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The scientific literature highlights how Mixed Reality (MR) simulations allow obtaining several benefits in healthcare education. Simulation-based training, boosted by MR, offers an exciting and immersive learning experience that helps health professionals to acquire knowledge and skills, without exposing patients to unnecessary risks. High engagement, informational overload, and unfamiliarity with virtual elements could expose students to cognitive overload and acute stress. The implementation of effective simulation design strategies able to preserve the psychological safety of learners and the investigation of the impacts and effects of simulations are two open challenges to be faced. In this context, the present study proposes a method to design a medical simulation and evaluate its effectiveness, with the final aim to achieve the learning outcomes and do not compromise the students' psychological safety. The method has been applied in the design and development of an MR application to simulate the rachicentesis procedure for diagnostic purposes in adults. The MR application has been tested by involving twenty students of the 6th year of Medicine and Surgery of Università Politecnica delle Marche. Multiple measurement techniques such as self-report, physiological indices, and observer ratings of performance, cognitive and emotional states of learners have been implemented to improve the rigour of the study. Also, a user-experience analysis has been accomplished to discriminate between two different devices: Vox Gear Plus® and Microsoft Hololens®. To compare the results with a reference, students performed the simulation also without using the MR application. The use of MR resulted in increased stress measured by physiological parameters without a high increase in perceived workload. It satisfies the objective to enhance the realism of the simulation without generating cognitive overload, which favours productive learning. The user experience (UX) has found greater benefits in involvement, immersion, and realism; however, it has emphasized the technological limitations of devices such as obstruction, loss of depth (Vox Gear Plus), and narrow FOV (Microsoft Hololens).

In the era of the fourth industrial revolution, human has still a central role. Manufacturing industries have to deal with human sustainability in order to guarantee workers’ health and well-being. Several studies have proved the importance of ergonomics in workplace design and the benefits related to the adoption of the human-centered approach. The enabling technologies of Industry 4.0 are changing the role of the operator and can support him from a physical and cognitive point of view. On the other hand, companies are increasingly implementing lean philosophies, such as World Class Manufacturing, to maintain their competitiveness by reducing wastes and costs. However, the need arises for a comprehensive methodology to support the design of manufacturing equipment considering human factors by integrating Industry 4.0 technologies and World Class Manufacturing elements. It aims at improving both ergonomic and efficiency aspects of the workstation. The proposed methodology allows identifying and in-depth analyzing the problem, thus finding and implementing a solution that complies with all the requirements and constraints defined. Each step of the methodology can be strengthened by Industry 4.0 technologies. The methodology has been experimented in a real case study with a global company of agriculture and industrial vehicles, leading to the design and implementation of a new equipment. Relevant benefits in terms of ergonomics, efficiency, and process standardization have been achieved.

Engineering design shows a growing interest in exploring cost analysis to anticipate manufacturing issues and integrate production aspects within the product development process. This research aims to highlight key elements (inputs, parameters, models) to accurately predict the cost of a forged part using a complete model, with important information that can be available during the design phase. For this purpose, a systematic literature review of existing engineering methodologies developed for cost analysis of forged parts (i.e., cost estimation, DtC, and ABC) was performed with characterizations of the different approaches for evaluating the most important topics related to this objective. As a result, the most important insights related to the aim of this review are provided: (i) among quantitative methods, analytical and parametric models are the most suitable approaches to develop a cost estimation, (ii) a cost model based on a linear equation supported by single or multiple variables seems to be the most accurate tool to establish a robust cost analysis in the design of forged components, and (iii) input parameters related to the material type and geometrical features are the most critical cost-drivers in the cost assessment. Moreover, this review contributes to identifying emerging applications and obsolete topics, providing the ground to investigate unexplored areas relevant to future research.

