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Life Cycle Assessment (LCA) has been used to evaluate the life-cycle Greenhouse Gas (GHG) emissions of pulp and paper production, and most previous studies rely on process-based models for specific product types (e.g., printing paper), industry-average data, or information from a few mills. In this work, a data-mining approach is used to quantify GHG emissions intensities of different paper products manufactured by the U.S. mills. Facility-level emission data collected from publically available governmental databases and mill-level production data collected from the private sector were integrated to track the GHG emissions for different product lines and paper products in mills (in total, 165 mills were matched and analyzed). The results highlight the ranges of GHG emissions intensities by different product groups and categories, and can be used as a transparent data source for LCA practitioners, policymakers, and the pulp and paper industry to perform further analysis on carbon accounting and strategic planning for GHG mitigation. [ABSTRACT FROM AUTHOR]

This paper investigates a Life Cycle Assessment (LCA) based methodology to determine baseline emissions for an aerospace manufacturer. Aerospace manufacturing entails high complexity and low throughput of a vast array of components. Rather than establishing the environmental footprint through waste, electric, and gas data alone; an LCA cradle-to-gate approach extends to a product's raw material acquisition and shipment to provide a comprehensive set of environmental performance indicators. The approach combines several products that follow a similar manufacturing process and can be denoted as a product family. This paper discusses the ability that LCA product families must develop baseline emissions for products validated with a case study of an aerospace component. The methodology can be extended to other product families manufactured within the facility which when combined will accumulate to a site-wide environmental footprint. The paper further evaluates how this methodology can identify environmental hotspots at a process and product level. The aerospace component case study incorporates several manual and automated stages. This work aims to demonstrate the ease of determining baseline emissions using an LCA product family and enable aerospace manufacturing companies to adopt a similar approach to establishing environmental hotspots. This can drive strategic internal change for sustainable manufacturing aligning with company environmental, social, and financial frameworks. [ABSTRACT FROM AUTHOR]

The increasing market share of electric vehicles leads to a growing demand for raw materials such as lithium and cobalt, where the supply situation is fraught with risk. Product-specific challenges regarding high voltage, product state/variance, and labor shortage require flexible automated non-/ semi-/ destructive disassembly. However, there is a need to implement industrial, scalable automation approaches to deal with this problem. This paper addresses the development of a flexible robotic cell for the fully automated disassembly of battery modules from battery systems. The paper presents all required tools and processes for battery diagnoses, machine learning-based object recognition, loosening and removing fasteners, opening sealings, gripping components, separating cables and plugs, and removing the battery modules. Based on this, a sorted disposal/recycling of the material can be realized. Finally, the holistic robot cell, including a safety concept, is described using the example of an actual disassembly process. [ABSTRACT FROM AUTHOR]

The global discourse surrounding plastics has been marked by a profound perceptual schism, also for plastic packaging in the fresh food industry. The public opinion expresses mounting concerns in terms of such plastic packaging solutions. However, in many cases the unique material properties and the well-established methodology of Life Cycle Assessment (LCA) actually demonstrate the environmental advantage of plastics for food packaging. This paper delves into the chasm between the two perspectives, leveraging empirical evidence to resolve the divide. While performing both a consumer analysis and LCA, this paper underscores the potential for innovative, yet practical design solutions to harmonise the public opinion with counterintuitive positive environmental impacts. A transformative design solution that centres around the concept of shape and material renewal is proposed. It demonstrates how a simple, yet effective redesign can enhance both the environmental impact and consumer acceptance in the industry for mass-produced fresh food packaging. It emphasises the role of LCE in design, with a focus on the pre-consumer phase. The findings provide a practical approach, emphasising the need to reconcile theory with consumer desires, to forge a sustainable path forward in packaging design. [ABSTRACT FROM AUTHOR]

In the recent decades, sustainability has emerged as a crucial concern for governments and industries worldwide. While the political sphere appears to take the lead in the pursuit of a greener world from a societal standpoint, industries play a pivotal role in implementing innovative technologies. Certain industries, however, still heavily rely on natural gas consumption for their operations. Metal manufacturers, in particular, face significant energy demands due to their melting processes, which have historically necessitated the use of combustion. This paper focuses on examining the current workflow of secondary aluminum manufacturing, with a specific emphasis on rolled sheet production. By analyzing combustion intensive equipment involved in the process, the paper identifies inherent deficiencies and energy losses throughout the production process and propose strategies that can effectively reduce the industry's global carbon footprint. Results show that optimizing work flow to retain embodied energy and heat of intermediate products, as well as smart waste heat reuse can result in significant savings in secondary aluminum manufacturing. [ABSTRACT FROM AUTHOR]

