Many factories encounter tricky‑problems: equipment shows no obvious fault‑alarms, raw‑materials come from same supplier, yet one‑batch finished‑goods perform well while next‑batch suffers collapse, under‑drying or poor rehydration. Batch‑to‑batch quality‑swing is hard to trace. Facing such fluctuation without explicit error‑messages, follow the step‑by‑step investigation sequence below.
Step one: check human‑operation factor. Verify operation‑logs from different shifts. Confirm whether spreading‑thickness, loading‑quantity vary among operators; whether pre‑freezing holding‑time is manually shortened; whether inter‑batch cleaning and inspection SOP are strictly followed. Quite a few fluctuations originate from differing shift‑team‑operation‑habits.
Step two: check real‑status of incoming raw‑materials. Even from one purchase‑lot, storage‑condition‑change, partial‑thaw‑refreeze or ripeness‑shift may happen. Sample‑test moisture‑content and sugar‑level for each incoming‑batch and compare physical‑chemical differences across lots.
Step three: export historical equipment‑operation‑curves. Do not judge merely by final‑product result. Retrieve full‑run‑data of every batch: actual achieved pre‑freezing temperature, holding‑duration, real shelf‑temperature fluctuation in sublimation phase, practical vacuum‑trend and real cold‑trap temperature. Compare curve‑difference between good‑batches and defective‑batches and find deviation‑points.
Step four: examine wearing‑parts condition: check slight aging of sealing strips; vacuum‑pump oil status; frost‑accumulation level of cold‑trap whether water‑capturing capacity degrades after successive batches; filter‑clogging status. Gradual‑deterioration of such components will not trigger direct fault‑alarms yet alter actual production‑conditions slowly.
Step five: ambient‑condition factor: workshop temperature shift between day & night; varying heat‑dissipation effect of machine‑room at different hours indirectly changes refrigeration‑unit output.
Compare good batches against abnormal batches following sequence: human‑factor → raw‑material → historical‑operation‑curves → wearing‑parts → environment. Root‑causes for most batch‑fluctuation‑problems can be located. Avoid modifying process‑parameters blindly before fluctuation‑source is identified.
