Manufacturing & assembling communication devices for motor vehicles
from Japanese
The client is a Japanese FDI manufacturer specializing in the production and assembly of communication devices and electronic components for the automotive industry, operating a factory in Dong Van II Industrial Park, Ninh Binh. The facility runs large-scale manufacturing operations with more than 50 assembly lines and over 100 injection molding machines, supporting high-volume, continuous production under strict technical requirements. As a member of a leading Japanese industrial group with a global manufacturing footprint, the client serves as a Tier-1 supplier in the automotive electronics supply chain, directly providing critical communication components to international automakers. Operating under Japanese manufacturing discipline and stringent international quality standards, the factory’s scale, operational complexity, and real-time control requirements clearly reflect the client’s strong market position and significant influence within the global automotive electronics manufacturing sector.
Ensuring stable cycle time and consistent throughput across multi-stage production lines.
Achieving real-time visibility into line performance, deviations, and bottlenecks.
Reducing reliance on manual logging and fragmented Excel-based reporting.
Standardizing production data for accurate, cross-line performance evaluation.
Detecting abnormalities early to prevent delays and protect delivery commitments.
Supporting high-volume operations with a scalable and reliable monitoring system.
Before implementing NxMES, the client faced multiple operational constraints that limited line efficiency and hindered daily production management:
Line balancing was inconsistent, causing fluctuating output and unstable cycle time across consecutive processes.
Production data was scattered and manually recorded, resulting in delays, inaccuracies, and difficulty consolidating reports.
Supervisors lacked real-time visibility, making it challenging to identify bottlenecks or respond quickly to deviations.
Manpower and machine capacity were underutilized due to a lack of accurate, timely performance insights.
Cycle time deviations were detected too late, leading to inefficiencies, extended lead time, and increased delivery pressure.
To overcome these challenges, NxMES was implemented as an end-to-end Smart Manufacturing Monitoring System, enabling real-time visibility, standardized production data, and proactive operational control across all assembly lines. The platform digitized key production processes and provided the factory with unified insights to stabilize cycle time, optimize line balancing, and improve overall throughput.
Real-time Cycle Monitoring: Supervisors could track cycle time at every process step, identify deviations early, and react immediately to performance drops.
Automated Data Capture: Data from terminals, workstations, and sensors was collected automatically, removing manual input and eliminating errors from paper- or Excel-based reporting.
Bottleneck & Deviation Detection: The system highlighted cycle delays and imbalance points across consecutive steps, enabling quick corrective actions to maintain stable throughput.
Digital Production Dashboards: Output, cycle time trends, and performance indicators were displayed clearly on centralized dashboards, supporting faster and more accurate decision-making.
Line Balancing Optimization: NxMES provided real-time insights that allowed supervisors to allocate manpower, adjust workloads, and rebalance lines to improve flow efficiency.
Unified Factory Analytics: Aggregated data from 50+ assembly lines and 100+ molding machines enabled management to compare line performance and drive continuous improvement.
50+
Production lines digitized
100+
Machines connected & monitored
9%
Cycle time reduction after 3 months
Improved Production Visibility: Real-time monitoring provided complete visibility into cycle time, output, and deviations across all process steps. Managers gained accurate, consolidated data to evaluate performance and make faster operational decisions.
Cycle Time Reduction & Efficiency Gain: After three months of deployment, the factory achieved a 9% reduction in cycle time, resulting in more stable throughput, fewer delays between steps, and smoother coordination across shifts.
Optimized Resource Utilization: Accurate, timely data enabled supervisors to adjust workforce allocation and machine loads proactively. This improved productivity, reduced unnecessary overtime, and strengthened on-time delivery performance.
Data Accuracy & Operational Stability: Automated data capture eliminated manual logging and minimized inconsistencies. With reliable data and immediate feedback, the factory improved daily operational control and built a stronger foundation for long-term continuous improvement.