Reducing raw and finished product waste in industrial manufacturing

Raw material waste is the enemy of sustainable manufacturing. Consider that it’s not just raw material being lost - but also the opportunity to produce a finished and more valuable end-product - and the cost implications of waste are eye-watering.

Added to immediate cost, every instance of waste engorges a firm's carbon footprint.

But there is a knight in shining armor. With Industry 4.0 the waste monster can be slain, whilst reducing costs and improving carbon footprint.


For instance, by moving to predictive maintenance, manufacturers can reduce waste-causing downtime by more than 50% and use up to 40% fewer replacement components.

Maintenance intervals specified by Original Equipment Manufacturers (OEMs) always tend towards the conservative (if not willfully wasteful), yet the information to reliably and safely extend intervals has until now been held by a privileged few.

There is tremendous opportunity to use industrial analytics techniques like predictive maintenance to run components to their true full life - and to do so without risking more failures – reducing waste and operational costs whilst improving reliability.

For more on saving waste - and money - see our new report exploring sustainability challenges in manufacturing. It covers how to cut waste when it comes to: 

  • Raw materials
  • Faulty or poor quality products
  • Prematurely replaced components

Read the report to find out what works in sustainable manufacturing:

How to stop wasting raw materials

  • Moving to additive manufacturing
  • How intelligently deployed industrial analytics helps prevent processes drifting out of control
  • How information from Industry 4.0 reduces raw material and labor waste

How to cut your rate of faulty completed products

  • Moving away from wasteful batch testing
  • How monitoring keeps processes working the way you need them to

How to get the full life from machine components without more failures 

  • Protecting components with real-time AI powered industrial analytics
  • Using predictive maintenance to stop serviceable components going to landfill

How all of this can be achieved with new machines as well as old.

To read the full report, click here.

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