Brilliant Digital Factory Services and Solutions
Improve plant KPIs, reduce operational costs and boost quality by connecting assets on the factory floor to generate real time insights

Our services and solutions for the Brilliant Digital Factory are designed to transform industrial data into actionable insights. Clients use our analytical services as fundamental building blocks of their intelligent factories that can predict failure, forecast material supply, ensure quality standards, improve overall equipment effectiveness (OEE), reduce errors and lower the cost of production.

Our solutions are backed by three decades of experience in IT management, a team of highly skilled data scientists, process and network engineers. Together, they deliver our 3 step accelerator package for IIoT, System Integration services and Industrial Analytics-based solutions for easy adoption of Brilliant Digital Factory:

Microland’s 3-Step Accelerator Package: A consulting-led approach to IIoT

  • Define - Understanding current state and defining new requirements via a scoping workshop
  • Design - Defining and capturing use cases through System Design Thinking workshops
  • Deliver – Deploying solutions using System Engineering and Agile methodologies

System integration

  • Clients using our service for large scale IIoT projects benefit from our strong partnerships with IoT platforms like Azure, ThingWorx, Predix and Cisco Kinetic.

Industrial Analytics

  • Microland’s data science team transforms data into actionable insights using our analytics suite. The insights are used to predict asset performance, forecast material supply and deliver quality standards.

The primary reason clients choose our consulting-led approach to IIoT is our ability to implement proven use cases that offer the highest levels of business benefits (with the lowest investments).

Blogs
How managed services for Internet of Things are transforming the industrial internet?
White paper
From concept to reality: tackling the inherent complexity of IoT projects
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