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.

We identified the root cause

of defective products, enabling the client to modify their production line and eliminate the error.

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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