Digital Transformation
at Tristar Steel with KFactory®

The Challenges

As a result, the company faced the following challenges:

• Lack of visibility: No overall visibility on the real-time performance of production lines.
• Incorrect data: Manual errors were affecting the accuracy of reports and analysis.
• Delays in reporting: Reports were generated late, making it difficult to take operational decisions.
• Difficulties in optimizing processes: Lack of accurate and up-to-date data prevents problems from being quickly identified and remedied.
• The operational processes of quality, stock management and production order management were hampered by the lack of real-time data.

KFactory® Platform Implementation

To overcome these challenges, Tristar Steel decided to implement the KFactory® platform. The solution was implemented on a complex production line, integrating various industrial machines. The KFactory® team worked closely with the company's operational team to ensure a successful implementation.

The main reasons for choosing the KFactory® solution are:

• The need to monitor performance in real time and identify bottlenecks so that we can make quick and informed decisions;
• The need to improve productivity and reduce downtime;
• The need for improved traceability of both materials and labor;
• The need of improving individual and group responsibilities;
• The need for real-time data collection and analysis to optimize processes and reduce costs;
• Flexibility and scalability;
• Improving the efficiency, quality and competitiveness of production operations, ultimately contributing to higher profitability and increased customer portfolio.

Best Practices of the Chosen Solution

Significant Impact in 3 Months

The implementation of KFactory® has had a significant impact on Tristar Steel's operations:

• In the first 3 months of implementation there was a 20% increase in production efficiency.
• Now the rules and execution times for orders can be set correctly.
• Real-time visibility on order execution status.
• Improved data quality: the data collected is more accurate and reliable, allowing more accurate performance analysis.