ISO 9001:2026 on the shop floor: using downtime and scrap data as evidence of control

This article is for quality managers, production managers, continuous improvement leaders and plant managers preparing the transition to ISO 9001:2026 and wondering what they will actually be able to show from the shop floor. It does not walk through the standard: it suggests a way to use data the plant already produces, machine downtime and scrap, to make the link between a finding, a decision and its result visible.

What Qualiblog highlights in the new edition

Jérémy Cicero published ISO 9001:2026 : les nouvelles exigences qui vont changer votre façon de piloter la qualité (in French) on Qualiblog. He states that the new version of the standard was published on 16 September 2026 and that organizations certified to ISO 9001:2015 have until 30 September 2029 to transition. He presents the changes to address: more visible leadership commitment, a bigger place for quality culture and ethical behavior, opportunities treated as seriously as risks, a more explicit link between strategy, quality policy and results, stronger emphasis on resilience and change management, and retention and sharing of knowledge. Among his practical suggestions for management review: “Préparer un tableau de bord alimenté par les réclamations, audits, non-conformités, risques et actions.” (in other words: prepare a dashboard fed by complaints, audits, nonconformities, risks and actions).

The common thread of the article is linking the signal, the decision and the result, with an example of supplier complaints followed through to the effectiveness check. This article carries that logic over to the shop floor. One important point: what follows is a practitioner’s reading, not a requirement of the standard. ISO 9001 does not prescribe machine data; it asks you to be able to demonstrate control. Downtime and scrap are simply good raw material for that demonstration.

Why downtime and scrap make good evidence

Convincing evidence of control has three qualities: it is dated, it is objective and it allows a before and after comparison. Downtime and scrap data, when measured automatically, meet all three. Each stop has a start, an end and a qualified reason; each scrapped part can be tied to a moment of production. A manual log filled in at the end of a shift, by contrast, is easy to challenge, because it misses short stops and rounds durations.

These data also connect quality and production. Scrap at restart, drift after a changeover, a run of micro-stops before a defect: these signals speak to both the quality manager and the production manager, and they give management review a shared basis.

Linking the themes of the new edition to shop floor data

The table below takes themes presented by Qualiblog and suggests, for each, a shop floor data point that can serve as an illustration. The examples of evidence are indicative, to adapt to each management system.

A signal, decision, result chain on one line

Qualiblog describes a five-stage chain: finding, analysis, decision, action, verification. Here is how it can play out on the shop floor, with a purely illustrative example.

1. Finding. Stops and scrap are recorded automatically, dated and tied to the machine. For example, an assembly line shows more frequent jam stops over the past three weeks.
2. Analysis. The data show that these stops follow restarts after changeovers and coincide with more scrap at restart.
3. Decision. Production management approves a revision of the restart standard and appoints an owner with a deadline.
4. Action. The standard is revised, teams are trained and the effective date is recorded.
5. Verification. Jam stops and restart scrap are compared before and after the effective date; the result goes to the next review.

Each step leaves a dated trace. That continuity, more than data volume, makes control readable for an auditor and for an executive.

Pitfalls to avoid

First, presenting indicators without linking them to actions: a monthly OEE figure shows nothing if no one can say which decision it triggered. Second, piling up indicators: three or four tracked and discussed data points beat a dashboard nobody reads. Third, self-reported data that cannot be checked, which weakens the effectiveness check. Finally, keeping quality and production in two separate dashboards loses the link between a stop and the defect that follows it.

What TEEPTRAK brings

TEEPTRAK measures OEE, stops and micro-stops in real time. A module wired into the electrical cabinet and a sensor at the line record machine activity automatically, with no connection to the PLC. Installation takes about one hour per machine and OEE is available within 48 hours. Stops are timestamped and qualified by reason, giving the quality management system dated findings and before and after comparisons. TEEPTRAK does not replace quality software or management review: it feeds both with measured facts. The solution is deployed in more than 700 plants in over 30 countries.

Further reading

• ISO 9001:2026 : les nouvelles exigences qui vont changer votre façon de piloter la qualité (Qualiblog, in French)
• Quality Rate OEE: How to Calculate, Measure and Improve This Critical Manufacturing Metric
• Performance tracking: 5 measurement pitfalls that distort decisions

FAQ

Does ISO 9001:2026 require tracking machine downtime? No. The standard does not prescribe specific data. Downtime and scrap are one way among others to demonstrate the link between finding, decision and result in a production setting.

Should you wait until the end of the transition period? According to Qualiblog, certified organizations have until 30 September 2029. Building a downtime and scrap history now gives you before and after comparisons on audit day.

What data should go to management review? Few data points, but tied to decisions: downtime and scrap trends on critical equipment, the actions decided and the check of their effect at the next review.