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Additive manufacturing (AM) technologies have been evolved over the last decade, enabling engineers and researchers to improve functionalities of parts by introducing a growing technology known as multi-material AM. In this context, fused deposition modeling (FDM) process has been modified to create multi-material 3D printed objects with higher functionality. The new technology enables it to combine several types of polymers with hard and soft constituents to make a 3D printed part with improved mechanical properties and functionalities. Knowing this capability, this paper aims to present a parametric optimization method using a genetic algorithm (GA) to find the optimum composition of hard polymer as polylactic acid (PLA) and soft polymer as thermoplastic polyurethane (TPU 95A) used in Ultimaker 3D printer for making a rectangular sample under flexural load in order to minimize the von Mises stress as an objective function. These samples are initially presented in four deferent forms in terms of composition of hard and soft polymers and then, after the optimization process, the final ratio of each type of material will be achieved. Based on the volume fraction of soft polymers in each sample, the equivalent topologically-optimized samples will be obtained that are solely made of single-material PLA as hard polymer under the same flexural load as applied to multi-material samples. Finally, the structural results and manufacturability in terms of the generated support structures, as key element of some AM processes, will be compared for the resultant samples created by two methods of optimization.

Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of −7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study. publishedVersion

The aim of the paper is to review the trends on low-cost open-source Internet of Thing (IoT) in the Framework of Industry 4.0. We hypothesize that open source IoTs benefits small and medium sized (SME) manufacturing companies to help them tackle economical and technical barriers for technology adoption at factory floors. This research reviews the state of the art of open-source hardware and software and identifies the challenges of open-source IoT by compiling scientific literature and relevant online resources. The methodology is twofold: (i) we use a grey literature review including online information, and (ii) we complement the analysis by a structured keyword search using IEEE scientific repository. The study finds that open source is and will be an essential part of developing Industry 4.0 solutions and its integral constituent, Industrial Internet of Things systems (IIoT). However, there are challenges to overcome, such as interoperability and reliability. publishedVersion

Interoperability is one of the biggest challenges in IoT. There is a need to connect tools and services from different platforms to improve performance and flexibility as well as to get rid of vendor-locks. Moreover, fully established practices to classify IoT systems to support the development of multi-platform systems have not been grounded. This paper addresses these issues on a two-fold approach. Firstly, by introducing a classification that is based on the tasks performed in IoT system. Secondly by proposing a conceptual middleware to connect different IoT platforms as for a possible solution for interoperability issues in IoT. publishedVersion

Direct foam writing allows the fabrication of highly porous and hierarchical ceramic structures with high specific mechanical properties. This manufacturing technique, however, has mainly used stabilized Al2O3 foam inks. In this work, we pressent a novel foam ink based on TiO2. This ink uses polyvinyl alcohol (PVA) as a binder and a small amount of zinc as a frothing agent. We used this ink to produce cylindrical foam samples via direct foam writing. The foams had a porosity of up to 65% and a mean pore size of 180 μm, which is significantly larger than previously reported for direct foam writing with Al2O3. The foams were tested in compression and were found to have an elastic modulus of 4–6.3 GPa and a compressive strength of 92–112 MPa. These mechanical properties are similar to those of porous ceramics produced by conventional manufacturing routes. Therefore, this work represents a step forward by broadening the direct foam writing process to a wider range of porous ceramics.

