Selective Heat Sintering Versus Laser Sintering: Comparison of Deposition Rate, Process Energy Consumption and Cost Performance

The Selective Heat Sintering (SHS) process has become available as a low cost alternative to Laser Sintering (LS) for the additive deposition of polymer objects. While both processes belong to the powder bed fusion variant of Additive Manufacturing (AM) technology, their operating principles vary significantly: SHS employs a thermal print head to selectively fuse material powder, whereas the LS approach utilizes a laser beam coupled with a galvanometer. Based on a series of build experiments, this research compares these technology variants along three dimensions of process efficiency: deposition rate (measured in cm³/h), specific process energy consumption (MJ/kg) and specific cost ($/cm³). To ensure that both platforms are assessed under the condition of efficient technology utilization, an automatic build volume packing algorithm is employed to configure a subset of build experiments. Beyond reporting absolute and relative process performance, this paper additionally investigates how sensitive the compared processes are to a variation in the degree of capacity utilization and discusses the application of different levels of indirect cost in models of low cost AM.Mechanical Engineerin

Informing additive manufacturing technology adoption: total cost and the impact of capacity utilisation

Informing Additive Manufacturing (AM) technology adoption decisions, this paper investigates the relationship between build volume capacity utilisation and efficient technology operation in an inter-process comparison of the costs of manufacturing a complex component used in the packaging industry. Confronting the reported costs of a conventional machining and welding pathway with an estimator of the costs incurred through an AM route utilising Direct Metal Laser Sintering (DMLS), we weave together four aspects: optimised capacity utilisation, ancillary process steps, the effect of build failure and design adaptation. Recognising that AM users can fill unused machine capacity with other, potentially unrelated, geometries, we posit a characteristic of ‘fungible’ build capacity. This aspect is integrated in the cost estimation framework through computational build volume packing, drawing on a basket of sample geometries. We show that the unit cost in mixed builds at full capacity is lower than in builds limited to a single type of geometry; in our study, this results in a mean unit cost overstatement of 157%. The estimated manufacturing cost savings from AM adoption range from 36 to 46%. Additionally, we indicate that operating cost savings resulting from design adaptation are likely to far outweigh the manufacturing cost advantage

How Can Material Jetting Systems Be Upgraded for More Efficient Multi-Material Additive Manufacturing

Multi-material Additive Manufacturing (AM) platforms are able to build up components from multiple materials in a single layer-by-layer process. It is expected that this capability will enable the manufacturing of functional structures within products, such as conductive tracks or optical pathways, resulting in radically novel products with unprecedented degrees of functional density. An important variant of commercially available multi-material AM technology is material jetting, which is currently in commercial use for the manufacture of prototypes and design studies. This paper presents a detailed process model of build-time, energy consumption and production cost for the Stratasys Objet 260 Connex system, analyzing the contemporaneous deposition of two different types of photopolymers (Veroclear RGD810 and Tangoblack FLX973). By using this process model to anticipate the effects of various upgrades to the investigated system, such as a larger build volume and a higher deposition speed, this forward-looking paper explores pathways to enhancing the value proposition of such multi-material systems through incremental technology improvement.Mechanical Engineerin

Energy Inputs to Additive Manufacturing: Does Capacity Utilization Matter?

The available additive manufacturing (AM) platforms differ in terms of their operating principle, but also with respect to energy input usage. This study presents an overview of electricity consumption across several major AM technology variants, reporting specific energy consumption during the production of dedicated test parts (ranging from 61 to 4849 MJ per kg deposited). Applying a consistent methodology, energy consumption during single part builds is compared to the energy requirements of full build experiments with multiple parts (up to 240 units). It is shown empirically that the effect of capacity utilization on energy efficiency varies strongly across different platforms.Mechanical Engineerin

Environmental impacts of selective laser melting: do printer, powder, or power dominate?

This life cycle assessment measured environmental impacts of selective laser melting, to determine where most impacts arise: machine and supporting hardware; aluminum powder material used; or electricity used to print. Machine impacts and aluminum powder impacts were calculated by generating life cycle inventories of materials and processing; electricity use was measured by in-line power meter; transport and disposal were also assessed. Impacts were calculated as energy use (megajoules; MJ), ReCiPe Europe Midpoint H, and ReCiPe Europe Endpoint H/A. Previous research has shown that the efficiency of additive manufacturing depends on machine operation patterns; thus, scenarios were demarcated through notation listing different configurations of machine utilization, system idling, and postbuild part removal. Results showed that electricity use during printing was the dominant impact per part for nearly all scenarios, both in MJ and ReCiPe Endpoint H/A. However, some low-utilization scenarios caused printer embodied impacts to dominate these metrics, and some ReCiPe Midpoint H categories were always dominated by other sources. For printer operators, results indicate that maximizing capacity utilization can reduce impacts per part by a factor of 14 to 18, whereas avoiding electron discharge machining part removal can reduce impacts per part by 25% to 28%. For system designers, results indicate that reductions in energy consumption, both in the printer and auxiliary equipment, could significantly reduce the environmental burden of the process

