Breakdowns are a headache!
Why do machinery manufacturers always have to play catch up?

Sudden breakdowns frustrate industrial machinery customers, especially when machines are already logging diagnostic and monitoring data. These customers demand operational efficiency and cost reduction, often asking:

  • What assets are at risk of failure? When should we replace their parts?
  • How can we reduce overheads and improve physical and visual inspections?
  • What’s the optimal way to utilize machinery and minimize waste or defects?

Machinery manufacturers struggle to meet these demands without a clear strategy. An engineering-only focus often results in solutions that solve no real problems, derailing business outcomes. Take turbine maintenance, for example. While lubrication is critical, sticking to regular schedules is often enough. Predictive maintenance adds more value when applied to components like gearboxes or generators.

But the iterative nature of predictive analytics clashes with customers' desire for rapid go-to-market timelines. Without a solid business case outlining ROI for various use cases - like predicting lifespans, optimizing schedules, or enabling AI-driven inspections - projects risk failure before they start.

But what does it take to build predictive maintenance applications?
Success hinges on four key elements - labeled data, mature teams with specialized knowledge and skills, the right estimation of the complexity and dependencies, and technology fitment to build a business case.

Predictive maintenance is no longer optional - it’s essential to staying ahead. However, building it requires expertise, strategy, and execution tailored to real-world challenges. That’s where we come in.

How we work with you - our Industrial IoT consulting approach

At Saviant, we collaborate with machinery manufacturers to scale their digital infrastructure while strategically aligning scope and GTM priorities. Whether enhancing an existing product or platform or joining your team to build a new one, our approach includes:

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1. Assessment

Conducting a 2-day rapid assessment to evaluate your digital capability maturity and develop a 3-year roadmap aligned with your organizational and product strategy.

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2. Design

Creating a custom predictive maintenance solution, outlining potential ROI through a value map, and crafting a 1-2year GTM strategy aligned with your goals.

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3. Implement

Delivering value through 90-day release cycles and building joint teams under independent SoWs and defined milestones to ensure timely and measurable outcomes.

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4. Run

Ensuring continuous value delivery by monitoring systems, training your teams, maintaining operational standards, and providing ongoing production support.

Industrial iot consulting services

World's leading
industrial furnaces
manufacturing company minimizes unplanned downtime with ML-driven predictive maintenance

Read detailed case study

Ready to assess the maturity of your current digital solutions?

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