Funding Information: We gratefully acknowledge the support of the Aalto University seed funding for the DEMINFUN-project ( 974110 ). Frans Nilsén also acknowledges (in part) support by Operational Program Research, Development and Education financed by European Structural and Investment Funds and the Czech Ministry of Education, Youth and Sports (Project No. SOLID21 - CZ.02.1.01/0.0/0.0/16_019/0000760 ). Publisher Copyright: © 2021 The Authors Laser powder bed fusion (L-PBF) is used to produce foam-like Ni-Mn-Ga with tailored microscale and mesoscale features. Ni50-Mn28.2-Ga21.8 (at%) powder was gas atomised and processed in an L-PBF system with a range of energy density from 26.24 and 44.90 J/mm3. We characterised microscale and mesoscale properties, such as the chemical composition, crystal structure, magnetisation measurements, density, and porosity measurements as a function of process parameters, in a systematic design of experiment. Preliminary research on macroscale properties included tensile testing and magnetic field induced strain (MFIS) measurements. Results show how controlling process parameters allows tailoring the Ni-Mn-Ga polycrystalline microstructure. Hence, obtaining twinned martensitic structures with a predominant orientation going across the visible grain boundaries. All the processed samples showed a 56 Am2/kg magnetisation level, close to Ni-Mn-Ga 10 M single crystals. Mesoscale results show a distinctive porosity pattern that is tailored by the process parameters and the laser scanning strategy. In contrast, macroscale mechanical tensile test results show a brittle fracture of Ni-Mn-Ga due to the high porosity with yield stress 2–3 times higher than shown in single crystals. In sum, we built geometrically complex demonstrators with (i) microscale twinned martensitic structures with a predominant orientation going across the visible grain boundaries and (ii) mesoscale tailored periodic porosity patterns created by modifying power, scanning speed, and scanning strategy systematically. L-PBF demonstrates great potential to produce foam-like polycrystalline Ni-Mn-Ga, reducing grain boundary constraints and thus the magnetic force needed for MFIS.

The scope of this research is to characterize and optimize the vibration-assisted ball burnishing of additively manufactured 18% Nickel Maraging steel for tooling applications. We evaluate the suitability of vibration-assisted ball burnishing as an alternative method to post-process additively manufactured tool steel. To do so, we assessed a single pass post-processing technique to enhance surface roughness, surface micro-hardness, and residual stress state. Results show that ultrasonic burnishing after age hardening functionalizes additively manufactured surfaces for tooling applications creating a beneficial compressive residual stress state on the surface. The surface micro-hardness (HV1) varied between 503 and 630 HV1, and the average surface roughness (Ra) varied between 1.31 and 0.14 µm, depending on process parameters with a maximum productivity rate of 41.66 cm2/min making it an alternative approach to functionalize additively manufactured tool components.

Purpose The purpose of this paper is to investigate the technology, business and intellectual property issues surrounding the production of spare parts through additive manufacturing (AM) from a digital source. It aims to identify challenges to the growth of the AM spares market and propose suitable solutions. Design/methodology/approach The paper begins with a systematic literature review and theoretical analysis. This is followed by case study research through semi-structured interviews, forming the basis of a triangulated, cross-case analysis of empirical data. Findings The paper identifies several obstacles to the development of the AM-produced digital spares market. The manufacturing industry will soon be forced to re-think AM as a real manufacturing alternative. Short-term, AM technology has implications for the production of components for legacy systems for which tooling facilities no longer exist. Long-term, AM will be used to produce a wide range of components especially when product and/or service functionality can be increased. To enable companies to navigate current uncertainties in the patent framework (especially the “repair vs make” doctrine), new intellectual property rights strategies could be developed around patenting both complex devices and their individual components, and seeking patent protection for CAD files. Further harmonization of the EU legal framework, the interpretation of claims and the scope of protection offered in the context of spare parts, will also be important. Originality/value This study pinpoints key issues that need to be addressed within the European AM business environment and the patent system and proposes recommendations for business and legal frameworks to promote the growth of a stable European digital spare parts market.

The purpose of this paper is to investigate the post-processing of Co-Cr and 316L stainless steel components made by additive manufacturing (AM) using ultrasonic burnishing. AM is able to produce functional parts for medical and industrial applications; however, the parts require support removal and post-processing to achieve the technical requirements. To this end, ultrasonic burnishing is a formative method used to improve surface quality and increase surface hardness. The aim of this work is to characterize the effect of process variable (e.g. machine and workpiece relative displacements and spring compression) in the surface quality of AM burnished materials. Two separate design of experiments were performed to find optimal values for the process parameters. The analysis of the experimental result was performed using “Minitab 16” statistical software. To this end, an analysis of variance (ANOVA) was performed to study the effect and interactions of process parameter on the final surface quality. The results showed that surface roughness (Ra) was decreased to 0.18 µm for as-built Co-Cr and 0.55 µm for as-built 316L stainless steel. In addition, the relative increase in average hardness from as-built Co-Cr was 47.4% (i.e. 551.07 Hv) and 70.7% from as-built 316L stainless steel (i.e. 338.17 Hv). The optimal process parameters for post-processing Co-Cr material are around 0.05 mm/r for the feed and 1.5 mm for the spring compression, whereas post-processing of 316L requires 1000 mm/min for the feed speed, 0.025 mm for the side shift and 1 mm for spring compression, when taking also productivity into consideration. The results of this experiment show that the subtractive methods and labour-intensive post-processing of AM metal parts can be replaced by burnishing methods, thus reducing the cost barriers of additive technology and drive its adoption in industry.

