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Use cases

What questions is Qynetic designed to answer?

These scenarios show the questions Qynetic is designed to answer and how its modules work together. They are illustrative design scenarios, not customer case studies.

  1. 01

    A dimension is drifting toward its upper limit

    “Is dimensional drift related to tool wear?”

    A Ø3.25 mm characteristic on one turning machine is still within tolerance, but the individual values are creeping upward. Short-term Cpk still looks healthy; the long-term index is falling.

    1. 1Quality computes Cpk and Ppk from the measurement history and sees the widening gap, which signals a moving mean rather than random scatter.
    2. 2Tool Manager shows that the drift lines up with the cutting time accumulated on one tool since its last change.
    3. 3Factory Director combines both into one recommendation: investigate the tool before the next inspection cycle, with the measurements as evidence and a confidence value.

    → The engineer sees the issue before scrap appears and starts from a probable cause instead of a blank page.

    QualityTool ManagerFactory Director

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

  2. 02

    A tool replacement could share a planned stop

    “Can the tool change coincide with the changeover?”

    A tool is predicted to reach the end of its useful life during the current production campaign, and a product changeover is already planned 43 minutes from now.

    1. 1Tool Manager estimates remaining useful life from process behaviour, not just the counter.
    2. 2Planner knows the changeover time and the order dependencies.
    3. 3Factory Director recommends combining the replacement with the changeover, showing the evidence and what it saves.

    → One planned stop replaces a planned stop plus an unplanned one.

    Tool ManagerPlannerFactory Director

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

  3. 03

    OEE is below target and nobody knows why

    “Where is OEE being lost?”

    A site's OEE has been flat for weeks. The dashboard shows the percentage but not what is behind it.

    1. 1OEE normalises machine states and events from different machines into one model.
    2. 2Losses are categorised — setup, tool changes, micro-stops, scrap, inspection delay — and ranked by size.
    3. 3The largest losses are linked to likely causes, for example scrap events that follow drift on a specific process.

    → Improvement work starts with the biggest addressable loss and its probable cause.

    OEEQualityMaintenance

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

  4. 04

    A customer asks which revision was used

    “Which drawing revision and instruction applied to this batch?”

    An audit or a complaint requires proof of exactly which drawing revision, inspection method and instruction were in force when a batch was made.

    1. 1CIM stores revisions as immutable records with effective dates.
    2. 2Every measurement and production record references the revision and instruction active at the time.
    3. 3Factory Memory links article, machine, program, tool and results, so the full history can be assembled.

    → There is no ambiguity: the answer is a query, not an archaeological dig.

    CIMFactory Memory

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

  5. 05

    A small offset correction is needed

    “Can the process safely be recentred?”

    A measured dimension has moved 3 µm from its target and an offset correction would bring it back.

    1. 1A validated algorithm calculates the correction; a simulation checks the predicted effect.
    2. 2The guardian checks absolute bounds, step size, the cumulative change in the time window, machine readiness and data freshness.
    3. 3Within authorised limits it may proceed; outside them it waits for a person with approval permission; outside absolute bounds it is rejected.

    → Corrections are fast when they are safe and always visible and attributable when they are not.

    APCQualityFactory Director

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

  6. 06

    Maintenance could use planned downtime

    “Can maintenance coincide with planned downtime?”

    A machine shows early signs of a condition that will need service soon, and a planned stop is coming up.

    1. 1Maintenance links alarms, failures and condition signals to the machine's history.
    2. 2Planner knows when planned downtime occurs and what depends on the machine.
    3. 3Factory Director proposes placing the work in the planned stop and shows the effect on the schedule.

    → Maintenance happens when it costs the least production.

    MaintenancePlannerFactory Director

    Illustrative scenario. Figures and names are synthetic and used only to explain the design.

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