As nearly one third of global energy demand and CO2 emissions are attributable to manufacturing activities, the reduction of energy/resource consumption in the industrial sector is increasingly crucial. Therefore, research and innovation for the factories of the future is not only a matter of developing and integrating new technologies, but also a challenge to make manufacturing less dependent on energy and managed in an optimized way. This requires considering the efficiency of resource exploitation according to a systematic approach. To this aim, the present paper proposes a resource-saving tool, called Resource Value Mapping (RVM), and describes its application in a smart multinational company that produces electromechanical components for the automotive industry. The RVM tool is composed by three main modules that jointly allow the involved stakeholders to collaborate toward the optimization of the plant management: the Cloud data center that represents the repository of the collected real-time and offline data, the Analytics module that is responsible for data elaboration with the aim of calculating a set of key performance indicators useful to identify process inefficiencies, and the Web-based platform that represents the user interface of the tool. The case study demonstrated how such a tool allows (1) mapping the energy/resource flows to multiple levels (machine, line, plant), (2) characterizing them to identify the most critical activities that do not generate value and (3) supporting multiple stakeholders (plant manager, energy manger, operators) in the management of resource anomalies and definition of a more sustainable action plan.

Even in the era of the fourth industrial revolution, companies should necessarily deal with human sustainability, with the aim of improving workers’ health and safety and enhancing their skills. Several studies have faced this issue by proposing approaches or framework to boost the consideration of human factors in the workstation design and support ergonomic evaluations. However, the need arises for a methodology that collects and systematizes existing methods and tools in order to create workplaces that fit to human needs. For this aim, this paper proposes a structured methodology that supports the design and engineering of manufacturing equipment in order to improve workstations in terms of ergonomics and efficiency. It allows identifying a problem, solving it and carrying out a complete and objective evaluation from different perspectives. The methodology has been experimented in a real case study in collaboration with a global manufacturer of agriculture and industrial vehicles. Significant benefits in terms of productivity, process standardization and human factors have been achieved.

This paper presents a novel framework for manufacturing and cost-related knowledge formalization. This artefact allows industries to capitalize the knowledge of experienced practitioners in the field of manufacturing and assembly, so that it can be used by designers for quickly and analytically estimating the production costs of components during product development. The framework consists of the following: (i) a cost breakdown structure used for splitting out the manufacturing cost, (ii) a data model (cost routing) to collect the knowledge required to define a manufacturing process, (iii) a data model (cost model) for collecting the knowledge required to compute the manufacturing cost of each operation within a manufacturing process, and (iv) a workflow to define the manufacturing process. The proposed framework provides several advantages: (i) knowledge formalization of product manufacturing cost, (ii) knowledge sharing among design/engineering departments, and (iii) knowledge capitalization for decision-making process. The proposed framework is used to formalize the knowledge required for analytically estimating the manufacturing cost of open-die forged components. Results highlight that the framework addresses the most important requirements for a knowledge-based cost estimation system.

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.

Composite materials are demonstrating the ability to face the challenge of competitive markets where high-performance, low costs, and reduced manufacturing time are mandatory. Vacuum bagging with autoclave curing is one of the most used manufacturing methods for carbon fiber composite parts. However, it shows some limitations, mainly due to manual operations and long processing time. Out-of-autoclave (OOA) methods, such as pressure bag molding (PBM), can lead to a strong reduction of the manufacturing time through the simplification of lay-up and curing phases. In this paper, a comparative analysis between the autoclave and the PBM processes has been performed, jointly considering both the economic and environmental aspects. An evaluation of the environmental impacts has been carried out following the standardized life cycle assessment (LCA) methodology. In addition, costs related to these two manufacturing techniques have been estimated through a parametric approach and successively compared. Different scenarios have been considered to take into account various production batches, mold manufacturing techniques, and end of life alternatives. The analyses show conflicting results demonstrating that a global optimum scenario does not exist and, depending on the chosen indicator and production batch, the best alternative varies. Considering only the environmental indicators, the autoclave process can be considered the most sustainable option, due to the lower consumption of energy.

Welding is a widely used technology that allows the joining of thick metal plates for the development of large structures (e.g. piping, tanks, vessels). Many industries are intensively using welding for manufacturing and assembly activities. Sustainability assessment of welded structures is currently performed with misleading information in terms of data heterogeneity (nature) and quality (source). The data required to carry out a robust environmental analysis are spread among different documents and become available only when the project is finalized. This paper aims to define a data framework for a life cycle inventory of metal arc welding processes to preventively assess the environmental performances of different processes for comparison and decision-making analysis. The framework is presented as innovative solutions for life cycle inventory that provide (i) a common data structure (model), (ii) necessary data (input/output), and (iii) physical allocation/placement of data (project design documents). This study was performed in accordance with the international standard organization ISO 14040/14044 by using an attributional life cycle assessment (aLCA). Two structures (an oil and gas riser and a ship hull) were investigated considering the same functional unit: the manufacturing, use, and disposal of a welded structure able to guarantee the engineering requirements (according to a specific standard) in terms of strain, stress, and corrosion allowance over the expected lifetime of 20 years. In both cases, the share of welding process in respect to an overall product/structure life cycle impact assessment is strictly dependant on the project design choice and can be negligible for high-corrosion-resistance materials (e.g., Inconel alloy). On the other hand, the use of traditional metals (e.g., carbon steel) allows a large decrease of the environmental load, and the influence of the welding process becomes significant in a life cycle perspective.

