Digital manufacturing can produce new and advanced tools more rapidly and at lower cost than traditional manufacturing. This new technology means manufacturers need to develop innovative business models adapted to this change in the manufacturing landscape. With digital manufacturing, companies have both an opportunity and a challenge. They can enter new markets where large-scale production provides competitive advantage. They can enter niche markets that become more attractive as old boundaries and structures lose relevance. Yet their additive manufactured components must meet the same standards set for conventional manufactured components. However, we know little about how companies manage this change as they make the transition from traditional manufacturing to digital manufacturing. This chapter presents two co-creation digital manufacturing projects between university researchers and Swedish companies. In each project, the goal was to develop sustainable and efficient digital production methods that offer tailor-made product solutions. Various technical methods used in the projects are described as materials, and prototypes are developed, tested, and analyzed.

Metrology and characterisation of products' functional surfaces are of key importance in smart and sustainable manufacturing. By proper measures of resulting topography and dimension at the micro-cm level, higher process control can be achieved, leading to more efficient production with products closer to defined targets. Commercial surface metrology systems for lab- and in/on-line applications have increased in the last decades, but the wood sector has not yet benefited from this development. A better understanding of sawn wood topography combined with smart online metrology systems is expected to lead to a substantial reduction of waste in sawmill production, both by transforming waste pieces and sideboards into engineered wood products and by optimising the sawing process (e.g. by using thinner saw blades and reduced tolerances). It would also open new design possibilities and challenge the construction sector to replace today’s materials with renewable raw materials. Additionally, sawmills will be less dependent on incoming timber dimensions. This study is the first step towards a better understanding of sawn wood topography and how relevant surface features can be detected and analysed to enable the next generation of functional wood surfaces for various applications. By identifying the measuring instrument’s capability to capture surface topographical features of sawn wood, this paper discusses the requirements for efficient measurement techniques. It opens for future implementation of machine learning algorithms to in-line monitor and control the machining process. All tested metrology techniques showed promising results. To capture machining marks, the instrumentation needs to have lateral resolutions on the um level and a measurement area covering some cm; thus, the laser scanning system seemed to be a good compromise. © 2024 The Authors.

Manufacturing sector is continuously identifying opportunities to streamline production, reduce waste and improve manufacturing efficiency without compromising product quality. Continuous improvement has been the primary objective to produce acceptable quality products and meet dynamic customer demands by using advanced techniques and methods. Considering the current demands from society on improving the efficiency with sustainable goals, there is considerable interest from researchers and industry to explore the potential, to optimize- and customize manufactured surfaces, as one way of improving the performance of products and processes.Every manufacturing process generate surfaces which beholds certain signature features. Engineered surfaces consist of both, features that are of interest and features that are irrelevant. These features imparted on the manufactured part vary depending on the process, materials, tooling and manufacturing process variables. Characterization and analysis of deterministic features represented by significant surface parameters helps the understanding of the process and its influence on surface functional properties such as wettability, fluid retention, friction, wear and aesthetic properties such as gloss, matte. In this thesis, a general methodology with a statistical approach is proposed to extract the robust surface parameters that provides deterministic and valuable information on manufactured surfaces.Surface features produced by turning, injection molding and Fused Deposition Modeling (FDM) are characterized by roughness profile parameters and areal surface parameters defined by ISO standards. Multiple regression statistics is used to resolve surfaces produced with multiple process variables and multiple levels. In addition, other statistical methods used to capture the relevant surface parameters for analysis are also discussed in this thesis. The selected significant parameters discriminate between the samples produced by different process variables and helps to identify the influence of each process variable. The discussed statistical approach provides valuable information on the surface function and further helps to interpret the surfaces for process optimization.The research methods used in this study are found to be valid and applicable for different manufacturing processes and can be used to support guidelines for the manufacturing industry focusing on process optimization through surface analysis. With recent advancement in manufacturing technologies such as additive manufacturing, new methodologies like the statistical one used in this thesis is essential to explore new and future possibilities related to surface engineering.

