Modelling of the Valley of Flowers National Park, a World Heritage Site, by Additive Manufacturing

ABSTRACTGeographical information system (GIS) data in digital elevation model (DEM) format contains surface data of terrain on the Earth. This surface data needs to be converted into a 3D faceted file before uploading to an additive manufacturing (AM) machine. Commercially available software packages perform this task indirectly by translating and modifying data through different file formats. This paper discusses a methodology to convert the United States Geological Survey (USGS) 7.5-minute and 1-degree DEM file formats directly to 3D stereolithography (STL) ASCII format. A software program in C is developed to create a base and walls around the surface data to make a 3D STL part of the terrain. The STL file was uploaded to an AM machine (EOSP395) to fabricate a physical scale model of the terrain. This work not only removes intermediate steps and the associated data loss but can generate an STL part in relatively less time.

There is currently significant demand for training in how to use metals additive manufacturing (AM) machines. Such training is important not only for the technicians who run and maintain the machines, but also for engineers and strategic decision makers who need to support AM part fabrication. Furthermore, there are a variety of AM machines, each with different details to be learned and potential hazards to overcome, and it is difficult to train more than a handful of users at one time. To address these challenges, a prototype training system has been developed, the AM Training Tutor, which uses interactive virtual reality (VR) to train users on a specific AM machine - the EOS M290. To make the training technology more widely available and expand its use across a variety of different AM machines, efforts are underway to develop a modularized and generic version of the AM Training Tutor that can be customized with relatively little effort to train users to operate other AM machines. This work-in-progress paper details the progress to-date, challenges and proposed solutions with the aim to demonstrate how standalone VR-based training systems can be redesigned for relatively easy repurposing and generalization.

Analyzing positional accuracy and structural efficiency in additive manufacturing systems with moving elements

Although there are more than 270,000 protected areas worldwide, there is currently little data on their protection and management effectiveness. As a kind of protected area, natural world heritage (WH) sites are small but represent some of the most important natural landscapes, covering a very large area. But natural WH is threatened by climate change, natural disasters and human activities. Therefore, to achieve the sustainable development of WH sites, it is very important to analyze the management status of WH sites. Based on this, the study extracts inspiration from Enhancing our Heritage Toolkit: Assessing management effectiveness of natural World Heritage sites. An assessment system of the management effectiveness (ME) of natural WH sites has been established, which has three dimensions (including management foundation, management measures, and management performances) and 21 indexes. The reliability and validity of the index system are tested using the exploratory factor analysis method, and the results show that the index system has good reliability and validity. Then principal component analysis and comprehensive assessment methods are used to analyze the ME of the Fanjingshan WH site. The results show that the management effectiveness of the Fanjingshan WH Site is relatively excellent, but it still faces challenges from tourism development and community participation.

Chapter 5 - Software interface issues in consideration of additive manufacturing machines and processes

PurposeThis study aims to evaluate and compare the macroscopic properties of commercial acrylonitrile-butadiene-styrene (ABS) processed by two different types of additive manufacturing (AM) machines. The focus is also on the effect of multiple closed-loop recycling of ABS.Design/methodology/approachA conventional direct-drive, Cartesian-type machine and a Bowden, Delta-type machine with an infrared radiant heating system are used to manufacture test specimens molded in ABS. Afterward, multiple closed-loop recycling cycles are conducted, involving consecutive AM (four times) and recycling (three times). The rheological, mechanical, morphological and physicochemical properties are investigated.FindingsThe type of machine affects the quality of the produced parts. The machine containing an infrared radiant system in a temperature-controlled chamber produces parts showing higher mechanical properties and filling fraction, although it increases the yellowing. Closed-loop recycling of ABS for AM is applicable for at least two cycles, inducing a slight increase in tensile modulus (ca. 5%) and in tensile strength (ca. 13%) and a decrease in the impact strength (ca. 14%) and melt viscosity. An increase in the filling fraction of the AM parts promotes an increase in tensile strength and tensile modulus, although it does not influence the impact strength. Furthermore, multiple closed-loop recycling does not affect the overall chemical structure of ABS.Practical implicationsControlling the environmental temperature and using infrared radiant heating during AM of ABS improves the quality of the produced parts. Closed-loop recycling of ABS used in AM is feasible up to at least two recycling steps, supporting the implementation of a circular economy for polymer-based AM.Originality/valueThis study shows original results regarding the assessment of the effect of different types of AM machines on the main end-use properties of ABS parts and the influence of multiple closed-loop recycling on the characteristics of ABS fabricated by the most suited AM machine with an infrared radiant heating system and a temperature-controlled environment.

