Enhancing Efficiency & Quality with Industrial AI at Pernod Ricard

The Customer

Pernod Ricard, a global leader in wine and spirits was looking to optimize their manufacturing operations. There was hidden capacity in their existing plants, which could get unlocked by leveraging machine data. This could drive operational improvements that could defer and possibly avoid heavy capital investments.
Pernod Ricard India partnered with Altizon Inc to deploy Altizon’s Digital Factory (DFX) platform in 140+ bottling lines spread across 28 plants.
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The Problem

The bottling industry has long grappled with challenges related to production optimization, waste reduction, & maintaining high-quality standards. Bottling lines are highly automated but the data generated during this process are spread across multiple hardware & software systems provided by a variety of OEM vendors.
For instance, OEE, a key metric that drives productivity was manually calculated by production teams. This leads to low-fidelity data and inaccurate baselining. Quality systems were separate, & the process was often non-digital leading to poor traceability and high cost of quality.
Bottling operations are heavy on energy and consumables (such as water). Calculating key KPIs such as specific energy consumption was manual, prone to approximations and inaccuracies.

The Solution

Step 1: Altizon designed an accurate data acquisition strategy.

Data-acquisition hardware and software was deployed to connect bottling lines across OEMs. High-fidelity data, directly from machines was transferred and analyzed on DFX in real-time. Integrations were made with ERP to pull production metadata to build plan vs. actual scenarios. QMS systems were integrated, and paper quality checks were digitized to bring quality data into the platform for co-relation analytics. Connected energy and water meters were deployed to collect information accurately and at the right precision.

Step 2: Leverage the power of Analytics & AI

Altizon deployed several DFX modules to drive data-driven insights. DFX Productivity: To establish baseline productivity that is accurate. To dive deep into factors that affect productivity & for insights on how to remediate. DFX Maintenance: To identify machine & process parameters that indicate an early failure. To move from periodic to predictive maintenance. DFX Quality: To establish end-to-end traceability of quality parameters. DFX Sustainability: To establish and track specific energy & water consumption. DFX Cockpit: To analyze performance across plants & establish benchmarks.

Step 3: Continuous improvement, driven by data

Altizon’s business consulting team worked with PRI’s operations team to ensure system stickiness. Ensuring that the accuracy and fidelity of the data being provided by the system could be trusted. Driving process change and system adoption across various stakeholders Measuring and presenting ROI metrics PRI initially deployed the system across 4 plants and 10 lines. Over the next two years, the solution was systematically deployed across the rest of the plants.

Benefits

Better Outcomes

10% throughput improvement over baseline within 1 year of implementation.

Reduced Costs

10% Reduction in in-direct labor cost

Better Resource Allocation

25% improvement in Mean Time to Recover (MTTR) resulting in higher availability.

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