Cross-referencing data collection is the innovative data management approach that leverages innovation and human intelligence.
Data collection allows insights to be accessed by companies, and business case studies illustrate how they have used data to drive sales and performance.
However, every business has unique characteristics and requirements, especially the yacht manufacturing industry.
In this segment, data not only has the power to influence or help revise strategies, but can improve quality of products, efficiency of systems and machinery.
The crucial role of human intelligence in technology innovation
In a world focusing on AI for answers, human intelligence and lateral thinking remains fundamental for finding long-term solutions. Innovation is enhancing the visions of specialized engineers and technicians.
This combination of innovation and expertise in the yachting industry is at the core of D.gree technologies.
D.gree bases its work on this concept, with a data comparison methodology and cross-referencing data collecting, both aiming to profile analyzed systems to ensure optimized information, leveraging its expertise.
Cross-referencing data collecting to achieve scalability and efficiency
Thanks to the different logging strategies with various frequencies and parameters, D.gree provides an accurate instrument for an efficient interpretation of any operational system profile.
Every system is considered like a musical instrument as every yacht has its own unique characteristics and rhythm.
By integrating AI and ML modules within its technologies, D.gree creates a comprehensive yacht profile in which any “offbeat sound” is analyzed within its context and compared to its own historical pattern, for full control in every phase of the process.
Case Study: Energy consumption anomalies
A significant case occurred within the production process of a well-known company that contacted D.gree’s dedicated service in regards to solving recurring overload disconnections.
After a consultation, it was decided to install a specific D.gree technology for the continuous monitoring of several power management system parameters.
This approach led to the detection of some relevant anomalies:
when the industrial plant was supposed to be operating at low capacity, during evenings and weekends, high power requests were recorded, resulting in the use of alternative generator sources and several kWh energy loss.
Peak detection and real operational load identification were just the beginning of a process involving further data interpretation resulting in the source problem of the anomaly being addressed.
After the anomaly analysis and identification, D.gree started to enhance overall system efficiency through a structured process.
- Overall Analysis
- Anomaly identification and solution planning
- Continuous Improvement through 24-hour monitoring to validate achieved results
Thanks to its innovative and customizable data acquisition approach, the D.gree process allows a continuous validation of achieved results.
Within one week, overall efficiency of the industrial plant increased by 23%.
In conclusion, D.gree’s innovative approach to data collection and management, combining technology with human intelligence, provides scalable and efficient solutions for the manufacturing industry.