Downtime happens, but nobody knows why
Stops are frequent, but without structured reason codes tied to machine events, the top causes stay invisible.
Today, and with Frontlink.
Whiteboard tallies, end-of-shift downtime sheets, and Excel. Reasons are guessed hours or days after the event, too late for root-cause action.
- 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.
- Time to value
- Days to 1 week
- Complexity
- Low
- Works with machine counters
- Yes
The problem
- Who feels it most
Operators (constant interruptions), maintenance leads, production managers, and continuous improvement teams.
- 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.
- 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.
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
Frequently asked questions.
Who typically feels this problem?
Operators (constant interruptions), maintenance leads, production managers, and continuous improvement teams.
Why doesn't an ERP or WMS system solve this?
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.
How does Frontlink solve this?
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.
How quickly does it deliver value?
Typical time to value: Days to 1 week. Implementation complexity: Low.
Which process takes you the most time?
Book a 30-minute call. We look at your own examples together.
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