Particle and gaseous contaminants from industrial scale additive manufacturing (AM) machines were studied in three different work environments. Workplaces utilized powder bed fusion, material extrusion, and binder jetting techniques with metal and polymer powders, polymer filaments, and gypsum powder, respectively. The AM processes were studied from operator's point of view to identify exposure events and possible safety risks. Total number of particle concentrations were measured in the range of 10 nm to 300 nm from operator's breathing zone using portable devices and in the range of 2.5 nm to 10 µm from close vicinity of the AM machines using stationary measurement devices. Gas-phase compounds were measured with photoionization, electrochemical sensors, and an active air sampling method which were eventually followed by laboratory analyses. The duration of the measurements varied from 3 to 5 days during which the manufacturing processes were practically continuous. We identified several work phases in which an operator can potentially be exposed by inhalation (pulmonary exposure) to airborne emissions. A skin exposure was also identified as a potential risk factor based on the observations made on work tasks related to the AM process. The results confirmed that nanosized particles were present in the breathing air of the workspace when the ventilation of the AM machine was inadequate. Metal powders were not measured from the workstation air thanks to the closed system and suitable risk control procedures. Still, handling of metal powders and AM materials that can act as skin irritants such as epoxy resins were found to pose a potential risk for workers. This emphasizes the importance of appropriate control measures for ventilation and material handling that should be addressed in AM operations and environment.

PurposeInnovative startups have begun a trend using laser sintering (LS) technology patents expiration, namely, by introducing LS additive manufacturing (AM) machines that can overcome utilization barriers, such as the costliness of machines and productivity limitation. The recent rise of this trend has led the authors to investigate this new class of machines in novel settings, including hub configuration. There are various supply chain configurations to supply spare parts in industrial operations. This paper aims to explore the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it.Design/methodology/approachThis study quantitatively examines the feasibility of different AM-enabled spare parts supply chain configurations. Using cost data extracted from a case study, three scenarios per AM machine technology are modeled and compared.FindingsResults suggest that hub production configuration depending on the utilized AM machines can provide economic efficiency and effectiveness to reduce equipment downtime. While previous studies have suggested the need for AM machines with efficiency for single part production for a distributed supply chain, the findings in this research illustrate the positive relationship between multi-part production capability and the feasibility of a hub manufacturing configuration establishment.Originality/valueThis study explores the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it. Although the existing body of knowledge contains research on production decentralization, research on various levels of decentralization is lacking. Using a real-world case study, this study aims to compare the feasibility of different levels of decentralization for AM-enabled spare parts supply chains.

PurposeThe purpose of this paper is to establish a general method for achievable speed and accuracy evaluation of additive manufacturing (AM) machines and an objective comparison among them.Design/methodology/approachFirst, a general schematic is defined that enables description of all currently available AM machines. This schematic is used to define two influential factors describing certain parts' properties regarding the machines' yield during manufacturing. A test part is defined, that will enable testing the influence of these factors on the speed and accuracy of manufacturing. A method for implementing and adapting test parts is established for individual machine's testing. This method was used to test four different machines that are predominantly used in Slovenia at the moment.FindingsResearch has proven that the machine's yield had a predominant influence on the achievable manufacturing speeds of all the tested machines. In addition, the results have shown different ranges of achievable manufacturing speeds for individually tested machines. Test parts' measurement results have shown comparable achievable accuracies for all the tested machines.Research limitations/implicationsSpeed evaluation is based on a 2k factorial design that assumes the linearity among individual points of the experiment. This design was chosen to keep the method as simple and quick as possible, in order to perform testing on those machines otherwise used in industrial environments. Accuracy evaluation was limited by a rather small sample size of ten fabricated test parts per machine.Practical implicationsThe presented evaluation method can be used on any existing or future type of AM machine, and their comparative placement regarding achievable manufacturing speed and accuracy.Originality/valueThe presented method can be used to evaluate a machine regardless of the AM technology on which it is based.

This paper presents a novel reconfigurable control software for Additive Manufacturing (AM) machines. At first, reconfigurable architecture is created based on the principle of layered manufacturing which all AM processes should follow. Then, the control software is designed aimed at providing consistent user experience for various AM machines. At last, the proposed control software is successfully applied to two different kinds of AM machines. Compared to the old control software on these machines, nearly 70% of functions are reused in the new one, which leads to a reduction of the research and development time eventually.

Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its specific context. However, the approaches are not flexible enough and could produce undesirable results as they are all based on multi-attribute two-way decisions. In this paper, a selection approach based on ontology-supported multi-attribute three-way decisions is presented. Firstly, an ontology for AM machine selection is constructed according to vendor documents, benchmark data, expert experience, and the Senvol database. Supported by this ontology, a selection approach based on multi-attribute three-way decisions is then developed. After that, four AM machine selection examples are introduced to illustrate the application of the developed approach. Finally, the effectiveness and advantages of the approach are demonstrated via a set of comparison experiments. The demonstration results suggest that the presented approach is as effective as the existing approaches and more flexible than them when the information for decision making is insufficient or the cost for undesirable decision results is high.

Entry-Level Additive Manufacturing (ELAM) machines are made far less sophisticated compared to premium Additive Manufacturing (AM) machines for the sake of affordability. Often, machine resolution is also compromised, which may raise a question mark on quality. It is essential to gain a working knowledge of quality issues, considering the present rate of penetration of 3D printers in manufacturing. The objective of this paper is to examine geometric limitations and challenges of entry-level AM machines when fabricating complex objects. A systemic literature review providing an overview of additive manufacturing technology, the definition of ELAM, followed by a discussion on challenges in ELAM and improvement in dimensional accuracy to help the end users understand their machine well are presented in the paper. Ten experiments were performed on ELAM using acrylonitrile butadiene styrene polymer to illustrate and classify the developed defects. Most of the parts produced from ELAM machine suffer from quality issues such as geometrical and dimensional inaccuracy, warpage, oozing and surface imperfection, nesting, non-formation and deposition. This investigation displays a more realistic picture of ELAMs by identifying important restrictions and limitations which otherwise are hardly available to the end users or the manufacturers. The findings will help ELAM manufacturers to innovate their machine and make it better for professional use.

More than 25% of natural World Heritage (WH) sites worldwide are estimated to be under pressure from existing or future mining and energy activities (IUCN 2008; UNESCO 2009). However, that ‘pressure’ has yet to be quantitatively defined and assessed for many regions of the world. We conducted a GIS-based analysis of overlap and proximity between natural WH sites and areas allocated to oil and gas concessions as well as pipelines and oil wells for all of sub-Saharan Africa. We found that oil and gas concessions were located within 27% of the WH sites, though no currently active oil wells were operating directly within the WH sites. A proximity-based assessment of oil and gas concessions within 5 km of WH site boundaries included only one additional WH site, suggesting that sites susceptible to indirect impacts from oil and gas development are likely to be those already overlapped by concessions. Our findings indicate that activity from oil and gas development in sub-Saharan WH sites has to date been limited; however, future pressure cannot be ruled out, due to continued presence of concessions within more than one quarter of the network, and projected expansion of oil and gas exploration within the region. Our results may be used to inform the inclusion of new sites into the WH network.

In this pilot-scale study, a wide range of potential emissions were evaluated for four types of additive manufacturing (AM) machines. These included material extrusion (using acrylonitrile-butadiene-styrene [ABS]); material jetting (using liquid photopolymer); powder bed fusion (using nylon); and vat photopolymerization (using liquid photopolymer) in an industrial laboratory setting. During isolated operation of AM machines, adjacent area samples were collected for compounds of potential concern (COPCs), including total and individual volatile organic compounds (VOCs), nano- and micron-sized particulate matter, and inorganic gases. A total of 61 compounds were also sampled using a canister followed by gas chromatography and mass spectrometry analysis. Most COPCs were not detected or were measured at concentrations far below relevant occupational exposure limits (OELs) during AM machine operations. Submicron particles, predominantly nanoparticles, were produced during material extrusion printing using ABS at approximately 12,000 particles per cubic centimeter (p cm−3) above background. After subtracting the mean background concentration, the mean concentration for material extrusion printing operations correlated with a calculated emission rate of 2.8 × 1010 p min−1 under the conditions tested. During processing of parts produced using material jetting or powder bed fusion, emissions were generally negligible, although concentrations above background of respirable and total dust were measured during processing of powder bed fusion parts. Results of this pilot-scale study indicate that airborne emissions associated with AM operations are variable, depending on printing and parts handling processes, raw materials, and ventilation characteristics. Although personal samples were not collected in this pilot-scale study, the results can be used to inform future exposure assessments. Based on the results of this evaluation, measurement of submicron particles emitted during material extrusion printing operations and dust associated with handling parts manufactured using powder bed fusion processes should be included in exposure assessments.

Hierarchical Scanning Data Structure for Additive Manufacturing