Additive Manufacturing in Supply Chains:
Environmental Risks and Benefits

Scott J. Warren, PhD
University of North Texas

Brent Tincher
Lockheed Martin

Brad Trussell
Texas Christian University

Sustainable Manufacturing Assessment Framework

Framework Integration: Synthesized from Bhakar et al. (2018), Bonilla Hernandez et al. (2019), Kumar & Mani (2022), Scharmer et al. (2024), and Swarnakar et al. (2022)

Five Core Dimensions

Assessment Methods & Tools
Methodologies for measuring environmental impact
Sustainability Dimensions
Environmental, economic, and social factors
Technology Comparison
AM versus traditional manufacturing methods
Materials & Properties
Raw material impacts and performance
Certification & Standards
Quality assurance and regulatory frameworks
This integrated framework enables comprehensive analysis of environmental trade-offs across the complete supply chain lifecycle

Research Methodology

Framework: Cooper et al. (2018) seven-stage literature search with Onwuegbuzie & Teddlie (2003) data transformation protocols

Study Corpus Development

Initial Collection
67 articles from databases
First Review
52 retained after vetting
Network Expansion
25 added via ResearchRabbit
Final Corpus: 77 peer-reviewed publications (2005-2024)

Six Thematic Categories

  • Hazardous materials in manufacturing
  • Raw materials mining & transportation
  • Materials disposal & recycling
  • Greenhouse gas emissions
  • Energy production & usage
  • Social challenges across lifecycle
Sources: JSTOR, Elsevier, Web of Science, Google Scholar, Elicit AI, ResearchRabbit.AI, Harzing's Publish or Perish

Supply Chain Speed and Efficiency

Rapid Prototyping and Production

AM enables companies to compress product development cycles from months to weeks by eliminating traditional tooling requirements (Ott et al., 2019; Rizzi et al., 2014)

On-Demand Manufacturing

Just-in-time production capabilities reduce inventory holding costs and warehouse space requirements while improving supply chain responsiveness (Liu et al., 2023; Yang et al., 2019)

Spare Parts and Maintenance

Digital inventories of spare parts can be produced on-demand, eliminating obsolescence concerns and reducing storage costs (Ott et al., 2019; Alsaadi, 2021)

These efficiency gains translate directly to reduced environmental impact through decreased transportation, warehousing energy consumption, and inventory waste

Localized Production and Transportation Reduction

Distributed Manufacturing Networks

AM enables production closer to end-users, dramatically reducing transportation distances and associated emissions (Bekker & Verlinden, 2018; Yang et al., 2019)

Reduced Carbon Footprint

Eliminating long-distance shipping and air freight can offset manufacturing energy consumption in many applications (Faludi et al., 2015; Burkhart & Aurich, 2015)

Environmental Benefits:
  • Lower transportation emissions
  • Reduced packaging waste
  • Decreased fuel consumption
  • Smaller carbon footprint
Economic Benefits:
  • Lower shipping costs
  • Faster delivery times
  • Regional manufacturing jobs
  • Supply chain resilience

Material Waste and Resource Efficiency

Additive vs. Subtractive Manufacturing

Traditional machining can waste 40-90% of input material, while AM typically uses 90-98% of feedstock material (Paris et al., 2016; Faludi et al., 2015)

Material Efficiency:
  • Minimal material waste during production
  • Complex geometries without excess material (Ingarao et al., 2018)
  • Optimized designs for strength-to-weight ratios
  • Reduced raw material extraction (Liu et al., 2023)
Environmental Context:
  • Lower mining and extraction impacts
  • Reduced transportation of raw materials
  • Decreased landfill waste
  • Conservation of finite resources
Material efficiency represents one of AM's most significant environmental advantages, particularly for high-value materials like titanium and specialized alloys

Design Innovation and Functional Integration

Complex Geometries and Optimization

AM enables designs impossible with traditional manufacturing, including topology optimization, lattice structures, and biomimetic forms that maximize performance while minimizing material use (Liu et al., 2023; Agustí-Juan & Habert, 2017)

