{"id":39373,"date":"2026-10-20T08:05:10","date_gmt":"2026-10-20T08:05:10","guid":{"rendered":"https:\/\/dev.accevo.com\/blog\/packaging-line-oee-measure-stops-changeovers-speed-loss-and-rejects\/"},"modified":"2026-10-20T08:06:11","modified_gmt":"2026-10-20T08:06:11","slug":"packaging-line-oee","status":"publish","type":"post","link":"https:\/\/accevo.com\/it\/blog\/packaging-line-oee\/","title":{"rendered":"OEE della linea di confezionamento: misurazione di fermi macchina, cambi di produzione, perdite di velocit\u00e0 e scarti"},"content":{"rendered":"

Packaging line OEE turns output, operating time and rejects into a way to locate lost production capacity.<\/strong> To make the number useful, define the line boundary and time policy first, then separate stops and changeovers from reduced speed, micro-stops and quality loss.<\/p>\n

\"AI-generated
Illustrazione generata dall'intelligenza artificiale. Non raffigura una struttura di Accevo n\u00e9 quella di un cliente.<\/figcaption><\/figure>\n

What packaging line OEE measures<\/h2>\n

Overall equipment effectiveness (OEE) combines three ratios: Availability \u00d7 Performance \u00d7 Quality. A common calculation uses run time divided by planned production time for Availability, actual output against the approved ideal rate for Performance, and good output divided by total output for Quality. The familiar formula is explained in the Guida ai fattori OEE<\/a>; ISO 22400-2<\/a> provides a broader framework for manufacturing operations KPIs.<\/p>\n

A line-level score is only comparable when the measured boundary is clear. Decide whether the KPI covers a single machine, a connected packaging line, or a whole production order. If a filler, cartoner, labeler and case packer run at different rates, identify the constraint and state how line output is counted. Do not add machine-level percentages together and call the result line OEE.<\/p>\n

\"OEE
OEE framework: map the score to an event category the team can investigate.<\/figcaption><\/figure>\n

Define planned time, stops and changeovers<\/h2>\n

Write down the production window before measuring. Planned breaks, no-order time, maintenance, cleaning and product changeovers may be treated differently by different sites or reports. Set a rule that fits the question, record it beside the result and apply it consistently. If changeovers are included in planned production time, they reduce Availability; if excluded, they will not appear as OEE loss. Either choice can be useful, but mixing the two makes comparisons misleading.<\/p>\n

For a packaging line, use event records to distinguish breakdowns, waiting for materials, setup and format change, line clearance, quality hold and other approved categories. Keep the smallest useful set of reason codes. A long list that operators cannot apply consistently creates false precision.<\/p>\n

Do not treat every machine stop as a line stop. A brief interruption at one machine may be absorbed by accumulation or buffering; the same event can stop the constraint machine and halt the whole line. Capture the event at the level needed to explain lost good output.<\/p>\n

Separate speed loss and micro-stops<\/h2>\n

Performance loss occurs when production runs below the agreed ideal rate, including slow cycles and short interruptions. On a packaging line, causes can include repeated jams, sensor faults, product feed problems, starved or blocked machines, and speed settings below the rate approved for that product and format.<\/p>\n

Use a product- and format-specific ideal rate with a documented source. A single maximum speed copied from a machine nameplate can distort the result if the real constraint is downstream or if the run uses a different container, label or pack configuration. Check that counters share the same unit and time basis.<\/p>\n

Set a consistent threshold for recording small stops, and review events just below the threshold as well. Otherwise, the largest number of short interruptions may disappear from the loss report. Combine machine states with operator reason codes where human context is needed, and mark unknown events as unknown until the cause is verified.<\/p>\n

Make reject and rework rules explicit<\/h2>\n

Quality measures good units against total units. Define how the calculation treats rejects, rework, start-up scrap, samples and units placed on hold. Use a consistent counting point: for example, accepted saleable packs at the end of the defined line boundary. A count from the cartoner cannot be compared with good cases leaving the packer unless the conversion and reject rules are clear.<\/p>\n

For pharmaceutical packaging, the OEE target should not override approved checks. A faster changeover is useful only when the required cleaning, line-clearance, label reconciliation and quality verification still happen under the site’s procedures. Track the duration and source of changeover losses so improvement work can focus on preparation and repeatable steps without skipping controls.<\/p>\n

Illustrative packaging line loss example<\/h2>\n

The graph below shows an example arithmetic bridge from planned time to good productive time. It is illustrative only, not Accevo or customer production data: a 480-minute planned window loses 72 minutes to stops and changeovers, 49 minutes of equivalent output to speed and micro-stops, and about 7 minutes of equivalent good output to rejects. That leaves approximately 352 minutes of good productive time, or 73.3% of planned time. Your own OEE factor calculation should use measured run time, total count and good count.<\/p>\n

\"Illustrative
Illustrative OEE loss bridge. Values are an example only and are not Accevo or customer production data.<\/figcaption><\/figure>\n

Use the loss breakdown to choose an action<\/h2>\n
    \n
  1. Confirm that the time window, line boundary, unit and ideal rate are correct.<\/li>\n
  2. Rank losses by lost time or lost good output, not by event count alone.<\/li>\n
  3. Check the top loss against the underlying machine events and operator notes.<\/li>\n
  4. Agree one corrective action and an owner; keep product quality checks intact.<\/li>\n
  5. Review the same KPI and event definitions after the change.<\/li>\n<\/ol>\n

    A single OEE percentage does not tell a team what to change. The event history, rate assumptions and quality rules explain why it moved. See Accevo’s OEE performance monitoring<\/a>, its micro-stops monitoring<\/a> and the guide to MES integration for packaging lines<\/a>. For a batch-process example of the same factors, read how to calculate OEE for pharmaceutical batch processes<\/a>.<\/p>\n

    Packaging line OEE questions<\/h2>\n

    Should changeover time count as OEE downtime?<\/h3>\n

    That depends on the planned-production-time rule used for the KPI. Document whether included changeovers reduce Availability, and avoid comparing results calculated with different denominator rules.<\/p>\n

    Are micro-stops Availability or Performance loss?<\/h3>\n

    Use the site’s chosen event threshold and calculation method. Many teams treat small stops as Performance loss, but consistency and event visibility matter more than the label.<\/p>\n

    Can I compare OEE between products or lines?<\/h3>\n

    Only when the boundary, time policy, ideal rates, units and good-output rules are compatible. Otherwise, compare each product or line with its own consistent baseline.<\/p>\n

    What should improve first?<\/h3>\n

    Start with the largest verified source of lost good output. A Pareto by time or equivalent units helps distinguish a few long stops from frequent short interruptions, recurring speed loss or rejects.<\/p>","protected":false},"excerpt":{"rendered":"

    Learn how to calculate packaging line OEE and separate stop, changeover, speed and reject losses, with practical rules for reliable comparisons.<\/p>","protected":false},"author":2,"featured_media":39365,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"wpai_generated_summary":"","footnotes":""},"categories":[30],"tags":[],"class_list":["post-39373","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"_links":{"self":[{"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/posts\/39373","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/comments?post=39373"}],"version-history":[{"count":1,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/posts\/39373\/revisions"}],"predecessor-version":[{"id":39374,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/posts\/39373\/revisions\/39374"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/media\/39365"}],"wp:attachment":[{"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/media?parent=39373"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/categories?post=39373"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/accevo.com\/it\/wp-json\/wp\/v2\/tags?post=39373"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}