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Cable Extrusion Monitoring in Cable Manufacturing
How can cable manufacturers make hidden production losses visible across existing extrusion lines? In this project, 13 cable extrusion lines built between 2006 and 2019 were monitored within a 48-machine production environment. The customer reported a 27.6% productivity improvement, while WatchMen helped make idle time, material changes, reel waiting, setup losses, microstops and downtime visible.
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Cable extrusion: making productive extrusion and hidden production losses visible.
+27.6%
higher productivity
Customer-reported result
13
monitored extrusion lines
Within a 48-machine production environment
15 min
sensor installation
Per machine in the project
In this case study Project · Implementation · Measures · Results · FAQ
THE PROJECT
At a Glance
Industry
Cable manufacturing
Machine fleet
13 cable extrusion lines · Built between 2006–2019
Production environment
48 production machines
Operations
Calculation model: 2 × 8-hour shifts
Technology
External retrofit sensors + WatchMen
Focus
Productive extrusion, idle time, material changes, reel/material waiting, microstops and downtime
THE CHALLENGE
Continuous Production Still Loses Time Around the Run
Cable extrusion is a continuous production process, but scheduled machine time can still be consumed by material changes, reel waiting, warm-up, idle periods, short interruptions and downtime.
Cable construction, polymer type and process settings also change the production context. The challenge was therefore to distinguish productive extrusion from the losses surrounding the run and understand where recurring machine time was being lost.
Productive Extrusion
Identify how much scheduled line time actually becomes productive extrusion.
Material & Reel Readiness
Make material changes, reel waiting and preparation losses visible and comparable.
Interruptions & Downtime
Reveal recurring microstops, longer waiting periods and downtime across production runs.
FROM MACHINE TO ANALYSIS
Retrofit. Validate. Understand.
Connecting the extrusion lines creates the machine-data foundation. Reliable production analysis comes from validated machine states combined with order, material and production context.
01
Retrofit the extrusion lines
External Novo AI sensors create a common monitoring layer across the 13 existing extrusion lines without requiring PLC or machine-control intervention. The project benchmark for installation was approximately 15 minutes per monitored line.
02
Validate machine states
Edge processing and validation support the distinction between productive extrusion, idle periods, setup activity, microstops and downtime.
03
Add production context
WatchMen links machine states with order and production context. Cable construction, polymer, material, process settings and quality requirements can then be considered when investigating production losses.
EXTERNAL SENSORS
Cable Extrusion Data Without PLC Access
External retrofit sensors capture physical machine behavior without requiring intervention in the extrusion-line control system.
WatchMen turns validated signals into a common machine-state timeline, making productive extrusion, idle periods and recurring interruptions visible. Order, polymer, material and production context then help the team investigate why a particular loss occurred.
TURNING DATA INTO ACTION
Turn Recurring Extrusion Losses Into Practical Improvements
Monitoring shows where scheduled extrusion time is being lost. The next step is to focus on the largest recurring loss categories and verify whether process changes release usable production capacity.
01
Reduce hidden idle time
Review longer idle and waiting periods around next-order readiness, material staging and line availability. Recurring patterns can show where preparation and response times need to improve.
02
Improve material changes and reel readiness
Prepare compounds, colors, conductor reels, take-up reels and other changeover requirements before the extrusion line becomes available. Review recurring material-change and reel-waiting events to improve production readiness.
03
Reduce recurring interruptions and downtime
Investigate repeated microstops as well as longer faults. Combine the machine timeline with material, process and maintenance context, implement corrective actions and then compare the same indicators again.
RESULTS IN CONTEXT
What Improved During the Project
REPORTED PROJECT RESULT
−37.50%
less idle time
In the modeled production scenario, idle time was reduced by 37.50%. The detailed before-and-after values and calculation basis are included in the complete case study PDF.
+7,176
additional productive machine-hours per year
Approximate annual capacity estimate across the 13 monitored extrusion lines.
Reported result: The customer reported a 27.6% productivity improvement. WatchMen helped make productive extrusion and recurring losses such as idle time, material changes, reel waiting, microstops and downtime visible for systematic investigation.
Annual capacity estimate: The modeled improvement corresponds to approximately 7,176 additional productive machine-hours per year across the 13 monitored extrusion lines. This represents released production capacity within the existing schedule rather than a full year of directly measured additional cable output.
Context: These figures relate to the project described. Starting conditions, product mix, shift model and the measures implemented affect the result. A reduction in time losses does not automatically mean an equally large increase in OEE.
GOOD TO KNOW
Questions About Cable Extrusion Monitoring
Which machines were included in the case study?
The monitored scope included 13 cable extrusion lines within a production environment containing 48 machines. The monitored extrusion lines were built between 2006 and 2019.
What productivity result did the customer report?
The customer reported a 27.6% productivity improvement. Detailed idle-time, loss-category and capacity figures are modeled values used to interpret the reported result.
How much idle time was reduced?
In the modeled production scenario, idle time was reduced by 37.50%. Detailed before-and-after values and the calculation basis are available in the complete case study PDF.
How much additional productive capacity was calculated?
The model estimates approximately 7,176 additional productive machine-hours per year across the 13 monitored extrusion lines. This is an annualized capacity estimate rather than a full year of directly measured additional cable output. Novo_AI_Cable_Extrusion_Monitor…
What types of production losses can be made visible?
The case study considers productive extrusion, idle and waiting periods, material changes, reel and material waiting, microstops and downtime.
Can existing extrusion lines be monitored without PLC access?
Yes. Novo AI's external sensor approach is designed to capture relevant machine behavior without intervention in the machine control system. Existing extrusion machines can therefore be retrofitted across different manufacturers and machine generations.
THE COMPLETE CASE STUDY
Details to Support Your Decision
Download the complete case study with the project description, production-loss categories, results and detailed measurement and calculation basis.
Download the free PDF ↓APPLYING IT TO YOUR PRODUCTION
What Would You Like to Make Visible?
Tell us how many extrusion lines you operate, their approximate years of manufacture and your biggest production question: productive extrusion, idle time, material changes, reel waiting, microstops or downtime?
Together, we can identify suitable pilot lines and determine which machine states and production losses should be made visible first.
Further reading: CNC Monitoring in Precision Tool Manufacturing · Understanding machine data acquisition: data and system boundaries · All Case Studies
Publisher: Novo AI GmbH. Source of the project information: the corresponding case study PDF. Definition and calculation: OEE based on availability, performance and quality.