Edscha Automotive’s Michigan plant now runs on metrics and movement that bear Abel Carrasco’s fingerprints. Production stabilized after he arrived in 2023, overallEdscha Automotive’s Michigan plant now runs on metrics and movement that bear Abel Carrasco’s fingerprints. Production stabilized after he arrived in 2023, overall

Systems That Think and People Who Matter

2026/01/05 20:00
4 min read

Edscha Automotive’s Michigan plant now runs on metrics and movement that bear Abel Carrasco’s fingerprints. Production stabilized after he arrived in 2023, overall equipment effectiveness more than doubled, cycle times fell by roughly one third, and scrap dropped sharply on lines he redesigned. Operators moved from repetitive inspection tasks to roles that require judgment and data interpretation. Those shifts lowered incident rates and raised retention across shifts.

Carrasco framed every change as a technical solution with a human result. He installed vision systems to catch microscopic defects and shifted manual inspections to automated checks. He reworked workstations so reach distances and posture angles reduced strain. He added data logging that linked part traceability with operator input. The result proved measurable: fewer stoppages, steadier throughput, and a quieter shop floor that required fewer emergency repairs. “A line that runs cleaner and steadier gives workers confidence to do better work,” he says. “Fix the process, and people notice the difference.”

Transforming Process and People

Carrasco’s work began with methodical observation. He mapped material flow and timed cycles until he could isolate causes of delay and sources of fatigue. Small changes often returned large gains. Adjusting a tool angle cut a station’s cycle time. Rerouting parts eliminated a risky manual transfer. Adding simple guard rails reduced minor injuries that once cost hours in lost time. Each correction fed the next experiment.

He applied a coaching routine known across his teams as kata. Technicians learned to run brief tests, record results, and iterate daily. Operators proposed layout tweaks and tool swaps. Line supervisors gathered those suggestions into rapid pilots that proved concepts in hours rather than weeks. The approach created ownership. Workers who once resisted change began to lead small improvement teams and to teach newcomers the new standards. The plant’s culture shifted toward disciplined attention to small gains, an ethos Carrasco kept visible in morning reviews and on-line boards.

Inventing Stability, Not Replacing People

Before Michigan, Carrasco faced a battered Stabilus piston-rod plant where the NISLIDE coating process caused repeated warranty work. He reorganized the sequence, honed process parameters, and standardized thickness controls. Weekly output climbed from below half a million parts to above one million. Quality failures dropped and a global task force adopted the revised standards. He later redesigned a flocking line so coating applied cleanly, waste fell by 95 percent, and the workspace became quieter and safer.

Those technical wins carried a shared purpose. Automation handled tasks that demand repeatable precision, while trained staff took on diagnostic roles and preventive maintenance. Cameras and sensors handled alignment and torque checks, and technicians learned to read analytic feeds and intervene before a part failed. Senior leaders in Germany and Asia studied the Michigan setup and began copying its inspection protocols and ergonomic standards. The replication confirmed a broader payoff: improved cost control, stronger supplier confidence, and faster launch readiness for new programs.

Where Machines Learn and People Lead

Carrasco measures success in durable gains rather than spikes. He watches error trends fall, not momentary production highs. He watches a technician smile at a small, newly solved problem. He watches fewer overtime calls. Those indicators prove that processes can run with steady cadence while people retain agency over quality.

Edscha Michigan now presents a model where automation and skilled labor reinforce one another. Lines operate with calibrated cycles. Operators oversee dashboards, run targeted interventions, and own local continuous improvement. The plant’s steady performance offers a case that engineering discipline, applied openly and respectfully, can lift output while protecting the people who make it possible.

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