Elevating packing & packaging processes through digitalization and smart factory implementation

The future of packing & packaging

The packing and packaging (P&P) industry is undergoing significant changes driven by a growing emphasis on sustainability, innovation, and digital transformation. The convergence of digital technologies with packing and packaging solutions is reshaping global manufacturing by improving efficiency, sustainability, and competitive advantage. The rising consumer awareness of environmental issues is further driving the need for sustainable packaging materials and solutions.

Companies in the packing and packaging sector are facing increased demands for innovation, flexibility, and precision in design and production. To succeed, they must develop a clear vision, position, and capabilities for comprehensive packaging optimization. Engaging the entire value chain is crucial for driving improvements through holistic packaging optimization, using supplier relationship management (SRM) and vertical integration. Companies should focus on transitioning to collaboration-based relationship management and expanding their focus beyond tier-1 suppliers. This involves leveraging automated information exchange and ensuring real-time data availability and transparency across the packaging value chain.

This article outlines a strategic roadmap for digital transformation within P&P, focusing on shop floor optimization, innovative packaging designs, and the integration of smart factory initiatives.

Achieving this transformation requires strategic alignment among key stakeholders—research & development (R&D), IT, engineering, operations—supported by a clear vision, robust governance, and a culture of continuous innovation.

Winning together

Digital transformation must be driven by a shared vision across functional areas. Collaboration between the P&P, R&D Leadership Team, Engineering & Workplace (E&W) Leadership, IT, and Operations is critical. An agile governance model, balancing global standardization with local flexibility, enables smooth digital adoption.

Crafting a unified digital strategy

Creating a digital strategy aligned with corporate goals enables collaboration and drives innovation. Two key objectives guide the strategy:

1. Driving innovation in packaging design: Use digital design tools and simulation platforms for faster prototyping, improved material efficiency, and enhanced product protection.
   
2. Shop floor optimization through smart factories: Implement Industry 4.0 technologies like internet of things (IoT), artificial intelligence (AI), and advanced automation to optimize packaging lines, reduce downtime, and enhance quality control.

Working to align stakeholders with these objectives will enable the effective scaling of digital initiatives across global production networks. This approach will also take into consideration local nuances and address economic, geopolitical, regulatory, and social pressures. All of these factors will compel companies to enhance their performance in financial, sustainability, and resilience efforts simultaneously.

Case example: Unilever’s digitalization in packaging

Unilever successfully deployed digital tools across its global network, standardizing packaging materials, leveraging data analytics for performance prediction, and using digital twins for manufacturing processes. This reduced waste and improving sustainability metrics globally.

Digital tools for smarter packaging

Digital tools have transformed packaging design from manual processes to highly efficient digital workflows. Designers can conceptualize, simulate, and validate packaging in a virtual environment, reducing physical prototyping.

Fueling innovation

• Advanced computer-aided design (CAD) and simulation tools: CAD platforms integrated with simulation engines allow teams to model packaging designs, optimize materials, and assess environmental impact before physical trials.
  
• Digital twins for packaging: Digital twin technology creates virtual models of packaging processes, allowing real-time monitoring and performance prediction, improving design continuously.
  
• Material selection platforms: Real-time data streams from suppliers help designers choose optimal materials while balancing cost and sustainability, speeding up market introduction.

Case example: Procter & Gamble’s digital transformation

Procter & Gamble utilized AI and machine learning in packaging design, significantly reducing material usage by 15% while maintaining product protection and enhancing consumer appeal through extensive simulations.

Smart factory in action to optimize shopfloor operations for packing & packaging solutions

P&P’s digital transformation includes smart factories, utilizing advanced automation, IoT devices, and real-time analytics to optimize production efficiency and quality. Smart factories are revolutionizing the packaging industry by streamlining shopfloor operations, minimizing waste, and maximizing precision. For instance, sensors integrated into packaging machinery enable real-time detection of errors, leading to immediate corrective actions. Predictive maintenance powered by AI ensures uninterrupted peak performance, maximizing throughput and minimizing downtime. These technologies accelerate production cycles, reduce costs, and improve sustainability metrics for packaging solutions.

Essential Smart Factory Components

• IoT-enabled machines: Sensors provide real-time data on machine performance and product quality, optimizing settings and enabling predictive maintenance.
  
• AI-driven predictive maintenance: AI predicts machine failures before they occur, reducing downtime in high-speed packaging environments.
  
• Robotics and automation: Advanced robotics handle tasks like palletizing, labeling, and secondary packaging, while collaborative robots (cobots) assist operators, enhancing flexibility.
  
