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Home » Performance PDF

Machine downtime costs UK manufacturers
more than £180 billion every year !

According to a study by Oneserve in partnership with British manufacturers. Without the right tools and knowledge, you may not be in a position to maximise your machine performance

When we look at improving the performance of heat treatment machines, we look at two key areas; finished product quality and machine downtime. Both have significant cost implications if not considered and implemented correctly.

Request our PDF to review 5 common mistakes that we help machine maintenance and design teams overcome every day.
Worried about your machines performance?

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What happens next?

This isn't an automated product-selection tool.

One of our team will look at the information you've provided and review the application from an engineering point of view.

We may come back with a few questions, but we'll normally be looking at things such as:

  • The type of electrical load
  • Supply and current requirements
  • The most appropriate firing method
  • REVO-S, REVO-C or multi-loop architecture
  • Diagnostics and monitoring requirements
  • PLC and communications
  • Opportunities to simplify the design
  • Future machine standardisation

No lengthy specification needed.

Just give us enough information to get the conversation started.

Prefer to talk?

Call us on 01323 811100

CD Automation UK

Industrial power control. Backed by people who understand the application.

Please send me this document

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You can access your PDF now by clicking the link below:
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Inside, you’ll discover the 5 common mistakes that can affect machine performance and how to avoid them to save time, reduce downtime, and improve product quality.

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You can access your PDF now by clicking the link below:
Download Your Guide
This paper explores how integrated thyristor power and temperature
control improves heating consistency, energy efficiency, and reliability,
helping UK manufacturers reduce downtime, extend equipment lifespan,
and shift from reactive to predictive maintenance.