Unlocking value for a circular economy through 3D printing: A research agenda

The circular economy (CE) aims to radically improve resource efficiency by eliminating the concept of waste and leading to a shift away from the linear take-make-waste model. In a CE, resources are flowing in a circular manner either in a biocycle (biomass) or technocycle (inorganic materials). While early studies indicate that 3D printing (3DP) holds substantial promise for sustainability and the creation of a CE, there is no guarantee that it will do so. There is great uncertainty regarding whether the current trajectory of 3DP adoption is creating more circular material flows or if it is leading to an alternative scenario in which less eco-efficient localised production, demands for customised goods, and a higher rate of product obsolescence combine to bring about increased resource consumption. It is critical that CE principles are embedded into the new manufacturing system before the adoption of 3DP reaches a critical inflection point in which negative practices become entrenched. This paper, authored by both academic and industry experts, proposes a research agenda to determine enablers and barriers for 3DP to achieve a CE. We explore the two following overarching questions to discover what specific issues they entail: (1) How can a more distributed manufacturing system based on 3DP create a circular economy of closed-loop material flows? (2) What are the barriers to a circular 3D printing economy? We specifically examine six areas-design, supply chains, information flows, entrepreneurship, business models and education-with the aim of formulating a research agenda to enable 3DP to reach its full potential for a CE

Cost Impact of the Risk of Build Failure in Laser Sintering

While the feasibility of adopting Additive Manufacturing (AM) has been demonstrated in a range of industrial sectors, the total costs associated with the operation of the technology are not fully understood. This study reports the results of a series of build experiments in a controlled environment for the analysis of the total cost of the AM technology variant Laser Sintering (LS). Incorporating a structured representation of the process flow of LS, the developed cost model shows for a LS system of the type EOSINT P100 that the expected cost impact of build failure has a substantial effect, responsible for a share of up to 38% of total costs. The analysis further demonstrates that, due to the adverse effects of such ill-structured costs, the cost efficient level of build volume utilization is sub-maximal. This result is discussed in the context of the operational reality of using LS technology and the availability of economies of scale.Mechanical Engineerin

On the economics of additive manufacturing: experimental findings

Additive manufacturing offers great potential for both product and process innovation in manufacturing across a wide range of industry sectors. To date, most applications that have been reported use additive manufacturing to produce either customized parts or produce at small scale, while the volume manufacture of standard parts largely remains a conjecture. In this paper we report on a series of experiments designed to elucidate how quantity, quality and cost relate in additive manufacturing processes. Our findings show that traditional economies of scale only partially apply to additive manufacturing processes. We also identify four build failure modes and quantify their combined effect on unit cost, exposing an unusual property whereby the cost-optimal operating point occurs below maximum machine capacity utilization. Furthermore, once additive manufacturing technology is used at full capacity utilization, we find no evidence of a positive effect of increased volume on unit cost. We do, however, identify learning curve effects related to process repetition and operator experience. Based on our findings we propose a set of general characteristics of the additive manufacturing process for further testing

The economics of additive manufacturing: towards a general cost model including process failure

The interest in Additive Manufacturing (AM) technology, also known as 3D printing, is unbroken. In many industries, however, stakeholders are struggling to understand AM's potential for manufacturing value creation. Most available literature on the cost of AM stresses the importance of ancillary processes and treats the relationship between process efficiency and capacity utilization. The most recently added - and overdue - aspect included in the extant AM costing literature considers the expected impact of so-called ill-structured costs, mainly relating to process failure and product rejection. Available research has investigated this aspect across a variety of technology types and process elements. This paper develops a new AM cost model that is generally specified so it can represent the probability and expected cost effect of failure events for all existing AM technologies. To demonstrate the implementation of this model, this paper applies it to the manufacture of pharmaceutical products (tablets) using the AM technology variant material jetting. The paper thus provides a robust indication of achievable unit cost levels, the cost effect of process failure, and also broaches the usefulness of cost models in guiding further process improvements