Resource-efficient Manufacturing Research Articles

Advancements in Hybrid Additive Manufacturing: Integrating SLM and LMD for High-Performance Applications

Additive manufacturing (AM) technologies enable near-net-shape designs and demand-oriented material usage, which significantly minimizes waste. This points to a substantial opportunity for further optimization in material savings and process design. The current study delves into the advancement of sustainable manufacturing practices in the automotive industry, emphasizing the crucial role of lightweight construction concepts and AM technologies in enhancing resource efficiency and reducing greenhouse gas emissions. By exploring the integration of novel AM techniques such as selective laser melting (SLM) and laser metal deposition (LMD), the study aims to overcome existing limitations like slow build-up rates and limited component resolution. The study’s core objective revolves around the development and validation of a continuous process chain that synergizes different AM routes. In the current study, the continuous process chain for DMG MORI Lasertec 65 3D’s LMD system and the DMG MORI Lasertec 30 3D’s was demonstrated using 316L and 1.2709 steel materials. This integrated approach is designed to significantly curtail process times and minimize component costs, thus suggesting an industry-oriented process chain for future manufacturing paradigms. Additionally, the research investigates the production and material behavior of components under varying manufacturing processes, material combinations, and boundary layer materials. The culmination of this study is the validation of the proposed process route through a technology demonstrator, assessing its scalability and setting a benchmark for resource-efficient manufacturing in the automotive sector.

SAMSax—An Innovative Living Lab for the Advancement of a Circular Economy through Additive Manufacturing Technologies

The sustainable development of products is of great interest to both industry and consumers due to various factors, such as anthropogenic climate change and the scarcity of resources and materials. In response to this, the simul+ Living Lab Sustainable Additive Manufacturing in Saxony (SAMSax) has been established as a physical experimental space aimed at improving the sustainability of products. This includes selecting resource-efficient manufacturing processes, using renewable materials, reducing energy consumption during use, and designing for recyclability. The innovative approach of the lab also integrates an open innovation process, involving present and potential stakeholders. Collaborating closely with stakeholders from industry, academia, and government fosters idea generation, provides solution approaches, and enhances acceptance and practical implementation. Methodologically, SAMSax focuses on upcycling organic and inorganic residues as well as by-products from industry and agriculture, reintegrating them as innovative components in industrial production using additive manufacturing (“3D printing”). The Living Lab provides a space for networking and active knowledge transfer through digital technologies, analyses, and collaborative developments, enabling the testing and evaluation of innovations in a real-world environment. Several potential waste materials suitable for additive manufacturing and new products have already been identified. In addition to industrial residues, materials, such as paper and wood dust; industrial by-products, such as sand; and agricultural residues, like harvest residues, are being analyzed, processed, and tested using additive manufacturing in the laboratory. In this way, SAMSax can contribute to an integrated and consistent circular economy. The research aims to demonstrate that the SAMSax Living Lab is a crucial driver of innovation in the field of additive manufacturing. Furthermore, this study contributes by presenting the Living Lab as an application-oriented research environment, focusing on innovative implementation in small- and medium-sized enterprises.

Data quality in environmental assessment methods – Implications for the operational management in manufacturing

To implement environmentally sustainable, resource-efficient manufacturing, the quantification of the environmental impacts is a central task. This task requires suitable methods. Various lifecycle phases, including remanufacturing concepts, and the associated increasing complexity demand a change from static to dynamic assessment methods. Flexible changes must be considered. Thereby, data quality has a major impact on the subsequent assessment results. Though the available data amount in a manufacturing environment is constantly increasing, the influence of data quality on the respective method – and thus, the reliability of the results – remains a key issue. To address this problem, this paper investigates the necessary developments regarding data quality for environmental assessment methods in dynamically changing manufacturing settings. First, relevant data quality dimensions are identified. Subsequently, a cross-comparison of data quality dimensions and different approaches of environmental evaluation in manufacturing is developed. The necessary changes to data quality requirements in operational environmental assessments are derived. Finally, a concept for the improvement of data quality in dynamic assessments is proposed and discussed based on the use case of battery modules’ remanufacturing. This paper contributes to the development of environmental assessment methods that are evolving from static, historical data-based evaluations to dynamic assessment tools of flexible productions.

