In today’s manufacturing environment, competitiveness relies on data-driven decision-making and process optimisation. This article explores how the integration of a digital machine monitoring platform with a Lean Six Sigma Green Belt project enabled a medium-sized manufacturer to achieve measurable gains in machine utilisation, energy efficiency, and operational agility.
Using the structured DMAIC framework, the team demonstrated how digital tools can underpin continuous improvement projects and drive significant return on investment.
Lean Six Sigma is a well-established methodology for process improvement that combines the waste-reduction principles of Lean with the variation-reduction goals of Six Sigma. Its structured approach enables organisations to make systematic, data-backed improvements that enhance performance and reduce inefficiencies. At the heart of Lean Six Sigma lies the DMAIC framework:
DMAIC provides a logical roadmap for tackling operational issues and is ideal for projects seeking to quantify the benefits of digital transformation.
In this case study, a Continuous Improvement Manager within a fabrication department recognised a fundamental gap: a lack of reliable data to support time and cost-based decision-making. While the team was committed to continuous improvement, they lacked the visibility needed to understand true machine utilisation, downtime causes, and energy consumption patterns.
To bridge this gap, the department implemented a plug-and-play machine monitoring platform suitable for their CNC machines. This digital tool provided real-time and historical data on machine activity, enabling a structured Lean Six Sigma project aimed at improving operational performance and validating the return on investment (ROI) of digitalisation.
The problem statement was clear: without accurate data, improvement efforts were based on assumptions rather than facts. The project goal was to gather utilisation data from CNC machines, make process improvements, and improve job quoting accuracy to strengthen customer relationships.
Stakeholder buy-in was critical. Operators and managers were engaged early to ensure they understood the purpose of the project and the benefits of the new digital tool.
Once the machine monitoring platform was installed, data was collected across five CNC machines. Key performance areas included:
The visibility provided by this data enabled the team to move from anecdotal feedback to actionable insights.
Using analytical tools such as fishbone diagrams, the team uncovered several root causes of inefficiency:
Each of these insights was derived directly from data provided by the monitoring platform.
The team developed and implemented targeted solutions:
All changes were trialled before full implementation to validate their impact.
To sustain the improvements, the department established a control plan. The machine monitoring platform continued to provide real-time feedback on utilisation, downtime, and energy consumption. Team leaders were trained to use the platform effectively, and responsibilities were distributed to maintain engagement and oversight.
The combination of ongoing training and clear visualisation tools ensured the changes were not only implemented, but also embedded in daily routines.
The project delivered a first-year ROI of £15,000 against a £9,000 annual software investment. Key benefits included:
Operators embraced the change, and the management team gained confidence in using data to make operational decisions. The success of this project has encouraged wider deployment of digital tools across the organisation.
This project illustrates how digital machine monitoring, when combined with a structured improvement framework like DMAIC, can deliver tangible operational and financial benefits. For manufacturers seeking to justify digital investment or enhance their Lean Six Sigma capability, this case offers a compelling example of what’s possible. The takeaway is clear: with the right tools and methodology, continuous improvement becomes a continuous advantage.