAD platform , Design for Additive Manufacturing , Topology optimization

An innovative airport control tower concept based on the use of modern augmented reality technologies has been developed and validated by means of human-in-the-loop experiments in a simulated environment. An optical-based augmented reality interface underpins the proposed concept that consists in providing air traffic control operators in the airport control tower with complete head-up information, as opposed to the current mix of information retrieval through both head-up real view and head-down interfaces. Specific measurement of the time spent by the operator working in either head-up or head-down position, show that the proposal has a clear effect in stimulating the air traffic control operator to work in a head-up position more than in a head-down position, with positive effects on his/her situational awareness and perceived workload, especially when dealing with low visibility conditions operational scenarios.

The implementation of symbiosis approaches is recognized as an effective industrial strategy towards the optimization of resource exploitation and the improvement of collaboration in the context of Industry 4.0. An industrial system can be considered as a complex environment in which material, energy, machine, and human resources should cooperate towards the improvement of efficiency and the creation of value. According to this vision, the paper presents a detailed literature review about the existing symbiosis approaches: (i) industrial symbiosis models, which mainly aim at the sharing of resources among different companies, and (ii) human symbiosis, which focuses on how to effectively strengthen the synergy among humans and machines. Strengths, weaknesses and correlations among the most common symbiosis approaches are analysed and classified. Finally, the existing symbiosis models are related with the pillars of the Industry 4.0 paradigm, in order to understand what should be the future directions of research in the context of collaborative manufacturing.

Keywords: collaborative manufacturing , human symbiosis , industrial symbiosis , Industry 4.0

Simulation tools for liquid composite molding processes are a key to predict and solve manufacturing issues of composite materials. Numerical processes are commonly used to analyse and predict mould filling, considering also resin cure and exothermic reactions. These evaluations are usually performed through dedicated software tools that require highly specialized operators and purchasing costs. The present study relates to a multi-objective optimization approach for evaluating the effect of different process parameters of the resin transfer molding (RTM) process using a multi-purpose tool. Starting from a simple case, useful for analysing the effect of mesh type and size on the simulations, and then increasing the complexity of the models, virtual simulations have been validated through real tests. Afterward, this approach has been used for the optimization of the RTM process for the manufacturing of an automotive component. Gate positions, injection pressure and resin temperature have been optimized using finite-volume analysis with a multi-objective genetic algorithm. Finally, the parameters have been used in real experiments in order to validate the efficiency and the reliability of multi-purpose tool in simulating RTM processes.

Keywords: Multi-objective optimization , Process simulation , RTM , Virtual prototyping

Advanced composite materials have been attracting the interest of many automotive companies for producing light and high-performance components. Out-Of-Autoclave methods have been recognized as the most promising processes to produce CFRP components. One of the most interesting process is Compression-RTM. The aim of this research is to demonstrate the validity of the C-RTM process for producing parts with a thickness greater than 10 mm. The authors fabricated a preform made by 17 layers of PAN based carbon fibre 800 g/m2 and 600 g/m2 twill fabric and injected more than 700 g of matrix. Process simulations have been run to test different boundary conditions without producing physical prototypes. Flexural tests have been performed to compare the behavior of thick parts produced by C-RTM with the ones produced by prepreg and autoclave. The results show comparable strength values between the samples tested. DSC, void content and ultrasound measurements have been investigated to fully understand the physical properties of the finished component. Moreover, cycle times has been analysed to demonstrate the effectiveness of the method both from process and product performances points of view. Results show that thanks to the use of C-RTM the manufacturing time decreases by 68% with respect to the autoclave processes.

Keywords: Compression Resin Transfer Molding , Experimental tests , Process simulation , Thick CFRP components

In this paper, an original approach for the virtual prototyping of composite pressure tanks is proposed. The main tests to be conducted for the homologation of the vehicle tank is the burst pressure, which is a quasi-static test. This method aims to reduce the finite element model development time by the integration between the computational software MATLAB and the FEA tool Abaqus. Since the dome shape has fundamental influence on the mechanical performances of the composite pressure vessel, the presented procedure allows the designer to quickly import the suitable dome geometry into Abaqus, without the need of going through CAD software. The first step of the method here reported is the definition of all the geometric and operational parameters necessary to the construction of the dome meridian profile. The second step is to enter those parameters in a MATLAB script, which is able to integrate the dome profile differential equation, to generate the whole tank profile and to import this profile into Abaqus. Once the geometry has been imported, a FE model of the high-pressure vessel can be built and virtual simulations can be performed. This approach could be implemented in a dome optimization process to find which dome meridian profile gives the best tank performances.

Keywords: Composite Vessels , Filament Winding , Virtual Prototyping