Studies on the Use of Laser Directed Energy Deposition for the Additive Manufacturing of Lightweight Parts

Despite the numerous benefits of battery electric vehicles, their relatively short maximal range compared to internal combustion engine vehicles limits their attractiveness to the consumer. Implementing lightweight structures is one solution to reduce the mass of the vehicle, which in turn lowers the energy consumption and thus extends the maximal range. Additive Manufacturing processes, such as the Laser Directed Energy Deposition (DED-LB), offer great potential for the resource-efficient manufacturing of lightweight components because they allow producing near-net-shaped parts of variable sizes and geometries. Therefore, in this study, DED-LB was assessed concerning its use for the rapid manufacturing or modification of lightweight parts. The additive process was performed on EN AW 6060 aluminum extrusion profiles commonly found in battery electric vehicles and an AlSi10Mg wire was used as feedstock. The investigations included temperature and microhardness measurements. Furthermore, the effect of the deposition rate on the geometric quality of the part was investigated. The results indicate that DED-LB can be performed on thin-walled structures to produce defect-free components. Furthermore, the findings reveal a trade-off between a fast build-up and the surface quality of the parts. Notably, it was observed that the different deposition rates had no impact on the hardness of the produced parts. Further studies on heat management are needed to optimize the process for producing lightweight parts with improved mechanical properties.

Developing the Additive Manufacturing Chain of AlSi7Mg with Laser Powder Bed Fusion and Tailored Heat Treatments for Railway Spare Parts

The use of metal additive manufacturing technologies in railways sector can provide increased flexibility in terms of spare part logistics. Combined with lightweight metals such as Al-alloys, the product performance can also be enhanced in terms of weight reduction, vibration and noise control. The railway sector is more likely to exploit large and bulky parts produced by laser powder bed fusion (LPBF), which should have appropriate mechanical properties. Therefore, the whole production chain should be analyzed considering the heat treatment steps suited for a distributed and resource efficient manufacturing scheme. Accordingly, this work analyzes the additive manufacturing of AlSi7Mg alloy by LPBF and its consecutive heat treatment steps. In particular, the impact of LPBF process productivity, heat treatment type and atmosphere composition were considered to analyze the most appropriate route for the needs of the railways applications. The results show that with an appropriate direct aging treatment in air, mechanical characteristics of the alloy could be improved, despite that the high layer thickness used in LPBF could increase process productivity. The absence of a quenching step was found to be favorable for large parts, while the absence of an inert gas such as Ar in the heat treatment did not generate any reduction in the mechanical properties.

Can industry 5.0 technologies overcome supply chain disruptions?—a perspective study on pandemics, war, and climate change issues

AbstractIndustry 5.0 (I5.0) is the next industrial revolution that will leverage human intervention in collaboration with intelligent, logical, and smart machines to attain even more user-preferred and resource-efficient manufacturing and supply chain solutions. The main aim of this article is to study I5.0 technologies in supply chains when these are affected by disruptive phenomena such as those created by wars, climate change or pandemics. A systematic literature review methodology was conducted to understand the present knowledge connected with this theme. This study summarises 194 research articles from the period 2009 to 2022 to understand the present knowledge connected with this theme. The research findings show a significant gap related to the adoption of I5.0 technologies to prevent or overcome supply chain disruptions. 194 articles, including journal and review articles, were identified in the literature. The study provides a novel and insightful concept related to I5.0 within the context of supply chain disruptions. The potential applications of I5.0 and Industry 4.0 are elaborately discussed in three areas, namely: (1) disruptions in supply chains due to pandemics; (2) disruptions in supply chains due to war; and (3) disruptions in supply chains due to climate change. Finally, this study highlights research implications and proposes future research avenues that will contribute to further exploring the adoption of I5.0 technologies to prevent, manage and overcome disruptions in supply chains.

