slower-forklifts-with-the-same-performance
title: "Slower forklifts with the same performance" description: "A white-goods hall cut average forklift speed from 15 km/h to 6 km/h while holding performance. Live paths plus pull dispatch turned a safety rule into measured impact, not a throughput argument." slug: "wiki/slower-forklifts-with-the-same-performance" type: wiki format: html section: "logistics-optimization" sectionTitle: "Logistics Optimization" topic: "impact" topicTitle: "Impact" readTime: "5 min read" order: 7
Average speed sits at 15 km/h (about 9 mph) because everyone believes slower means late. Safety audits still walk the hall with clipboards. Nobody has a continuous trail that proves whether a lower speed cost throughput or only cut risk.
Why speed policy dies in the meeting
Without path evidence, a speed cut sounds like a service cut. Drivers and supervisors argue from memory. Insurance and legal teams ask for records that do not exist. Manual audits sample a moment. They do not show a shift of forklift motion across 55,000 m² (about 592,000 ft²).
Live logistics tracking changes that debate. Medium-precision location around 1–3 m (3–10 ft) is enough to rebuild corridors and dwell for a speed review. twinzo carries that view under internal logistics optimization. When the same plant also runs pull dispatch, drivers are not forced to chase radio jobs at the old pace.
What the RTLS case measured
A documented 55,000 m² (about 592,000 ft²) white-goods plant invested €50,000 in logistics optimization with RTLS. Direct communication between logistics and production, combined with MES data, helped avoid unnecessary drives. Average speed fell from 15 km/h (about 9 mph) to 6 km/h (about 4 mph), about −60%, while performance held. An audit trail stayed available the whole time.
The slide labels the saving as priceless. That is honest for human safety impact. Do not invent an OPEX euro figure the case did not publish. Path context for the same evidence class sits under real travel paths on the floor.
How pull on the same hall removes the throughput fight
On the same white-goods footprint, documented AOS (commonly known as FGS) cut unnecessary patrolling by about 95%, recovered about +20 minutes of production daily, eliminated micro-stoppages, and balanced driver workload. Investment was €100,000. First-year increased production value was €5,080,000.
When jobs are claimable and drivers stop circulating, a lower average speed is no longer competing with empty search. Customers who run both layers treat speed compliance and service level as one story. Production minutes sit under twenty minutes of production back every day. Congestion that still forces risky shortcuts sits under congestion on shared aisles from the track.
What the audit trail feeds beyond safety
Stored paths become part of the spatially oriented dataset. Management can reopen a disputed hour under historical replay. Correlation and causality analytics can later ask whether speed breaches cluster in the same choke points that precede delays. Safety and continuous improvement read the same record.
How teams decide the speed rule is enforceable
1. Capture average and peak speeds on one normal peak shift before changing policy - Get a baseline, not a slogan.
2. Pair the speed pilot with pull on the noisiest loop - If drivers still hunt by radio, they will push the old pace.
3. Keep performance KPIs on the same dashboard as speed - The white-goods case held performance at 6 km/h (about 4 mph).
4. Store the trail for audit and later pattern work - Capability depth sits on the features overview. Rollout shape is under pricing.
Get in touch if you want to walk a speed-and-service review on your own facility model before the next safety meeting.