This case study is based on a UK biotechnology manufacturer supplying to clinical, pharmaceutical, food and industrial sectors worldwide, operating across two highly regulated cGMP production sites.
The business runs fully automated, continuous-process filling lines supported by cleanrooms, sterilisation facilities and integrated logistics. With around 100 employees, it delivers high-quality, compliance-driven products across a wide range of formats and volumes, supported by strong R&D, QA and technical functions.
Machine utilisation increased from 30 percentage points to over 50 percentage points on key lines
Production increased from 30m → 45m → 50m units in two years
Reduced downtime during product changeovers
Improved shift start performance and greater consistency across shifts and teams
Clear visibility of maintenance-related downtime
Increased visibility and confidence for leadership
With production increasing from 30 million units in 2023 to 50 million units in 2025/26, the business required greater operational visibility to support sustained growth and meet new contract demand.
The immediate priority was to maximise efficiency within existing production hours before considering expansion to 24/7 operations. However, despite advanced manufacturing processes, there was limited visibility of machine performance.
Data was either inaccurate or unavailable, making it difficult to:
Understand true production capacity
Identify inefficiencies and downtime
Confidently plan improvements
This lack of visibility impacted decision-making across the organisation. Leadership teams were unable to answer (with confidence) three critical operational questions clearly:
When are our lines stopping?
How long are they stopped for?
What is the real reason for each stoppage?
After exploring alternative approaches such as stack light systems, the manufacturer implemented FourJaw to introduce real-time machine monitoring across production.
FourJaw was deployed across plate and bottle lines without complex infrastructure changes, providing immediate visibility and a consistent, reliable source of production data.
Key capabilities included:
Real-time machine state monitoring
Automatic tracking of stoppage duration
Structured downtime categorisation
Tablet-based operator input and messaging
Historical performance analysis
This established a single source of truth for production data, accessible from the shopfloor through to senior leadership.
With clear visibility of downtime patterns, the production team focused on reducing lost time and improving consistency across operations.
This led to:
Machine utilisation increased from mid-30% to over 50% on key lines
Reduced downtime during product changeovers
Improved shift start performance
Greater consistency across shifts and teams
Engineering and maintenance teams gained clear insight into the biggest sources of downtime, enabling faster and more targeted interventions.
Clear visibility of maintenance-related downtime
Elimination of major recurring breakdown losses
Faster identification and resolution of issues
Data-driven prioritisation of engineering activity
FourJaw created a shared, trusted view of performance across the organisation, improving alignment from the shop floor to the boardroom.
Performance data used in weekly production reviews
Increased visibility and confidence for leadership
Faster, more informed decision-making
Stronger cross-team collaboration and accountability
By improving both machine reliability and process efficiency, the business significantly increased output while maintaining control and consistency.
Production increased from 30m → 45m → 50m units in two years
New contract demand delivered on time
Additional capacity unlocked within existing operating hours
Increased confidence in operational delivery
FourJaw is now embedded as a core part of the company’s operational strategy, connecting engineering, production and leadership through a shared, structured view of performance.
With strong operational foundations in place, the business is well-positioned to continue scaling efficiently and sustainably while maintaining high levels of quality and control.