Automated Root Cause Analysis

Detect and prevent the complex causes of product and process failure –
and save millions in operational costs 

Get Demo

Automated Root Cause Analysis

Detect the complex causes of product and process failures to mitigate disruption – and save millions in operational costs

Get Demo
Traditional Root cause analysis in manufacturing

Traditional root cause analysis – lengthy, costly, and error-prone

Traditional Root Cause Analysis takes time your teams don’t have. 

Massive volumes of data, with thousands of tags captured each minute, makes it nearly impossible to find correlations between the operational variables that lead to process disruption.

The longer the analysis takes, the longer process disruption occurs: extra shifts, reduced production capacity, increased waste, and a spike in operating costs.

Manufacturing teams need a faster, more accurate way of finding and mitigating the early events that lead to process and production failures.

IoT Use Cases: Root Cause Investigation

Automated Root Cause Analysis – faster, more reliable results

Seebo Automated Root Cause Analysis software speeds up problem investigation and prevention.

Seebo production line modeler enriches historical and real-time machine data with process flow and production batch data.

Machine learning algorithms – advanced techniques of Mutual Information and process-based anomaly detection – then harness the data to automatically trace the causal chain of events for unplanned downtime and product quality issues.

Investigation teams get fast, accurate insight into early symptoms of process disruptions, making it easy to pinpoint and mitigate the root causes.

Automated RCA Applications in Manufacturing

  • Predictive Quality - A food manufacturing company misidentified high oven temperature as the single cause of broken wafers. Seebo Root Cause Analytics software traced the failure to a combination of two factors: high oven temperature and abnormal jumps in conveyor belt speed. Based on these findings, the operational team used Seebo to create predictive quality alerts to avoid future blockages and maintain high quality standards.
  • Predictive Maintenance - A biotech factory experienced unplanned downtime due to a viscous solution blocking pipes between machines. Using Seebo, they traced the source of the viscosity and blockage to a correlation between minute deviations in mixing duration, distillation duration, and reaction temperature. The team quickly resolved the issue and added predictive maintenance alerts to notify them before the problem reoccurs. 
  • Waste - A plastic bottle manufacturer scrapped over 11,000 bottles after back-to-back batches had severe paneling. With Seebo RCA, the production line process engineer identified a correlation between bottle paneling, bottle thickness, and a specific pressure value. The company adjusted the pressure sensor thresholds and set up predictive waste alerts on the Seebo platform for pressure deviations, reducing scrap from that line.
  • Health & Safety Compliance - After a chemical manufacturing company faced health and safety issues with a leaking discharge pump, process engineers used Automated Root Cause software for chemical process control and to solve the leak issue. Advanced alerts for pump breakdown and a short maintenance cleaning eliminated future leakage and helped the company ovoid major health and safety compliance issues. 

Access our free case study

How a global manufacturing enterprise implemented AI tools to increase uptime,
reduce quality issues, and improve production capacity.