At an oxide refractory manufacturing company, one product line suffered from long-standing quality issues—specifically cracking and M-check defects—that consistently disrupted production. The yield for large-size blocks remained low at around 50%. Given the extended production time required to make these blocks, the defects often led to significant order delays and expensive air freight shipments to meet delivery commitments.

BEJ tackled the issue by thoroughly analyzing historical process data, evaluating the temperature profiles of the elements, and assessing their positioning within the kiln. This investigation uncovered the root cause of the defects. With targeted process interventions, BEJ helped the client boost the yield of large-size units from 50% to 85%. This breakthrough not only improved product consistency and reliability but also resulted in major operational efficiencies and substantial cost savings.

A company planned to relocate one of its business units to a facility in the U.S., requiring the industrialization of eleven new product lines across two distinct manufacturing processes — vibratory casting and brick pressing. Each product line had unique material and process characteristics, leading to a range of challenges during scale-up—including cracking, voids, dimensional inconsistencies, and other defects.

BEJ led the industrialization effort, systematically addressing these challenges through process optimization and troubleshooting. As a result, the plant achieved over 90% yield across the product lines and successfully fulfilled customer orders within a short time frame.

Notably, BEJ enabled the delivery of the first batch of unmachined units that met exact customer dimensional requirements—eliminating the need for post-processing. This was a significant achievement, as machining is one of the most costly steps in the production process.

A bio-manufacturing company was launching its first full-scale commercial facility in Europe when it encountered a critical challenge during scale-up: not a single batch could be successfully produced. This unexpected issue threatened timelines, customer commitments, and overall project viability.

BEJ was brought in to help resolve the problem. Through in-depth data analysis and process evaluation, BEJ identified the root cause and implemented targeted corrective actions. As a result, the production process was stabilized, enabling a smooth and successful commercial launch.

A company had spent over a decade developing a novel biobased technology aimed at transforming the cement industry. However, despite years of effort, the process remained inefficient, costly, and difficult to scale for commercial use.

During small-scale prototype trials, BEJ uncovered a new approach that fundamentally shifted the way the technology works. Through multiple iterations and development cycles, BEJ’s solution emerged as the most efficient, scalable, and successful version of the technology to date.

Although the initial proposal met with considerable resistance from decision-makers, the undeniable results spoke for themselves. The solution was ultimately adopted—and embraced—with enthusiasm, marking a major turning point in the commercialization of the technology.

Our client, a manufacturing company, was struggling with a sudden, significant drop in production efficiency. A team of engineers was performing new process optimization experiments to resolve the issue, but their efforts weren't successful.

When BEJ was brought in, we realized a crucial step was being overlooked: analyzing the existing process data. Many companies collect this type of data but fail to use it effectively. By analyzing the historical data, BEJ identified an unintentional change in a key process parameter that had occurred just before the problems started. This shift was the root cause of the production issues.

By correcting this simple change, we were able to quickly resolve the problem without the need for complex and costly experiments. This experience highlights the importance of leveraging existing data to quickly identify and solve problems.