Resource-efficient manufacturing process of composite materials: Fibrillation of recycled textiles and compounding with thermoplastic polymer

This study aimed to develop a manufacturing process for recycled textile long fiber thermoplastics (RT-LFT) and thereby contribute to circular economy. Three different post-consumer textiles (cotton denim and plain weave, and silk plain weave) were cut into strips and fed directly into a co-rotating twin-screw extruder in which the textile was fibrillated and compounded with polypropylene (PP). The fibrillation of the textile, fiber dispersion, and interaction with the matrix polymer were studied, and the thermal and mechanical properties of the composites were evaluated. For example, cotton denim composites containing 30 wt% fiber content resulted in 26% increase in yield strength and a 72% increase in modulus when compared with that of PP. The RT-LFT process is a straightforward method for transforming used textiles into composites like cups and bottoms, offering advantages such as reduced manufacturing costs, add value for waste material, and lower carbon emissions.

On the Possibility of Replacing Scheil-Gulliver Modeling with Machine Learning and Neural Network Models

Resource-efficient manufacturing is a foundation for sustainable and circular manufacturing. Semi-solid processing typically reduces material loss and improves productivity but generally requires a better understanding and control of the solidification of the cast material. Thermal analysis is commonly used in high-pressure die casting (HPDC) processes to determine casting process parameters, such as liquidus and solidus temperatures. However, this method is inadequate for semi-solid casting processes because the eutectic temperature is also a crucial parameter for successful semi-solid casting. This study explores the feasibility of using machine learning and artificial neural networks to predict fundamental values in Al-Si alloy casting. The Thermo-Calc 2022 software Scheil-Gulliver calculation function was used to generate the training and the test datasets, which included features such as melting temperature, alpha aluminium solidification temperature, eutectic temperature, and the solid fraction amounts at eutectic temperature. The results show that both models have a symmetric mean absolute percentage error (SMAPE) of less than 2 % with temperature prediction, with the machine learning model achieving a better accuracy of less than 1 %. A case study comparing practical measurements with prediction results is also discussed, demonstrating the potential of AI methods for predicting semi-solid casting processes.

EREMI: An Innovative Interdisciplinary Approach for Higher Education in Resource Efficient Manufacturing Environments

This paper presents an overview of EREMI, a two-year project funded under ERASMUS+ KA203, and its results. The project team’s main objective was to develop and validate an advanced interdisciplinary higher education curriculum, which includes lifelong learning components. The curriculum focuses on enhancing resource efficiency in the manufacturing industry and optimising poorly or non-digitised industrial physical infrastructure systems. The paper also discusses the results of the project, highlighting the successful achievement of its goals. EREMI effectively supports the transition to Industry 5.0 by preparing a common European pool of future experts. Through comprehensive research and collaboration, the project team has designed a curriculum that equips students with the necessary skills and knowledge to thrive in the evolving manufacturing landscape. Furthermore, the paper explores the significance of EREMI’s contributions to the field, emphasising the importance of resource efficiency and system optimisation in industrial settings. By addressing the challenges posed by under-digitised infrastructure, the project aims to drive sustainable and innovative practices in manufacturing. All five project partner organisations have been actively engaged in offering relevant educational content and framework for decentralised sustainable economic development in regional and national contexts through capacity building at a local level. A crucial element of the added value is the new channel for obtaining feedback from students. The survey results, which are outlined in the paper, offer valuable insights gathered from students, contributing to the continuous improvement of the project.

All-Printed ZnO Nanowire-Based High Performance Flexible Ultraviolet Photodetectors

Sensor-laden flexible electronic systems offer opportunities to develop a wide range of applications including healthcare, electronic skin (e-skin) in robotics, Internet of Things (IoT) etc. However, the mass production of sensors, needed for these applications, could be a huge challenge when developed with inherently wasteful conventional fabrication processes. In this regard, a resource efficient manufacturing method using eco-friendly (green) materials is desirable. Herein, we present a resource efficient additive manufacturing route for printing a 4×4 ultraviolet (UV) photodetectors array on flexible substrates. Specifically, we use contact printing technique to realise high-grade UV sensitive and uniform electronic layers of ZnO nanowires (NWs). Next, high-resolution extrusion-based Direct Ink Write (DIW) printing is employed to define metal electrodes and the sensing channel area. The fabricated devices exhibit excellent UV sensing performance at low bias voltage (1V) and light intensity (0.5μW/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), including an average responsivity of ~7.8×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> A/W, specific detectivity ~1.7×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">16</sup> Jones, external quantum efficiency ~2.6×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9</sup> % and current on/off ratio ~2×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . The mechanical loading (bending) tests performed under different radii of curvature (10 to 40mm) confirm the robust performance of devices. This work shows a potential way towards next generation of sustainable electronics manufacturing.

