Packaging is a necessary part of modern trade. However, its production and environmental impact are on track to cost the world billions to resolve, and businesses are now searching for a better solution.
The Packaging Waste Crisis
Packaging waste is an unpleasant reality of industrialization. If you walk through a busy city street or a tourist-laden beach, you will likely come across litter — a plastic bag, a piece of tin, a cardboard box — outside the garbage bin.
As the world improves its manufacturing processes, garbage also grows at a massive rate. The combination of industrial growth and poor waste management systems makes it a huge global problem.
Plastic is a significant culprit — around 15 million tons of plastic waste enter the world’s oceans each year, and scientists expect the figure to rise a lot by 2040. Without proper intervention, managing this trash could cost governments $670 billion from 2021 to 2040.
Aside from the financial cost, poorly managed packaging waste harms the environment. It pollutes the land and sea, affecting wildlife, the surroundings and human health.
How AI Is Aiding the Sustainable Packaging Industry
With the rising need for more sustainable packaging solutions, companies are exploring AI as a solution. Its quick data processing and machine learning capabilities reduce waste, alongside other applications.
Optimizing Packaging Design
Design is a significant factor in making something sustainable. AI helps create packaging that maintains structural integrity while using recyclable materials and the least amount of resources possible. You can explore different prototypes and iterations to find the best version that works with your product, audience, resources and environmental commitment.
Improving Material Sourcing
The materials used in packaging manufacturing can affect its sustainability. Does it fit local recycling facilities? How long will it degrade when thrown away? Is it reusable?
AI tools can analyze large datasets to find eco-friendly materials that meet environmental and packaging standards. It takes the hassle out of researching the vast catalog of available items and helps manufacturers make better choices.
Reducing Waste Through Analytics
Most waste comes from inefficient materials usage or a mismatch between production and consumer demand. AI-powered predictive analytics makes it easier to process stored information and glean relevant insights. As a result, packaging manufacturers can more accurately anticipate consumer needs. AI-optimized design also helps minimize waste by making the most of available materials.
Improving Recycling Systems
The world generates a lot of garbage, making traditional recycling and waste management time- and resource-intensive. Some recycling facilities are now using AI to improve efficiency and accuracy in sorting and identification.
While humans can sort 50 to 80 items an hour, AI robots can go through up to 1,000 items in that same time frame. This process improvement helps facilities recycle more materials and contribute to a cleaner environment.
Refining Logistics and Supply Chain Efficiency
Logistics, transportation and other supply chain processes form a significant part of the packaging industry’s ecological footprint. Many vehicles and electrical grids run on fossil fuels and other nonrenewable energy sources, which emit various pollutants, including greenhouse gases like carbon dioxide.
AI helps logistics fleets create more efficient routes that save fuel and minimize travel time, reducing operating costs and the company’s carbon emissions.
Reducing Downtime Through Maintenance
Regular maintenance is essential to keep equipment running smoothly. AI can monitor the status of packaging machinery, alerting staff and managers of any issues or maintenance needs before they escalate. AI tools can take only a couple of and create detailed condition reports.
Timely alerts allow companies to be more proactive with maintenance, reducing costly breakdowns and ensuring production continuity.
Encouraging Data-Driven Decisions
One of AI’s largest contributions is its ability to process large volumes of information quickly and accurately. This capability makes data analysis and visualization easier for packaging companies.
You can easily create dashboards that show relevant information contributing to your sustainability efforts, such as carbon emissions, production time, travel time, and fuel and energy consumption.
These numbers give companies a more accurate picture of their operations, allowing them to formulate more effective changes that lead to efficient and more sustainable processes.
Other Benefits of AI in Packaging Operations
Aside from promoting sustainability, AI also offers many benefits for packaging companies, such as:
Cost Savings
The efficiency AI brings to your company saves time and resources, which translates into reduced costs. Automation also minimizes the need for manual labor, allowing employees to save their energy for more critical tasks that require human expertise.
Improved Reputation
Companies that practice sustainability experience a boost in their reputation, especially among younger audiences. Aside from improving authority and popularity, a good reputation also translates to sales.
More consumers are prioritizing sustainability when finding brands they trust. Millennial and Gen Z customers are 27% more likely to buy from a brand if they believe it cares for people and the environment.
Better Quality Control
AI-powered vision and monitoring can easily detect inconsistencies in visuals and the quality of packaging materials. This strict adherence to standards enables companies to improve client satisfaction and ensure only top-caliber products hit the market.
Challenges of Adopting AI in the Packaging Industry
While AI has many advantages, it is not a perfect solution. Using it to improve your company’s sustainability initiatives will have drawbacks and challenges.
High Initial Investment
AI systems, especially on an enterprise scale, can cost a lot of money to install and maintain. As a result, small and medium-sized businesses might not have the resources to adopt these solutions.
Data Security
Businesses need to scrutinize potential vendors to ensure they have robust cybersecurity features. Enterprise-level software often deals with sensitive or private information. Prioritizing cybersecurity in AI keeps your company and clients safe from data breaches.
Skills Requirements
AI software requires specialized knowledge and training to operate. Companies may need to invest in additional staff or continuing education to bring qualified AI professionals to the team.
The Future of Packaging
Packaging waste presents a significant problem to humanity and the environment. However, new technologies like AI are turning the tide by offering smarter ways to reduce trash and improve sustainability. Through thoughtful implementation, companies can help the environment while improving operational efficiency.
Emily Newton is the Editor-in-Chief of Revolutionized. She regularly covers trends in the industrial sector.
