Bednar FMT: AI Optimization of Production Planning Enabled Annual Revenue Growth of $1.9M

Challenge

Rapid Growth Brought a Level of Complexity that Manual Planning Could No Longer Handle

Bednar FMT, one of the world’s leading manufacturers of mounted agricultural machinery, faced a major challenge as it scaled up and shifted to a new production strategy. During the COVID-19 pandemic, the company built a new production hall and transitioned from a cell-based model—where entire machines were assembled in one place—to a line-based manufacturing system.

This shift significantly increased the complexity of production planning, leading to:

• Underutilized production lines, limiting overall capacity
• Inaccurate labour planning, causing missed delivery deadlines
• Delays due to supply chain issues and inconsistent supplier quality

At the same time, the company had to navigate a downturn in the agricultural sector and react quickly to changing market conditions.

To overcome these challenges, the project aimed to:

• Standardize the planning process for the new line-based structure
• Speed up planning and improve line utilization
• Minimize errors and reduce reliance on manual planning
• Establish a digital planning foundation adaptable to future needs

Solution

The Optimization Application on the OptiSuite Platform Evaluates Millions of Production Scenarios Within Seconds

1. Review of the operational model

During the initial review of the operational model, we identified problematic areas in planning, supply, logistics, and warehouse management. As part of the analysis, we also reassessed labour hour norms and the method of planning production line capacities.

2. Design of a digital planning process

We designed a digitized production planning process that included:

• Key business processes
• Technical components
• Data sources needed for automated planning

3. Application on the Adastra OptiSuite platform

Based on the analysis, we developed a production planning application built on the Adastra OptiSuite optimization platform. This application:

• Uses advanced AI algorithms to evaluate millions of planning scenarios within seconds
• Generates an optimal plan that takes into account key criteria such as line capacities, delivery deadlines, shifts, breaks, work sequences and dependencies, and technological constraints
• Enables easy re-planning and flexible testing of alternative scenarios

Impact

Bednar FMT Automated its Planning Process and Now Plans with Flexibility

The solution allows the planning team to focus on more complex, high-value tasks and long-term challenges instead of manual, repetitive scheduling—potentially enabling the company to meet up to €1.75 million in additional annual demand.

Thanks to the introduction of a new application, Bednar FMT significantly accelerated and standardized its production planning process, reduced the burden on the planning team, gained flexibility, and can now fully optimize its production capacity.

The implementation of the optimization platform ensures:

• Increased flexibility: The new system enables real-time automated planning and testing of new scenarios throughout the day. This allows production to quickly adapt to changes in demand, supply, or unexpected situations.
• Faster planning, from hours to minutes: A process that previously took hours is now completed in minutes. Instead of three workers, one person can now create the plan. Planners can focus on handling exceptional situations rather than routine planning.
• Reliable and transparent planning: By standardizing the planning process, the plan became a reliable backbone of the company’s operations. This led to greater manufacturing standardization, better alignment of support activities with the plan, reduced material in production areas, and moved internal logistics closer to JIT, increasing safety in production.

In addition to the immediate benefits, Bednar FMT also laid the foundation for future growth and digitalization development. The new application offers further development opportunities, such as integrating more advanced AI features or expanding to other areas of production and logistics.