Swizzels had production data, but lacked complete visibility of performance across the manufacturing process. Finished-goods reporting and periodic line studies provided useful snapshots, yet they did not consistently show where losses occurred or which issues had the greatest effect on line performance.
As demand grew across key product lines, the Continuous Improvement team needed a clearer, more reliable view of downtime and production losses. Their goal was to improve stability, increase capacity and create greater confidence that production plans could be achieved consistently.
Swizzels selected Vorne XL for its straightforward implementation, user-friendly interface and ability to deliver meaningful production insight without the complexity of a large manufacturing software project.
XL gave the team real-time visibility of OEE, downtime and production losses. Rather than replacing established Continuous Improvement practices, it strengthened them: line studies, root-cause analysis and problem-solving workshops could now be guided by accurate, objective data.
The team used XL to identify the largest sources of downtime, create Pareto analysis of losses, prioritise improvement initiatives by impact and track performance over time. Operators were involved in defining downtime reasons and shaping how the system was used, helping build trust, ownership and engagement on the shop floor.
Vorne XL helped Swizzels uncover a significant source of downtime on a critical piece of equipment. Investigation found that machine settings and adjustments varied between operators, creating inconsistent performance.
With clear evidence of the issue, Swizzels introduced a structured improvement programme focused on standardisation, equipment optimisation and process control. Downtime on the asset was reduced by more than 60%, falling from approximately eight hours per week to around two hours.
The business now has stronger production stability, more effective use of Continuous Improvement and engineering resources, and greater confidence in production planning and forecasting. Teams spend less time gathering information and more time solving the problems that matter.
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