Evaluate monitoring software against the factory decisions it must support. Start with a production question, trace the numbers back to their source, and test one complete operating scenario. A polished dashboard is useful only when its counts, timing and context are trustworthy enough for that decision.
Start with one decision the team must make
Choose a concrete question: which line is behind its current plan, which stop needs attention, or which work order needs a material check? Specify who needs the answer and how quickly. That becomes the basis for your demonstration instead of a tour through every feature.
Vorne’s production-counter guide distinguishes counts from broader production context such as time, rate and target. Ask a supplier to show how the information needed for your chosen decision is connected, not merely displayed on separate screens.
Use this checklist in the demonstration
| Area | Question to ask | Evidence to request |
|---|---|---|
| Count definitions | What do total, rejected and good output mean here? | Visible calculation and reset/correction rules |
| Factory data sources | How would this exact line supply its data? | A supported collection method and named implementation work |
| Data freshness | What appears when the source stops updating? | Source timestamp, missing-data indication and recovery behavior |
| Operating context | How are product, work order, shift and target attached? | One complete example with consistent identifiers |
| Loss definitions | How are stops, slower running and rejects separated? | Time boundaries, reason rules and metric definitions |
| People and actions | How does an operator observation reach the responsible person? | A demonstrated issue record and ownership workflow |
| History and export | Can we reconstruct this shift later? | Retained events, corrections and a usable export |
| Roles and effort | Who can change the plan, and who maintains the setup? | Role behavior and a documented delivery/support scope |
Mark each item as demonstrated, documented, unconfirmed or unnecessary for your use case. Do not turn a promised roadmap feature into a passed requirement.
Trace the connection from source to screen
Ask the supplier to trace one count or event from the original source through collection, timestamps and the displayed result. Identify where product mappings, rejected counts and shift boundaries are assigned. If an integration is proposed, establish whether it exists for your environment or requires new engineering.
NIST’s smart-manufacturing test-bed report describes the integration of standards and technologies for collecting, curating and reusing manufacturing data. A standards name alone is not proof that your required end-to-end connection has been implemented.
Worked pilot: reconcile a known production window
Use an agreed pilot on one line before judging a broader rollout. Here is a hypothetical acceptance example for one product from 9 to 10 am:
- The approved target is 240 good units.
- The independently checked total count is 240 units.
- Five units fail acceptance, leaving 235 good units.
- A recorded zero-production stop runs from 9:20 to 9:30 am.
Ask the system to retain the target, show total and good counts separately, and report actual accepted output as 235. Target attainment is 235 ÷ 240 × 100 = 97.9%, with five good units below the target. Check that the stop appears at the correct time and duration without silently changing the approved target.
Then review a late correction and an interrupted-data scenario with the supplier in an approved test environment. Confirm that incomplete data is visible and that reconciliation does not duplicate counts. These are proposed pilot checks, not claims about a specific product’s behavior.
Evaluate metric definitions, not just metric names
If OEE is included, ask for its planned-production-time boundary, ideal cycle time, total count and first-pass good count. The OEE calculation guide separates availability, performance and quality. A target-attainment percentage answers a different question and should not be labeled OEE.
Also ask whether a shown forecast is a constant-rate extrapolation, a statistical estimate or another method. Request visible assumptions and behavior when the input is stale. A prediction label does not establish accuracy for your plant or product mix.
Make the delivery scope comparable
Compare the effort needed to reach a usable result: hardware or manual-entry setup, line mapping, product configuration, training, support, retention and export. Ask which responsibilities belong to your team and which are included in the supplier’s scope.
Document unresolved requirements separately from optional capabilities. A successful one-line pilot is evidence for that tested scope; it does not establish behavior on different machines, across sites or under a different product mix. Define the next rollout check before expanding.
Bring the checklist to a product walkthrough
Use your actual operating question and a sample production window when evaluating MagicWand production monitoring. If scheduling or material context is central, also review production planning and material readiness.
Request a MagicWand demo and bring the counts, timing and workflow you want to inspect. Ask for evidence of each requirement rather than assuming a marketing description covers your factory’s implementation.
Practical questions
Should every production monitoring tool include OEE?
It depends on your decision. If OEE is a requirement, evaluate its input definitions and calculation. If the immediate need is target-versus-actual visibility, test that flow explicitly rather than choosing on the length of the metric list.
Does a listed integration prove our line is supported?
No. Confirm the specific source, collection method, mappings and delivery work for your environment, then test the result with known data.
What is a useful pilot success criterion?
A criterion agreed before the test that demonstrates the intended decision with reconciled counts, correct timing and visible incomplete data. Keep the conclusion limited to the tested scope.
Sources and definitions
The linked sources support the manufacturing definitions. The checklist, worked examples and recommendations are MagicWand’s editorial guidance.
SEE THE PRODUCT WORKFLOW
Bring this question to your demo.
We’ll review your current production process, demonstrate the relevant MagicWand views and discuss data requirements. Screenshots use demo data; examples are not customer results.
Request a monitoring demo ↗Your email app opens with a short request you can edit. You can also email founders@magikwand.in.