LINKS

Colourite - Maximising Cullet Additions in the Glass Container Industry

Container Lite: Light-weight Glass Containers - the Route to Effective Waste Minimisation

Container Lite - Opportunities for the Co-op to lightweight glass packaging

Feasability Study for the Reduction of Colour within the Glass Furnace

Materials recovery from waste cathode ray tubes (CRTs)

Study into the Interaction of Imported Wine Bottles and the UK's Cullet Supply

A Study of the Balance between Furnace Operating Parameters and Recycled Glass in Glass Melting Furnaces

Assessment of the International Trading Markets for Recycled Container Glass and their Environmental Applications

Recovered Container Glass: Development of test methods and inorganic contamination limits

Increasing collection and recycling of post consumer domestic window waste

Recycled CRT Panel Glass as an Energy Reducing Fluxing Body Additive in Heavy Clay Construction Products

New Approach to Cathode Ray Tube Recycling

RELATED LINKS

Glass Technology Services Ltd
Sheffield
Tel: +44 (0)114 290 1801
Fax: +44 (0)114 290 1851
Email: info@glass-ts.com

A Study of the Balance between Furnace Operating Parameters and Recycled Glass in Glass Melting Furnaces

Glass making is a high-temperature, energy-intensive process and manufacturers are well aware that over 70% of the energy they use in the furnace is in melting the glass.   As a result, the glass industry has long been cognisant of the benefits of using recycled glass in its processes ie that it is easier to melt than virgin raw materials thus significantly reducing the fuel consumption and CO2 emissions, and that each tonne of glass returned also reduces demand on raw materials by 1.2 tonnes.

 

However to maximise this potential requires furnace operators to be able to optimise fuel consumption when melting loads containing higher and possibly changing levels of recycled glass.

 

GTS, with funding and support from The Carbon Trust and glass container manufacturers, was able to produce a mathematical model able to predict furnace energy consumption, taking into account furnace ageing, moisture levels and any combination of production level and cullet ratio.  The model can also be used as a forecasting tool able to predict furnace energy demand under a number of operating scenarios.

 

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