Fused Deposition Modeling (FDM) is mostly used to develop functional prototypes and in some applications for end-use parts. It is important to study the surfaces produced by FDM to understand the certainty of process. Truncheon design test artefacts are printed at different print settings and surfaces are measured using stylus profilometer. Taguchi’s design of experiments, signal-to-noise ratio and multiple regression statistics are implemented to establish a concise study of the individual and combined effect of process variables on surface texture parameters. Further, a model is developed to predict the roughness parameters and is compared with experimental values. The results suggest significant roughness parameter values decrease with increase in build inclination and increases with increase in layer thickness except the roughness peak count. © 2018 The Authors. Published by Elsevier B.V

Deemed as one of the established additive manufacturing technique, fused deposition modelling (FDM) is commonly used for creating functional prototypes. Additive manufacturing, in general, generates surfaces that are different compared to conventional manufacturing and consists of features that are either not well-defined or satisfactorily characterized using the existing surface standards. The generated surfaces vary with respect to different techniques, materials, geometries and process parameters Additive manufacturing boosts of manufacturing individualized parts and as claimed, product with complex design can be easily manufactured but the problem lies in manufacturing it with highest surface quality or produce a well-defined robust surface. The aim of the study is to characterize the FDM surfaces generated at different process settings using areal surface parameters. The experimental study includes surface measurements of study sample build at different orientation and layer thickness. A general statistical methodology is implemented to identify the deterministic features on the manufactured surface. The results include topography characterization using the significant features and detailed study on the influence of geometry and process settings on FDM surfaces.

The adverse effects of lead on human health and the recycling problems of copper alloys with lead content has led to the increase in concern for reducing/eliminating the use of lead in brass and other copper alloys. The real challenge prevails in sustainable manufacturing of lead free brass and to maintain as well as control the surface integrity when lead is substituted in the brass with silicon. This article is part of the study that focuses on characterizing the surface integrity of machined lead brass and lead free brass. This paper deals with the study of surface layer characteristics of brass samples, investigating the subsurface deformation influenced by the turning operation. It is important to study the plastic deformation under the machined surface which directly affects the performance of the material on further machining or application. In this study, metallographic investigations are performed on turned samples of lead brass and lead free brass and include comparisons between the study samples based on the plastic deformations quantified by grain orientations and microhardness measurements. The study performed successfully characterizes the subsurface deformation and the results suggest slightly higher subsurface deformation in turned lead brass as compared to lead free brass.

The negative effects of lead on human health and the recycling problems of copper alloys with lead content has led to the increase in concern for reducing/eliminating the use of lead in brass and other copper alloys. Many materials are considered to replace lead in brass; silicon is one such alternative. The real challenge prevails in sustainable manufacturing of lead free brass, to maintain control of the surface integrity when substituting the lead content in the brass with silicon. The investigation includes defined areal surface parameters measured on the turned samples of lead- and lead free brass using an optical coherence scanning interferometer, CSI.This paper deals with the study of surface topography of turned samples of lead and lead free brass. It is important to study the topographical characteristics of the brass samples which are the intermediate link between the manufacturing process variables and the functional behaviour of the surface. To numerically evaluate the sample’s surface topography and to validate the measurements for a significant study, a general statistical methodology is implemented. The results suggest that the surface roughness is higher in lead brass compared to lead free brass and tool coatings have significant influence on the hybrid (Sdr & Sdq) parameters in the surface topography of brass samples.

Manufactured surfaces usually consist of topographical features which include both those put forth by the manufacturing process, and micro-features caused by disturbances during this process. Surface characterization basically involves study of these features which influence the functionality of the surface. This article focuses on characterization of the surface topography of machined lead brass and lead free brass. The adverse effect of lead on human health and the environment has led the manufacturing sector to focus on sustainable manufacturing of lead free brass, as well as how to maintain control of the surface integrity when substituting the lead content in the brass with silicon. The investigation includes defined areal surface parameters measured on the turned samples of lead- and lead free brass using an optical coherence scanning interferometer, CSI. This paper deals with the study of surface topography of turned samples of lead-and lead free brass. It is important to study the topographical characteristics of the brass samples which are the intermediate link between the manufacturing process variables and the functional behaviour of the surface. To numerically evaluate the sample's surface topography and to validate the measurements for a significant study, a general statistical methodology is implemented. The results indicate higher surface roughness in turned samples of lead brass compared to lead free brass. © 2017 IOP Publishing Ltd

