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CASE STUDY / PRECISION TOOL MANUFACTURING

CNC Monitoring in Precision Tool Manufacturing

How can older CNC machines be monitored without PLC access? This case study shows the use of external sensors and the WatchMen platform across 25 CNC machines operating in three shifts. Following process improvements based on these insights, the project reports 36.83% less idle time.

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CNC milling of a clamped metal workpiece

CNC manufacturing: understanding machine activity in the context of production.

36.83%

less idle time

Reported project result

25

CNC machines

Across three shifts

16.8 min

sensor installation

Average per machine

In this case study   Project   ·   Implementation   ·   Measures   ·   Results   ·   FAQ

THE PROJECT

At a Glance

Industry
Precision tool manufacturing

Machine fleet
25 CNC machines · Built between 1990 and 2025

Operations
Three shifts

Technology
External AVA sensors + WatchMen

Integration
LAN and ERP/BDE

Focus
Utilization, idle time, downtime and OEE

THE CHALLENGE

Order times did not explain machine time.

The ERP data showed when an order started and ended. What happened in between remained unclear: productive machining, waiting for the next order, brief interruptions or longer periods of downtime. The production team needed a comparable overview of actual machine activity across all three shifts.

Machine States

Distinguish periods of production, idle time and downtime.

Interruptions

Identify waiting times and recurring microstops.

Shift Comparison

Make differences visible and investigate their causes.

FROM MACHINE TO ANALYSIS

Retrofit. Validate. Understand.

Installing the sensors was the first step. Reliable insights came from validated machine states and the right production context.

01

Install sensors

External AVA sensors were fitted to existing machines without PLC access. Installation took an average of 16.8 minutes per machine and was carried out during planned changeovers. According to the project report, no additional production downtime was required.

02

Validate signals

The machines were connected to WatchMen via LAN. During an initial learning and validation phase, the team checked the classification of signals as production, idle time and downtime.

03

Add order context

The connection to ERP/BDE data linked machine activity with order information. This allowed recurring losses to be investigated using the recorded baseline data.

Retrofitting machines with a Novo AI sensor for real-time machine data

EXTERNAL SENSORS

Machine Data Without PLC Access

The sensors capture signals at the machine. WatchMen classifies the validated states; ERP/BDE data adds order information. Together, they show when losses occur and under which conditions.

More about machine data acquisition with Novo AI →

TURNING DATA INTO ACTION

What the Team Changed in Daily Operations

Transparency alone does not change a process. WatchMen provided the data foundation; the production team used it to investigate causes and make targeted adjustments to workflows.

01

Prepare the next order

Materials, approvals or the next order were sometimes not yet ready. Idle alerts and earlier preparation helped reduce waiting times between production steps.

02

Organize shift starts more effectively

Microstops occurred more frequently during shift changes and material replenishment. Readiness checks at the start of each shift and alerts for repeated interruptions made these patterns actionable.

03

Clarify responsibility for alarms

Repeated alarms and delayed responses prolonged downtime. Clear responsibilities and defined triggers for maintenance measures supported a systematic response.

RESULTS IN CONTEXT

What Improved During the Project

REPORTED PROJECT RESULT

−36.83%

less idle time

Relative reduction in idle time compared with the baseline in the CNC machine fleet described. This figure represents neither a decrease of 36.83 percentage points nor an equally large increase in OEE.

4,083

additional productive machine-hours per year

Reported annual extrapolation for the entire fleet of 25 machines following operational improvements.

Observed result: The project report states a 36.83% reduction in idle time following operational improvements. WatchMen made time losses visible; the production team adjusted workflows and reviewed the results.

Annual extrapolation: The 4,083 additional productive machine-hours apply to all 25 machines combined. They are not an increase directly measured over a full year and do not indicate additional unit output or revenue.

View the measurement basis in the PDF ↓

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 CNC Monitoring

Can older CNC machines also be monitored?

The project included a mixed machine fleet built between 1990 and 2025. External sensors enabled monitoring without PLC access. For a new project, Novo AI reviews the machines and requirements together with your team.

Does sensor installation interrupt production?

In this project, installation took an average of 16.8 minutes per machine and was carried out during planned changeovers. According to the project report, no additional production downtime was required. Installation must fit the respective production schedule.

What can WatchMen make visible?

Depending on the validated machine and production configuration, WatchMen can display productive operating time, idle time, downtime, microstops, cycles, utilization, shift differences and process deviations. OEE additionally requires suitable performance and quality data.

Can WatchMen be connected to our ERP or BDE system?

In the CNC project described, order information from ERP/BDE was linked to machine activity. For your production operations, the available interfaces, machine and order identifiers, and the desired data exchange need to be reviewed. Our solution page explains the requirements for an ERP/MES connection.

What is the difference between OEE and machine utilization?

Utilization describes the use of a machine within a defined reference period. OEE combines availability, performance and quality. Machine states reveal time losses; a complete OEE calculation also requires appropriate performance and quality data.

THE COMPLETE CASE STUDY

Details to Support Your Decision

Download the English PDF with the project description, results and measurement notes.

Download the free PDF ↓

APPLYING IT TO YOUR PRODUCTION

What Would You Like to Make Visible?

Tell us the number and years of manufacture of your CNC machines, the shift model and your most important question: idle time, downtime or order changeovers? Existing ERP/BDE interfaces help determine the appropriate pilot scope.

Discuss your application →

Further reading: Stretching Machine Monitoring · Understanding machine data acquisition: data and system boundaries · All Case Studies & Downloads

Publisher: Novo AI GmbH. Source of the project information: the corresponding case study PDF. Definition and calculation: OEE based on availability, performance and quality.