No ownership of the whole
Each manufacturer checked its own technology, but no one took responsibility for the overall result of the line.
Analytical Case Study
How a tile manufacturer increased its effective production capacity by 36%.
Through an independent performance analysis and the implementation of line-wide KPIs, a major tile manufacturer raised production from 70% to 95% of design capacity.
A new line that was not reaching its design capacity
A major tile manufacturer invested in a new production line designed to reach a given capacity of m² per month. The line is made up of machines from different brands and countries (Italy, the Netherlands, China and Brazil).
About 18 months after start-up, however, the output achieved was still significantly below the targets set during design.
About 18 months after start-up, production was still around 70% of the capacity planned at the design stage.
Machines from different brands, no ownership of the overall result
The various manufacturers involved in the project had each verified that their own technology was working correctly, but none was willing to take responsibility for a result below expectations. The technicians of the respective machines kept refusing ownership of the overall outcome.
Production stuck at 70%
Actual output stalled at around 70% of design capacity, with inefficiencies spread across the process.
Bottlenecks not visible
Bottlenecks could not be clearly identified and there was no structured measurement of overall performance.
High downtime and scrap
High downtime and scrap limited the production potential of the plant.
An independent view to measure real performance
To identify the causes limiting productivity, the client asked for our help, considering Inter Ser to be completely independent from all the brands that make up the line. The analysis was entrusted to Marco Grani, who has extensive experience in plant engineering and has held leadership positions in production and process improvement.
The proposed activity included:
- defining the critical issues and improvement objectives;
- measuring and collecting data on initial performance;
- analysing inefficiencies, comparing with design data and identifying bottlenecks;
- implementing improvement actions together with the team, with training, modifications and optimisation of operating parameters;
- checking results, defining guideline parameters and consolidating the new operating conditions.
On-site analysis and involvement of the whole organisation
The activity was carried out directly at the client’s plant, through a period of on-site observation and analysis lasting about two weeks.
The intervention involved every organisational level (from managers to technicians and operators across the various production areas) to build shared ownership of common objectives, gather information, understand operating practices and support the improvement path identified.
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On-site observation
About two weeks of direct observation and analysis at the client's plant.
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Involvement of every level
From managers to technicians and operators, to build shared ownership of common objectives.
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Independence from the brands
A neutral view of all the technologies that make up the line.
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A preventive approach
Synchronising departments and planning stoppages to shift from corrective to preventive.
Measuring in short intervals and defining KPIs for each department
It proved essential to analyse the process over short time intervals, so as to precisely identify and record stoppages, micro-stoppages and drops in performance linked to production activities. Particular attention went to synchronising activities between departments and planning stoppages, to favour a preventive rather than corrective approach.
The analysis of the different areas, supported by precise measurements, highlighted the need for both mechanical and operational changes to some machines. The activities covered all the main process stages: body preparation and milling, pressing, glazing and decoration, firing, rectification, sorting and packaging.
For each area, specific performance indicators were defined: KPIs and production ranges for each machine, hourly and shift targets for each department, monitoring systems, real-time dashboards and line monitors, and specific indicators assigned to department managers.
In the Field
Photo gallery of the project
From 70% to 95% of design capacity
Before
70%
Design capacity (initial situation)
After
95%
Design capacity (after the intervention)
By bringing to light the inefficiencies spread across the line and introducing a structured KPI system, production was brought back close to design targets, with a direct impact on scrap and downtime.
| Metric | Result | Impact |
|---|---|---|
| Effective output | +36% | Compared with the initial situation |
| Design capacity | 95% | From the initial 70% |
| Scrap | -46% | Reduction in production scrap |
| Downtime | -40% | Reduction in machine stops |
| KPI system | Implemented | Across all departments of the line |
What this case demonstrates
The case shows how structured measurement and an independent view can unlock the production potential of a line, turning inefficiencies into improvement opportunities with an immediate economic return.
01
Measure continuously
Production potential must be measured and monitored continuously over time: without structured data, inefficiencies stay invisible.
02
From data to opportunities
Analysing data brings inefficiencies to light and turns them into solutions with an immediate economic return.
03
The value of an independent view
An independent, data-based view of the machine builders creates concrete value for the client.
Next step
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