Bottling and Canning Line KPIs: Benchmarks and How to Measure Them
The KPIs that run a packaging line, from filler OEE and line efficiency to loss, giveaway and changeover: how to measure each, what moves it, and which figures have a cited source.
Use these benchmarks as reference points for spotting a gap worth investigating, not as targets. Your own trend, measured the same way run over run, says more about your line than any single published figure.
Every figure shows its basis. A superscript number links to a public source in the Sources list, and the sentence gives that source's context. A figure marked no cited source is kept as originally published because no public source stating it has been verified, so treat it as illustrative.
At a glance
Bottling and canning line KPI benchmarks at a glance
KPI
Typical
Strong
Basis
Filler OEE
Around 65% to 75% (solid but ordinary); 45% to 60% (struggling lines)
Words in parentheses are the original guide's or the source's own labels. The 85% threshold is a cross-industry world-class figure, not a packaging survey1. The 2009 study row covers 725 consumer-goods packaging operations3.
Method: How the figures in this guide are sourced
A figure with a superscript number is stated by the cited source, listed under Sources with its publisher, location in the document and access date. A figure marked no cited source is kept exactly as originally published because no public source stating it has been verified. It is illustrative, not measured industry data. Worked examples show arithmetic only and are not benchmarks.
Filler OEE
Filler OEE is the headline KPI, and the spread between world-class and typical is wide. High-speed beverage lines that are run well hold filler OEE at 85% or better1, 2, the cross-industry world-class threshold traced to Nakajima and the Japan Institute of Plant Maintenance.
A solid but ordinary line sits around 65% to 75% no cited source, and struggling lines live in the 45% to 60% range no cited source.
Packaging data gives useful context. In PLC data from 725 consumer-goods packaging operations, collected January to June 2009, top-quartile lines averaged 82% OEE, the middle half 54.9%, and the lowest performers 29%3. The single best plant in that study reached 90.6%3.
Because OEE is availability times performance times quality, decompose it before you judge it. Many lines carry 70%+ availability but bleed performance down to 80% through slow-cycling and minor stops no cited source. In the 2009 study, even top-quartile lines were running only 82.8% of scheduled time, yet produced at nearly 100% performance while running3.
How to measure
Multiply availability, performance, and quality for the filler.
Track the three factors weekly, not just the blended number.
Set the improvement target on whichever factor is furthest below its own benchmark.
What moves it
Minor stops and slow cycling, which drag performance.
Breakdowns and changeovers, which drag availability.
Rejects at the filler, which drag quality.
Compare filled containers with scheduled containers using the Fill Rate calculator.
Line efficiency
Line efficiency, measured across the whole line rather than the filler alone, benchmarks a notch below filler OEE because it absorbs every downstream loss. World-class packaging line efficiency runs 90% to 95% no cited source, and a typical line runs 75% to 85% no cited source.
Anything below 70% signals a chronic bottleneck or staffing problem no cited source. The gap between filler OEE and line efficiency is itself diagnostic, so chase the difference to the constraint machine.
For example, if the filler shows 82% but the line delivers 68%, the 14 point spread is sitting in the labeler, case packer, accumulation, or palletizer.
How to measure
Count good containers packed at the end of the line, not at the filler.
Divide by the rated capacity of the line over the same scheduled time.
Trend the spread between filler OEE and line efficiency.
Loss and quality KPIs should be small and stable. Container loss on glass typically targets 1.0% to 1.5% no cited source, with world-class glass lines under 0.8% no cited source. Cans are generally tighter at 0.3% to 0.7% because they handle better no cited source.
Pack-out rate is the share of filled containers that become packed finished goods. It should sit at 97% to 99% on a healthy line no cited source; dropping below 96% usually points at case packer feed, glue, or accumulation faults rather than the filler no cited source.
How to measure
Measure container loss against empties issued.
Measure pack-out against filled containers available.
Trend both run over run rather than reacting to a single bad shift.
What moves it
Container handling, where glass is less forgiving than cans.
Fill accuracy and giveaway are the quality KPIs finance cares about most. Well-controlled fillers hold net content with a standard deviation tight enough to run a target overfill of roughly 0.5% to 1.5% above declared volume no cited source. Loose fillers drift to 2% to 4% giveaway no cited source, which is pure product cost.
How much you give away is your own decision. In the U.S., NIST Handbook 133 requires the average net contents of a lot to at least equal the declared quantity and limits individual shortfalls, but it sets no limit on overfilling4.