Sustainable development should meet the needs of the present without compromising future generation needs. While political and standards approaches insist on regulatory directives, this paper proposes a quasi-satisficing methodology considering the sustainability topic within a larger encompassing framework. Starting from three reflections originated by the classical thermodynamics, the effect of knowledge accumulation on the Production Possibility Frontier (PPF), and a model for the human wellbeing in manufacturing ecosystem, this paper proposes a new production model and a heuristic approach to drive the decision process towards sustainable manufacturing. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Over the last years two factors have deeply affected research in Manufacturing: the growing interest around Additive Manufacturing (AM) processes and the need to reduce the anthropogenic environmental impact. As result, a large papers concerning the environmental impact performance of AM compared to conventional processes have been published. Specifically, very complex models accounting for the impact of each life cycle stage of AMed components have been released. Results revealed that AM, at present, guarantees energy savings only within some domains, and the potential saving depends on several factors: product complexity, eco-properties of the material, energy intensity of the material deposition, light-weighting enabled by AM approaches and extent of the use phase. Above all, the result of the comparative analysis depends both on the considered factors and on the selected system boundaries. The already proposed models are very complex and many inventory data are needed, this could make them unapplicable at industrial level. In the presented paper, simplified models are proposed and the performances of these are quantified with varying the analyzed scenario (considered factors and selected system boundary). Results revealed that, for given scenarios, simplified models characterized by low computational effort, can provide reliable results. Guidelines for the implementation of different models with varying the system boundary are provided for the cumulative energy comparison of Electron Beam Melting and conventional turning for the production of titanium alloys components. [ABSTRACT FROM AUTHOR]

This paper discusses the first development of the industrial PhD project research project sponsored by Simonelli Group at Politecnico di Milano, aimed to develop and patent a heating system technology that enhances the energy efficiency of professional coffee machines. This paper crosses the issue of the sustainable design of products through a qualitative life cycle assessment on three professional coffee machines of Simonelli Group. The LCA analysis considers the manufacturing, use, and disposal phases. The analysis was performed using the Simapro software that integrates the Ecoinvent3 database. The life cycle impact assessment is carried out in accordance with other case studies in the literature, relying on the parameter "GWP" in accordance with the IPCC method. Laboratory tests are used to assess the kWh of energy consumed during the use phase of professional coffee machines. Following that," use phase scenarios" were created for the life cycle impact assessment, based on existing scenarios in the literature, and elaborated with the company's marketing support. The findings indicate that the most critical environmental phase is the use phase and that the heating elements are the most energy-consuming items in professional coffee machines. Click here and insert your abstract text. [ABSTRACT FROM AUTHOR]

Industrial technologies have evolved towards circular-oriented manufacturing. New approaches in the management of production systems are needed to guarantee the success of such a circular approach. This paper identifies three research questions related to the complexities of decision-making within CEs and defines the concept of Green Gateways in the circular economy. A Green Gateway is a type of decision that supports to realizing the full potential of products and materials. Indeed, the potential value of products and materials must be assessed and leveraged and the concept of Green Gateway will be useful to identify common decisions and to define a common framework in the future. The integration of digital information and digital twins of products, processes, and circular value and supply chains emerges as a key factor in guiding decision-makers effectively, especially for Green Gateways where adequate information, tools and methods must be used to manage value retention options, product flows, production and pricing decisions jointly with the multiple objectives of profitability and sustainability. Additionally, this paper explores specific examples of circular economy use cases, drawing attention to their similarities and highlighting key insights. [ABSTRACT FROM AUTHOR]

Current challenges such as climate change, the limits of natural resources, and increasing customer-specific sustainability demands require a transformation of value creation. The aim is to move from global sourcing to more local value creation by creating synergistic energy and circular material flows and making better use of capacities while taking urban structures into account. This paper discusses an approach of Smart Glocal Production that combines spatially networked production in global enterprise networks. Based on a literature review, examples of Smart Glocal Production in Germany and Austria are presented. The core of the paper is a novel assessment approach for manufacturing companies to determine their readiness level for glocal production. On this basis, smart measures can be derived with special consideration of digitization initiatives to support manufacturing companies on their way to a more sustainable value creation in industrial areas. [ABSTRACT FROM AUTHOR]