Summary 3D printers are currently widely available and very popular among the general public. However, the use of these devices may pose health risks to users, attributable to air-quality issues arising from gaseous and particulate emissions in particular. We characterized emissions from a low-end 3D printer based on material extrusion, using the most common polymers: acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA). Measurements were carried out in an emission chamber and a conventional room. Particle emission rates were obtained by direct measurement and modeling, whereas the influence of extrusion temperature was also evaluated. ABS was the material with the highest aerosol emission rate. The nanoparticle emission ranged from 3.7·108 to 1.4·109 particles per second (# s−1) in chamber measurements and from 2.0·109 to 4.0·109 # s−1in room measurements, when the recommended extruder temperature was used. Printing with PLA emitted nanoparticles at the rate of 1.0·107 # s−1 inside the chamber and negligible emissions in room experiments. Emission rates were observed to depend strongly on extruder temperature. The particles’ mean size ranged from 7.8 to 10.5 nanometers (nm). We also detected a significant emission rate of particles of 1 to 3 nm in size during all printing events. The amounts of volatile organic and other gaseous compounds were only traceable and are not expected to pose health risks. Our study suggests that measures preventing human exposure to high nanoparticle concentrations should be adopted when using low-end 3D printers.

Voxel-based multimaterial jetting additive manufacturing allows fabrication of digital materials (DMs) at the meso-scale (∼1 mm) by controlling the deposition patterns of soft elastomeric and rigid glassy polymers at the voxel-scale (∼90 μm). The digital materials can then be used to create heterogeneous functionally graded material (FGM) structures at the macro-scale (∼10 mm) programmed to behave in a predefined manner. This offers huge potential for design and fabrication of novel and complex bespoke mechanical structures.\ud \ud This paper presents a complete design and manufacturing workflow that simultaneously integrates material design, structural design, and product fabrication of FGM structures based on digital materials. This is enabled by a regression analysis of the experimental data on mechanical performance of the DMs i.e., Young’s modulus, tensile strength and elongation at break. This allows us to express the material behavior simply as a function of the microstructural descriptors (in this case, just volume fraction) without having to understand the underlying microstructural mechanics while simultaneously connecting it to the process parameters.\ud \ud Our proposed design and manufacturing approach is then demonstrated and validated in two series of design exercises to devise complex FGM structures. First, we design, computationally predict and experimentally validate the behavior of prescribed designs of FGM tensile structures with different material gradients. Second, we present a design automation approach for optimal FGM structures. The comparison between the simulations and the experiments with the FGM structures shows that the presented design and fabrication workflow based on our modeling approach for DMs at meso-scale can be effectively used to design and predict the performance of FGMs at macro-scale.

Increasingly, metal parts made by additive manufacturing are produced using powder bed fusion (PBF). In this paper we report upon the combined effects of PBF parameters, including power and scan speed, in layer-by-layer manufacturing of gas atomized non-modulated (NM) Ni-Mn-Ga alloy. The effects of process parameters upon PBF is studied by applying nine different parameter sets in the as-printed state and after homogenization and ordering. The chemical composition of the samples is analyzed using EDX attached to an SEM, and the crystal structures are determined by X-ray diffraction. The phase transformation temperatures are measured using a low-field ac susceptibility measurement system and the magnetic properties are measured with a vibrating sample magnetometer (VSM). Before the heat-treatment, all as-printed samples showed paramagnetic behavior with low magnetization and no phase transformations could be observed in the susceptibility measurements. After annealing, the samples recovered the ferromagnetic behavior with comparable magnetization to annealed gas atomized powder. The as-printed samples were composed of a mixture of different crystal structures. However, after annealing the original NM structure with a = b = 5.47 Å and c = 6.66 Å with a c/a -ratio of 1.22 was recovered and crystallographic twins could be observed in an SEM.

