Strategy & Ops
Facts & Figures
six
opportunity
figures
In avoidable losses identified through a VA/NVA observation of seat installation
71.8%
RATE
USAGE
On AOS across all 3 production lines within six months over a rollout that had only reached one
3
MONTHS
DEPLOYMENT
To transfer a full 40-hour production weekly shift to a new robot equipment
57%
of target
in 5 months
Reached five months into a twelve-month APSYS maturity evaluation, up from 34%, across 7 of 11 EPU managers
Case Studies
Ran a VA/NVA observation of a seat-installation workstation to document losses and build the case for bringing in outside teams to fix them. Diagnosed the process on the floor, classified time as value-added or not, and calculated losses from the data provided, then presented findings to project and industrialization managers. Found ninety-five percent of observed time non-value-added, with six figures already lost and a further six figures identified as avoidable. Official analysis, plan, and results were handed off to management, who scheduled a workshop and a site visit from the outside engineering team to act on the findings.
Took over the facilitation of a site-wide AOS rollout that had only reached one of three production lines. Supported the key users, escalated blockers, managed the change, and mitigated resistance to bring the remaining lines on board. Onboarded all three lines over six months, with only specific resistance cases left to manage.
Supported readiness and the production transfer onto a new robot. Coordinated across teams, tracked critical points, and resolved blockers. The first full shift transfer was completed within three months, with a second now underway.
Coordinated and forecasted the production deployment of the APSYS Wave 22 yearly maturity roadmap. Managed monthly follow-ups and pushed for management engagement, which stayed inconsistent. Handover for self-assessment was prepared after the score had climbed well past its starting point, with the evaluation continuing after.
Took the worldwide APSYS cross-training model and automated it in two ways: color-coding to show managers where training coverage was weakest, and a full line view built by standardizing data entry across every post so Power Pivot/Query could aggregate it consistently. Entered the required training movements for each post across the complete line to make that standardization work. The result was a color-coded, line-wide view that showed exactly where training gaps were putting the line at risk.
Assigned to support a logistics flow for a new mirror zone under the logistics manager's lead, but found at kickoff that the groundwork, task sequencing, line balancing, and production zone implementation, was still missing, with departments working independently and no coordination across stakeholders. Mapped the gaps, had other departments report that work directly to her, sequenced the work needed, then proposed taking over coordination of the whole effort since no one had been assigned that role, a proposal accepted on the spot. Reached a working production zone with reduced takt time despite robot issues along the way, though the mirror zone itself was set aside after the logistics manager left.
Case studies soon available
Additional initiatives in root-cause problem-solving, process rollout coordination, and culture & engagement programming, currently in progress.