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Iowa State University

Improving Recycling Efficiency of Portable Electronics by Automating Battery Disassembly

Improving Recycling Efficiency of Portable Electronics by Automating Battery Disassembly

This project proposes to develop an automated and integrated battery disassembly process for EOL PCEs using a modular approach, as well as design and develop a component disassembly and battery removal process using a combination of mechanical (e.g., robotic disassembly, water-jet cutting), chemical, and thermal approaches to increase EOL PCE materials recover and processes throughputs

Upon completion, this project will design a prototype system, built and operated to confirm system effectiveness. This project will increase secondary materials by 0.03 million metric tons (MMT) of e-waste, 3.6 PJ energy reduction, 0.180MMTCO2e. Assumptions based on recovery of 20% of 150,000 metric tons per year of PCE discarded.

Project Team:
Idaho National Laboratory (INL), Sunnking, University at Buffalo (UB), Iowa State University (ISU)

21-01-RM-5083

Hybrid Laser Processing for Metallic Surface Remanufacturing

Hybrid Laser Processing for Metallic Surface Remanufacturing

The goal of this project is to develop a novel remanufacturing strategy using hybrid laser surface processing for effective removal of corrosion and coatings and fast repair of metallic surfaces. In specific, laser surface ablation will be used to remove coating/corrosion, while laser surface remelting will be applied to repair surface defects (cracks and wear damages) to restore the surface integrity. The outcomes of this research will yield a prototype robot-integrated hybrid laser system that can be used for surface remanufacturing of components with complex geometry. This project's energy savings are estimated at 16.5MJ/kg of reman product. 

Project Team:
Iowa State University (ISU), University of Nevada, Reno, Volvo

21-01-RM-5086

Data-Driven Design Decision Support for Remanufacturing of High-Value Components in Industrial and Agricultural Equipment

Data-Driven Design Decision Support for Remanufacturing of High-Value Components in Industrial and Agricultural Equipment

This project aims to develop and validate a new tool package (D4Reman) for design decision analysis to improve the reuse rates of high-value components at end-of-life. The project is a continuation of exploratory project 18-02-DE-06. Upon completion, this project will create a software tool package (D4Reman) for data-driven design decision support consisting of a cloud-based software application along with an Excel plugin. It will utilize field reliability data and reman reuse data to identify design improvement decisions and quantitatively assess their influences on the initial cost, life-cycle warranty cost (LCWC), and energy and emissions. This project will reduce primary feedstock by 0.55 million metric tons (MMT) of steel and aluminum, 7 PJ energy reduction, 0.42 MMCO2e. Assumptions based on preliminary results of exploratory project.

Project Team:
Iowa State University (ISU), University of Illinois at Urbana-Champaign (UIUC), Mississippi State University, John Deere, Automotive Parts Remanufacturers Association (APRA)

21-01-DE-5071

Development of Hybrid Repair and Nondestructive Evaluation Technologies for Aerospace Components

Development of Hybrid Repair and Nondestructive Evaluation Technologies for Aerospace Components

The objective of this project is to develop an integrated hybrid DED/insitu multi-modal data acquisition and NDE modeling of DED repairs for aerospace materials (i.e. medium carbon low alloy steel and a nickel-based superalloy) to increase the successful repair and reuse of these materials. This proposed project is a continuation exploratory project 18-01-RM-09.  

The final product will be a complete software package that can automatically perform multi-modal (surface topography and thermal imaging) in-situ data acquisition (residual stresses) and nondestructive evaluation (NDE) analysis for industry users without expertise in 3D scanning, thermal imaging, and XRD. This project will create embodied energy savings of 1.56PJ and GHG emissions reduction of 0.0915MMT of CO2, based on an increase in successful repair of 0.021MMT of aerospace parts such as turbine shafts.

Project Team:
Rochester Institute of Technology (RIT), Iowa State University (ISU), The Ohio State University (OSU), Simufact, Hybrid Manufacturing Tech, Proto Mfg. Inc., Pratt & Whitney

21-01-RM-5062

Rapid Damage Identification to Reduce Remanufacturing Costs

Rapid Damage Identification to Reduce Remanufacturing Costs

The objective of this project is to develop and validate a remanufacturability assessment method that will support decision making about the viability of remanufacturing a component. The proposed method is based on development of machine learning (ML) techniques for recognizing different types of component damage, embedding developed ML algorithms in low-cost, damage-identification hardware for use in-process at the remanufacturing factory floor, and using this in-process technique to develop a real- time estimate of remanufacturing costs for a component. Although most high-value, metal-alloy components can be remanufactured, sufficiently accurate and rapid decision making support tools are needed to significantly reduce remanufacturing costs and increase the throughput and volume of remanufactured components.

