About the client. Our client, one of the largest steel manufacturing and mining companies in the world, with locations in more than 60 countries and 100k+ employees, set out on an aggressive strategy to secure a position as the undisputed leader in its industry. Part of this strategy is to establish steel’s dominance as the material of choice for the future by investing in technology and innovation to manufacture a smarter, stronger, more sustainable end product.
The steel industry has faced challenges related to overcapacity due to recent volatile unpredictable global events, leading to intense price competition. Seeing this trend, our client realized that they weren’t as competitive as they needed to be. They needed to take drastic steps to reduce costs and become more competitive. This prompted them to embark on an Overall Equipment Effectiveness (OEE) journey.
Increased price
Reduced cost andKPI Digital chosen as strategic partner
This manufacturing giant chose KPI Digital as their strategic partner to implement OEE. The customer chose us for our expertise in Industry 4.0 for manufacturing and mining and for our proven track record of delivering robust analytics solutions to solve complex business problems with leading-edge technologies.
Data analysis exposes data integration and interoperability problems
Our first priority was to complete an in-depth data analysis to expose any potential data challenges for calculating OEE. We discovered that they had data integration and interoperability problems due to diverse systems and processes between plants. This led to inconsistencies in data collection and methodologies for calculating the availability, performance, and quality metrics that would make it impossible deliver an accurate OEE.
Establishing data quality
We established a standardized methodology for calculating availability, performance, and quality. To ensure calculation consistency, we developed automated processes to collect, validate and cleanse real-time data from equipment across all plants. This was ingested into a
centralized data lake-house built on Microso Azure for high data throughput and performance.
We implemented Machine Learning (ML) and AI to analyze the data, identify patterns, and detect areas for improvement. This information flowed into KPI Digital Smart Manufacturing™ dashboards to provide real-time analytics to executives and managers for better monitoring and decision making.
OEE is a key performance indicator used in the industrial automation and Industry 4.0 context to measure the efficiency and effectiveness of machines or automation processes. OEE considers three main factors: availability, performance, and quality.
In a very short time, our client increased OEE by 10% and saw profits increase from $11M to $20M at just one plant.
Through our efforts, the company developed a foundation of trusted, high-quality data. This positions them well to implement a full scope of Industry 4.0 initiatives & KPIs and begin to transform their global operations.