Part Consolidation:
  • Multiple components into single parts
  • Eliminated assembly steps (Ren et al., 2022)
  • Reduced failure points
  • Simplified supply chains
Lightweighting:
  • Aerospace fuel savings (Ingarao et al., 2018)
  • Automotive efficiency gains
  • Reduced operational emissions
  • Extended product lifetime
Use-phase environmental benefits from lightweighting can offset higher manufacturing energy consumption in transportation applications (Peng et al., 2018; Ingarao et al., 2018)

Material Production Energy and Emissions

High Energy Powder Production

Metal powder production through atomization is energy-intensive, requiring 10-50 times more energy than producing bulk metal (Fredriksson, 2019; Peng et al., 2018)

Material Processing Impacts:
  • Energy-intensive atomization processes
  • Specialized powder handling requirements
  • Quality control and certification (Liao & Cooper, 2020)
  • Material purity requirements
Environmental Burden:
  • Increased embodied energy (Ingarao et al., 2018)
  • Higher greenhouse gas emissions
  • Additional processing steps
  • Specialized facility requirements
The choice between powder and bulk material forms significantly influences the total environmental impact of the manufacturing process (Priarone & Ingarao, 2017)

Manufacturing Process Energy Intensity

High Process Energy Requirements

Metal AM processes like selective laser melting require substantial energy due to high laser power, controlled atmospheres, and thermal management (Peng et al., 2018; Alsaadi, 2021)

Energy Consumption Factors:
  • High-power laser or electron beam systems
  • Inert atmosphere generation and maintenance
  • Precise thermal control systems (Liao & Cooper, 2020)
  • Extended build times for complex parts
Material-Specific Challenges:
  • Aluminum requires more energy due to high reflectivity and thermal conductivity (Ingarao et al., 2018)
  • Some processes are order of magnitude worse than conventional methods
  • Energy grid carbon intensity matters
AM can be less environmentally friendly than conventional methods unless significant use-phase benefits are achieved (Ingarao et al., 2018; Peng et al., 2021)

Emissions and Occupational Health Impacts

Particulate Matter and VOC Emissions

AM processes emit ultrafine particles and volatile organic compounds that pose health risks and environmental concerns (Khaki et al., 2022; Sittichompoo et al., 2020)

Health Concerns:
  • Ultrafine particle inhalation risks
  • VOC exposure in work environments (Khaki et al., 2022)
  • Metal powder handling hazards
  • Long-term health effects unclear
Regulatory Challenges:
  • Varying international standards
  • Uncontrolled emissions in some regions (Rizzi et al., 2014; Sovacool et al., 2020)
  • Inadequate ventilation systems
  • Monitoring and compliance gaps
Proper ventilation, filtration, and safety protocols are essential but not universally implemented, particularly in emerging markets and smaller facilities

End-of-Life and Recycling Challenges

Complex Material Recycling

AM often uses specialized alloys, composites, and multi-material parts that are difficult or impossible to recycle with current technology (Di & Yang, 2022; Liu et al., 2023)

Recycling Barriers:
  • Mixed materials in single parts
  • Contaminated metal powders (Fredriksson, 2019)
  • Degraded material properties after recycling
  • Limited recycling infrastructure
Disposal Challenges:
  • Unused powder disposal concerns
  • Support structure waste (Paris et al., 2016)
  • Hazardous material handling
  • Landfill contamination risks
Emerging Solutions: Research into closed-loop material systems and improved recycling technologies shows promise but requires significant development (Di & Yang, 2022; Ott et al., 2019)

Context-Dependent Environmental Impact

The environmental impact of AM versus traditional manufacturing depends critically on application context, production volume, material choices, and use-phase considerations (Ingarao et al., 2018; Peng et al., 2018)

Favorable AM Applications

✓ Low-Volume Production

Spare parts, custom medical devices, rapid prototyping (Ott et al., 2019)

✓ High-Value Lightweighting

Aerospace, motorsport, where use-phase energy savings exceed manufacturing impact (Ingarao et al., 2018)

Less Favorable AM Applications

✗ High-Volume Mass Production

Traditional methods often more efficient at scale (Paris et al., 2016)

✗ Non-Critical Weight Applications

Where lightweighting provides no operational benefit (Peng et al., 2021)