The paper aims to analyze and compare the environmental performances of metal arc welding technologies: gas metal arc welding (GMAW), shielded metal arc welding (SMAW), gas tungsten arc welding (GTAW), submerged arc welding (SAW), and flux-cored arc welding (FCAW). Welding is considered one of the most energy-intensive processes in manufacturing. This study was performed in accordance with the international standard ISO 14040/14044 by using attributional life cycle assessment (aLCA). The functional unit is defined as the “the development of 1 metre of welding seam (qualified by ASME section IX requirements) to join 25 millimetres thick of metal plates made in carbon steel material and considering a V-bevel configuration.” Different configurations of base/filler materials and standardized bevel geometries have been analyzed as welding scenarios. The inventory considers all inputs (e.g., electric energy and filler material) and outputs (e.g., fume emissions and slags) involved in each welding process. A framework for data collection starting from available project documentation is presented as an innovative solution for the inventory phase. The impact assessment includes the human health, resources (midpoints/endpoint), and ecosystems (endpoint) categories from the ReCiPe (H) and cumulative energy demand (CED) methods. This study reveals a notable dominance in terms of the environmental burdens of GTAW and SMAW processes, as they present higher impacts in most of the impact categories. SMAW is the most energy-consuming process, and this aspect is reflected in the environmental performance. Conversely, GMAW presents the least environmental load, accounting for less than one third compared with GTAW in terms of the CED indicator and performing very well in terms of the ReCiPe endpoint indicator. Via analysis of different scenarios, the main outcomes are the following: (i) the use of V bevels significantly increases the environmental load when the metal plate thickness increases and (ii) the use of specific materials such as Inconel alloy exacerbates the environmental concerns associated with welding processes. The use of project documentation allows robust analysis of welding activity. Sensitivity analysis shows how the range of values for specific parameters (e.g., volts and amps) affects each technology in a different manner. Indeed, those ranges have a limited impact on the result accuracy (up to 20%) for more automatized welding processes (e.g., GMAW, SAW, and FCAW), in which only a small number of parameters are set by the operator, and the operator skills are less influential on the quality of the weld.

This paper proposes a methodological approach for the multi-objective optimization of steel towers made from prefabricated cylindrical stacks that are typically used in the oil and gas sector. The goal is to support engineers in designing economical products while meeting structural requirements. The multi-objective optimization approach involves the minimization of the weights and costs related to the manufacturing and assembly phases. The method is based on three optimization levels. The first is used in the preliminary design phase when a company receives a request for proposal. Here, minimal information on the order is available, and the time available to formulate an offer is limited. Thus, parametric cost models and simplified 1-D geometries are used in the optimization loop performed by genetic algorithms. The second phase, the embodiment design phase, starts when an offer becomes an order based on the results of the first stage. Simplified shell geometries and advanced parametric cost models are used in the optimization loop, which present a restricted problem domain. In the last phase involving detailed design, a full 3-D computer-aided design model is generated, and specific finite-element method simulations are performed. The cost estimations, given the high levels of detail considered, are analytic and are performed using dedicated software.

Nowadays, the increasing of global climate change and warming is leading governments, consumers, and firms towards a low-carbon economy. A lot of research shows that about 75% of the environmental impacts related to energy-related products is due to the use phase. Therefore, energy-related products, such as household appliances, are responsible for the consumption and depletion of natural resources. The eco-design of household appliances is a necessary approach to analyze and reduce the environmental impacts related to these products, considering materials, efficiency, and energy consumptions. In Europe, as well in China and America, the eco-design is becoming an Integrated Product Policy to support the Energy Labelling of several energy-related and consuming products. This paper deals with a design methodology to support the eco-design of cooking ovens by the simulation of the product performance. Two simulation cases have been analyzed: the energy consumption, which is provided by EU regulations No 66/2014 and No 65/2014 and the baking test. Even if regulations only provide the energy consumption test, the baking test is necessary to analyze the functional quality of the product. Therefore, two levels of simulations are necessary to complete the eco-design approach of cooking ovens. The results show that the proposed methodological approach can reduce the time-to-market and enhance the design optimization from the early design phases.

