Industrial parts often demand high dimensional accuracy and mechanical strength. This study introduces a method using Response Surface Methodology and composite desirability to simultaneously optimize these performances in components manufactured through additive processes. The approach was validated on Polylactic Acid parts fabricated through Fused Filament Fabrication. Optimized process parameters included a print speed of 80 mm/s, a layer height of 0.2 mm, a fan speed of 50%, and an extrusion temperature of 210 °C, yielding tensile strength of 53.27 MPa and dimensional deviations under 5%. Experimental validations showed less than a 5% deviation between predictions and outcomes. The findings provide valuable insights into improving the quality and performance of printed components in various industrial applications, such as gears, highlighting the significance of multi-response optimisation in 3D printing processes. This study ultimately contributes to more efficient and cost-effective manufacturing processes.

The dependencies between process parameters and the resulting geometrical accuracy of additively manufactured parts are usually highly non-linear and thus complex to investigate and mathematically quantify. Therefore, the application of artificial intelligence techniques is promising to generate mathematical models that reduce effort and increase the prediction quality. The overall goal is to establish a procedure to automatically determine the optimal settings of the manufacturing process parameters to guarantee the highest geometrical accuracy of parts in additive manufactured production. This paper presents the first step towards this fully automatic procedure – the training and evaluation of a mathematical model based on artificial neural networks to quantify the effects of varying process parameters of a material extrusion process on both macro- and micro-geometrical performances. Therefore, a dataset is established based on the Design of Experiment of an additively manufactured part made from Polylactic Acid filament. The dataset is then used to train an artificial neural network that predicts the dimensional and micro-geometrical deviations of the manufactured parts. Finally, the evaluation of the network's prediction quality and reliability indicate that it is possible to predict the parameters linked to resulting print quality with a mean absolute error from 0.0004 to 0.036.

In this chapter, an overview is given of the research work during the years 2007 until 2016 in the field of tolerance analysis, optimization and synthesis of mechanisms ([11] and [17]). At the beginning, the challenges related to mechanisms are highlighted, especially the time-dependent behaviour of a mechanism during its operation and the different kinds of deviation occuring during the production and the operation of the mechanism. After that, the integrated approach for the statistical tolerance analysis of mechanisms is described. This approach is then enlarged to a complete tolerance analysis, optimization and synthesis approach before its applicability is demonstrated in a case study. The chapter will end with a summary.

Purpose - This study aims to address challenges in the Laser Powder Bed Fusion process of polymers, focusing on the considerable amount of unsintered powder left post-printing. The objective is to understand the altered properties of this powder and find solutions to improve the process, reduce waste, and explore reusing reprocessed powder.

Design/methodology/approach - A novel methodology is employed to generate reprocessed powder without traditional printing, reducing time, cost, and waste. The approach mimics the aging effects during the printing process, providing insights into particle size distribution and thermal behavior.

Findings - Results reveal insights into artificial aging, showing an 8.2% decrease in particle size (60.256 - 69.183 μm) and a 9.1% increase in particle size (17.378 - 19.953 μm) compared to unsintered powder. Thermal behavior closely mirrors used powders, with variations in enthalpy of fusion (-0.55% to 2.69%) and degree of crystallinity (0.19% to 2.64%). The proposed methodology produces results that differ from those due to printing under 3% from a thermal point of view. The
new process reduces the time needed for aged powder, contributing to cost savings and waste reduction.

Originality/value - The study introduces a novel method for reprocessed powder generation, deviating from traditional printing. The originality lies in artificially aging powders, providing comparable results to actual printing. This approach offers efficiency, time savings, and waste reduction in the Laser Powder Bed Fusion process, presenting a valuable avenue for further research.

Additive manufacturing has transformed the production process by enabling the construction of components in a layer-by-layer approach. This study integrates Artificial Neural Networks to explore the nuanced relationship between process parameters and mechanical performance in Fused Filament Fabrication. Using a fractional Taguchi design, seven key process parameters are systematically varied to provide a robust dataset for model training. The resulting model confirms its accuracy in predicting tensile strength. In particular, the mean squared error is 0.002, and the mean absolute error is 0.024. These results significantly advance the understanding of 3D manufactured parts, shedding light on the intricate dynamics between process nuances and mechanical outcomes. Furthermore, they underscore the transformative role of machine learning in precision-driven quality prediction and optimization in additive manufacturing.

