Chapter 22: Case Studies (Automotive, Food, Pharma, Electronics)

Summary: Case studies translate technology into outcomes by showing measurable improvements in uptime, quality, compliance, and cost. They help executives and plant leaders assess feasibility, risk, and the path from pilot to scale. In North America, credible case narratives include regulatory context, change management, and KPIs tied to financial impact. This chapter outlines anonymized, representative scenarios and the architectures that enabled them.

Context and Scope: Four mini-cases spanning discrete (automotive, electronics) and process/hybrid (food, pharma). Each covers business drivers, technical approach, integration, and outcomes.

Key Concepts:

Pilot-to-Scale: Proving value on one line, then templating for other lines/sites.
Closed-Loop Improvement: Data-driven triggers flowing into MES/QMS/CMMS actions.
Template Governance: Standard artifacts that accelerate replication.

Standards and Regulations:

Automotive: IATF 16949, APQP/PPAP for supplier quality.
Food: FSMA, HACCP for food safety.
Pharma: GMP, 21 CFR Part 11 for e-records/e-signatures.
Electronics: IPC standards; strict SPC and traceability expectations.

Architecture/Processes:

Reference: PLC/SCADA → Edge (OPC UA/MQTT) → MES/QMS → Data Platform → ERP/Analytics.
Event-driven actions for deviations, downtime, and quality escapes.
Role-based dashboards for operators, engineers, and managers.

Data and Interoperability:

Harmonized equipment tags and downtime codes.
Work order, BOM, and routing sync between ERP and MES.
SPC and genealogy integrated with QMS for NC/CAPA.

Security and Compliance:

Segmented networks and controlled vendor access.
Audit-ready logs and validated workflows (where applicable).
Backup/DR and change control with approvals.

KPIs and Metrics:

OEE improvement, FPY uplift, scrap reduction.
Unplanned downtime hours and MTTR.
Compliance deviations and CAPA closure time.
Order cycle time and on-time delivery.

Implementation Checklist:

Define case scope, baselines, and success metrics.
Map integrations, data models, and roles.
Execute pilot; collect before/after evidence.
Template solution and rollout plan.
Train users and embed governance.

Common Pitfalls and Mitigations:

Unclear baselines: Measure pre-implementation metrics.
Over-customization: Stick to standards; document justified exceptions.
Weak handover: Provide runbooks and operational ownership.

Automotive (Discrete): Summary: A Tier-1 supplier reduced line stops by 22% using standardized downtime capture and analytics. Approach: OPC UA edge gateway, MES integration for work orders, downtime model harmonization, RCA workflow in QMS. Outcomes: OEE +8 points, FPY +3 points, expedited shipments down 40%.

Food & Beverage (Process): Summary: A beverage plant cut changeover time by 18% via digital work instructions and SMED analysis. Approach: Tablet-based instructions from PLM, MES step enforcement, CIP scheduling integration. Outcomes: Throughput +7%, waste -12%, safety incidents related to changeovers -30%.

Pharma (Hybrid): Summary: A sterile filling line improved batch right-first-time by 5% with in-line SPC and e-records. Approach: Validated QMS, Part 11-compliant MES, historian integration, deviation management. Outcomes: Deviations -25%, CAPA closure time -35%, audit observations zero in follow-up.

Electronics (Discrete/High-Mix): Summary: An EMS increased first-pass yield on SMT by 6% using ML-based inspection triage. Approach: Vision data to data platform; recommendation service for stencil and reflow adjustments; MES recipe management. Outcomes: Rework -20%, throughput +9%, training time for new SKUs -15%.