Colourite - Maximising Cullet Additions in the Glass Container Industry
GTS has conducted an 18-month project to investigate options for maximising cullet use in production of container glass. The project, supported by WRAP with collaboration from glass processors, container glass manufacturers and retailers and various technical organisations, aimed to maximise the amount of furnace-ready cullet able to be recovered from glass waste streams collected in an increasingly colour-mixed form.
In simple terms, the UK has a large, unsatisfied demand for clear glass but an oversupply of green glass. Mixed colour systems, while effective in collecting large quantities, are problematical in that once mixed, it is harder to seperate the valuable clear glass and contamination with green glass becomes a major issue.
Taking the problematic view that glass would continue to be collected by mixed colour schemes, GTS sought ways to maximise the amount of cullet that container glass manufacturers could incorporate in their furnaces. Initially, technical solutions were evaluated which would allow clear glass furnaces to produce an acceptable product from feedstock containing colour-contaminated cullet. At the same time the project took the bold step of challenging the long-held beliefs of glass manufacturers as to the overriding importance of colour integrity, with the help of the Psychology Department at the University of Leeds.
The full report details the detailed literature search, the laboratory-scale melting and full-scale manufacturing trials in all its aspects, including the use of decolourisers, and a series of customer perception studies with regard to glass container packaging, as well as the full outcome of the technical solutions thus covering both ends of the quality spectrum.
An important output of the project was a user-friendly Excel-based programme which can quickly and efficiently assist busy furnace managers to predict the effect of adding decolourisers to an already complex batch recipe. This is available by email email@example.com with the words "Predictive Excel Model" in the subject line.