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Particle > Case Studies > IoT-Driven Data Optimization: A Case Study on Service Thread
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IoT-Driven Data Optimization: A Case Study on Service Thread

 IoT-Driven Data Optimization: A Case Study on Service Thread - IoT ONE Case Study
Technology Category
  • Functional Applications - Computerized Maintenance Management Systems (CMMS)
  • Functional Applications - Manufacturing Execution Systems (MES)
Applicable Industries
  • Electronics
  • Equipment & Machinery
Applicable Functions
  • Maintenance
  • Procurement
Use Cases
  • Additive Manufacturing
  • Digital Thread
  • Hardware Design & Engineering Services
  • System Integration
The Challenge
Service Thread, a leading American manufacturer of commercial thread and yarn, faced significant challenges in monitoring and analyzing their factory performance. With over 3,000 spindles across 115,000ft2 of floor space and 24 different machine types, the company struggled to effectively determine the actual utilization percentage of their factory. The traditional method of frequent and selective in-person inspections of the machines was not only time-consuming but also lacked accuracy. The company was in dire need of a solution that could provide real-time, accurate data on machine utilization to help them make informed business decisions and optimize their operations.
The Customer

Service Thread

About The Customer
Service Thread is a leading American manufacturer of commercial thread and yarn. The company operates a large factory in Laurinburg, NC, which houses over 3,000 spindles across 115,000ft2 of floor space and 24 different machine types. Service Thread is committed to optimizing its operations and was seeking a solution to effectively monitor and analyze its factory performance. The company's goal was to increase efficiencies, reduce costs, and fully optimize their production.
The Solution
Service Thread partnered with Logical Advantage to implement an IoT-based monitoring solution using the Particle Photon. This hardware solution was designed to gather data from the machines’ existing sensors, capable of monitoring 16 spindles simultaneously. The collected data was then transmitted through the Particle Cloud and onto Microsoft’s Azure IoT Hub using Wi-Fi. Logical Advantage also developed a mobile app for spindle sensor provisioning. This IoT solution provided Service Thread with real-time data on machine utilization, enabling them to identify inefficiencies and make informed decisions on equipment purchases, labor allocation, and overall operational optimization.
Operational Impact
  • The IoT solution implemented by Service Thread not only provided valuable data for capital planning but also helped the company make smarter decisions regarding labor, sales, and supply-chain management. The real-time data collected by the IoT devices allowed the company to quickly identify and address issues, reducing downtime and maintenance costs. The solution also provided leading indicators of potential problems, enabling proactive maintenance and further reducing downtime. The IoT solution has proven to be a valuable tool for Service Thread, providing the data needed to maximize their operations and significantly reduce costs.
Quantitative Benefit
  • Service Thread found that their spindle utilization was 15% less than their estimate, providing crucial information for capital planning.
  • Using insights from the IoT solution, Service Thread invested in a $400,000 machine that replaced roughly 75 spindles from an older machine.
  • The IoT solution is estimated to reduce per-spindle operating costs by at least 50%.

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