Comprehensive angular scattering distribution analysis for resource-efficient manufacturing

Most measuring principles for surface topography measurement cannot be broadly used within machine tools due to the rough environment featuring vibrations, dust, cooling liquid, or temperature gradients. Having to measure outside of the machine tool results in large quality control loops. The angular-resolved scattering light sensor is an established measuring principle which can be used directly in the manufacturing environment and thus allows small quality control loops and a resource-efficient manufacturing since deviations in the manufacturing process can be detected almost immediately. For the evaluation of the surface characteristics, the angular distribution of the surface within a lightspot is typically characterized by its center of gravity (M-parameter) and its variance (Aq-parameter) as described in the guideline VDA 2009. These two parameters provide only little information about the angular distribution and the workpiece quality and for certain, function-oriented applications and expanded data analysis can be beneficial to allow the monitoring in more manufacturing systems with high benefits for resource-efficient manufacturing. We suggest using additional parameters of the angular distribution and perform a correlation analysis with the machining parameters of an exemplified manufacturing process to find parameters that feature a more pronounced correlation with the process parameters than Aq and thus allow an improved monitoring of the manufacturing process in this paper. The example process chosen is a grinding process with different tool grit sizes, tool surface speeds, feed rates, and coolant air flow power. With this case study it can be demonstrated how a more comprehensive analysis of the scattering of surface angles can lead to an improved process monitoring since the correlation between the process parameters and the parameters of the angular distribution shows how sensitively different deviations in the process can be detected, e.g. when the grinding belt must be replaced. For an efficient implementation of quality control loops, simple and traceable monitoring parameters are essential. A smart evaluation of the measurement data allows an optimization of the manufacturing process and the associated quality control loops.

Development, characterisation, and modelling of processability of nitinol stents using laser powder bed fusion

Additive manufacturing (AM) of customised vascular or peripheral stents is of great potential for surgeons and patients, enabling the patients to have customised stents and achieving better outcomes from stenting procedures, with further advantages of having a resource efficient manufacturing process. In this study, the potential for AM of superelastic NiTi-based shape memory alloy (Nitinol) stents was investigated. Two stent designs, which are used for the treatment of complex peripheral artery stenosis in the lower limbs, were studied. Laser Powder Bed Fusion (LPBF) of two stent designs was studied to investigate the impact of the process parameters on the stent geometry, strut size, structural integrity and the phase transformations. The study demonstrated the successful manufacture of Nitinol stents via LPBF, with strut sizes in the range between 250 µm and ≈ 560 µm. The elastic modulus of the stents was between 56 and 73 GPa, which matches well with the elastic modulus of standard austenitic Nitinol. Chemical etching was used to reduce the strut diameter and to remove the partially melted particles. It was shown that the laser energy input has a vital role in controlling the Ni-evaporation and the subsequent changes in the transformation temperatures, as well as the morphology of the stents. The lower energy input results in a reduced Ni-evaporation, maintaining the austenite finish temperature at the expected range, in addition to generating a good build morphology.

Comparison of Melting Processes for WPC and the Resulting Differences in Thermal Damage, Emissions and Mechanics.

The necessity for resource-efficient manufacturing technologies requires new developments within the field of plastic processing. Lightweight design using wood fibers as sustainable reinforcement for thermoplastics might be one solution. The processing of wood fibers requires special attention to the applied thermal load. Even at low processing temperatures, the influence of the dwell time, temperature and shear force is critical to ensure the structural integrity of fibers. Therefore, this article compares different compounding rates for polypropylene with wood fibers and highlights their effects on the olfactory, visual and mechanical properties of the injection-molded part. The study compares one-step processing, using an injection-molding compounder (IMC), with two-step processing, using a twin-scew-extruder (TSE), a heating/cooling mixer (HCM) and an internal mixer (IM) with subsequent injection molding. Although the highest fiber length was achieved by using the IMC, the best mechanical properties were achieved by the HCM and IM. The measured oxidation induction time and volatile organic compound content indicate that the lowest amount of thermal damage occurred when using the HCM and IM. The advantage of one-time melting was evened out by the dwell time. The reinforcement of thermoplastics by wood fibers depends more strongly on the structural integrity of the fibers compared to their length and homogeneity.

