Our AI & Data service redefines industrial operations through data automation and actionable insights, addressing challenges posed by an aging operator population.
Our AI & Data service redefines industrial operations through data automation and actionable insights, addressing challenges posed by an aging operator population.
About
Our AI & Data service is your gateway to redefining industrial operations. We specialise in automating tasks by tapping into existing data resources and transforming them into actionable insights. With a focus on big data, statistics, and machine learning, we help you deal with loss of domain knowledge while increasing the efficiency of your processes.
What we do
We focus our approach on four pillars, with potential intersections between them. We help you to determine which technology or combination of technologies aligns with your objectives:
- Quality control and assurance: Use advanced technologies like computer vision and intelligent process monitoring to detect production process faults and rectify issues early on.
- Anomaly detection: Go beyond quality control and improve process stability and availability by identifying irregularities in sensor data.
- Predictive maintenance: Detect statistical outliers in process values to predict equipment failures, leading to significant cost savings.
- Process optimisation: Deploy AI agents in control rooms to enhance energy efficiency and control loop stability.
How we do it
We base our approach on your preferences and technology stack, whether it is cloud-based or requires local computing and storage. In most cases, we prefer using Databricks due to its integration with Microsoft Azure, but we also support other platforms.
Our AI & Data projects encompass four phases:
- Project exploration :
We analyse your data, requirements, and technical specifications in a feasibility assessment, resulting in a detailed report that covers costs, risks, and impact. This assessment is also available as a standalone service.
- Solution exploration:
We gather and process necessary data, design the solution architecture, and develop machine learning models through an iterative process. Based on this, we propose our solution and move on to implementation or further model refinement.
- Solution implementation:
We set up the data pipeline, hardware, and software components. The machine learning model is trained iteratively, and a Site Acceptance Test (SAT) evaluates its performance under various conditions, including stress tests.
- Delivery and upkeep:
After a successful SAT, we provide high-level documentation for your solution, which we continuously update. We use MLOps for CI/CD pipelines and remote testing. Regular performance evaluation, retraining, and validation corrects model drift and ensures your solution performs consistently.
Why invest in AI & Data?
Embracing AI & (big) data in your production processes unlocks significant operational benefits and cost savings, while helping you achieve critical KPIs:
- Higher product quality: boost Return on Assets (ROA) and extend Mean Time Between Failures (MTBF).
- Increased efficiency: enhance Overall Equipment Efficiency (OEE), increase throughput, and reduce cycle time and manufacturing cost per unit.
- Avoid maintenance costs: prevent shutdowns, reduce machine downtime rate, and decrease the overall maintenance cost per unit.
