Powerful Analytics Boosts High-Tech Threat Detection

技术

分析与建模 - 大数据分析
分析与建模 - 预测分析
功能应用 - 制造执行系统 (MES)

适用行业

安全与公共安全

适用功能

产品研发
质量保证

用例

机器状态监测
预测性维护
过程控制与优化
供应链可见性(SCV)

服务

数据科学服务
系统集成
培训

挑战

FLIR Systems needed a way to analyze massive amounts of data within its Explosive Threat Detection business to improve product quality, reduce downtime, and accelerate R&D. The company faced challenges in monitoring incoming parts from suppliers, as any slight variation could have huge consequences. Additionally, the manual analysis of streaming data from multiple systems was time-consuming and inefficient, often taking hours to interpret and translate into usable information.

关于客户

FLIR Systems Inc. is a technology company based in the United States, employing around 2,800 people. The company specializes in the development and manufacturing of high-tech threat detection systems, including handheld devices designed to detect trace levels of explosives. The Explosive Threat Detection business unit at FLIR focuses on ensuring the highest levels of product quality and detection accuracy, which is critical for their operations. The company works with various suppliers to source parts for their highly calibrated technologies, making supply chain monitoring a crucial aspect of their business.

解决方案

FLIR Systems implemented Statistica’s advanced analytics platform to automate the analysis of their manufacturing and testing data. This solution allowed FLIR to detect problems early in the process, reducing downtime by 30 percent and cutting per-unit costs by 50 percent. The platform aggregates and analyzes high volumes of streaming data from internal processes and the supply chain, providing automated alerts and reports to stakeholders. By setting up automated workflows, FLIR can now complete complex processes in minutes, significantly improving productivity and allowing more focus on other critical areas.

运营影响

Increased productivity through task automation, allowing employees to focus on other critical areas.
Improved supply chain monitoring, ensuring top quality and consistency of incoming parts from suppliers.
Enhanced detection accuracy and product quality by reducing variability in production processes.

数量效益