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Is a Changeover Planned Downtime or an Availability Loss? — How the Definition Changes OEE
Whether a changeover (also called a setup) counts as planned downtime or as an availability loss differs from source to source, and because that choice alone changes availability and OEE substantially, changeover time must be tracked as a metric separate from OEE. The "Downtime" entry in the Lean Enterprise Institute (LEI) lexicon classifies changeovers to produce other products as planned downtime, while the Japan Institute of Plant Maintenance (JIPM) classifies setup and adjustment as a stop loss in availability. In an assumed shift (loading time 27,600 s, changeovers 3,000 s, breakdowns 600 s), availability is 87.0 % under the JIPM approach and 97.6 % under a planned-downtime approach that subtracts…
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LFP High-Compaction-Density Conversion and the Calendering Interface: How Nip Pressure and Line Speed Affect Takt Time
Line Changeover Design in the Era of Low-Price ESS Round-3 Bidding — Flexible Assembly Viewed Through Takt Time and OEE
Designing the Merge Point in a 10 GWh Pack-Container Integration Line: Synchronizing Two Upstream Lines and Sizing AGV Fleet from the Powertrac × Sunka Lead Order
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FAT and SAT Differ in More Than Location — How IEC 62381:2024 Defines the Tests
IEC 62381:2024 defines the factory acceptance test (FAT) as an activity to demonstrate that the automation system is in accordance with the specification, typically conducted at the vendor's facility, and the site acceptance test (SAT) as an activity to demonstrate, at the site of the installation, that the installation is in accordance with the applicable standards, codes, specifications, and installation instructions. The two tests differ not only in location but also in what they demonstrate, and the 2024 edition adds the optional factory integration test (FIT) and defines requirements and checklists for the FAT, FIT, SAT, and site integration test (SIT). Loop checks and commissioning lie outside the scope of…
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Edge AI Vision Inspection and Battery-Pack Leak Testing: How Gateway Aggregation Affects Traceability Completeness
Re-Reading the ESS Grid-Interconnection Queue in the Language of Line Balancing
Between the Continuous Solid-Electrolyte Process and the Assembly Line: How Should the Buffer Interface Be Designed?
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If Availability, Performance and Quality Are All 80 %, OEE Is 51.2 % — How to Calculate OEE
OEE (overall equipment effectiveness) is calculated as availability × performance × quality, and the Japan Institute of Plant Maintenance (JIPM) gives the example that when all three factors are 80 %, OEE is 51.2 %. When the three factors are multiplied as JIPM defines them, OEE is organized as "standard (planned) cycle time × number of good units ÷ loading time," that is, the share of loading time spent making good units at the standard speed. In an assumed shift (loading time 27,600 s, standard cycle time 32 s, 690 good units), availability is 90.0 %, performance 90.4 % and quality 98.3 %, giving an OEE of 80.0 %. If…
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Line Changeover Design in the Era of Low-Price ESS Round-3 Bidding — Flexible Assembly Viewed Through Takt Time and OEE
Grid-Forming PCS Mandate Redesigns FAT Takt Time and the BMS-PCS-EMS Interface
Between the Continuous Solid-Electrolyte Process and the Assembly Line: How Should the Buffer Interface Be Designed?
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Don’t Subtract Breakdowns When Calculating Takt Time — Takt Time vs. Cycle Time vs. Lead Time
Takt time is the target production interval obtained by dividing available working time by customer demand, whereas cycle time is the measured time a process actually takes to make one unit. The calculation rule in the workbook published by the Lean Enterprise Institute (LEI) subtracts from shift time planned operator breaks, meetings, cleanups, etc., but not time for unplanned machine downtime, changeovers or other internal problems. Dividing the 27,600 s of available working time per shift obtained under this rule by the demand per shift of 690 units gives a takt time of 40 s. To cover stopped time as well, the measured cycle time must be shorter than takt…
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Edge AI Vision Inspection and Battery-Pack Leak Testing: How Gateway Aggregation Affects Traceability Completeness
