Client: Woodward

Streamlining Manufacturing: 30% Reduction in Manual Work with AI

Case study details


Woodward is an independent designer, manufacturer, and service provider of energy control and optimization solutions for aerospace and industrial markets.

The company was founded over 150 years ago. It was focused on delivering proven systems for aero engines, industrial engines and turbines, power generation, and mobile industrial equipment from the very beginning.

Solutions developed by Woodward enable their clients to reduce emissions by increasing energy efficiency and introducing alternative energy sources.

Woodward struggled with the huge amount of manual labor during testing processes. With data closed in separate silos, the old methods made processes prone to error and jeopardized the whole business stability as the company operates in the aerospace sector. Woodward realized that without the implementation model of AI-driven solutions, the situation has zero chance for improvement.



Challenge


The Woodward, for years, had used excel sheets for process capability analysis, statistical interpretations, and MSA simulations during its quality testing processes. The manual methods can’t be used to prevent mistakes efficiently. All engineers could do was fix them when they had already occurred.



Approach


Woodward was looking for a partner able to deliver a comprehensive AI platform for process capability to measure how well the processes perform to meet given specified outcomes. With statistical analysis powered by Machine Learning, the system was expected to validate if the process outcomes were delivered to meet the customer’s specifications and will identify the improvement opportunities.

  • Historical data collection and trend analysis
  • Analysis of statistical process stability (i.e., in control)
  • Process monitoring and ensuring
  • Updating the process capability indexes if needed
  • Predict future outcomes


Goal


Woodward was looking for a solution that would enable its engineers to automate the testing process, increase their scalability, and improve the efficiency of data analysis, by using historical data.



Outcome


Addepto team built a comprehensive Visual System for process capability analysis enriched with predictive AI modules modeling that allowed Woodward to reduce manual labor, cut operational costs, and improve testing life cycles.

 


Challenge

Woodward struggled with the huge amount of manual labor during testing processes


Within the Aerospace Manufacturing industry, companies are required to test produced product components very accurately to provide end products without faults. The test process is very complex, generates a lot of data, and needs to be adjusted to the changing products and trends.

The Woodward, for years, had used excel sheets for process capability analysis, statistical interpretations, and MSA simulations; however, with the usage of these methods, staff engineers were not able to detect future problems with the product testings and any inconsistencies. The company realized that only by implementing AI technologies can it boost the efficiency of processed and – by doing that – the general operations performance.


The vast amount of manual labor



Slow and inefficiency of testing processes



Inability to analyze historical data



Inability to predict events



Approach

Implementing statistical analysis powered by Machine Learning


Woodward was looking for a partner able to deliver a comprehensive AI platform to measure how well the processes perform to meet given specified outcomes. With statistical analysis powered by Machine Learning, the system was expected to validate if the process outcomes were delivered to meet the customer’s specifications and will identify the improvement opportunities.

The Data Science team of Addepto has developed an intelligent Visual System for process capability analysis that analyses vast amounts of data processed and visualized for CPK, PPK, and MSA analysis.

Additionally, this system predicts which product test fill fails and which specific test step. We have used predictive analytics and regression techniques to indicate test results beyond the limits.



Goal

Woodward was looking for a partner able to build and implement AI solutions aim to


Automating testing process


Reducing manual labor


Improving testing processes' efficiency


Improving quality end products


The decreasing number of errors


Outcome

Outcome


Addepto team built a comprehensive Visual System for process capability analysis enriched with predictive AI modules modeling that allows Woodward to reduce manual labor, cut operational costs, and improve testing life cycles.

  • Visual System for process capability analysis
  • Predictive AI Modules


Before


  • Massive amount of manual labor
  • High operational costs of delivering products to the customer
  • Error-prone processes


After


  • It has reduced manual work by 30%.
  • Operational costs of delivering products to the customer are reduced by 25% because of detection and prevention of sending bad products to the customers.
  • Improved product testing life cycles by replacing test steps as well as by eliminating some of them.

About Addepto


Addepto is a fast-paced, growing company focused on innovations in Artificial Intelligence area.


Here you can learn more about the technologies used in this project:



We support digital transformation at companies operating in Manufacturing Aerospace, to increase the efficiency of their performance with Machine Learning methods and data processing.


About us


We are recognized as one of the best AI, BI, and Big Data consultants


We helped multiple companies achieve their goals, but - instead of making hollow marketing claims here - we encourage you to check our Clutch scoring.

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