The practical benchmark is giveaway per 1,000 containers converted to dollars. For example, even 1.5 cents of product per container across a shift of 48,000 units is over 700 dollars a shift.
How to measure
Express giveaway as fill above declared volume, as a share of declared volume.
Convert giveaway per 1,000 containers to dollars.
Treat a rising giveaway line as a filler valve or checkweighter alarm, not an accounting rounding item.
What moves it
Filler valve condition.
Checkweighter feedback.
A tighter fill spread, which lets you lower the target overfill.
Changeover and CIP time
Changeover and clean-in-place (CIP) time separate flexible lines from rigid ones. World-class beverage changeovers, size or flavor, land in the 20 to 45 minute range using SMED discipline no cited source. Typical lines take 60 to 120 minutes no cited source, and allergen or full CIP changeovers stretch to 2 to 4 hours no cited source.
The benchmark to watch is changeover as a share of scheduled time. Keep it under 10% on a multi-SKU line no cited source, and treat anything above 20% as lost capacity you are paying for no cited source.
Single-minute exchange of die (SMED), the method behind fast changeovers, sets its target at single-digit minutes, less than 10 minutes, by converting setup work into steps done while the line still runs5.
How to measure
Time each changeover from the last good container to the first good container at rate.
Report changeover hours as a share of scheduled time.
Log sanitation and CIP windows separately from size and flavor changes.
What moves it
Internal steps moved outside the stop.
Parts and materials staged before the stop.
Steps run in parallel instead of in sequence.
Realistic sanitation windows reserved in the schedule.
Line speed and labor productivity
Speed and staffing benchmarks put the rate KPIs in context. Your standard speed is the denominator behind performance, so it must reflect the actual rated speed of the constraint machine, not the filler nameplate.
Line speed by line type (CPM is containers per minute)
Filler ratings are manufacturer maximums for one machine; running line speeds are lower6, 7.
Labor benchmarks track cases per labor hour. A lean high-speed line delivers 800 to 1,500 cases per labor hour no cited source, while a manual or heavily hand-packed line may sit at 100 to 300 no cited source. Compare against lines of similar automation before concluding a crew is over or under strength.
How to measure
Set standard speed from the constraint machine's actual rated speed.
Divide cases produced by labor hours on the line.
Group lines by automation level before comparing them.
Improve the KPIs in the right order: stabilize before you accelerate. Attack minor stops and short interruptions first, because they usually cost more OEE than the visible big breakdowns and they hide the true speed ceiling.
The 2009 packaging study shows the scale. The average line had 8.6 minor stops an hour, each lasting 10 minutes or less, which is about one every 7 minutes; top-quartile lines averaged 2.2 an hour and the lowest performers 17.83.
Then tighten fill control to pull giveaway toward the 0.5% to 1.5% band no cited source, and run SMED to move changeover under 10% of scheduled time no cited source. Finally, balance line speeds so the filler is neither starved nor blocked by the labeler and case packer.
Measure each lever with the matching calculator. Hold the gains with a weekly review rather than a one-time project.
How to build your own baseline
Write down each KPI's definition and denominator, and keep them fixed.
Collect several months of data per line before you set a target.
Compare against your own trend first and published ranges second.
Record what changed on the line whenever a KPI moves.
Sources
Anatomization of the overall equipment effectiveness (OEE) for various machines in a tool and die shop. Journal of Intelligent Manufacturing and Special Equipment, Vol. 3 No. 1, pp. 97-105 (Emerald, CC BY 4.0), DOI 10.1108/JIMSE-01-2022-0004. published 2022. p. 101 (PDF p. 5): sentence "Seiichi Nakajima included the above four “world-class” numbers." and Table 1 "The world-class OEE factor"; p. 103 (PDF p. 7): "worldwide threshold of >85% set by the Japan Institute of Plant Maintenance (JIPM)". Accessed September 30, 2026.
World-Class OEE: Set Targets To Drive Improvement. Vorne Industries (OEE.com). Sections 'What Is World-Class OEE?', 'TPM and World-Class OEE', 'Some Perspective on World-Class OEE'. Accessed September 30, 2026.
Innofill Glass DPG bottle filler (product page). KHS GmbH (filling-equipment manufacturer). Product description, output statement (the KHS beer-equipment listing page shows up to 80,000 bottles/h for the same machine; the detail page figure is used). Accessed September 30, 2026.