Electronic Waste Reduction Through Devices and Printed Circuit Boards Designed for Circularity

The development of printed circuit boards (PCBs) has so far followed a traditional linear economy value chain, leading to high volumes of waste production and loss of value at the end-of-life. Consequentially, the electronics industry requires a transition to more sustainable practices. This review article presents an overview of the potential solutions and new opportunities that may arise from the greater use of emerging sustainable materials and resource-efficient manufacturing. A brief contextual summary about how the international management of waste PCBs (WPCBs) and legalization have evolved over the past 20 years is presented along with a review of the existing materials used in PCBs. The environmental and human health assessments of these materials relative to their usage with PCBs are also explained. This enables the identification of which ecofriendly materials and new technologies will be needed to improve the sustainability of the industry. Following this, a comprehensive analysis of existing WPCB processing is presented. Finally, a detailed review of potential solutions is provided, which has been partitioned by the use of emerging sustainable materials and resource-efficient manufacturing. It is hoped that this discussion will transform existing manufacturing facilities and inform policies, which currently focus on waste management, toward waste reduction and zero waste.

3D printing floating modular farms from Plastic Waste

As demographic growth and climate change effects increase, agriculture intensifies its pressure on the natural ecosystems from which life on Earth depends. In recent years, novel designs and resource-efficient manufacturing methods have been studied to alleviate the impact of food production, many of them incorporating farms into the urban context. However, farming in freshwater bodies remains largely unexplored and constitutes a great opportunity for innovation when land is scarce. Physical requirements for floating farming demand water barrier, solid, inert, and food-grade material with sufficient natural light transmittance, and lightweight, large-scale, complex-shaped components. Therefore, Polyethylene Terephthalate (PET) is presented in this paper as an ideal material for the fabrication of deployable floating farm modules, and Fused Deposition Modeling (FDM) is selected as the most appropriate manufacturing process for the required geometries. Today, recycled polymers in 3D Printing have progressed as a more sustainable feed for small-scale applications. However, there are limited built examples of Additive Manufacturing (AM) using recycled polymers in large-scale real-life applications. This project explores digital designs and fabrication approaches to large-scale manufacturing using PET obtained from single-use bottles to produce empirical prototypes tested in real-life conditions. The research prompted the digital design of a one-meter diameter translucent dome and a flotation platform, their fabrication using large-scale FDM, the assembly of the printed elements, and the monitoring of the farming module performance during operation. The paper covers the state of the art of related 3D printing technologies and their application in food production devices, details the design process of the floating module, explains the selected printing processes and interfacing strategies, and discusses the empirical evidence on the benefits and drawbacks of large-scale AM applied to the cultivation of food. Overall, the research demonstrates the possibilities of 3d Printing using recycled polymers, adding novel insights from a fully-functional project to the incipient body of research on digital manufacturing in food production.

Multi-objective optimization of lean and resource efficient manufacturing systems

In the manufacturing industry, target-oriented and efficient use of resources is gaining importance, alongside economic optimization. The economic and organizational optimization of manufacturing systems according to the lean principles is only partly compatible with the goals of resource-efficient manufacturing. Therefore, an approach is sought to improve individual analyses of manufacturing systems. This paper proposes an approach for the multi-objective optimization of lean and resource-efficient manufacturing systems. To predict the dynamic effects of several configurations of manufacturing systems, material, energy, and information flows of a discrete event simulation are coupled with an assessment model, based on objectives of lean and resource-efficient manufacturing. Using design of experiments, Gaussian process meta-models are computed for the behavior of the simulation model. These meta-models allow the approximation of the system behavior to be computed in a short period of time and enable extensive multi-objective optimization and more adequate decision-making support systems. The proposed approach is tested in the metalworking industry.