• Integrated manufacturing execution systems (MES) and enterprise resource planning (ERP) systems: Integration between MES and ERP improves communication between production lines and enterprise systems, driving efficiency.

Case example: Schneider Electric’s smart factory initiative

Schneider Electric’s Lexington facility exemplifies smart factory adoption. IoT sensors on packaging lines enable real-time data collection and AI-driven predictive maintenance, reducing downtime by 20% and improving throughput by 25%.

Powering packaging with seamless integration

Automation is only effective when supported by robust digital platforms. Bridging automation with digital infrastructure ensures scalable, flexible, and responsive packaging processes.

Closing the Loop

Bridging Automation and Digitalization requires:

• Unified data architecture: Consistent data architecture ensures interoperability between robotics, MES, digital twins, and AI algorithms.
  
• Closed-loop automation systems: Closed-loop systems use real-time feedback from IoT devices to continuously optimize automated packaging systems.
  
• Advanced analytics for process optimization: Real-time data drives dynamic optimization, improving quality, reducing waste, and enhancing productivity.

Case example: Johnson & Johnson's automation strategy

Johnson & Johnson integrated automation with digitalization across its packaging lines using a unified data architecture. This approach reduced material waste by 18% and improved production speed by 30%.

From data to insight

Harnessing data from smart factories and digital packaging systems is essential for strategic decision-making. Advanced business intelligence (BI) platforms aggregate, analyze, and visualize data, driving continuous improvement.

Key data requirements

Operational, quality, inventory, sustainability, and supply chain data are essential for real-time monitoring and predictive maintenance.

BI platform structure and capabilities

The BI platform for P&P should integrate data from multiple sources, including IoT devices, MES, ERP, and digital twin systems. A robust BI platform integrates data from global production sites, offering real-time visualization, predictive analytics, and automated reporting for consistent global benchmarking.

Turning data into a competitive edge

Embedding analytics into decision-making processes, with well-defined key performance indicators (KPIs) reflecting operational performance and strategic goals, ensures informed leadership.

Transformative capabilities of BI platforms

A robust BI platform integrates data from global production sites, offering real-time visualization, predictive analytics, automated reporting, and global benchmarking.

Case example: PepsiCo’s data-driven operations

PepsiCo’s BI platform aggregates data from global packaging operations, providing real-time insights. Predictive analytics reduced packaging costs by 12% and minimized material waste by 10%.

Measuring what matters

KPIs are vital for monitoring, evaluating, and optimizing P&P performance. Core KPIs include:

• Material efficiency: Reducing material usage per unit supports sustainability and cost objectives.
• First pass yield (FPY): Ensures packaging meets quality standards without rework, improving efficiency.
• Throughput time: Shorter design-to-production times accelerate time-to-market.
• Overall equipment effectiveness (OEE): OEE measures packaging line efficiency.
• Defect rate: Monitoring defects per million units’ signals (PPM) process control improvements.
• Sustainability metrics: Tracking carbon emissions, energy consumption, and waste reduction is key to meeting sustainability goals.
• Cost savings from digital initiatives: Tracking cost savings from digital investments ensures return on investment (ROI).
• Cycle time for changeovers: Shorter cycle times enhance production flexibility.

Case example: Colgate-Palmolive’s use of KPIs

Colgate-Palmolive employed KPIs to monitor OEE, material efficiency, and sustainability, leading to an 18% improvement in packaging line efficiency and a 12% reduction in material waste.

Smart spending, smart scaling

Effective capacity management and budget allocation are crucial to ensuring successful digital transformation initiatives.

Capacity management in P&P

Accurate demand forecasting, flexible manufacturing systems, and scenario simulations align production capacity with business needs.

Budgeting for digital transformation

Establishing phased investments, conducting cost-benefit analyses, and maintaining budget flexibility ensures financial control and maximizes ROI.

Case example: Mars Inc.’s digital transformation budget

Mars Inc. employed phased investments in smart factory technologies and BI platforms, improving overall equipment effectiveness by 20% while maintaining budget flexibility for future investments.

The road ahead: Packaging transformation through digital mastery

At Cognizant, we combine cutting-edge technology with in-depth consulting capabilities to support industries and complex scenarios in their journey toward packaging innovation.  The future of P&P lies in the strategic integration of digital tools, smart factory systems, and data-driven processes. Defining clear KPIs, building robust BI platforms, and managing capacity and budget effectively will unlock improvements in efficiency, sustainability, and innovation. This roadmap offers a comprehensive approach for successfully driving digital transformation in packaging.