Assembler AI provides an Operator Vision system that uses a standard overhead camera and existing SOPs to automatically capture step‑level cycle times, idle periods, and variance on manual workstations.
Funding
Funding not disclosed
Founders
Product
Problem
Manual workstations in high‑mix, low‑volume factories lack continuous, objective measurement of how tasks are performed, making it difficult for continuous‑improvement (CI) teams to identify bottlenecks, waiting time, or rework, and for operators to receive timely guidance to improve first‑pass yield.
Solution
Assembler AI’s Operator Vision system uses a standard overhead camera and existing standard operating procedures (SOPs) to automatically capture step‑level cycle times, idle periods, and variance across operators, shifts, and product mixes. The platform continuously analyzes production runs, providing CI leaders with real‑time metrics and actionable insights without the need for stopwatches or manual data entry. Simultaneously, operators receive on‑screen guidance and error flags that help them correct actions during the shift, improving cycle time and reducing scrap. The solution requires only camera installation and SOP upload, with no changes to operator workflow, and becomes operational within two weeks.
Target Audience
Primary customers are continuous‑improvement engineers and production managers in high‑mix, low‑volume manufacturing sectors such as aerospace, automotive, electronics, and medical devices, as well as the operators on manual assembly lines.
Features
- Standard camera installation with no custom hardware or workflow modifications
- Automatic extraction of step‑level cycle times, variance, waiting, and idle time from live video
- Real‑time operator guidance and error flagging displayed on‑site during production
- Continuous analytics dashboard for CI leaders showing metrics by operator, shift, and product mix
- Integration of existing SOPs without rewriting or reformatting
- Elimination of manual stopwatch studies and observer bias