Project Team:
Iowa State University, John Deere & Company

19-01-RM-05

In-situ Nondestructive Evaluation of In-flight Particle Dynamics and Intrinsic Properties for Thermal Spray Repairs

In-situ Nondestructive Evaluation of In-flight Particle Dynamics and Intrinsic Properties for Thermal Spray Repairs

The quality of coated surfaces from thermal spray repairs is determined by the particles impacting the surface. A better understanding of in-flight particle dynamics will enable improved success rates for repairs in the remanufacturing industry.

Project Team:
Iowa State University, John Deere

18-01-RM-09

Quantification of Financial and Environmental Benefits Tradeoffs in Multi-Generational Product Family Development Considering Re-X Performances

Quantification of Financial and Environmental Benefits Tradeoffs in Multi-Generational Product Family Development Considering Re-X Performances

The objectives are to develop fundamental models and new design tools with capabilities of generating and comparing design for Re-X alternatives considering economic profitability and environmental impact savings. The specifics of the research objectives are to (1) identify design for reliability processes factors that are interdependent with Re-X options, thus establish models for the interdependencies, (2) integrate these interdependence models with existing reliability analysis tools so that new analysis tools could take into account Re-X options in design for reliability, (3) create a decision support system for the optimization of product family design considering reliability and Re-X options concurrently, and (4) take into account the uncertainties resulted from post design activities so that robust design tradeoff decisions can be made.

Project Team:
University of Illinois at Urbana-Champaign, Iowa State University, Deere and Company, Green Electronics Council

19-01-DE-01

Cross-Industry Utilization of Ground Tire Rubber for Energy Efficient Pavements

Cross-Industry Utilization of Ground Tire Rubber for Energy Efficient Pavements

This project will examine ways to better utilize ground tire rubber from recycled tires and use the particles in asphalt pavement. Ground tire rubber is currently being used as an asphalt modifier, however because of the difference in density with asphalt it suffers from inadequate storage stability, rendering it an un-preferred material in asphalt paving.

Iowa State University has developed a technology that matches ground rubber tire density with asphalt (and enables the substitution of SBS elastomers that are otherwise used in asphalt) with simple compounding techniques, producing a asphalt product that meets storage stability specifications that would be more acceptable to the paving industry.  The energy savings opportunity from this technology is estimated at 4.2 PJ per year.

Project Team:
Iowa State University, Michelin, Lehigh Technologies (Subsidiary of Michelin)

18-02-MM-03

Design Iteration Tool to Sustain Remanufacturability

Design Iteration Tool to Sustain Remanufacturability

The overall goal of this project is the development and application of a software plug-in to enable the design of components that will satisfy both EPA standards-driven light weighting efforts and parametric feature designs that enable remanufacturability (e.g., remove material where feasible for light-weighting and, at the same time, add material where needed to sustain remanufacturability). To achieve this goal, the first objective of this project is to establish a best practice approach to modify a typical design process for DfReman. The second objective is the creation of a software plugin for mainstream CAD software to enable design for remanufacturing consideration of high-value components. This tool will use realistic life estimates to automatically generate design alternatives for sustained remanufacturability, thereby reducing energy, emissions, material consumption and cost. This tool development will focus on engine cylinder heads and industrial pump components and will facilitate the generation of designs that will make components more readily available for remanufacturing processes, such as, re-machining of critical wear features for return to service, complete with estimates of cost/benefit of analysis for multiple lifecycles. The third and final objective disseminate the results of this project by developing training videos on the application of DfReman rules and the software plugin and creating a website to disseminate the plugin and training materials.

Project Team:
Iowa State University, Danfoss

19-01-DE-09

Data-Driven Design Decision Support for Re-X of High-Value Components in Industrial and Agricultural Equipment

Data-Driven Design Decision Support for Re-X of High-Value Components in Industrial and Agricultural Equipment

This project will create a tool to evaluate and recommend the optimal designs of components in industrial and agricultural equipment. By designing components with optimum material utilization and end-of-life in mind, there is a 60% reduction in carbon emissions.

The novelty of this tool lies in its ability to incorporate real-world load/component health data that has been acquired by condition monitoring systems in the field into early-stage design assessment using random variable models. This approach enables data-informed design for Re-X.

Project Team:
Iowa State University, John Deere

18-02-DE-06

 

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