The upscaling of technology encompasses many facets a designer concerned with reducing environmental impacts must manage. Therefore, previous research proposed an environmental assessment for upscaling (EAU) methodology. This method hinges on Life Cycle Assessment (LCA) approaches (e.g., prospective, absolute) and coordinates the environmental modelling from an ecodesign perspective. The originality of this paper is to present an illustrative application on photovoltaic systems. The focus is on the modelling practices (step 3 of the method) using upscaling design levers and generating parametrized scenarios meant to be interpretable for a design team. Examples of data collection and upscaling modelling are provided for the upscaling of silicon-based photovoltaic technology in France from 2021 to 2050. This case study shows that integrating upscaling parameters, such as industrial process evolutions, the technology deployment strategy, and the socio-technical context associated with the technology upscaling phenomenon influence LCA results significantly. The paper, therefore, discusses recommendations for design teams to support them in assessing the environmental implications of their technology choices. [ABSTRACT FROM AUTHOR]

With Industry 5.0 on the horizon, research and innovation is prioritising the transition to sustainable, human-centred and resilient manufacturing. In this context, Zero Defect Manufacturing (ZDM) strategies combine tools, resources and rules with the aim of avoiding defects and increasing the sustainable performance of complex manufacturing systems. Five distinct strategies for ZDM have been identified in the literature: (I) detection, (II) prediction, (III) prevention, (IV) repair, and (V) mitigation or compensation. The main motivation of this paper is to discuss an extension of these five existing dimensions by three more, which will enable the transformation of classical ZDM towards a more sustainable production. The main objective of this paper is to conduct a systematic literature review that covers the state of the art of ZDM and highlights the need to add the three (Zero3) dimensions: i) Zero Resource Loss (resource and emission improvement) ii) Zero Human Potential Loss (productivity and stability improvement) iii) Zero Data Gap (increase in efficiency of data use). [ABSTRACT FROM AUTHOR]

The push to decarbonize has spurred the demand for clean energy technologies such as electric vehicles (EVs) and wind turbines (WTs). These technologies rely on rare earth permanent magnets (REPMs), namely Neodymium-Iron-Boron (NdFeB) magnets that in turn rely on rare earth elements (REEs), including Neodymium (Nd), and Dysprosium (Dy). As the demand for clean energy technologies increases, so will the demand for Nd and Dy-containing REPMs. Both Nd and Dy are critical elements that are prone to supply chain risks. As our reliance on them increases, it becomes essential to anticipate future market dynamics for these elements. This paper aims to address the current gap in the literature in the context of forecasting future Nd and Dy demand quantities. The Bass Diffusion Model is a widely used approach to forecast the adoption of new products or technologies and, to predict demand trends. Over the years, the model has found applicability in a wide variety of sectors including consumer durables, medical services, and agricultural innovations. This paper demonstrates the use of the Bass Diffusion Model to estimate future global Nd and Dy demands, enabling a better understanding of swiftly evolving clean energy technology and REPM-related market dynamics. [ABSTRACT FROM AUTHOR]

The problem of effectively managing Configuration Lifecycle Management (CLM) processes for customizable products in the manufacturing industry presents challenges in striking the right balance between product customization and standardization, particularly for complex products like wind turbines. This paper addresses this issue through a comprehensive analysis and enhancement of CLM processes in a case company that manufactures, install, and service energy solutions focusing on wind turbines. This paper addresses the challenges in CLM processes through a comprehensive analysis and enhancement within a case company specializing in the manufacturing, installation, and servicing of energy solutions, with a specific emphasis on wind turbines. Specifically, within the CLM framework, the study delves into the Input Signal Management (ISM) process, addressing challenges associated with handling specific requirements, features, or functionalities that customers or stakeholders want in the product. The study maps the current state of the processes, identifies weaknesses, and proposes two suggestions to enhance the so-called Input Signal Management (ISM) process. The ISMs are the specific requirements, features, or functionalities that customers or stakeholders want to be included in the product. The challenge in the ISM process lies in handling a large number of requests, ensuring consistency, avoiding conflicts, and making timely decisions. Hence, the paper proposes two key enhancements to the process: the development of guidelines for data creation and categorization of ISM requests, and the prototyping of a Natural Language Processing (NLP)-based system for expedited request assessment. The paper emphasizes the significance of optimizing CLM processes for effective configuration management. Incorporating data-driven methods, the ISM process can become agile, efficient, and customer-centric, leading to better management of customization, reduced response times, and increased customer satisfaction. [ABSTRACT FROM AUTHOR]

Since the machining of complex aerospace components, like integral compressor-rotors (blade integrated disks), is very cost-intensive, optimizing the process by means of process simulations is an active field of research. With the rise of Quantum Computing, a new instrument with high optimization potential is moving into focus. In this paper, a possible application of Quantum Computing for the machining simulation of multiaxis milling of thin-walled aerospace components is discussed. For this reason, a simulation framework used for the milling simulation is analyzed and each component is evaluated separately in relation to Quantum Computing. Parts of the Harrow, Hassidim, and Lloyd algorithm are proposed to enhance the Finite-Element simulation-based component, like the modal analysis for dynamics simulation. This algorithm can solve linear system problems with exponential speed-up over the classical method. The paper presents a roadmap on how the classical steps of a modal analysis for dynamics simulation could be replaced by quantum algorithms based on quantum phase estimation. The implementation of the first working steps is presented to validate this approach. The linear system problem, arising from the dynamics simulation, is analyzed in detail and a minimal value problem of linear coupled oscillators is derived. [ABSTRACT FROM AUTHOR]

