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Press Brake Monitoring in Sheet Metal Manufacturing
How can sheet metal manufacturers make hidden bending losses visible across an existing press-brake fleet? In this project, 36 press brakes were monitored within a 136-machine production environment. The customer reported a 28.76% productivity improvement, while machine-state data helped make idle time, setup, tool changes, handling losses, microstops and downtime visible.
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Sheet metal manufacturing: making productive bending and hidden machine-time losses visible.
+28.76%
higher productivity
Customer-reported result
36
monitored press brakes
Within a 136-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
Sheet metal manufacturing
Machine fleet
36 press brakes
Production environment
136 production machines
Machine generations
Build years 2012–2022
Operations
Calculation model: 2 × 8-hour shifts
Technology
External Novo AI retrofit sensors + WatchMen
Focus
Productive bending, idle time, setup, tool changes, handling, microstops and downtime
THE CHALLENGE
A Bending Job Can Occupy the Process Longer Than Planned
A press-brake order can remain on the machine considerably longer than its planned bending time. Setup, tool changes, part handling, inspection, waiting, microstops and downtime can all become part of the elapsed order window.
The challenge was therefore to separate productive bending from the hidden losses around it and understand why an order took longer than expected.
Productive Bending
Identify how much scheduled machine time actually becomes productive bending.
Setup & Tool Changes
Measure setup and tool-change activity consistently and identify avoidable preparation losses.
Handling & Interruptions
Make waiting between bends, part handling, microstops and longer downtime visible.
FROM MACHINE TO ANALYSIS
Retrofit. Validate. Understand.
Connecting the press brakes creates the machine-data foundation. Reliable production analysis comes from validated bending events and machine states combined with the order and production context needed to explain why productive bending stops.
01
Retrofit the press brakes
External Novo AI sensors were installed on the 36 monitored press brakes without PLC intervention. Installation took approximately 15 minutes per machine.
02
Validate bending events and machine states
Edge processing and validation support the recognition of productive bending, idle periods, setup activity, microstops and downtime.
03
Add production context
WatchMen connects machine states with order and production information so that losses can be interpreted together with geometry, material, tooling, batch size and quality requirements.
EXTERNAL SENSORS
Press Brake Data Without PLC Access
External retrofit sensors capture physical machine behavior without requiring access to the press-brake control system.
WatchMen turns the validated signals into a machine-state timeline, making productive bending, idle periods and recurring interruptions visible. Order, tooling and production context then help explain why a particular loss occurred.
TURNING DATA INTO ACTION
Turn Bending Losses Into Practical Improvements
Monitoring shows where scheduled press-brake time is being lost. The next step is to focus on the largest recurring losses and verify whether operational changes release usable bending capacity.
01
Reduce hidden idle time
Review longer waiting periods around material readiness, preparation of the next order and machine availability. Use recurring patterns to improve readiness before the press brake should begin producing.
02
Improve setup, tool changes and part handling
Prepare tools, programs and material before the machine becomes available. Review recurring delays between productive bends and improve part staging, handling flow, workplace layout and standardized work.
03
Reduce recurring microstops and downtime
Investigate short repeated interruptions as well as longer faults. Combine the machine timeline with maintenance and production context, implement corrective actions and then compare the same indicators again.
RESULTS IN CONTEXT
What Improved During the Project
REPORTED PROJECT RESULT
−42.86%
less idle time
In the modeled production scenario, idle time was reduced by 42.86%. Detailed before-and-after values and the calculation basis are included in the complete case study PDF.
+20,707.2
additional productive machine-hours per year
Approximate annual capacity estimate across the 36 monitored press brakes.
Reported result: The customer reported a 28.76% productivity improvement. WatchMen helped make productive bending and recurring losses such as idle time, setup, tool changes, part handling, microstops and downtime visible for systematic investigation.
Annual capacity estimate: The modeled improvement corresponds to approximately 20,707.2 additional productive machine-hours per year across the 36 monitored press brakes. This represents released bending capacity within the existing machine schedule rather than a full year of directly measured additional 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 Press Brake Monitoring
Which machines were included in the case study?
The monitored scope included 36 press brakes operating within a 136-machine sheet-metal production environment. The project environment includes machines built between 2012 and 2022.
What productivity result did the customer report?
The customer reported a 28.76% productivity improvement. Detailed idle-time, setup, handling 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 42.86%. Detailed before-and-after values and the calculation basis are available in the full case study PDF.
How much additional productive capacity was calculated?
The model estimates approximately 20,707.2 additional productive machine-hours per year across the 36 monitored press brakes. This is an annualized capacity estimate rather than a full year of directly measured additional output.
How long did sensor installation take?
The supplied installation time is approximately 15 minutes per press brake. The external sensors were installed without PLC intervention.
What happened to waiting between productive bends?
The modeled interval between productive bends was reduced by 35.42%. This area can be influenced by part staging, handling flow, workplace layout and standardized work.
THE COMPLETE CASE STUDY
Details to Support Your Decision
Download the English PDF with the complete project description, modeled 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 press brakes you operate, their approximate years of manufacture and your biggest production question: productive bending, idle time, setup, tool changes, part handling, microstops or downtime?
Together, we can identify suitable pilot machines and determine which 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.