{"id":155983,"date":"2026-10-29T09:46:36","date_gmt":"2026-10-29T09:46:36","guid":{"rendered":"https:\/\/teeptrak.com\/injection-press-downtime-cycle-time-tracking\/"},"modified":"2026-10-29T09:46:36","modified_gmt":"2026-10-29T09:46:36","slug":"injection-press-downtime-cycle-time-tracking","status":"publish","type":"post","link":"https:\/\/teeptrak.com\/en\/injection-press-downtime-cycle-time-tracking\/","title":{"rendered":"Injection molding presses: tracking downtime and cycle time drift in real time"},"content":{"rendered":"
This article is for production, maintenance and continuous improvement managers in plastic injection molding shops, and for plant managers running a fleet of presses. Your CMMS schedules preventive work and keeps the breakdown history, but your presses also lose time in stops lasting a few seconds and in cycles that creep longer without anyone logging it. It explains how to measure those losses in real time, press by press and mold by mold, and how to connect them to the work of maintenance.<\/p>\n
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In short<\/div>\n
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A CMMS documents declared stops and organizes maintenance.<\/li>\n
Micro-stops and cycle time drift are almost never declared.<\/li>\n
A reference cycle per mold and automatic measurement make them visible.<\/li>\n
Maintenance gets dated facts, and the history stays in the CMMS.<\/li>\n<\/ul>\n<\/div>\n
What the CMMS documents, and what it does not see<\/h2>\n
What automatic measurement shows<\/th>\n<\/tr>\n<\/thead>\n
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Micro-stops<\/td>\n
Part stuck in the cavity, sprue not ejected, pick-and-place robot fault, alarm reset at the control panel<\/td>\n
Each stop lasts from a few seconds to a minute; the operator restarts without opening a request<\/td>\n
Their count and cumulative duration by shift, by mold and by hour<\/td>\n<\/tr>\n
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Cycle time drift<\/td>\n
Cooling or hold time extended after an adjustment, press running below the rate on the setup sheet<\/td>\n
The press is producing, no stop appears, the loss is spread over the whole day<\/td>\n
The gap between actual and reference cycle, and when it started<\/td>\n<\/tr>\n
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Restart after a mold change<\/td>\n
Heat-up, purging, first parts scrapped, setting tweaks<\/td>\n
The changeover is logged, not the stabilization phase that follows<\/td>\n
The real time between the press stopping and its return to reference rate<\/td>\n<\/tr>\n
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Waiting on auxiliaries<\/td>\n
Material not dry enough, temperature control unit off setpoint, empty hopper<\/td>\n
The stop is attributed to the press, or not attributed at all<\/td>\n
Repeated stops at the same hours or on the same molds, pointing to the asset at fault<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Taken one by one, these losses look negligible. For example, a press whose cycle goes from 30 to 32 seconds makes about 6% fewer parts, all day long, without a single stop being recorded.<\/p>\n<\/figure>\n
Step-by-step method to track stops and cycles on a press<\/h2>\n
Test the method on one or two presses, ideally the ones running the most heavily loaded molds, before extending it to the whole fleet.<\/p>\n
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Set a reference cycle time for each press and mold pair.<\/strong> It comes from the approved setup sheet, not from the observed average: an average already includes the drift you are trying to see.<\/li>\n
Define the micro-stop threshold.<\/strong> Beyond a given time without a cycle, the press is considered stopped. Write the threshold down, apply it to every shift and do not change it again.<\/li>\n
Capture the cycle automatically.<\/strong> One signal per cycle, for example the mold opening, is enough to rebuild the actual rate, stops and micro-stops across all shifts, nights and weekends included.<\/li>\n
Qualify long stops when they happen.<\/strong> The operator enters the reason at the press, using the same breakdown as the CMMS: press, mold, auxiliary. Measurement and maintenance then speak the same language.<\/li>\n
Review three indicators every week.<\/strong> The gap between actual and reference cycle, the number of micro-stops per shift, the downtime Pareto by mold. A mold that climbs this Pareto from one week to the next deserves a look before its next run.<\/li>\n
Hand over to maintenance what belongs to maintenance.<\/strong> Cycle drift linked to cooling, ejection micro-stops rising on one mold: the technician opens the work request in the CMMS, and the asset history stays complete.<\/li>\n<\/ol>\n
Measurement and CMMS: who does what<\/h2>\n
The two do not overlap; they answer each other. The CMMS organizes upkeep: what, when, with which parts and against which history. Automatic measurement shows how the press actually used its time: producing, slowing down, stopped. In practice:<\/p>\n
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The cycle counter becomes reliable.<\/strong> Preventive work triggered by cycle count is only as accurate as the meter reading. An automatic cycle count per mold gives the technician a real value to enter rather than an estimate.<\/li>\n
Stop durations are measured, not reconstructed.<\/strong> The start and end of a long stop are timestamped, so the duration entered in the CMMS rests on a fact, and reliability indicators improve.<\/li>\n
Weak signals surface earlier.<\/strong> For example, ejection micro-stops rising week after week on the same mold point to a check of the ejector pins or vents before an outright failure.<\/li>\n
The effect of an intervention can be checked.<\/strong> After maintenance, does the press return to its reference cycle? The curve shows it from the next shift.<\/li>\n<\/ul>\n
Where TEEPTRAK fits: measuring, not planning maintenance<\/h2>\n
TEEPTRAK measures OEE, downtime and micro-stops on each press in real time, along with the actual rate compared to the reference rate. A module wired into the electrical cabinet and a sensor at the edge of the line take about one hour to install per machine, with no connection to the press PLC, and OEE is available within 48 hours. Every stop is timestamped with its duration, then qualified by the operator. TEEPTRAK is neither a CMMS nor an MES: it does not schedule preventive work, manage spare parts or run production orders. It provides the measurement of production time that production and maintenance can both rely on. It is used in more than 700 plants in over 30 countries, with on average 30% fewer unplanned stops.<\/p>\n
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