12 research outputs found
Is Economic value an Effective Proxy for Embodied Energy and Environmental Impact in Material Systems?
This paper uses economic value metrics to evaluate the retention of value of secondary materials and provides a framework for characterizing value throughout a material and product life-cycle. These economic value metrics are compared with analogous life cycle assessment metrics in order to determine the conditions under which economic value effectively represents environmental impact for EoL material recovery decision-makers. A comparison of these metrics using several different material types indicates that there is a strong correlation between LCA metrics and economic value metrics for most of the materials studied. However, there were a few cases in which the economic value metrics were poor indicators of the LCA metrics
Supply and demand in the material recovery system for cathode ray tube glass
This paper presents an analysis of the material recovery system for leaded glass from cathode ray tubes (CRTs). In particular, the global mass flow of primary and secondary CRT glass and the theoretical capacities for using secondary CRT glass to make new CRT glass are analyzed. The global mass flow analysis indicates that the amount of new glass required is decreasing, but is much greater than the amount of secondary glass collected, which is increasing. The comparison of the ratio of secondary glass collected to the amount of new glass required from the mass flow analysis indicates that the material recovery system is sustainable for the foreseeable future. However, a prediction of the time at which the market for secondary glass will collapse due to excess capacity is not possible at the moment due to several sources of uncertainty
A Methodology for Robust Comparative Life Cycle Assessments Incorporating Uncertainty
We propose a methodology for conducting robust comparative life cycle assessments (LCA) by leveraging uncertainty. The method evaluates a broad range of the possible scenario space in a probabilistic fashion while simultaneously considering uncertainty in input data. The method is intended to ascertain which scenarios have a definitive environmentally preferable choice among the alternatives being compared and the significance of the differences given uncertainty in the parameters, which parameters have the most influence on this difference, and how we can identify the resolvable scenarios (where one alternative in the comparison has a clearly lower environmental impact). This is accomplished via an aggregated probabilistic scenario-aware analysis, followed by an assessment of which scenarios have resolvable alternatives. Decision-tree partitioning algorithms are used to isolate meaningful scenario groups. In instances where the alternatives cannot be resolved for scenarios of interest, influential parameters are identified using sensitivity analysis. If those parameters can be refined, the process can be iterated using the refined parameters. We also present definitions of uncertainty quantities that have not been applied in the field of LCA and approaches for characterizing uncertainty in those quantities. We then demonstrate the methodology through a case study of pavements
Selection of Lightweighting Strategies for Use Across an Automaker's Vehicle Fleet
Vehicle lightweighting, or mass reduction, via materials substitution is a common approach to improve fuel economy. The many subsystems in a vehicle, choices of materials, and manufacturing processes available, though, lead to numerous paths to achieving the mass reduction and identifying the best ones for an automaker to implement can be a challenge. In this paper, that challenge is addressed through the development of a selection model designed to inform the lightweighting strategy decision for an automaker's fleet. The model, implemented with a genetic algorithm, identifies the strategies that enable an automaker to optimize the net present value of its cash flow, as well as to meet its CAFE obligations over the coming years. A case study of various strategies implemented in three vehicles over a three-year timeframe is used to demonstrate application of the genetic algorithm selection model and contrast it to an alternative period-by-period search implementation
Understanding dynamic availability risk of critical materials: The role and evolution of market analysis and modeling
Many advanced energy technologies are fundamentally “materials-dependent”; they are enabled directly by, or designed around, a particular material or materials. Society's acute dependence on materials has increased in recent years as these technologies tap into an ever broader range of the periodic table and, therefore, into a broader set of underdeveloped and complex supply chains. Ultimately, concern around the supply of materials strategic to energy and security interests has led to the development of a range of systems used to assess criticality—the confluence of vulnerability and risk. Concerning the assessment of criticality risk, this review accomplishes two primary goals. First, through a review of several broad assessments of criticality metrics, we identify those metrics that incorporate assessment of future production and consumption. We review the methods that have been applied to project production and consumption along two axes, one around degree of detail or granularity pursued by the model and the second around the degree to which market function is modeled endogenously. Regarding the second, material projection methods can be broadly classified as (a) those which project material flows only and (b) those which use market modeling to explicitly simulate (endogenously) the associated economic behavior and its implication on material flows
Strategies to Address Risks of Platinum Scarcity for Supply Chain Downstream Firms
Increased recycling, product redesign and substitution can improve firm resilience in the face of uncertainties in materials availability. The delays involved in implementing these strategies may result in unprepared firms losing market share to competitors who are better prepared to address these challenges. This paper will expand from previous work in this area by examining the statistical significance of the effect of recycling in the face of limited supply. It has been shown that the timing and magnitude of a supply shutdown can influence the magnitude of price response. On average, increased recycling is a means for stabilizing price effects owing to its faster response times