In machine hammer peening, an actuator system moves a ram in oscillating motion, which is oriented in angular position, preferably perpendicular, to a workpiece surface. On the tip of the ram, a hammer head with application specific shapes can be mounted. The hammer head is moved across the targeted workpiece surface area by means of a machine tool or an industrial robot. The impacts in defined patterns enable modifications of the surface integrity like smoothing the surface roughness or increasing fatigue strength by induced compressive residual stresses. This paper presents a novel DC-driven actuator system using a highly dynamic short-stroke linear reluctance motor to provide a time or trigger controlled hammer head movement including a system for process monitoring. In contrast to conventional systems, Deterministic Impact Peening (DIP) can be realized by position or speed related triggering of the impacts. The reluctance-based actuator with its geometrically optimized mechatronic system design provides performance characteristics favorable to known machine hammer peening systems. The position-controlled triggering of the hammer head is able to achieve uniform or defined local elastoplastic deformations on the workpiece surface, thus resulting in deterministic residual stress distributions. [ABSTRACT FROM AUTHOR]

The surface topography of workpieces is generated by and related to the manufacturing process. The blasting process specifically leads to dimples caused by accelerated particles hitting the surface. As the number of impacts increases over time, the surface topography changes. The scope of the study was to find a suitable areal roughness parameter or parameter set that correlates with this change. Additionally, the optimal time for creating a uniformly covered surface was analyzed. To conduct the research, an automated blast wheel process was applied. The workpieces were set on a rotating carrier with the spin wheel in the middle to ensure uniform coverage. 1.4301 steel specimens were blasted with spherical blast media at a spin wheel speed of 9000 min-1. The time varied between 1 and 20 minutes. The areal measurement was carried out by confocal microscopy. After obtaining the areal surface data, areal roughness parameters according to ISO 25178-2 and additional parameters based on motif analysis were calculated. For each measurement, 75 parameters are analyzed. The paper will present the applicability and correlation of the chosen parameters to the various blasting times. [ABSTRACT FROM AUTHOR]

This paper investigates the surface texture on trapezoidal thread flanks manufactured by whirling, which is used for machining long threaded spindles. An analytical and numerical approach for describing surface texture is compared, and texture parameters are developed based on existing methods. Although the analytical model provides a good description of texture height and length, it has limitations in representing the surface as a topography. In contrast, the numerical approach enables detailed modeling of the surface topography on the thread flank as a function of the process parameters. The effective number of flank cutters is found to significantly influence the resulting topography, leading to differences between the measured values and the analytical model within a specified investigation range. Using a material removal simulation, this effect could be explained by the flank cutter position error. In addition, material removal simulation offers great potential for optimizing the surface texture on thread flanks and for tailoring tribologically optimized surfaces in the whirling process. [ABSTRACT FROM AUTHOR]

The paper deals with a novel method for the edge preparation of cutting tools using an advanced approach. Cemented carbide cutting inserts were used as a sample in the experiment, and were prepared using plasma discharges in electrolyte. This technique is an environmentally-friendlier method in contrast to electropolishing treatment. The experiment aimed to determine the influence of process parameters of plasma treatment on the material removal rate and cutting edge radius size. In the experiment, concentration of electrolyte, voltage between electrodes, temperature of electrolyte, and operating time were varied. The material removal rate and cutting edge radius size increased faster with the decreasing concentration of electrolyte, decreasing voltage, and decreasing temperature of electrolyte. The material removal percentage increase was 155 percent, and 57 percent for cutting edge radius size during the 10 seconds of operation time in the specified range of process parameters. This change can be achieved by setting various process parameters. The results of the experiment proved that plasma treatment can control the forming of cutting edge radii. Cutting edge preparation using plasma discharges in electrolyte takes only a few seconds, depending on the cutting edge radius sizes. [ABSTRACT FROM AUTHOR]