Interior automotive plastic components are often manufactured by injection moulding since this technique enables cost-efficient manufacturing, large design freedom, and easy integration of functions. However, to obtain a high-quality impression, it is important to produce components with uniformity in texture, colour, and gloss. Unfortunately, this is rather difficult since a large number of material and processing parameters affect the surface topography and thereby the texture, colour, and gloss. It is therefore important to improve the understanding of how different material and processing parameters affect the surface topography, and in the present study, the influence on surface topography of ABS (Acrylonitrile Butadiene Styrene) and PP (Polypropylene) by melt temperature, tool temperature, and injection speed is investigated by coherence scanning interferometry. Area scale analysis is used to identify the wavelengths of interest, and areal surface parameters are statistically screened to identify robust surface parameters that can be used to discriminate between the surfaces and quantify the influence on surface topography by different material and process variables. Results from the study suggest that tool temperature and injection speed have significant influence on certain surface parameters and, particularly, arithmetic mean height (Sa) and root mean square gradient (Sdq) by approximately 40%, core material volume (Vmc) by 35%, and core roughness depth (Sk) by 50%. These surface parameters are identified as significant and used to discriminate between the sample surfaces. © 2023, The Author(s).

Automotive interior components are produced by injection moulding due to its cost effectiveness in mass production. The surfaces of these components are textured to control the appearance and other surface functional properties such as wear and scratch resistance. Key challenges lie in replicating the features of mould tool with high aspect ratio which are influenced by the polymer and large number of process variables. Hence, to control the aesthetic properties, it is important to improve the understanding of the replication of textured surfaces and its relationship with measured gloss. In this study, the surface topography of PC-ABS samples is investigated using coherence scanning interferometry. Replication of two types- coarse and fine grain surface texture are investigated to identify the effects of tool temperature, injection speed and holding pressure. Areal surface parameters are scrutinized for the quantitative characterization and discrimination of study samples surface topographies. The correlations between process parameters, measured gloss and areal surface parameters are discussed. The results show significant influence of process variables on the replication of surface topography and measured gloss. The grain pattern governed the set of surface parameters selected and the variation in gloss. The process variables are observed to influence different region or distribution of specific surface features represented by surface parameters. © 2023 IOP Publishing Ltd.

Additive Manufacturing (AM) is gaining prominence due to its massive advantage in fabricating components without any geometrical limitations. The most widely used AM technique is Fused Deposition Modelling (FDM). FDM is an extrusion-based AM mostly focused on producing functional prototypes and in some cases as an end-product. One of the most common challenges associated with FDM is its reduced dimensional accuracy and surface quality. A fair amount of research has been carried out to identify the factors affecting print quality and measures to reduce surface roughness. On a few occasions, it is still necessary to achieve higher precision and quality to meet the standards set by conventional manufacturing. Hence, post-processing is employed as an additional step to reach the finish required. This paper focuses on enhancing the surface quality of FDM parts by subjecting it to Acetone vapour smoothening, Shot-blasting and Laser-assisted finishing post-processing methods. A comparative study is presented in this paper, where surface produced by different post-processing methods were compared to the reference injection moulding components. The results suggest that the acetone-based process has the best surface finish compared to the other two means; however, it leaves a very glossy appearance to the part. Shot blasting is very aggressive, and blasting time has a strong influence on the part quality. Laser-assisted finishing slightly ignites the top layer during melting leading to discolouration of the part. The optimum solution was found to be combining the post-processes, which not only reduced the roughness but also enhanced the aesthetic properties of the product. © 2020 IOP Publishing Ltd.