Operational Strategies for Increasing Secondary Materials in Metals Production Under Uncertainty
Increased use of secondary raw materials in metal production offers several benefits including reduced cost and lowered energy burden. The lower cost of secondary or scrap materials is accompanied by an increased uncertainty in elemental composition. This increased uncertainty for different scraps, if not managed well, results in an increased risk that the elemental concentrations in the final products fall outside customer specifications. Previous results show that incorporating this uncertainty explicitly into batch planning can modify the potential use of scrap materials while managing risk. Chance-constrained formulations provide one approach to uncertainty-aware batch planning; however, typical formulations assume normal distributions to represent the compositional uncertainty of the materials. Compositional variation in scrap materials has been shown to have a skewed distribution, and therefore, the performance of these models, in terms of their ability to provide effective planning, it may then be heavily influenced by the structure of the compositional data used. To address this issue, this work developed several approximations for skewed distributional forms within chance-constrained formulations. We explored a lognormal approximation based on Fenton’s method; a convex approximation based on Bernstein inequalities; and a linear approximation using fuzzy set theory. Each of these methods was formulated and case studies executed using compositional data from an aluminum remelter. Results indicate that the relationship between the underlying structure/distribution of the compositional data and how these distributions are formulated in batch planning can modify the use of secondary raw materials.National Science Foundation (U.S.) (Award 1133422
Integrated planning for design and production in two-stage recycling operations
Recycling is a key strategy to reduce the environmental impact associated with industrial resource use. Recent improvements in materials recovery technologies offer the possibility for recouping additional value from recycling. However, incorporation of secondary raw materials into production may be constrained by operational complexity in two-stage blending processes. In this paper, we derive an analytical solution to demonstrate the importance of integrated planning (IP) approaches for two-stage blending operations in recycling. Our results suggest that the quality of materials obtained from the first stage strongly influences performance in the second stage. Current disjointed planning (DP) approaches in the recycling industry, where individual stages are independently planned without decision-making about intermediate blend design, overlook this interaction and, therefore, make conservative use of lower quality materials. We develop an IP model using a formulation of the pooling problem and apply it to an industrial-scale aluminum recycling facility located in Europe. The results suggest that the IP model can reduce material costs by more than 5%, for the case examined, and can enable increased use of undervalued raw materials. This study also investigates the impact of variations in operational conditions on the benefits of IP. Keywords: Production; Material recycling; Integrated planning; Two-stage blending process (pooling problem); Design of intermediate productsNational Science Foundation (U.S.) (Award 1605050)Fundação para a Ciência e a Tecnologia (Project MITP-TB/PFM/0005/2013
End-of-life LCA allocation methods: open loop recycling impacts on robustness of material selection decisions
Materials selection decisions exhibit great influence on the environmental performance of firms through their impact on processing technology, product form, and supply chain configuration. Consequently, materials dictate a product's environmental profile via the burden associated with extraction and refining, transformation from material to product, product performance characteristics during use, and potential recovery at end-of-life (EOL). While lifecycle assessment (LCA) methods provide quantitative input to a product designer's materials selection decision, LCA implementations are evolving and disparate. This work explores several analytical variations of LCA related to the allocation of recycling impacts at product EOL and the implications of these variants across a range of contexts. Stylized analyses across a range of materials are presented, focusing on materials with varying primary and secondary materials production burdens. This work illustrates that a) the application of distinct EOL allocation methods give different values of cumulative environmental impact for the same material, b) these impacts change at differing rates between the various methods, and c) these disparities can result in different rank ordering of materials preference. Characterizing this behavior over a range of parameters illustrates the potential trends in allocation method bias for or against particular materials classes
Modeling the Impact of Product Portfolio on the Economic and Environmental Performance of Recycling Systems
hrough the development of a general model of electronics recycling systems, the effect of product portfolio choices on economic and environmental system performance is explored. The general model encompasses the three main functions of a recycling system-collection, processing, and system management-and allows for the effect of both contextual and architectural inputs-including product scope-to be explored. Overall model results indicate that collecting a broader portfolio of products can be economically favorable, even for cases in which lower-value products are added to a recycling system. In these cases, the higher total mass throughputs that are realized by the collection of additional product types can help to drive down the cost per unit mass collected. Expanding product scope can also yield improvements in environmental performance, as the energy per unit mass collected can also decrease with higher mass throughputs