Lightweight engineering is a current topic in mechanical industry. The mass reduction is a common design objective to reduce product cost and environmental impacts. Virtual prototyping tools are widely applied to study new lightened solutions and check the compliance with regulations and standards. However, an integrated approach, involving simulations and life-cycle analysis, is necessary to support design optimization and decision-making. The scope of this study concerns the definition of an Ecodesign approach to support the lightweight engineering of cast iron parts through the redesign of the product shape. In particular, this paper deals with the optimization of a ductile cast iron manhole. The test case shows a redesign method which considers structural analysis with environmental impacts. The structural analysis has been evaluated using a finite element method tool. In particular, the simulation results have been compared and validated with physical tests. The environmental analysis is based on the methodology provided by the standardized ISO 14040:2006 and ISO 14044:2006. The proposed LCA study considers the phases of manufacturing and transport related to one ductile iron product. The described manufacturing phase is related to a Chinese foundry which produces roughly 12,000tons of ductile cast-iron castings. The results show the possibility to achieve about 20% of mass reduction for one casting. Considering such mass decreasing, the related reduction in terms of carbon emission is about 7%. Summarizing, this paper shows a design approach to integrate the structural improvements with the reduction of the environmental impacts related to a lighter weight casting.

Conceptual design is a fundamental phase for developing optimal product configurations. During conceptual design, the degree of freedom in engineering choices can propose optimal solutions in terms of assembly, manufacturing, cost and material selection. Nevertheless, in current industrial practices, each aspect is analysed independently and a guided decision-making approach based on multi-objective criteria is missing. Multi-objective analysis is a way of combining each production aspect with the aim of choosing the best design option. The goal of this research work is to define a multi-objective design approach for the determination of optimal and feasible design options during the conceptual design phase. The approach is based on the concept of functional basis, module heuristics for defining product modules and the theory of multi-criteria decision-making for mathematical assessment of the best design option. The novelty of this approach lies in making the design process, currently based on company know-how and experience, systematic. A complex product (i.e. tool-holder carousel of a computer numerical control machine tool) is the case study used to assess the economic sustainability of different design options and to validate the proposed design workflow in a real manufacturing context. Different product modules have been re-designed and prototyped for comparing the assemblability, manufacturability and cost of the design solutions.

Circular economy (CE) is a new business model that is pressing manufacturing companies to think about closed loop scenarios for materials and products. Design for End-of-Life (DfEoL) and Design for Disassembly (DfD) are key enabling methods for the effective application of this model. The paper presents a time-based method for the calculation of disassembly sequences, adopting basic theories and techniques in this topic and integrating new concepts for the assessment of the disassembly time. The method consists of five steps and starts from the documentations (e.g., CAD model) generally available early in the product development process. The first three steps encompass the product analysis by including (i) the definition of target components from the general assembly, (ii) the analyses of the virtual model, and (iii) the assessment of the so-called level matrix, which is based on the concept of disassembly levels and liaisons characterization among components. The last two steps allow for the assessment of the time-based disassembly sequence by including (iv) the analysis of feasible sequences and (v) the generation of the best disassembly sequence for target components. The method mainly overcomes two issues highlighted in the literature regarding the reliability of the disassemblability analysis using a time-based approach and the quality of results accounting for the real condition of the product at the time of disassembly. The calculation of the effective disassembly time is grounded on a specific repository developed to gather knowledge about the disassembly tasks and related disassembly time. This is the main contribution and novelty of the proposed approach. By using the proposed method, different target components of a washing machine are analysed with the aim of demonstrating the robustness of the method and its consistency in the estimation of disassembly time. A maximum deviation of 10% between the estimated and measured disassembly times is noticed.