The aim of this paper is to improve surface and subsurface workpiece properties in steel grinding by using nearly spherical ceramic grains in an elastic bond system. To characterize and evaluate the potential of this rather new tool concept, the resulting workpiece microtopography and the subsurface characteristics are analysed and cover residual stresses, micrographic cross sections, and EBSD images. The results include the effect of the different process parameters on increased mechanical process loads resulting in favorable surface properties characterized by mechanically induced plastic deformation and compressive residual stresses. With regard to the metallographic analyses, an increased grain refinement was identified in micrographs and EBSD images, which results from the changed chip generation mechanisms. The sum of the above effects shows an increase in the residual compressive stresses introduced into the workpiece. This reveals the potential of spherical ceramic grains in an elastic bonding system. [ABSTRACT FROM AUTHOR]

Powder metallurgy (PM) processed nickel-based superalloys are increasingly employed in the hot section of gas turbine engines for parts such as high-pressure (HP) compressors and turbine rotor discs over more traditional cast and wrought options such as Inconel 718 due to its improved high-temperature properties. In this paper, the surface integrity and geometrical/dimensional accuracy of holes initially rough drilled using worn tools and subsequently finish plunge end milled in a proprietary PM-processed Ni-based superalloy, were assessed and compared. The influence of tool wear on hole quality after finish plunge end milling was also investigated. Significant improvement in hole quality was evident following finishing with reductions in surface roughness (up to ~86%), subsurface microhardness (up to ~125 HK 0.05) and workpiece microstructure deformation/damage (up to ~80% in terms of average depth) compared to corresponding rough drilled holes. Evidence of chatter marks on holes machined with worn plunge end mills was observed, despite exhibiting reduced surface roughness levels (~45-73%). Generally, somewhat improved hole surface integrity (reduced subsurface deformation by ~47-64%) and geometrical accuracy (circularity decreased by ~10-25%) were produced when employing new tools. [ABSTRACT FROM AUTHOR]

The in-process detection of grinding burns has earned considerable interest from both researchers and industries in recent years. Various Non-destructive testing (NDT) technologies, including Eddy Current (EC), Barkhausen Noise (BN), and Acoustic Emission sensors (AE), have been employed to address this issue, yielding successful results for specific applications. However, a comprehensive understanding of burn generation and its prevention in grinding operations remains an area of interest that has not yet been fully resolved. This paper focuses on investigating the electromagnetic response of a custom-made EC sensor applied to UNE F-522 (AISI 01) steel during in-process inspections. Experimental grinding tests have been performed using a special EC inspection head installed in the grinding machine. The impedance change of the material during grinding is discussed in terms of the machine out-puts (Power consumption) and other grinding variables, such as number of passes, the roughing stock removal, and the finishing strategy. The experimental results demonstrate that the proposed EC technology not only enables the detection of burns, but also enhances comprehension of the surface integrity changes occurring during the grinding process. [ABSTRACT FROM AUTHOR]

Deep rolling is a conventional machining process used to modify the surface and subsurface properties of components. It entails subjecting a component's surface to controlled plastic deformation through the application of mechanical forces. This technology is important in various technical fields, as it offers the possibility of improving the mechanical properties and performance of components. In the case of mechanical deep rolling tools, the deep rolling force is modified by altering the roller's position through displacement of the machine axis. When dealing with the deep rolling of hybrid components consisting of multiple materials, a highly dynamic change of the deep rolling force is required in the material transition zone for adapting the deep rolling force to the different materials. Therefore, a piezo-actuated deep rolling tool was developed to enable a precise and dynamic deflection of the rolling element. The paper focuses on the application behavior of this new tool. For this purpose, the influence of the rolling element's highly dynamic actuation on rolling force, tool temperature, and surface topography as a function of different material properties were investigated. Within the framework of these investigations, correlations between actuation frequency, amplifier amplitude, deep rolling force, as well as the resulting surface and subsurface properties were identified. [ABSTRACT FROM AUTHOR]

Polycrystalline diamond (PCD) is an important material in the tool industry due to its superior wear resistance and strength. Picosecond laser machining enables accurate cutting, geometric profiling, and precise dimensional features to be produced on PCD. The industrialisation of this manufacturing process necessitates the development of laser systems and process strategies that facilitate high throughput and quality. This paper investigates the feasibility of using a 300 W picosecond laser to machine PCD. It examines the influence of fluence, average power, pulse duration and number of passes on the material removal rate and surface quality. The surface integrity after machining is ascertained using a surface profilometer, optical microscopy and Raman spectroscopy. The results have shown that a high material removal rate of 33 mm3/min (0.11 mm3/min W) at a surface roughness of 2.3 μm is achievable using a fluence of 0.9 J/cm2 at 41.3 MHz and 300 W average power. Raman's analysis of the machined sample suggests a laser-induced graphitisation which is prevalent at high pulse overlap, peak power, and the number of passes. Overall, the study strengthens the idea that with optimised process parameters, a balance is established between productivity and high surface integrity. [ABSTRACT FROM AUTHOR]