In times of digitalisation, visual assistance systems in assembly are increasingly important. The design of these assembly systems needs to be highly complex to meet the requirements. Due to the increasing number of variants in production processes, as well as shorter innovation and product life cycles, assistance systems should improve quality and reduce complexity of assembly processes. However, many large kitchen manufacturers still assemble kitchen cabinets manually, due to the high variety of components, such as rails and fittings. This paper focuses on the analysis and evaluation of virtual assistance systems to improve quality and usability in individualised kitchen cabinet assembly processes at a large German manufacturer. A solution is identified and detailed.

Epoxy resins are widely used polymers in the automotive and aerospace fields. Different blends of novel biodegradable resins have been studied in the last years in order to provide sustainability while maintaining the same properties of epoxy resins. Bio-based thermoset resins made with acrylated epoxidized soybean oil are well-studied in different vat polymerization techniques. The present work compares a bio-based resin and a petroleum-based resin. A benchmark with different features was designed and manufactured by a VAT photopolymerization process using both materials; measured with an optical scanning device; thus, the dimensional deviations were analyzed through inspection software. Tensile and flexural specimens were manufactured with the same procedure and tested with a dynamometer machine. Therefore, the comparison between a biodegradable resin and a petroleum-based resin is discussed in terms of the quality and mechanical performances of manufactured parts, considering the use of identical printing conditions. Some parts are required to satisfy both the requirements at the same time, such as the gears. Therefore, dimensional accuracy and mechanical strength need to be controlled and evaluated in a unique final quantification. This work proposes a novelty performance index to quantify dimensional accuracy and mechanical strength simultaneously. By combining the two aspects it is possible to define the overall performance obtained with the used material, optimizing the manufacturing process by choosing the proper material for each purpose.

In spring 2022, we implemented e-portfolios at a product design course for engineers in the bachelor's programme on ‘Sustainable Engineering’ at the University of Applies Sciences, Ansbach. The use of e-portfolios was new to both students and lecturers. To evaluate the effect the e-portfolio had on students, we accompanied the implementation with surveys and interviews. This paper provides a comprehensive analysis of the evaluated results. Among other things, the following three main findings convinced us to continue with e-portfolio work. First, ~91% of the interviewed students felt that they were supported very well by our introduction. Second, ~93% got along well / very well with the functions of the e-portfolio software. Third, ~86% of those interviewed appreciated the freedom of design. Prior to the implementation of e-portfolios in our first test course, we identified the following factors as crucial for the successful implementation of e-portfolios: a comprehensive personal introduction, extensive information material, continuous guidance, clear work instructions, room for flexibility and creativity to foster learners' individual strengths, and exchange between learners and teachers. This paper reflects on these initial factors. The aspects identified for further improvement in the second round of e-portfolios, in the summer of 2023, are better technical preparation of the lecturers, the communication of technical borders in advance, timing of the accompanying e-portfolio workshops and a more comprehensive promotion of teamwork. The suggested modifications will be discussed in detail in this paper.

Students not always enjoy an in-depth practical learning experience with an adequate portion of hands-on during their academic education. In many fields of study, traditional laboratories are common learning spaces that are, however, not accessible 24/7 and, the practical work is mostly pre-defined by the lecturer, resulting in a short and very “passive” active learning. To overcome this limitation and to provide a broader availability and to foster individual learning experience, we aim to transform this analog world into a modern learning and teaching environment using digital technologies and a corresponding digital framework for courses and laboratories. An existing laboratory on prototyping from our university’s bachelor program on sustainable engineering with an extensive machine park consisting of 3D printers, milling machines, lasers and various hand tools is digitized and will finally be linked with the real-world lab. In addition to digitizing the basic process of product development and prototyping as part of students' project works, all additional activities arising in the lab are also transferred from the analog to the digital world. This digitalization is implemented alongside the already existing (partly browser-based) software tools of the individual devices in the e-learning platform Moodle. This results in a digital copy of the lab, its equipment and defined processes – structured in accordance with the established proceedings on product development (such as Pahl/Beitz and VDI 2221). We consider it a digital twin of the work and learning environment, calling it the “digital learning environment twin” of the real-world lab. For the product development process, a course area is available in Moodle with various feedback loops and assessment levels for the individual development steps of the student projects. Through this, students can submit their project plans, design ideas, sketches, CAD-models, manufacturing codes (such as G-codes for 3D printers, laser cutters and carving machines), or “just” request feedback and initiate meetings on technical and/or organizational topics of their product design process, the lab equipment, etc. Also, a safety instruction with instructional videos, PDF documents with hazard warnings and operating instructions as well as a final test (to allow operating the lab equipment) are provided to introduce the students to the lab. In this paper, we will illustrate the overall methodological approach on the established digital learning environment twin of the lab. Furthermore, we will have a detailed view on the challenge of transferring underlying manufacturing process to the digital world and linking them to provide a continuous digital workflow. The paper will be closed with an analysis of feedback (by both students and lecturers) on the pros and cons as well as on the usability of the digital twin of the lab.