Life cycle assessment must consider complete supply chain, use phase, and end-of-life to make informed decisions (Agustí-Juan & Habert, 2017; Faludi et al., 2015; Farjana et al., 2019)

Future Innovations and Opportunities

Generative AI and Design Optimization

AI-driven generative design can create highly optimized structures that maximize performance while minimizing material use and environmental impact (Filz & Thiede, 2024; Westphal & Seitz, 2024)

Technology Advances:
  • More energy-efficient processes
  • Faster build speeds (Liu et al., 2023)
  • Expanded material options
  • Improved recyclability
Sustainable Materials:
  • Bio-based polymers
  • Recycled feedstocks (Di & Yang, 2022)
  • Lower-energy materials
  • Circular economy integration
Continued research in digital transformation and AI-driven manufacturing is crucial for realizing AM's full sustainability potential (Filz & Thiede, 2024; Westphal & Seitz, 2024)

Strategic Recommendations for Sustainable AM Implementation

1. Conduct Comprehensive Life Cycle Assessments

Evaluate complete environmental impact including material production, manufacturing, use phase, and end-of-life before implementing AM (Bhakar et al., 2018; Kumar & Mani, 2022)

2. Prioritize Appropriate Applications

Focus on low-volume, high-value, or lightweighting applications where AM provides clear environmental advantages (Ott et al., 2019; Ingarao et al., 2018)

3. Invest in Sustainability Training

Develop organizational knowledge and capabilities in sustainable manufacturing practices and assessment methodologies (Birou et al., 2019; Scharmer et al., 2024)

4. Develop Closed-Loop Material Systems

Implement powder recycling, material recovery, and circular economy approaches (Di & Yang, 2022; Fredriksson, 2019)

5. Monitor and Control Emissions

Ensure proper ventilation, filtration, and environmental controls in AM facilities (Khaki et al., 2022)

Conclusion: Balanced Path Forward

Additive manufacturing presents both unprecedented opportunities and significant challenges for supply chain sustainability
Key Benefits:
  • Dramatic waste reduction (Paris et al., 2016)
  • Supply chain localization (Bekker & Verlinden, 2018)
  • Design optimization possibilities (Liu et al., 2023)
  • Operational efficiency gains (Ott et al., 2019)
Critical Challenges:
  • High energy consumption (Peng et al., 2018)
  • Material production impacts (Fredriksson, 2019)
  • Emissions concerns (Khaki et al., 2022)
  • End-of-life limitations (Di & Yang, 2022)
Path Forward: Success requires context-appropriate applications, comprehensive life cycle thinking, continued innovation, and integration with circular economy principles (Scharmer et al., 2024; Kumar & Mani, 2022)
Future innovations in AI-driven design, sustainable materials, and closed-loop systems offer promise for enhancing AM's environmental performance (Filz & Thiede, 2024; Westphal & Seitz, 2024)

References (Part 1 of 2)

Agustí-Juan, I., & Habert, G. (2017). Environmental design guidelines for digital fabrication. Journal of Cleaner Production, 142, 2780-2791.
Alsaadi, N. (2021). Prioritization of challenges for the effectuation of sustainable additive manufacturing: A case study approach. Processes, 9(12).
Bekker, A. C. M., & Verlinden, J. C. (2018). Life cycle assessment of wire + arc additive manufacturing compared to green sand casting and CNC milling in stainless steel. Journal of Cleaner Production, 177, 438-447.
Bhakar, V., Digalwar, A. K., & Sangwan, K. S. (2018). Sustainability Assessment Framework for the Manufacturing Sector - A Conceptual Model. Procedia CIRP, 69, 248-253.
Birou, L. M., Green, K. W., & Inman, R. A. (2019). Sustainability knowledge and training: outcomes and firm performance. Journal of Manufacturing Technology Management, 30(2), 294-311.
Bonilla Hernandez, A. E., Lu, T., Beno, T., Fredriksson, C., & Jawahir, I. S. (2019). Process sustainability evaluation for manufacturing of a component with the 6R application. Procedia Manufacturing, 33, 546-553.
Burkhart, M., & Aurich, J. C. (2015). Framework to predict the environmental impact of additive manufacturing in the life cycle of a commercial vehicle. Procedia CIRP, 29, 408-413.
Cooper, H. M., Hedges, L. V., & Valentine, J. C. (Eds.). (2018). The Handbook of Research Synthesis and Meta-Analysis (3rd ed.). Russell Sage Foundation.
Di, L., & Yang, Y. (2022). Towards closed-loop material flow in additive manufacturing: Recyclability analysis of thermoplastic waste. Journal of Cleaner Production, 362, 132427.
Faludi, J., Bayley, C., Bhogal, S., & Iribarne, M. (2015). Comparing Environmental Impacts of Additive Manufacturing vs. Traditional Machining via Life-Cycle Assessment. Rapid Prototyping Journal.
Farjana, S. H., Huda, N., & Mahmud, M. A. P. (2019). Impacts of aluminum production: A cradle-to-gate investigation using life-cycle assessment. Science of the Total Environment, 663, 958-970.