Digital platforms have become an integral part of user experience innovation in a short period of time. When coupled with innovative production technologies like 3D printing, these platforms facilitate prosumption (production by consumers). Prosumption is very much anticipated in the food sector, especially after the emergence of 3D food printing technology. The goal of this chapter is to create an understanding on how digital platforms could work together with future 3D food printing systems to foster food prosumption. An extensive literature review was conducted for comprehending the concept of prosumption and the state of the art of 3D food printing. After the literature review, 15 semistructured interviews were carried out in four countries, with experts from both academia and industry. These interviews have helped in creating knowledge on the change drivers for prosumer-driven 3D food printing, nature of the prosumer platform, future of food, and the potential use cases for prosumer-driven 3D food printing systems. Overall, the qualitative research data implies that leveraging 3D food printing technology and digital platforms would generate value chains that are transparent, data driven, connected, collaborative, and sustainable.

Additive manufacturing technologies are opening new opportunities in term of production paradigm and manufacturing possibilities. Nevertheless, in term of environmental impact analysis supplementary research works require to be made in order to compare and evaluate them with traditional manufacturing processes. In this article, we propose to use Life Cycle Assessment (LCA) method and to associate decision criteria to support the selection of manufacturing strategies for an aeronautic turbine. The dimensionless criteria allow to define environmental trade-offs between additive and subtractive methods. This study provides an approach generalizable to other parts and processes.

The use of commodity polymers such as polypropylene (PP) is key to open new market segments and applications for the additive manufacturing industry. Technologies such as powder-bed fusion (PBF) can process PP powder, however, much is still to learn concerning process parameters for reliable manufacturing. This study focusses in the process&ndash, property relationships of PP using laser-based PBF. The research presents an overview of the intrinsic and the extrinsic characteristic of a commercial PP powder as well as fabrication of tensile specimens with varying process parameters to characterize tensile, elongation at break, and porosity properties. The impact of key process parameters, such as power and scanning speed, are systematically modified in a controlled design of experiment. The results were compared to the existing body of knowledge, the outcome is to present a process window and optimal process parameters for industrial use of PP. The computer tomography data revealed a highly porous structure inside specimens ranging between 8.46% and 10.08%, with porosity concentrated in the interlayer planes in the build direction. The results of the design of experiment for this commercial material show a narrow window of 0.122 &ge, Ev &ge, 0.138 J/mm3 led to increased mechanical properties while maintaining geometrical stability.

Purpose Additive manufacturing requires a systemic approach to help industry on technology applicability research. Towards this end, the purpose of this research is to help manufacturing business leaders decide whether digitalised manufacturing based on additive manufacturing are suitable for engineering applications and help them plan technology transfer decisions. Design/methodology/approach The methodology is based on case study research and action research, involving a mix of quantitative and qualitative research methods. The empirical part involved the study of the fatigue life of industrial component manufactured by laser sintering as well as a combination of quantitative and qualitative methods to define a strategic decision-making. Findings Laser-sintered plastic materials are suitable in end use automotive applications, especially when there are multiple product variations. Fatigue life of the tested coupling meets the design requirements. Additionally, production of mechanical parts can be substituted by additive methods while digitalising the manufacturing process to gain productivity, especially when there is a need for mass-customisation. Research limitations/implications This research relies on a single case study research. The application used is unique and its technical empirical data cannot be transferred directly to other applications. Practical implications Industry practitioners can use this research to shed light on technology transferability challenges considering technical feasibility of additive polymer materials, economic aspects as well as strategic implications for implementing digitalised manufacturing methods based on additive manufacturing. Originality/value This research presents a combined study of technical and strategic factors for additive manufacturing transferability using an industrial mass-customisation case as an example. In addition, a new cost comparison model is presented including the impact of geometry variations.

