Smart Plastics: How Data Intelligence Is Reshaping Production

Find ways to boost production, meet environmental regulations, and cut costs using data-driven tech solutions.

Data has changed from a resource to a crucial driver in manufacturing. This is especially true in the plastics industry. According to McKinsey adding data intelligence to production can cut costs by 20% and boost efficiency by up to 30%.

At Plastic Engineering, we talked to Aleks Zlatic from eProductivity Software. He is an expert in manufacturing technology and demonstrated how companies can enhance production through the intelligent use of data. He also explained how technology and artificial intelligence are transforming the sector.

You can also read: Tooling Digitalization: Applications.

Data: The Engine of Efficiency

Plastic manufacturing generates a substantial amount of data. To get the most out of it, you need a clear strategy. Many companies still make decisions based on assumptions rather than precise data.

Defining key performance indicators (KPIs) such as waste, traceability, and production efficiency helps optimize processes. Sharing this data across all company levels facilitates informed decision-making and helps prevent disputes. “When data are clear and accessible, it  strengthens objectivity,” says Zlatic.

Traceability and Sustainability: Market Keys

Companies must closely monitor materials in plastic packaging. This is particularly crucial in the food and pharmaceutical industries, where quality and origin are paramount.

Environmental regulations are becoming more stringent. Understanding how plastics are made and recycled helps us follow rules and care for the environment. “In the U.S. and Europe, manufacturers must be responsible for their products. They also need to pay taxes for their environmental impact,” says Zlatic.

Data analysis helps combat greenwashing. It also gives reliable information on recyclable materials. This helps companies adhere to rules and enhance their reputation. Sustainability is gaining importance in the market.

Technology and Artificial Intelligence in Manufacturing

Tools for collecting and analyzing data can now connect manufacturing to artificial intelligence.

Many companies still use old ERP systems. These systems limit their ability to analyze data. Manufacturing Execution Systems (MES) connect modern machinery to centralized data systems.

“MES combines old and new equipment. It gathers important data on efficiency, production speed, and waste,” says Zlatic.

AI utilizes this data to plan more effectively. It helps cut machine changeover times and makes resource use more efficient.

A company can utilize just-in-time sourcing if it understands its production times and material requirements. This helps cut costs and reduce waste.

Investing in Data: Key to Competitiveness

Many companies have advanced machines, but they fail to utilize their full potential. This is due to a lack of accurate data.

Zlatic warns, “If a machine costs thousands of dollars each hour, you must know if its use is efficient.” Without this information, companies waste resources and hinder their ability to achieve continuous improvement.

The plastics industry must use data to improve efficiency and sustainability. Beyond improving production, this allows for regulatory compliance, cost reduction, and maintaining competitiveness.

As Zlatic concludes: “It all starts with the data.” Investing in analysis and visualization tools enables companies to enhance their processes. It also prepares them for a digital and sustainable future.