References (Part 2 of 2)

Filz, M. A., & Thiede, S. (2024). Generative AI in Manufacturing Systems: Reference Framework and Use Cases. IFAC-PapersOnLine, 58(27), 238-243.
Fredriksson, C. (2019). Sustainability of metal powder additive manufacturing. Procedia Manufacturing, 33, 139-144.
Ingarao, G., Priarone, P. C., Deng, Y., & Paraskevas, D. (2018). Environmental modelling of aluminium based components manufacturing routes: Additive manufacturing versus machining versus forming. Journal of Cleaner Production, 176, 261-275.
Khaki, S., Rio, M., & Marin, P. (2022). Characterization of Emissions in Fab Labs: An Additive Manufacturing Environment Issue. Sustainability, 14(5).
Kumar, M., & Mani, M. (2022). Sustainability Assessment in Manufacturing for Effectiveness: Challenges and Opportunities. Frontiers in Sustainability, 3.
Liao, J., & Cooper, D. R. (2020). The environmental impacts of metal powder bed additive manufacturing. Journal of Manufacturing Science and Engineering-Transactions of The ASME.
Liu, W., Liu, X., Liu, Y., Wang, J., Evans, S., & Yang, M. (2023). Unpacking Additive Manufacturing Challenges and Opportunities in Moving towards Sustainability: An Exploratory Study. Sustainability.
Onwuegbuzie, A. J., & Teddlie, C. (2003). A framework for analyzing data in mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of Mixed Methods in Social and Behavioral Research (pp. 351-383). Sage.
Ott, K., Pascher, H., & Sihn, W. (2019). Improving sustainability and cost efficiency for spare part allocation strategies by utilisation of additive manufacturing technologies. Procedia Manufacturing, 33, 123-130.
Paris, H., Mokhtarian, H., Coatanéa, E., Museau, M., & Ituarte, I. F. (2016). Comparative environmental impacts of additive and subtractive manufacturing technologies. CIRP Annals, 65(1), 29-32.
Peng, T., Kellens, K., Tang, R., Chen, C., & Chen, G. (2018). Sustainability of additive manufacturing: An overview on its energy demand and environmental impact. Additive Manufacturing, 21, 694-704.

References (Part 3 of 3)

Peng, T., Zhu, Y., Chen, Y., Yang, Y., & Tang, R. (2021). An energy aware approach for sustainable additive manufacturing. Journal of Cleaner Production, 312.
Priarone, P. C., & Ingarao, G. (2017). Towards criteria for sustainable process selection: On the modelling of pure subtractive versus additive/subtractive integrated manufacturing approaches. Journal of Cleaner Production, 144, 57-68.
Ren, D., Choi, J. K., & Schneider, K. (2022). A multicriteria decision-making method for additive manufacturing process selection. Rapid Prototyping Journal, 28(11), 77-91.
Rizzi, F., Frey, M., Testa, F., & Appolloni, A. (2014). Environmental value chain in green SME networks: The threat of the Abilene paradox. Journal of Cleaner Production, 85, 265-275.
Scharmer, V. M., Vernim, S., Horsthofer-Rauch, J., Jordan, P., Maier, M., Paul, M., Schneider, D., Woerle, M., Schulz, J., & Zaeh, M. F. (2024). Sustainable Manufacturing: A Review and Framework Derivation. Sustainability, 16(1).
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