This work presents a synthetic geometrical performance index that combines all dimensional and geometrical deviations of a printed part to
express its quality. Smaller is the value of this index, greater is the part quality. The paper demonstrates the effectiveness of this index by printing
a set of parts through Fused Filament Fabrication in a biological polymer. These parts, characterized by representive hollows, were measured by
optical scanning technology. The proposed methodology shows the advantages of this index, thus future work can focus on further printing
techniques and varying process parameter values.

Industrial requirements to design high quality products in shorter and shorter times impose the use of numerical models
to estimate the geometrical deviations of these products, which are assemblies, starting from the geometrical deviations
of their components. Numerical models may support this estimation activity, thus reducing the time to market and the
design costs.
The free-body model is an interesting numerical method to translate the tolerance chain into a static problem solved by
algebraic or graphical procedures by using the free-body diagrams of force analysis. This work presents a free-body
model that is able to deal with dimensional and geometrical tolerances that involve translations of the features to which
the tolerances are applied. Moreover, it validates the free-body model for tolerance analysis of rigid parts by defining and
solving a case study through numerical and experimental activities. The present work uses a case study to demonstrate
the effectiveness of the free-body model by underlining that the experimental results obtained are very close to those
from the numerical model.

Statistical tolerance analysis based on Monte Carlo simulation can be applied to obtain a cost-optimized tolerance specification that satisfies both the cost and quality requirements associated with manufacturing. However, this process requires time-consuming computations. We found that an implementation that uses the graphics processing unit (GPU) for vector-chain-based statistical tolerance analysis scales better with increasing sample size than a similar implementation on the central processing unit (CPU). Furthermore, we identified a significant potential for reducing runtime by using array vectorization with NumPy, the proper selection of row- and column- major order, and the use of single precision floating-point numbers for the GPU implementation. In conclusion, we present open source statistical tolerance analysis and statistical tolerance synthesis approaches with Python that can be used to improve existing workflows to real time on regular desktop computers.

The importance of geometric deviations of components for the aesthetic and functional quality of products has been undisputed for decades. So, it is not surprising that not only have numerous researchers devoted themselves to this field, but also commercial software tools for the analysis and optimization of tolerance specifications (currently already fully integrated in 3D-CAD systems) have been available for around 30 years. However, it is even more surprising that the well-founded specification of tolerances and their analysis using a so-called statistical tolerance analysis are only established in a few companies. There is thus a contradiction between the proclaimed relevance of tolerances and their actual consideration in everyday business life. Thus, the question of the significance of geometric deviations and tolerances as well as the use of statistical tolerance analysis arises. Therefore, a survey among 102 German companies was carried out. The results are presented and discussed in this paper.

Air-conditioning of vehicles is important to improve driver comfort and motivate users to invest. The heating and cooling processes required for this are very energy-intensive processes. In conventional battery-operated commercial vehicles, the energy required to operate the air-conditioning system is used from the battery. This reduces the range of the vehicles by up to 30%. One of the greatest challenges in making electric commercial vehicles usable across the board is to increase their driving range. To reduce energy losses through air-conditioning, it is preferable to develop a technology that is independent of the battery. There are a number of options for controlling the temperature of a moving vehicle, but only a limited number that is CO₂-neutral. In this paper, we focus on adsorption chiller technology in combination with an auxiliary heater based on bioethanol. To understand the advantage of an adsorption machine, a simulation model can provide useful data on scaling and ease of use and thus be the basis for design and assembly of a prototype system. Therefore, a mathematical model of the adsorption technology is combined with the known dimensional parameters of electric vehicles, and the results are presented in form of a simulation model.

The specification of cost-optimal tolerances is ever since a major challenge for design engineers to ensure functionality as well as economic efficiency of mechanical assemblies. However, the underlying conflict "as tight as required, as wide as possible" is as old as the design, manufacturing of mechanical parts and their assembly itself – going back to times, when first plain tools were produced by hand using stones and wood. Since then, a long and challenging path has been taken by researchers and industrial experts to develop today’s effective methods and tools on tolerance engineering. In this paper a historical review on tolerance engineering of dimensional and geometrical tolerances in mechanical engineering is presented. Starting with the early beginnings during the age of individualized manufacture, four ages of tolerance engineering are analyzed and its major achievements are presented and discussed. Finally, we are looking ahead – focusing on current and upcoming trends in tolerance engineering.