Extending the decision-making capabilities in remanufacturing service contracts by using symbiotic simulation

Remanufacturing is a critical enabler of a resource efficient manufacturing industry that has long been associated with high value products. Over time, the commercial relationship between customers and service providers has been made through the fulfilment of rights and obligations under remanufacturing service contracts. Nonetheless, financial analysis to evaluate the contract terms and conditions are becoming increasingly difficult to conduct due to complex decision problems inherent in remanufacturing systems. In order to achieve better and safer decision-making to shape the business strategies, remanufacturers often employ computer-based simulation tools to assess contractual obligations and customers’ needs. This paper discusses the roles of a symbiotic simulation system (SSS) in supporting decision-making in remanufacturing systems. An industrial case study of power transformer remanufacturing illustrates how SSS can support contract remanufacturers in managing service contracts planning and execution. By linking the simulation model to the physical system, it has been demonstrated that the capabilities of the remanufacturers to make critical decisions throughout the entire service contract period can be extended.

Handling of Blackplate in Metallographic Preparation and Heat Treatment Optimization via Quenching Dilatometry

Abstract A prerequisite for the successful optimization of a heat treatment for high-alloyed steels is the knowledge about the present initial microstructure. The metallographic preparation and characterization of the initial microstructure poses a challenge, especially for blackplate, due to its low thickness. In this article, a method is presented which facilitates the handling of blackplate during metallographic preparation. With a precise knowledge of the initial microstructure, tests for the optimization of a heat treatment for such blackplate can also be performed. An optimization of the heat treatment process is particularly important for energy and resource efficient manufacturing processes. In this work, a preparation method was developed which allows winding blackplate to hollow cylinders to determine the optimized heat treatment parameters with the help of a quenching and deformation dilatometer. It will be shown that the two methods presented are an efficient but yet reliable way to optimize heat treatment processes of blackplate via laboratory tests.

Approaches for an energy and resource efficient manufacturing in the aircraft industry

Over the recent years, several studies have pointed out the impact of manufacturing on the environment. Especially machining offers great potential for the conservation of energy, resources and the reuse of raw materials. This article gives an overview on the approaches that are currently under investigation at the Institute of Production Engineering and Machine Tools with the aim of improving these aspects. The approaches cover regrinding methods for worn tools, recycling of titanium chips and process planning for hybrid process chains. In the first part of the article, a novel process chain for the automatic regrinding of cemented carbide tools is presented. It is shown that production costs can be reduced significantly, as well as the required energy for production of carbide tools. In the second part of the article, approaches for the recycling of titanium chips from machining processes are described. The last part focuses on the resource and energy efficiency of process chains that contain additive and subtractive processes.

Resource Efficient Process Chain Development of a Modular CubeSat Spaceframe

A CubeSat is a 10×10×10 cm cube that can weigh up to 1.33 kg. This design offers a less expensive alternative for space enthusiasts to explore the cosmos, even though the total weight is very limited. For a CubeSat to be allowed to launch, it must adhere to certain specifications outlined in the CubeSat Design Specifications document. This places several restrictions on the satellite in terms of weight, size and center of gravity, and innovative solutions need to be explored during integration to meet these specifications. Having a spaceframe that can easily be assembled and disassembled will help smooth out the integration stage and save a significant time that can then be allocated elsewhere in the developmental stages. The increasing relevance of resource efficient manufacturing is prevalent through the continually rising costs of resources and energy. In order to stay competitive, manufacturers must develop resource efficient process chains to gain an advantage in the market. This study focused on developing a resource efficient process chain to manufacture a modular CubeSat spaceframe. This spaceframe must adhere to the CubeSat Design specifications, as well as meet the customer’s needs. A unique assembly process was designed that eliminated the need for screws structure together. Instead the spaceframe relies on interference fits, and utilizes the unique deployment method of the Poly-Picosatellite Orbital Deployer to ensure that the assembly does not fail. A material selection procedure was utilized, along with resource efficient manufacturing process chains to develop a CubeSat structure that is very cost effective to produce, easily assembled and disassembled and weighed less than most of the market leading CubeSat structures.