ACG Packaging reduces defects 71% and lead times 40% with IIoT and generative AI at Shirwal

ACG Packaging Materials' Shirwal facility operates in pharmaceutical packaging — a sector where quality failures carry regulatory and patient-safety consequences far beyond typical manufacturing. The site faced compounding pressures: a commoditizing market squeezing margins, rising energy costs, and quality defect rates that threatened both compliance standing and customer relationships. Lead times were too long to remain competitive against leaner rivals, and existing manual inspection and scheduling processes lacked the granularity to identify root causes quickly. Without systemic change, the plant risked losing ground on cost, agility, and the stringent quality standards that pharmaceutical customers require.

The Shirwal site undertook a broad digital transformation, deploying more than 30 discrete use cases across IIoT sensor integration, machine learning, digital twin modeling, and generative AI. IIoT infrastructure provided real-time visibility into machine states, energy consumption, and process variables across the production floor. Digital twins of key lines enabled virtual scenario testing before physical changes were made. Generative AI was layered on top — used to synthesize operational data, surface anomalies, and support decision-making in quality control and logistics planning. Rather than a single-vendor point solution, the transformation was structured as an integrated capability stack, with use cases rolled out in waves to validate impact before scaling across the site.

The combined technology stack delivered measurable improvement across every targeted dimension. Defects dropped by 71%, the headline outcome reflecting the direct impact of AI-assisted quality inspection and real-time process monitoring. Additional verified outcomes include:

• 40% reduction in lead times, improving responsiveness to pharmaceutical customers
• 20% reduction in raw material costs through tighter inventory and process control
• 31% reduction in energy consumption, driven by IIoT-based load optimization
• 34% improvement in on-time delivery in full (OTIF), a key pharmaceutical supply chain metric

The breadth of improvement across cost, quality, and service simultaneously signals that gains came from systemic process change, not isolated point fixes.

• A portfolio approach — deploying 30+ use cases rather than one flagship tool — distributes risk and surfaces wins faster than a single large-bet implementation.
• Digital twins and IIoT must be in place before generative AI can add value; the AI is only as good as the real-time data infrastructure beneath it.
• In pharmaceutical packaging, quality and compliance improvements are the highest-leverage starting point — they build organizational trust in AI outputs and unlock further adoption.
• Energy and material cost reductions can be pursued in parallel with quality initiatives without trading one off against the other when root-cause data is available.
• Lighthouse-recognized sites demonstrate that mid-size packaging operations can achieve enterprise-grade AI outcomes without greenfield infrastructure.