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Qlik > Case Studies > Global Medical Devices Manufacturer Drives Efficiency with Qlik & Cloudera
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Global Medical Devices Manufacturer Drives Efficiency with Qlik & Cloudera

Technology Category
  • Analytics & Modeling - Real Time Analytics
  • Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
  • Healthcare & Hospitals
  • Consumer Goods
Applicable Functions
  • Discrete Manufacturing
  • Quality Assurance
Use Cases
  • Predictive Maintenance
  • Manufacturing System Automation
Services
  • Data Science Services
The Challenge
The global medical devices, pharmaceutical and consumer packaged goods manufacturing company was previously collecting data off-hours and storing it in highly structured data warehouses. The reporting was generally at aggregate levels and done in silos. The structured reports were designed to show what happened by plant, by product, over time. This approach was not efficient and did not provide real-time insights into the manufacturing process.
About The Customer
The customer is a leading global medical devices, pharmaceutical and consumer packaged goods manufacturing company. They are involved in the production of a wide range of products and have a significant presence in the global market. The company is known for its commitment to innovation and quality, and it continually seeks ways to improve its operations and drive efficiency. The company has a vast manufacturing network and deals with a large amount of data from various sources, including machine sensors. The company's goal is to leverage this data to drive efficiency gains and cost savings.
The Solution
The company implemented Qlik and Cloudera to drive efficiency in their operations. They started collecting all data relevant to the use cases from a variety of on-premise and off-premise sources. Critical data is stored in the data lake, while non-critical data is moved directly to Qlik. The quality output is tracked in real-time as products move through the manufacturing process. The data is consumed through self-service exploration and displayed on monitors throughout the factory with standardized reports where needed. This approach allows the company to have real-time insights into their manufacturing process and make informed decisions.
Operational Impact
  • The company was able to track quality output in real-time as products move through the manufacturing process.
  • The data is now consumed through self-service exploration and displayed on monitors throughout the factory with standardized reports where needed.
  • The company was able to correlate data coming from machine sensors and various other sources to drive efficiency gains.
Quantitative Benefit
  • Efficiency gains of between 5% - 12%
  • Saving of between $35 and $40 million per year

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