Ayna at CONEXPO-CON/AGG

About Ayna

Ayna provides advisory and implementation services to companies, executives, and both private equity and public market investors in the industrial technology space.

We work in an engaged operator model to optimize performance and drive growth. Ayna actively engages in advisory and execution with our clients, aligning incentives with outcomes. Thanks to our deep understanding of the industrials space and a wide breadth of experience, we’re able to flex our offerings for each client, creating a bespoke experience that delivers the most value.

Top 3 Challenges in AI Implementation for Heavy Industry

Data Silos from Mixed Heavy Fleets
47% of heavy industry leaders cite silos as #1 barrier; old crushers (2010-era) and new haulers (2024 models) generate mismatched data that AI can't process on mine or quarry sites.
70% of pilots fail when sensors from different equipment brands yield junk inputs for models.
Talent Shortage in Site Operations
58% of mining and aggregates firms lack workers who know dirt-moving ops and AI setup, worsened by retiring rig experts.
Only 12% of earthmoving or lifting projects use AI daily due to this skills void.
Data Silos from Mixed Heavy Fleets
28% of execs balk at $50M+ costs for mine-wide AI (sensors on SAG mills, drills), fearing no quick payback amid volatile freight.
75% of heavy equipment AI trials stall from integration bills without clear fuel or uptime gains.

Driving AI Value & ROI in Heavy Industry

Predictive Maintenance
30-50% fewer breakdowns on SAG mills, excavators, and cranes; extends gear life 20-40% in mining ops.
AI flags motor vibes early, saving $1M+/day at large quarries vs. reactive fixes.
Fuel & Cycle Efficiency
25% fuel cut via smart routing on earth diggers and haulers; 15% faster concrete pours with robotic batching.
Lifting ops see 20% idle time drop, direct hit to volatile diesel costs.
ESG & Energy Savings
Comminution (up to 56% of mine power) stabilized by AI, trimming spikes 10-15% and CO₂ output.
Aggregates crushers run leaner, cutting reagents 20% for greener balance sheets.

Asset Integration Challenges in Heavy Industry

Incompatible Asset Protocols
65% of quarry sites mix old asphalt mixers (manual logs) with new haulers (IoT streams), blocking unified AI dashboards across fleets.
Scaling Pilots to Full Sites
70% of digital twin tests pass on single crushers but fail linking 50+ assets like lifts, batch plants, and drills.
Cyber Risks in Connected Fleets
40% of execs skip site-wide integration fearing hacks — $10K/hour downtime cripples aggregates ops.

Our Experts

Alan a President at Ayna with more than two decades of experience leading turnarounds, scaling operations, and modernizing asset-intensive businesses across building materials, construction, and natural resources. He has held senior operating and advisory roles at companies including Accenture, CEMEX, CRH/Oldcastle, Rinker Materials, U.S. Silica, and Proudfoot, where he built and led high-performance teams, ran P&Ls, and delivered measurable financial and operational results.

Most recently as a Principal Director at Accenture, Alan led the firm’s Building Materials practice in North America, helping clients undertake large-scale transformations that combine SAP S/4HANA, advanced planning, digital twins, and AI-enabled decision tools.

Contact Alan: alan.maio@ayna.ai

Sources:
Top 3 Challenges: https://imubit.com/article/ai-adoption-in-manufacturing/, https://thinaer.io/blog/5-iot-and-ai-integration-mistakes-that-cause-70-of-projects-to-fail/,  https://www.jsheld.com/insights/articles/enterprise-ai-implementation-in-heavy-industry-a-digital-transformation-strategy-for-su, https://www.rics.org/news-insights/artificial-intelligence-in-construction-report, https://cio.works/blog/why-75-of-businesses-arent-seeing-roi-from-ai-yet/,  https://imubit.com/article/ai-adoption-in-manufacturing/
Driving Value: https://www.miningdoc.tech/question/how-can-predictive-analytics-lower-maintenance-costs-in-fixed-plant-circuits/ , https://symx.ai/revolutionizing-predictive-maintenance-in-the-mining-industry-with-ai , https://www.samsara.com/blog/construction-companies-reduce-fuel-waste, https://www.intangles.ai/smart-route-optimization-how-ai-is-slashing-fuel-costs-driving-green-logistics/,  https://miningdigital.com/news/allianz-addressing-mining-concerns-opportunities, http://www.ceecthefuture.org/wp-content/uploads/2013/01/Ballantyne.pdf, https://imubit.com/article/comminution-optimization-ai/
Asset Integration: https://xmpro.com/the-top-10-challenges-preventing-industrial-ai-at-scale-and-exactly-how-to-beat-them/, https://www.jsheld.com/insights/articles/enterprise-ai-implementation-in-heavy-industry-a-digital-transformation-strategy-for-su, https://imubit.com/article/ai-adoption-in-manufacturing/,  https://ifactory.jrsinnovation.com/blog/ai-heavy-manufacturing-downtime-quality