The relationships between machining conditions, boundary layer and mechanical component functionality are known qualitatively for selected Wire Electrical Discharge Machining (Wire EDM/WEDM) applications and continuous further developments of this manufacturing technology minimize the thermal influences significantly. Nevertheless, the use of WEDM processes has so far been severely limited in safety-critical applications, especially in the field of turbomachinery construction and aerospace. For example, the removal of the generated surface layers is often still mandatory, although cutting processes can also leave a distinct thermo-mechanically influenced rim zone on the component. This conservative approach currently unnecessarily reduces the manufacturing potential of WEDM processes considerably and calls for an objective comparison of component function. In this paper, therefore, the flexural bending fatigue strengths of differently wire-eroded surfaces based on roughing-finishing sequences and optional post-processing treatment are compared with industrially established reference process chains. [ABSTRACT FROM AUTHOR]

Thin-walled aluminium components used in the structure of aircrafts are subjected to fatigue loads. Fatigue performance of those components is affected by the surface integrity generated in the last machining step. This paper proposes an analytical model to identify the fatigue crack initiation site considering the surface topography, residual stresses (RS) and mechanical properties induced by machining. To validate the model fatigue samples of aluminium 7050-T7451 were prepared by face milling. Machining-induced RS were measured by hole-drilling and the surface topography of the gauge region of the fatigue samples was characterised using a confocal microscope. Then, uniaxial fatigue tests were done at R = 0.1 and subsequently the fracture was analysed. The model predicted nucleation of cracks at the surface when the stress amplitude was above 290 MPa. Fatigue tests done at an amplitude of 350 MPa confirmed crack initiation at the points with the highest stress concentration predicted by the model. By contrast, the cracks were nucleated at the side of the samples when the stress amplitude was below 290 MPa. In fact, compressive RS induced by face milling protected the surface from crack nucleation at lower applied stresses as predicted by the model. [ABSTRACT FROM AUTHOR]

Additive manufacturing processes for the production of large structural components, such as wire arc additive manufacturing (WAAM), offer great manufacturing potential due to their flexibility and design freedom, e.g. for the automotive industry. In order to achieve the desired surface and properties of the surface zone, additive manufacturing is usually followed by mechanical finishing. In this paper, the influence of the process parameters during WAAM and deep rolling (DR) on the residual stresses and the lifetime of AlSi12 components is investigated. Knowledge of the interactions between the process parameters in WAAM and DR as well as their effect on the surface zone properties and the application behavior is elementary. This enables the prediction of the component properties and quality. With the help of the appropriate selection of the process parameters, the residual stress state and the service life can be increased in such a way that components with high fatigue strength can be manufactured. This results in an average increase in service life of up to 17.8 times. [ABSTRACT FROM AUTHOR]

Destructive testing methods, such as Vickers hardness test or hole drilling methods for residual stress evaluation have long been conventional approaches in manufacturing to investigate surface integrity and are widely being used in industry to date. However, their limitations in terms of material damage and high costs have spurred the exploration of non-destructive testing alternatives like Barkhausen noise analysis. So far almost exclusively data-driven and empirical models have been used to employ Barkhausen noise analysis as a non-destructive testing method in manufacturing. These models provide valid predictions for the manufacturing process and the specific material studied. However, they lack the capability to be generalized to other process conditions and materials. Physics-based models on the other hand provide the generalizability needed for widespread industrial applications. This strength turns out to be a weakness when trying to extract residual stress or microstructural properties from these models. The goal of this paper is, to provide an overview of published data-driven models in literature with thematic relevance to manufacturing processes and to propose a new, generalizable model. [ABSTRACT FROM AUTHOR]

Inconel 718 represents a large portion of high-temperature metals in key industries, where the machining-induced surface integrity is quite important. As the different grain size results in various densities of grain boundaries in the deformed area, the surface integrity can be significantly affected. This paper studies the effect of workpiece grain size on machining-induced surface integrity when cutting Inconel 718. Workpiece materials with fine or coarse grain features are prepared with various heat treatment methods. Orthogonal cutting experiments are conducted with uncoated carbide tools under different cutting speeds (20 - 100 m/min). The cutting force results indicate that Inconel 718 with larger grain size will cause lower cutting forces and the percentage reduction approximately ranges from 20 % to 33 %. An interesting phenomenon is found that the workpiece with coarse grains exhibits large-scale geometrical defects due to tearing within the grains at low cutting speed (v c = 20 m/min). This phenomenon can be diminished if the cutting speed v c is increased to 60 m/min. In addition, the subsurface deformation layer is reduced with decreasing workpiece grain size due to the barrier effect of grain boundary on plastic deformation. [ABSTRACT FROM AUTHOR]

