Key Takeaways
- In 2022, the US forging industry employed 28,500 workers directly
- Global forging workforce estimated at 1.2 million in 2022, with 40% in Asia
- India forging sector employed 250,000 people in FY2022
- Automotive industry consumed 55% of global forged steel, 18.2 million tons 2022
- Aerospace sector used 12% of world forgings, 5.5 million tons 2022
- Oil & gas applications accounted for 15% forging demand, 6.8 million tons 2022
- In 2022, the global forging market was valued at USD 82.5 billion and is projected to reach USD 112.4 billion by 2030, growing at a CAGR of 3.9% from 2023 to 2030
- The North American forging market size was estimated at USD 12.4 billion in 2022 and expected to grow at a CAGR of 4.2% from 2023 to 2030, driven by automotive demand
- Asia Pacific dominated the forging market with a 45% revenue share in 2022, fueled by rapid industrialization in China and India
- Global steel forging material usage reached 42.3 million tons in 2022, representing 65% of total forgings
- Aluminum alloys comprised 18% of global forging materials by volume in 2022, totaling 7.8 million tons
- Titanium and superalloys used in 2.1% of forgings, 950,000 tons globally 2022
- In 2022, US forging industry shipped 2.1 million tons of forgings, up 4% from 2021
- China produced 12.5 million metric tons of forged products in 2022
- Global steel forging production reached 45.6 million tons in 2022
In 2022, forging employed 1.2 million people globally and grew worldwide demand across key end markets.
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Production Statistics Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Isabelle Moreau. (2026, February 13). Forging Industry Statistics. Gitnux. https://gitnux.org/forging-industry-statistics
Isabelle Moreau. "Forging Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/forging-industry-statistics.
Isabelle Moreau. 2026. "Forging Industry Statistics." Gitnux. https://gitnux.org/forging-industry-statistics.
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