Companies lack a trained workforce with the ability to justify the utilization of Additive Manufacturing (AM) technologies in manufacturing activities. The problem is that traditional education in engineering design and manufacturing is heavily constrained by the design rules imposed by conventional manufacturing, which are based on subtractive and formative methods. AM applications have been originally tightened to prototyping applications, generating misconceptions regarding its suitability for companies accustomed to playing by the rules of economies of scale. Thus, the economic aspects of AM implementation in end-production applications are not fully understood. This book chapter presents several interrelated AM technology transfer case studies which were performed in collaboration with Aalto University and companies involved in European and Finnish funded research and innovation initiatives. The objective is to provide a pedagogical and comprehensive approach to the key parameters to consider when a design engineer needs to asses AM for production environments (i.e. cost, time and functionality). The results of this research show that justification of AM technology transfer based on cost will only allow the ‘manufacturing of few’ and production of one-of-a kind component. On the other hand, availability of AM parts, reduction of time-to-market as well as reduced delivery lead times can become fundamental in the service operation of manufacturing companies, thus enabling AM technology transfer. Nevertheless, mass-customization applications and improved product functionality become the key parameters that makes AM truly competitive versus other conventional manufacturing methods. The understanding of these parameters and its interlinks with industrial decision-making will open a window with a huge potential for AM applications in traditional OEMs, especially in manufacturing applications from which complete new products and processes can be innovated.

The purpose of this research is to develop a computer-driven decision support system (DSS) to select optimal additive manufacturing (AM) machines for metal powder bed fusion (PBF) applications. The tool permits to evaluate productivity factors (i.e., cost and production time) for any given geometry. At the same time, the trade-off between feature resolution and productivity analysis is visualized and a sensitivity analysis is performed to evaluate future cost developments. This research encompasses a decision support system that includes a data structure and an algorithm which is coded in “MathWorks Matlab,” considering cost structures for metal-based AM (i.e., machine cost, material cost, and labor cost). Results of this research demonstrate that feature resolution has a crucial effect on the total cost per part, but displays decreasing impacts for higher build volume rates. Based on assumptions of business consultancies, productivity can be increased, resulting in a potential decline of cost per part of up to 55% until 2025. Using this DSS tool, it is possible to evaluate the most optimal AM production systems by selecting between several input parameters. The algorithm allows industry practitioners to retrieve information and assist in decision-making processes, including cost per part, total cost comparison, and build time evaluations for typical commercial metal PBF systems.

This study corresponds to the first stage of a project that focuses on optimizing the mechanical properties of titanium dioxide (TiO2) for use in bone implants. The goal of the study is to characterize and compare the stiffness of solid and scaffold TiO2 samples fabricated via three-dimensional material extrusion method. The sample specimens were sintered in a furnace at three different temperatures, namely-1200 °C, 1250 and 1300 °C- for 4 h. The sintering procedure caused shrinkage in all dimensions and the maximum shrinkage (57.5%) was observed in the direction perpendicular to the work plate. The morphology of the sintered samples was analyzed via scanning electron microscopy. This revealed that increasing the sintering temperature increased the grain size and decreased porosity. For example, the porosity of the samples sintered at 1300 °C was 20% less than that of samples sintered at 1200 °C. Uniaxial compression tests showed that scaffold structures had a lower stiffness than their solid counterparts, and the decrease in stiffness was comparable to the reduction in cross-sectional area. The elastic modulus of TiO2 produced here by material extrusion was between 2.08–5.90 GPa, which is close to the elastic modulus of high density cancellous bone at 0.8–1.5 GPa. This is an important advantage as minimizing the mismatch in stiffness between bone and implant is critical to avoid problems such as stress shielding and bone resorption.

