Mill Operations & Industrial Engineering
Sets the reorder point for a discrete spare from an exact Poisson model of demand during the lead time, compares the policy service level against the economically optimal one derived by marginal analysis, and reports what the gap between them costs a year.
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Mill Operations & Industrial Engineering
Splits annual quality spend into the four ISO 9004 categories, expresses the total as a share of turnover, and reports the diagnostic ratios – appraisal against prevention, prevention against failure, external against internal – then sizes the saving available from rebalancing towards prevention.
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Mill Operations & Industrial Engineering
Multiplies stage-by-stage first-pass yields through a spinning to finishing chain into a rolled throughput yield, compares it against the final yield that rework achieves, and sizes the hidden factory – the units that only shipped because they were processed twice.
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Mill Operations & Industrial Engineering
Builds Shewhart control limits from baseline subgroup data using the published d2 and d3 constants, reproducing A2, D3, D4, B5 and B6 exactly, names the chart the subgroup size demands, and reports how many subgroups the chart needs to catch a stated shift and how much wider the limits would be if the overall standard deviation were used instead.
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Mill Operations & Industrial Engineering
Loads one fabric order against the machine hours three work centres actually offer inside the due-date window: percentage load at weaving, dyeing and finishing, which centre binds, the schedule slip in days, the machine hours short at the constraint, the quantity that genuinely fits the window and the whole dyeing batches the order mass forces.
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Mill Operations & Industrial Engineering
Separates short-term from long-term capability on any measured characteristic: estimates the within-subgroup standard deviation from the mean subgroup range as Rbar / d2, computes Cp and Cpk against it, computes Pp and Ppk against the overall standard deviation of every reading, reports the gap between the two pairs, the expected nonconforming rate in ppm and a lower confidence bound on Cpk.
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Mill Operations & Industrial Engineering
Finds the age-replacement interval that minimises long-run maintenance cost per operating hour for a Weibull-distributed wear-out failure, compares it against your current interval and against running to failure, and reports the annual saving and the unplanned stops avoided across the fleet.
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Mill Operations & Industrial Engineering
Multiplies the fan-in of every blending step from bale laydown to cut lay to show how much finished product one contaminated lot implicates, converts that mass into units and cartons, and contrasts the pull a complete record chain permits against the whole shipping window a broken chain forces you to quarantine.
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Mill Operations & Industrial Engineering
Brings the electricity, steam, direct-fired gas and compressed air meters onto one kWh basis, converts metered steam back to the fuel that raised it so the boiler house and the steam mains sit inside the boundary, then allocates the site total across saleable output, scrapped output and standby hours to give an ISO 50001 energy performance indicator per good kilogram and per good metre.
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Mill Operations & Industrial Engineering
Tests a CAPA closure against the sampling error of its own verification window: baseline and verified nonconformity rates, the one-sided confidence limit on the post-action rate, the reduction that limit actually defends, the sample size and elapsed days needed to prove the closure target, and the payback booked at the proven rate rather than the observed one.
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