The increasing interest in Additive Manufacturing (AM) is due to its huge advantage in producing parts without any geometrical limitations. It is due to this reason, AM is extensively utilized in automotive, aerospace, medical and dental applications. Despite their popularity, AM is often associated with inferior surface quality which is one of the many reasons why it has failed to fully replace traditional methods. Hence, AM is always followed by a subsequent post-processing step to produce the end-product. To establish control over the surface quality it is first necessary to fully understand the surface behaviour concerning the factors affecting it. In this paper, the focus is mainly on having a better understanding of the surfaces by using scale-sensitive fractal analysis. In addition, the paper documents the influence of build inclination and post-processing in particular shot blasting on surface topography and utilizes a multi-scale approach to identify the most important scale and parameters for characterization. Results of this study reveal that shot blasting has a minimalistic effect on surface features at a large scale as it cannot remove the waviness completely. At smaller scales, blasting imparts additional features on the surface due to the impact of abrasive particles at high pressure. At the intermediate scales, the influence of shot blasting is highest as it successfully eliminates the surface features comprising of partially melted powder particles and stair-step effect. © 2020 IOP Publishing Ltd.

In this paper, an attempt is made to explain the surface texture of Selective Laser Melting (SLM) parts more satisfyingly than the existing methods. Investigations were carried out on the 316L stainless steel SLM samples. To account for most of the surface conditions, a truncheon artefact was employed for the analysis. A Stylus Profilometer was employed as a metrology tool for obtaining the 3D surface measurements. A methodology is proposed to extract and characterize the topographic features of Additive Manufactured (AM) surfaces. Here, the overall roughness of the surface is segregated into the roughness of the powder particles and the waviness due to thermal and the “staircase” effects. Analyzing these features individually results in an increased understanding of the AM process and an opportunity to optimize machine settings.

A major drawback of the optical microscope is its limitation to resolve finer details. Many microscopes have been developed to overcome the limitations set by the diffraction of visible light. The scanning electron microscope (SEM) is one such alternative: it uses electrons for imaging, which have much smaller wavelength than photons. As a result high magnification with superior image resolution can be achieved. However, SEM generates 2D images which provide limited data for surface measurements and analysis. Often many research areas require the knowledge of 3D structures as they contribute to a comprehensive understanding of microstructure by allowing effective measurements and qualitative visualization of the samples under study. For this reason, stereo photogrammetry technique is employed to convert SEM images into 3D measurable data. This paper aims to utilize a stereoscopic reconstruction technique as a reliable method for characterization of surface topography. Reconstructed results from SEM images are compared with coherence scanning interferometer (CSI) results obtained by measuring a roughness reference standard sample. This paper presents a method to select the most robust/consistent surface texture parameters that are insensitive to the uncertainties involved in the reconstruction technique itself. Results from the two-stereoscopic reconstruction algorithms are also documented in this paper. © 2018 IOP Publishing Ltd.

Additive Manufacturing (AM) is increasingly being used in healthcare sectors for its potential to fabricate patient-specific customized implants, and specifically in dentistry, AM finds its applications in maxillofacial implants, dentures, and other prosthetic aids. However, in most applications, AM is largely being used for prototyping purposes. The full-scale realization of AM can only be achieved if the downsides of AM are addressed and resolved. Hence this paper focuses on providing a detailed analysis of surface quality, dimensional accuracy, and mechanical properties of the biocompatible material produced, using the Stereolithography (SLA) method for a dental application. For quality analysis, test artefacts were produced, and the quality was assessed before and after the sterilization process. The results suggest that micro-surface roughness essential for cell growth is similar for all build inclinations and well within the control limit required for effective bone regeneration. Multi-scale surface characterization revealed that the sterilization process involving heat can potentially alter the micro-roughness features of resin-based materials. The results from the dimensional analysis show that the SLA parts produced had negligible dimensional deviations from the CAD model to the printed parts and were unaffected by the sterilization process. The tensile test results suggest that the part orientation does not affect the tensile strength and that the sterilization process seems to have an insignificant effect on the tensile properties of the SLA parts. Furthermore, the results were validated by producing a membrane barrier for Guided Bone Regeneration (GBR). The validation results showed that excess resin entrapment was due to the geometrical design of the membrane barrier. In conclusion, this paper provides an overview of quality variations that can help in optimizing the AM and sterilization process to suit dental needs. © 2023 IOP Publishing Ltd.