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In the competitive landscape of fiber optic manufacturing, optimizing operational efficiency is paramount for success. A leading fiber optic manufacturer in USA faced numerous challenges in their manufacturing processes, including data silos, manual measurement methods, high setup times, and inefficient coordination.

To address these issues, they embarked on a digital transformation journey leveraging Industrial Internet of Things (IIoT) technologies.

Challenges Faced

1. Data Silos: The presence of several OEM systems and vendor-driven applications led to fragmented data storage, hindering holistic analysis.

2. Manual Measurement: Manual measurement of Overall Equipment Effectiveness (OEE) resulted in inaccuracies and inefficiencies.

3. High Setup Times: Lengthy setup times during SKU changeovers reduced operational agility and productivity.

4. Isolated CTQ Parameters: Critical-To-Quality (CTQ) parameters were scattered across isolated systems, making analysis challenging.

5. Manual Scheduling: Manual scheduling processes led to poor coordination and suboptimal resource utilization.

6. Lack of Downtime Tracking: Absence of downtime reason tracking and duration analysis prevented proactive maintenance and optimization efforts.

Solution implemented

The company opted for Ignition as the IIoT platform to integrate over 65 machines from different OEMs. Unified Namespace (UNS) was built to streamline data accessibility.

Canary Labs Historian was employed to historize time-series data for comprehensive analysis. Key solutions included:

1. Development of an online OEE and downtime tracking system providing real-time insights.

2. Implementation of an alerts and escalation matrix via email and SMS for proactive issue resolution.

3. Deployment of analytics dashboards, live trends, and production reports for informed decision-making.

results achieved

Over the subsequent 6 months post-implementation, the company observed significant improvements:

1. OEE Improvement: OEE surged by 28%, indicating enhanced operational efficiency and machine utilization.

2. Production Consistency: Elimination of material starvation led to consistent factory output, facilitating better production planning.

3. Enhanced Coordination: Digitization of processes improved coordination among subsystems, reducing setup times and enhancing agility.

4. Efficient Maintenance: Quicker and more accurate measurement of Mean Time To Repair (MTTR) and Mean Time Between Failures (MTBF) facilitated proactive maintenance planning.

5. Optimized Parameters: Machine parameters were optimized based on Statistical Process Control (SPC) analysis, enhancing product quality and yield.

ROI Calculation

At the 6-month mark, data for Return on Investment (ROI) calculation was collected. The company realized a total ROI of $400k USD from increased production capacity, improved OEE, and reduced waste, against a $100k USD investment.

Next phase

Buoyed by the success of the initial phase, the company is now focusing on the next phase of digital transformation. This involves integrating the Manufacturing Execution System (MES) with the Enterprise Resource Planning (ERP) system to automate work orders and scheduling processes. Real-time posting of production and consumption data aims to eliminate paper-based workflows and provide business systems with a real-time view of the manufacturing process.


Through strategic integration of IIoT technologies and data-driven approaches, the fiber optic manufacturer successfully addressed key operational challenges, resulting in significant improvements in efficiency, productivity, and quality.

This case study underscores the transformative power of IIoT in modern manufacturing environments, driving operational excellence and sustainable growth.