The objective of this research is to define an optimal innovation policy and funding strategy to improve Additive Manufacturing (AM) capabilities in Finnish companies. To do so, we present an international review of innovation programs in the area of AM. In addition, the study replied upon a survey prepared to evaluate factors for AM implementation. The ultimate goal is to help in the definition of a national policy strategy in the area of AM based on the characteristics of the Finnish industrial ecosystem. The methodology and data collection method involved defining the taxonomy of Finnish AM industry. The target group of the survey was a population of AM experts, and individuals with knowledge on AM and industrial processes. Overall, the survey revealed that research and innovation activities are well positioned in Finland. In order for future innovation policies to further support developments in the field, we estimated that policy strategies need to generate about 6-8 M€/year in national and EU- funding instruments for AM technology transfer, development, and innovation activities. Efforts should be targeted towards strengthening uses of AM in final production. In fact, only 36% of Finnish respondents declared to use AM for final production, while leading countries in AM use it in average more than 50%. Another area in need of development in Finland is the use of AM high performance materials. Moreover, outsourcing of AM services in Finland is 23 percentage point higher in national and 13 percentage point higher in international outsourcing to service bureaus and suppliers. In this regard, future policies and funding strategies should maintain the created momentum. However, there is a need to acquire high-end research and industrial equipment to stimulate AM integration to the existing production systems. This in the end can trigger the creation of new products, processes and intellectual property, enabling innovation and competitive advantage.

3D printing is moving towards end-part production. However, the high-cost structures of 3D printing have a negative impact on technology transferability. Manufacturing time per part becomes a critical enabling factor for whether the technology can be implemented or not. The aim was to investigate the effect of build orientation and the number of parts relative to manufacturing time per part in the material extrusion, binder jetting, vat photopolymerisation, material jetting, powder bed fusion, and sheet lamination. The tested geometry was a Nokia Lumia 820 mobile phone cover. Manufacturing time per part depends heavily on the geometry, orientation, printing process, and amount of parts manufactured in a single build. Manufacturing time per part varies substantially between the tested technologies. The optimal processes in regards to the production speed were found to be powder bed fusion and binder jetting. In addition, material costs and costs related to process time per manufactured part were compared.

This paper presents the current state of additive manufacturing (AM) implementation in complex supply chains, focusing especially on the globalised consumer electronics industry. A literature review sought to identify bottlenecks to technology transfer, while a qualitative study was carried out using interviews with case company personnel. Finally, an industry survey was used to quantitatively evaluate current production costs and delivery times for AM units. The results highlight the considerable barriers to transferring AM technology to engineering applications. However, there is an untapped potential for manufacturing applications in small-series and pre-series production at the product refinement stages. Furthermore, future projections of AM production throughput and cost reductions will disrupt organisational supply chains. This will lead organisations to create faster design, development and manufacturing cycles, unlocking novel applications and introducing new possibilities to change product architecture at any stage of the product development while compressing the supply chain and allowing for quick responses to changing customer demands.

Additive manufacturing has been presented as a novel and competitive method to achieve unprecedented part shapes and material complexities. Though this holds true in niche markets, the economic viability of additive manufacturing for large-scale industrial production is still in question. Companies often struggle to justify their investment in additive manufacturing due to challenges in the integration of such technologies into mainstream production. First, most additive technologies exhibit a relatively low production rate when compared with traditional production processes. Second, there is a lack of robust design for additive manufacturing methods and tools that enable the leveraging of the attendant unique capabilities, including the ability to form organic part geometries and automated part consolidations. Third, there is a dearth of systematic part screening methods to evaluate manufacturability in additive manufacturing. To tackle the challenge of manufacturability evaluation, the present work proposes a novel approach derived from latent semantic analysis and dimensional analysis to evaluate parts and their production for a variety of selected metrics. The selected metrics serve as descriptors of design features and manufacturing functions, which are developed using functional modeling and dimensional analysis theory. Singular-value decomposition and Euclidean distance measurement techniques are used to determine the relative manufacturability for a set of parts for a specified manufacturing process technology. The utility of the method is demonstrated for laser powder bed fusion technology. While demonstrated for additive manufacturing here, the developed approach can be expanded for any given set of manufacturing processes. Expansion of this systemic manufacturability analysis method can support part design decision-making, process selection, and design and manufacturing optimization.