Arconic
Root Cause Analysis To Eliminate Defective Products
Arconic is a leading manufacturer of aluminum sheets, plates and extrusions, as well as innovative architectural products. They strive to advance the automotive, aerospace, commercial transportation and construction markets. Hiflylabs helped optimize one of their production lines based on sensor data to eliminate production errors.
Root cause
identification fixes manufacturing defects based on industrial IoT data.
Challenge
For ten years, the client has been experiencing a rare, but typical error in wheel manufacturing, called pitting. Arconic decided to consult us when the defect’s root cause couldn’t be found by conventional methods. Fortunately, they could provide a long history of sensor data, recorded at various stages of the production process, from pressing through heat treatment to micro logistics. The challenge lay in the effective analysis of billions of sensor records’ lines, and making recommendations to lower the failure ratio by improving manufacturing processes. Different wheel types and historical changes to the production line further complicated the project.
Solution
We received data from the most important stages of the manufacturing process, captured by IIoT (industrial internet-of-things) sensors throughout the years. In the first step, we filtered the affected wheel types and stations. Data preprocessing emerged as a pivotal and unexpectedly intricate step in our analysis. Employing a blend of sophisticated statistical methodologies, deep-learning, and even gene-sequencing algorithms, we meticulously traced the lifecycle stages of product parts. By using several predictive models, we presented multi-variable correlations for the possible causes of the defect, from which six intervention points were identified. The Arconic team benchmarked the suggested settings in test production runs and modified the production line according to the results of the analysis. This modification has successfully eliminated the defect.
Services
Anomaly Detection
Big Data Analytics
Machine Learning
Predictive Modeling
Complex Correlation Analysis
Sequence Modeling
Logistic Regression
Lift Value
Weight-of-Evidence
Industries
Manufacturing
Technologies
MS SQL
Python
R
Historian
Osisoft PI
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