Context

In a production environment, the smallest interruption can trigger a cascade of incidents, affecting quality, deadlines, and profitability. Missing parts, non-conformities, or machine failures can quickly spread, causing costly delays and production losses. Identifying and addressing these risks proactively is becoming essential to maintain the fluidity of operations and meet market requirements.

Solution

Our solution uses advanced algorithms to estimate the extent of the disruptive effect or snowball effect of a disruption that has just occurred in the production chain such as a quality problem, uncompleted work, missing parts or machine failures. By analyzing the data related to these various events in real time, it identifies disturbances with a high disruptive risk (of a snowball). Thus, operators can prioritize their actions in order to minimize interruptions and ensure operational continuity of your business.

Benefits

  • Improving operational reliability through proactive risk identification
  • Reduction in unexpected downtime and production losses
  • Optimizing the use of resources and maintenance costs
  • Strengthening customer satisfaction by respecting delivery deadlines

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Résultats

-25%

reduction in the number of orders delivered late

-12%

reduction of unexpected production downtime

30%

of businesses experience significant disruptions in their supply chain every year

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