Challenges in drilling nickel-based superalloys, such as Inconel 718 (IN718), are multifaceted. High requirement of hole surface quality in drilling such alloy must deal with extreme material properties and complex process condition in drilling operation. This paper presents an experimental investigation on the effect of PVD coated solid carbide drills under different internal cooling schemes on hole quality in drilling IN 718 alloy. Three types of solid carbide drills were used in the series of drilling experiments, including PVD coated and uncoated drills, and different design in the number of internal cooling channels, two channels and four channels. The objective of the investigation is to assess the effect of coating and efficiency of internal cooling on surface quality in drilling IN718 alloy. Surface quality on drilled holes in terms of roughness, burr formation, subsurface deformation and strain hardening has also been measured and analyzed on the machined specimen. The roughness and burr size on drilled holes demonstrated little differences among the three types of testing drills. Surface roughness was severely deteriorated by the chip trapped in the hole leaving scratch and smears on the surface. Nevertheless, the scheme of internal cooling channels and PVD coating exhibited noticeable influence on quality of drilled hole surface. [ABSTRACT FROM AUTHOR]

In the metal cutting process, a substantial portion of the mechanical energy in the cutting zone is transformed into heat, causing a rapid rise in temperature. The uneven distribution of temperature results in workpiece distortion, leading to reduced machining accuracy. As the demand for higher product quality increases, the prediction of cutting temperature and compensation for thermally induced deformations has become a crucial area of research. This paper introduces a novel experimental setup that enables in situ monitoring of process temperature using infrared thermography. Through the analysis of experimental data, a numerical model is proposed and calibrated to quantitatively predict the temperature evolution in the workpiece. The derived model facilitated the prediction of workpiece distortion, and the results can enhance machining accuracy by integrating contour correction. The developed approach offers valuable insights into mitigating the adverse effects of temperature-induced distortions in turning operations. [ABSTRACT FROM AUTHOR]

Metal matrix composites (MMCs) show enhanced mechanical and physical properties compared to monolithic alloys, which make them attractive for various engineering applications. However, their actual use in industry is limited due to their low machinability. The hard reinforcements present in the matrix may lead to high tool wear and poor surface integrity. In this context, the paper aims at studying the drillability of an Al-SiC MMC when using DLC-coated tungsten carbide tools at varying feeds. After the machining trials, a quantitative evaluation of the tool wear as well as the analysis of the hole surface roughness and damage was carried out. The results demonstrate that, at increasing feed, the tool wear, surface roughness, and surface defect density decrease, leading to the counterintuitive conclusion that increasing feed when drilling causes an increase in the MMC drillability. [ABSTRACT FROM AUTHOR]

The reliable detection and precise assessment of white etching layers (WEL) are key challenges in the investigation of a component's surface integrity. This paper proposes an innovative methodology for evaluating the extent of WEL in quenched and tempered steels, machined by Boring and Trepanning Association (BTA) deep hole drilling. Micrographs obtained by light microscopy were partitioned into classes by three methods, separating the WEL from the base material and the embedding resin. Traditional manual segmentation was performed as a benchmark for automatic segmentation methods. A gray level thresholding-based method served for the segmentation of micrographs partitioned into subsets. In addition to conventional manual and thresholding-based segmentation, a machine learning-based approach for image segmentation was applied. The segmented images were further analyzed by a newly developed set of algorithms, implemented to obtain detailed information on the WEL, e.g. their average thickness as well as the area covered by WEL in the micrographs. Results indicate that both, gray level thresholding, as well as machine learning-based image segmentation, show potential for the automated diagnosis and assessment of WEL. They both yield quantitatively similar, but less biased results compared to manual segmentation. [ABSTRACT FROM AUTHOR]

Laser cleaning technology is a promising technology for selective removal of coatings from substrates to facilitate re-use and recoating. A leading coating of interest for reduced friction and operating forces is Diamond like Carbon (DLC) coating. This paper reports on the energy requirements and associated unit process scope 2 emissions for the DLC laser removal process to facilitate re-use of tooling in a circular economy. This work can assist in providing a greater understanding of the energy requirements and of energy consumption and emissions reduction strategies for the DLC removal process. This is important for the transition to net-zero emissions in manufacturing. [ABSTRACT FROM AUTHOR]

