Serba Dinamik is an engineering company specializing in operations and maintenance (O&M), engineering, procurement, construction and commissioning (EPCC), and IT solutions for energy exploration and production firms. Their team worked with Altair to develop a Smart Predictive Maintenance Data System (SPMDS) utilizing Knowledge Studio and Panopticon. Maintenance crews use Panopticon-powered dashboards built into SPMDS to monitor every sensor mounted on operating turbines in real time. AI models built with Knowledge Studio identify potential failures or issues that require engineering attention, and, based on that understanding, take turbines offline only when necessary.

In a world where everything is becoming more and more connected, Mabe, a leader in home appliances, is leveraging the convergence of big data, analytics and simulation to accelerate innovation. Martin Ortega, Senior Design Engineer at Mabe, explains how they are using Altair's AI, data analytics and simulation solutions to uncover insights, create new business opportunities, and advance product development. Learn more - click here to read how connected products deliver big ROI.

Low-cost sensors and new wireless connectivity tools enable manufacturers to employ digital analytics more effectively than ever before. With the right tools, they can gather, cleanse, process, and visualize massive amounts of data from disparate sources that cover all phases of the product lifecycle.

Manufacturers are incorporating advanced machine learning and AI tools into their technology stacks to predict and optimize outcomes in real time—across quality, maintenance, and throughput, in addition to monitoring processes and results. Knowledge graphs running on top of the data infrastructure can map complex relationships across systems, products, and processes; then turn raw data into a connected AI fabric. These technologies empower manufacturers to move from reactive to prescriptive decision-making comprising their complete operational ecosystem. 

This eGuide provides an overview into how manufacturers can extract more value from their data and make accurate predictions about component life, replacement requirements, energy efficiency, utilization, and other factors that have direct impacts on production capacity, throughput, quality, sales, customer acceptance, and overall equipment efficiency.

Increase shop floor efficiency by identifying hidden anomalies and delivering insights for proactive, insight-driven monitoring and maintenance. Explore how Altair enables enterprises to leverage operational data throughout the complete data lifecycle – from shop floor to top floor – to increase value and reduce risk with a comprehensive self-service data analytics and machine learning platform.