Downtime happens, but nobody knows why
Stops are frequent, but without structured reason codes tied to machine events, the top causes stay invisible.
The problem
Who feels it most
Operators (constant interruptions), maintenance leads, production managers, and continuous improvement teams.
How common is this?
Very common in SMEs with limited digital tools. Downtime is consistently the #1 cited pain point in manufacturing digitisation surveys, and paper-based execution remains pervasive.
Typical workaround today
Whiteboard tallies, end-of-shift downtime sheets, and Excel. Reasons are guessed hours or days after the event — too late for root-cause action.
Why ERP / WMS doesn't solve it
ERP captures orders and confirmations, not second-by-second stop/start events or structured reason codes tied to machine states. Collecting downtime data in ERP is too slow and the interface is unusable on the shop floor.
Business impact
Lost output hours, overtime, and late orders from unplanned stops
Chronic repeat stops — the top 3 reasons typically drive the majority of loss
Without categorised data, MTBF/MTTR improvement is impossible to target
Auto-detect downtime from counters, then capture reasons in one tap
Machine counters detect state changes automatically — running, idle, or down — based on configurable thresholds (e.g., no count increment for 60 seconds).
When downtime starts, the operator tablet pushes a 1-tap reason prompt with hierarchical categories: mechanical failure, changeover, material shortage, quality hold, planned maintenance.
Operators can add free-text notes and photos for context. Optionally tag 'maintenance needed' to create a work request.
OEE-lite view breaks down Availability (downtime), Performance (speed loss), and Quality (scrap) — updated in real time.
Downtime Pareto analysis by reason, line, shift, and time period powers targeted improvement actions.
Ready to solve this?
Book a demo and we'll show you exactly how Frontlink addresses this problem in your environment.