End-of-life (EoL) modelling in life cycle assessment has already been broadly discussed within several studies. However, no consensus has been achieved on how to model recycling in LCA, even though several approaches have been developed. Within this paper, results arising from the application of two new EoL formulas, the product environmental footprint (PEF) and the multi-recycling-approach (MRA) ones, are compared and discussed. Both formulas consider multiple EoL scenarios such as recycling, incineration and landfill. The PEF formula has been developed within the PEF programme whose intent is to define a harmonized methodology to evaluate the environmental performance of products. The formula is based on a 50:50 allocation approach, as burdens and benefits associated with recycling are accounted for a 50% rate. The MRA formula has been developed to change focus from products to materials. Recycling cycles and material losses over time are considered with reference to material pools. Allocation between systems is no longer needed, as the actual number of potential life cycles for a certain material is included in the calculation. Both the approaches have been tested within two case studies. Methodological differences could thereof be determined, as well as applicability concerns, due to the type of data required for each formula. As far as the environmental performance is concerned, impacts delivered by MRA are lower than those delivered by PEF for aluminium, while the opposite happens for plastic and rubber due to the higher share of energy recovery accounted in PEF formula. Stainless steel impacts are almost the same. The application of the two formulas provides some inputs for the EoL dilemma in LCA. The use of a wider perspective, better reflecting material properties all over the material life cycle, is of substantial importance to properly represent recycling situations. In MRA, such properties are treated and less data are required compared to the PEF formula. On the contrary, the PEF model better accommodates the modelling of products whose materials, at end of life, can undertake the route of recycling or recovery (or landfill), depending on country-specific EoL management practices. However, its application requires more data.

3D optical scanning systems are used more and more for quality control purposes. The effective utilization of such systems needs an efficient virtual planning of the product acquisition viewpoints. Literature shows how 3D CAD product models can be used as reference in order to manage the verification process and as a basis for the computation of the optimal viewpoints. However, in the mechanical field, a variety of inspection tasks is experienced by engineers involved in the quality control process: GD&T verification, production phases control such as sheet metal cutting, evaluation of aesthetic appearance of parts, global shape deformation measurement and specific point deviations assessment. This leads to the necessity of flexible view planning approaches which adapt to the specificity of the required inspection task. The present work targets the development of a comprehensive view planning approach in which several algorithmic options are triggered by the product features to be inspected. Algorithms have been implemented in a prototypal software system which has been experimented as an off-line application to provide inputs to a multi-axis degree of freedom robot arm mounting an optical 3D scanner. Two test cases from die casting and automotive fields are presented. They show the computation of acquisition poses in a suitable sequence and efficiency in the obtained results.

The development of modular products is diffused in modern production due to the achievable flexibility and to the required product personalization. Modular products can maximize the efficiency of productive processes if they are structured to be easily configurable during the assembly phase. In this context the present work proposes an approach to optimize the product’s modular architecture aimed to improve manual assemblability. The goal of this method is to assess the product assembly sequence during the early design stage. In particular it improves the conceptual design for assembly approach by taking into account the role of different flows in the modular product structure and the types of interface between modules. A case study regarding the household appliance field is reported and it allows the method results to be shown and to highlight advantages and drawbacks. A relevant improvement in terms of the reduction of assembly time is obtained.

The paper explores the potentialities of virtual reality (VR) to improve the learning process of mechanical product design. It is focused on the definition of a proper experimental VR-based set-up whose performance matches mechanical design learning purposes, such as assemblability and tolerances prescription. The method consists of two main activities: VR technologies benchmarking based on sensory feedback and evaluation of how VR tools impact on learning curves. In order to quantify the performance of the technology, an experimental protocol is defined and an testing plan is set. Evaluation parameters are divided into performance and usability metrics to distinguish between the cognitive and technical aspects of the learning process. The experimental VR-based set up is tested on students in mechanical engineering through the application of the protocol.

In the conceptual design stage, outcomes of industrial designers work are generally represented by set of sketches where curves, notes, shadows, and colors implicitly represent creative ideas. Signs and annotations are used to synthesize and concretize the design intent that, finally, will be transformed into the styling product visual appearance. The loss of the original design intent may be due to the complexity of the design process, and the involvement of different actors. Our aim is to provide a method and relative tools in order to interpret signs on sketches for eliciting the design intent. The analysis result is a set of aesthetic features that can be used for driving CAD modeling, in the case both of Reverse Engineering applications and of product modeling for restyling purposes. Sketches analysis is based on a semiotic interpretation driven by the formalization of the cognitive models used in the conceptual design phase. The approach showed promising results on different styling products test cases.