Artificial intelligence is transforming industrial operations by improving machine reliability, as seen in toilet paper production. Tino Pietraßyk from FactoryPal emphasizes AI’s role in boosting efficiency and profitability by addressing common production issues. Despite initial skepticism from experienced operators, data-driven insights demonstrate AI’s advantage over traditional methods. Concerns about job losses are unfounded, as AI enhances productivity, allowing workers to engage in more strategic roles.
The Role of Artificial Intelligence in Industrial Efficiency
Artificial intelligence (AI) is revolutionizing the industrial landscape by ensuring machines operate with greater reliability. Numerous companies are already reaping the benefits of AI technology, particularly in sectors such as toilet paper production.
Unlocking Potential in Production Processes
Tino Pietraßyk, a Senior Data Scientist at the Berlin-based AI firm FactoryPal, passionately discusses the intricacies of toilet paper manufacturing. From single-ply to two-ply production and the various challenges along the way, Pietraßyk’s expertise shines through. His role highlights how AI can significantly enhance production efficiency, ultimately boosting profitability for businesses.
According to Pietraßyk, every machine has its flaws. Issues like paper tearing, roller jams, and feed problems are common in production lines. Typically, a toilet paper facility achieves only 60 to 70 percent of its potential output due to these operational hiccups.
At a recent conference in Berlin focused on ‘AI in production,’ industry leaders and scientists discussed real-world applications rather than futuristic theories. This gathering highlighted the practical implications of AI technology in enhancing production processes.
FactoryPal aims to improve output, promising to elevate the ‘Overall Equipment Efficiency’ (OEE) by at least three percentage points for their clients. While this may seem minor, every percentage point could equate to an annual financial impact of up to one million euros.
Modern industrial facilities are intricate systems, where even a straightforward production line, like that for toilet paper rolls, can become overwhelmingly complex. Pietraßyk and his team analyze between 200 and 2,500 input parameters and adjust 30 to 70 machine settings, leading to countless combinations for optimization.
Pietraßyk explains that this process involves billions of adjustments. Advanced algorithms autonomously determine which settings yield the most efficient production processes, resulting in increased output with fewer failures. The core of AI, as he puts it, is fundamentally mathematics, indifferent to the specific products being manufactured.
Despite the presence of seasoned industry experts, convincing them of the potential for improvement can sometimes be challenging. Pietraßyk recounts instances where operators prefer to run machines at slower speeds to avoid paper tears. However, data analysis often contradicts this instinct, revealing that the algorithms can outperform human intuition.
Concerns about AI-induced job losses are prevalent, but Pietraßyk reassures that AI in this context has not led to a single job elimination. Instead, the technology enhances efficiency, allowing human workers to focus on more strategic tasks.