SCHOTT — AI-Powered Transportation Load Optimization

SCHOTT is one of the world's leading manufacturers of specialty glass and advanced materials, supplying products to industries including pharmaceuticals, electronics, automotive, and industrial manufacturing. Transporting large glass panels presents unique logistical challenges. Every shipment must be carefully planned to ensure proper weight distribution and positioning of individual glass elements on transportation frames. Incorrect load balancing can compromise transportation safety, increase operational risk, and potentially result in product damage. Historically, these calculations relied heavily on manual planning and engineering expertise, making the process time-consuming and difficult to scale consistently across operations. Key objectives included:

• Improving transportation safety
• Eliminating manual load planning activities
• Optimizing positioning of glass panels
• Preventing instability and frame tipping
• Reducing operational risk
• Increasing planning speed and consistency
• Leveraging AI to support operational decision-making

SnapStack partnered with SCHOTT to design and develop an AI-powered optimization platform capable of automatically calculating the optimal placement of glass panels during transportation loading operations. The solution analyzes multiple variables including panel dimensions, weight distribution, transportation constraints, and frame characteristics. Using a Delphi-based optimization engine enhanced with AI-driven decision support capabilities, the platform generates loading recommendations designed to maximize balance and transportation safety. The system provides planners with automated recommendations that previously required extensive manual calculations and engineering expertise, significantly simplifying the planning process while improving consistency and accuracy.

Bringing AI into Industrial Operations

Many AI initiatives focus on customer-facing applications, but some of the greatest business value can be created by optimizing critical operational processes. Through this engagement, SnapStack helped SCHOTT apply artificial intelligence to a real-world industrial challenge where precision, safety, and operational efficiency are essential. The resulting solution demonstrates how AI can augment engineering expertise and enable faster, more reliable decision-making within manufacturing and logistics environments. The project serves as an example of practical AI adoption focused on measurable business outcomes rather than experimentation alone.

From Engineering Expertise to Intelligent Automation

The success of the initiative demonstrated the value of combining domain expertise, software engineering, and artificial intelligence to solve complex operational problems. By transforming manual calculations into an intelligent decision-support system, SCHOTT gained a scalable solution capable of supporting growing operational demands while reducing risk and improving consistency. The project illustrates how industrial organizations can leverage AI not only to automate processes but also to enhance safety, efficiency, and operational excellence.

The solution transformed a complex engineering task into an automated, repeatable, and scalable process.

• Improved transportation safety
• Automated load planning and optimization
• Reduced dependency on manual calculations
• Lower operational risk during transportation
• Increased planning efficiency
• Consistent and repeatable decision-making
• Foundation for future AI-driven optimization initiatives

Artificial intelligence delivers the greatest value when applied to complex operational challenges where decisions must be accurate, consistent, and scalable. This engagement demonstrates SnapStack's ability to combine AI, engineering expertise, and domain knowledge to create practical solutions that improve safety, optimize operations, and generate measurable business value for industrial organizations.