Across all types of manufacturing operations, packaging is among the most challenging and demanding. Facility teams are under pressure from all sides, navigating equipment breakdowns, tight production schedules, and rigorous quality demands as best they can.
If you're aiming to stay ahead of safety and production risks, revenue losses, and your competitors, optimizing key performance indicators (KPIs) is non-negotiable. That means embracing smart maintenance strategies and technologies to keep production smooth and steady and costs at a minimum. Across the packaging industry, many facilities are shifting to predictive maintenance and seeing major benefits and savings from the start.
As of 2023, 71% of packaging and processing companies reported having some form of predictive maintenance in place—up from 45% two years prior. Key gains cited include less unplanned downtime, improved productivity, lower maintenance costs, decreased spare parts (MRO) inventory, increased run times, and improved overall equipment effectiveness (OEE).
If you want to maximize the value of predictive maintenance, you have a powerful tool within easy reach: the precision of artificial intelligence (AI) combined with the invaluable insights of experienced industry experts. Balancing these two sides of the equation is essential for empowering your team to do more with less and drive real progress.
Why Packaging Manufacturing is So Complex—and Ripe for a Predictive Revolution
Packaging manufacturing processes demand meticulous attention to detail, rapid production speeds, and constant adaptability. To meet these requirements and succeed long term requires a high degree of visibility and precision as well as ongoing innovation that only smart technologies—along with dedicated human support—can provide.
The most pressing industry concerns, risks, and realities include:
Precision and Rapid Cycles
Machinery must sustain high precision under constant stress, frequently changing products while maintaining strict quality.
Harsh Operational Conditions
Assets such as rolls, presses, pumps, and fans operate under extreme temperatures and pressures, leaving them vulnerable to moisture, dust, and debris.
Regulatory and Sustainability Pressures
Facilities must comply with stringent industry standards and reduce energy consumption to meet sustainability goals.
Costly Downtime
Unexpected machinery failures disrupt schedules, waste resources, and elevate safety risks, directly impacting KPIs like Overall Equipment Effectiveness (OEE), Mean Time Between Failures (MTBF), and Mean Time to Repair (MTTR).
After implementing predictive maintenance for their packaging equipment so they could predict potential seal failures and respond in a timely way, a global food and beverage company reduced packaging defects by 80%.
Predictive Maintenance Done Right: Combining Advanced AI with Human Expertise
AI is essential for optimizing maintenance, production, reliability, and asset value. As impressive as AI technologies are, however, they can’t entirely replace human judgment and expertise. In the absence of sufficient human support, these technologies can even create headaches and diminish in value.
What AI and Machine Learning Offer
AI technologies can handle vast amounts of data and swiftly identify subtle anomalies that might indicate potential equipment issues. Specifically, AI and machine learning provide:
- Rapid Data Analysis: Algorithms quickly sift through large datasets, identifying unusual patterns and pinpointing emerging risks.
- Predictive Alerts: AI generates early warnings that allow proactive interventions before minor issues escalate into significant problems.
- Consistent Monitoring: Continuous surveillance of asset conditions, providing ongoing insights into machinery health and performance.
Why Dedicated Human Support Is a Must
Despite their potential, some AI-driven maintenance solutions fall short due to critical gaps. Teams struggle to keep up, interpret what they’re seeing, and determine next steps.
- Preventing Alert Fatigue: False alarms can and do occur. Without proper validation by a seasoned analyst, the sheer volume of AI-driven alerts can overwhelm teams and lead to confusion, desensitization, and a return to reactive maintenance.
- Prioritizing Maintenance Needs: Teams can’t afford to spend time on relatively minor equipment issues at the expense of catastrophic failure risks. A dedicated expert can provide clarity on which preventive measures are needed first.
- Providing Prescriptive Recommendations: Many predictive maintenance solutions produce generic alerts without prescriptive, actionable recommendations, leaving maintenance teams uncertain about how to proceed effectively.
When time is on the line, having to wait days to connect with an expert is a huge disadvantage. A condition monitoring engineer (CME) with advanced certifications—who is dedicated to a facility and proactively reaches out with prescriptive recommendations when failure risks emerge—makes predictive maintenance easier, more valuable, and more sustainable over time.
Looking to get traction on overall equipment effectiveness (OEE), mean time between failures (MTBF), and mean time to repair (MTTR)? Download our recent white paper The Role of Condition Monitoring in Enhancing Key Performance Indicators, and discover how monitoring asset health will empower you to transform these KPIs.
Discover the Predictive Power of CAT III+ Support for Your Plant
To keep your packaging operations running smoothly and optimize production and resource use, combining advanced AI with seasoned human expertise isn't just smart—it's essential. Having a dedicated expert on hand to help your team interpret the data and address equipment issues in a timely manner will allow you to boost productivity and efficiency while significantly improving asset health, reliability, and lifespan.
AssetWatch has been helping leading packaging companies, and manufacturers across all industries, eliminate unplanned downtime starting on day one. Our CAT III+ CMEs are proactive partners who work closely with facility teams to resolve issues before they become problems.
Watch our recent webinar Top Tips & Tricks to Improve Your Condition Monitoring Program, featuring three of our CMEs, for valuable insights that can help you enhance the value of your predictive maintenance program. You can access the replay here.
.webp)