By integrating data-driven analysis methods into existing procedures, quality and failure management performance can be increased systematically. Linking product and process data with existing failure and quality knowledge offers significant potential for enhancing the continuous improvement of processes and products. Nevertheless, the potential of data-driven analysis still needs to be fully exploited. Despite the apparent advantages of analysis-oriented approaches, many companies are hesitant to implement such transformation projects because quantifying possible benefits is challenging. Thus, there is an economic risk due to the limited availability of resources, which must be utilized purposefully. An approach that allows the systematic identification and prioritization of promising use cases and reduces the risk of introducing data-based approaches is missing. This paper conceptualizes a model to evaluate the potential for introducing data-based analysis in production processes. A maturity assessment, consisting of four dimensions and seventeen sub-dimensions, is presented, which enables the identification of promising use cases for implementing data-based approaches. The conceptualized model is validated using an expert survey. [ABSTRACT FROM AUTHOR]

Strategic planning of industrial systems has become increasingly challenging for decision makers at different production levels, due to everal aspects, such as global competition, market uncertainty and volatility, and changing regulations. These evolving aspects often lead to unplanned and high-effort reconfigurations of systems. Additionally, high-paced innovation in industrial technologies and the diffusion of software, data analytics, and big data technologies in industrial systems, while potentially supporting ever smarter, safer, and greener decisions, also challenge decision makers, as often multi-disciplinary knowledge is required to successfully plan and operate increasingly complex systems. Existing literature provides little guidance on how strategic planning of industrial systems is expected to evolve in order to fully exploit advanced industrial technologies to responsively and cost effectively respond to global challenges. To fill this gap, this paper reviews existing literature on industrial systems' planning and reconfigurability and derivesmulti-sectorial requirements. Based on the findings, a life cycle conceptualmodel for strategic planning of reconfigurable industrial systems and value chains is provided. Moreover, the concepts of hierarchical interfaces, functional interfaces, and reconfigurability bottleneck are introduced and directions for future research are accordingly outlined. [ABSTRACT FROM AUTHOR]

The increase in global material demands while having finite natural reserves has made the transition from a linear to a Circular Economy (CE) more crucial. Various approaches have been proposed for such a transition, which closed-loop system is an approach aiming to maximize resource efficiency ensuring that materials are continually reused and recycled, thereby reducing waste and conserving resources. However, there are some obstacles/gaps in the implementation of CE practices, one of them is the lack of a proper Circularity assessment unit, as called Circularity Indicators (CIs). The CIs play a crucial role by enabling to quantify the success of circularity strategies. This paper critically reviews the existing CIs and introduces a novel scoring system that evaluates them against five main circularity categories. This scoring system allows for assessing CI's alignment with core CE principles. Our findings reveal that some CIs demonstrate broad applicability and robustness, while others have more narrowed focuses. This dementated the need for a unified CI that is versatile, comprehensive and integrates various 'R' strategies with the triple bottom line model of sustainability. This scoring system can be used in policy making and business strategy decisions to embed CE in new developments such that support sustainable development. [ABSTRACT FROM AUTHOR]

The industrial transition towards sustainable production systems is a fundamental step for companies to achieve environmental, social and economic goals. This transition includes implementing sustainable practices across the entire value chain, by which sustainability management can quickly become data intensive and increasingly complex. The integration of digital solutions into sustainability management can massively increase the efficiency of data collection and aggregation, prevent errors and data inconsistencies, besides further supporting industrial decision-making based on sustainability data evaluation. This paper presents a case study with a manufacturing company in the German state of Baden-Württemberg, in which its sustainability management system is evaluated and screened for digital optimization opportunities. The development and creation of a digital solution concept is comprised of the initial assessment through a detailed requirement analysis, then a systematically determination of an information system architecture that fulfills all requirements and can be implemented to improve the sustainability performance of the company. This developed approach assists the company to reach environmental reporting obligations through the continuous evaluation of internal sustainability KPIs. The insights gained and the developed concept can further support other companies in making their sustainability management more efficient and transparent through digitalization. [ABSTRACT FROM AUTHOR]

Several factors are influencing the spread of Electric Vehicles (EVs) in the automotive market. However, while battery-electric vehicles emit no tailpipe emissions, the manufacturing phase, particularly the manufacturing of the battery packs, can have significant environmental impacts. In addition, as the EV market expands, there will be a significant increase in demand for critical materials used in lithium-ion batteries, such as lithium, cobalt, and nickel. These materials are essential for producing high-performance batteries, and their global demand is expected to rise rapidly to meet the demands of the expanding market. This paper investigates the main challenges that need to be tackled to reach a sustainable path in the battery industry. A cradle-to-gate boundary is set to focus on raw material extraction, production of precursors, cell and module production, and battery pack assembly. In addition, because 7.8 million tons of EV batteries per year are expected to reach the end-of-life phase by 2040, a brief overview of the recycling issue is provided to investigate the potential usage of recycled material in the early stages of battery production. [ABSTRACT FROM AUTHOR]