Micro-stops and catch-up gestures: what machine stops reveal about work at the station

This article is for team leaders, supervisors, production managers, continuous improvement leaders and EHS managers who want a clearer view of what really happens at the workstation. It addresses one specific question: what micro-stops and machine stops reveal about the gestures operators make outside the standard (clearing jams, refeeding, catching up on the rate), and how the frontline manager can use this data to target observations and escalate the right issues. This is not a medical article: machine data measures neither posture nor pain.

The frontline manager, between what is asked and the real work

Moovency, a French company that develops tools for analysing work movements and postures and supports companies in preventing musculoskeletal disorders (MSDs), published Encadrants de proximité : un rôle clé dans la prévention des TMS (in French) on its blog, written by Lucie from the Moovency team. The article shows that frontline managers are in direct contact with the activity, can spot early warning signs (awkward posture, repetitive movement, poorly adjusted handling), that production demands can clash with health, and that managers must be given the means to act. It sums up the role this way: “L’encadrant de proximité voit donc ce que l’entreprise demande et ce que le travail impose réellement.” (in other words: the frontline manager sees both what the company asks for and what the work really demands).

What the work really demands is not always in the routing. A machine that jams regularly forces the operator to step in: clear a part, refill a magazine, restart a cycle. After a stop, the team sometimes speeds up to hit the day’s target. These catch-up gestures are rarely written down or counted, and they add to the prescribed work. Moovency’s article provides the prevention method and the manager’s role; this one looks at what machine stop data can offer as a starting point.

What micro-stops reveal about non-standard gestures

A micro-stop often lasts less than a few minutes and almost never appears in manual logs. Yet behind many micro-stops there is a human intervention. The table below lists matches to check on the shop floor, not conclusions.

None of these signals says an operator is exposed to an MSD risk. They show where to look. Assessing physical strain is a matter for observation of real work, prevention specialists, ergonomists and dedicated tools.

Using stop data in the frontline manager’s routine, step by step

1. Review micro-stops by workstation every week. Identify the two or three machines with the most frequent micro-stops. That is often where operators make the most unplanned gestures.
2. Go and observe with a precise question. Rather than “is everything OK?”, ask for example: “When the machine jams, what do you do, and how?”. Observe the real gesture, access to the area, frequency.
3. Check catch-up after stops. If the rate rises sharply after every long stop, the issue is not technical: it concerns how targets are set and communicated to the team.
4. Escalate to the right people. A recurring jam is for maintenance or engineering; an awkward gesture is also for the prevention specialist or ergonomist. Stop data makes the escalation factual and dated.
5. Track the effect of actions. After a fix (adjustment, chute, raised platform, new procedure), compare micro-stop frequency before and after. Fewer micro-stops also means fewer manual interventions.

Performance and working conditions, one data source

Micro-stops weigh on line performance: they erode OEE without anyone noticing. They also weigh on the work: each jam requires a gesture, often in a hard-to-reach area, under time pressure. Fixing a recurring micro-stop therefore often improves both at once.

This link has a practical consequence for the frontline manager: a technical fix can be defended with two arguments, performance and working conditions, not just one. It also helps avoid a trap Moovency’s article highlights: reminding people of good gestures changes nothing if working conditions stay the same. Removing the cause of the jam is acting on conditions.

What TEEPTRAK brings to the frontline manager

TEEPTRAK measures OEE, stops and micro-stops in real time. A module wired into the electrical cabinet and a sensor at the line record each machine’s activity automatically, with no connection to the PLC. Installation takes about one hour per machine and OEE is available within 48 hours. The manager sees, by workstation and by shift, where micro-stops cluster and how the rate changes after a stop. TEEPTRAK measures neither posture nor operator health: it shows where to look, and prevention happens with the teams and the specialists. The solution is deployed in more than 700 plants in over 30 countries.

Further reading

• Encadrants de proximité : un rôle clé dans la prévention des TMS (Moovency, in French)
• Eliminating micro-stops: Pareto, top root causes and targeted SMED
• The 6 big losses: what your manual log doesn’t see

FAQ

Can machine stop data detect an MSD risk? No. It flags situations where the operator steps in often or works under time pressure. Risk assessment relies on observing the work, prevention specialists, ergonomists and suitable tools.

Should this data be shared with operators? Yes, if it is used to improve the machine and the organisation, never to assess a person. Presented in a team meeting, it often helps operators get recognition for difficulties they were already reporting.

Where should you start on a line? With the machine that has the most micro-stops. Observe the real interventions there, address the most frequent cause of jams, then check that the frequency drops.