One of the greatest fears for manufacturing executives is the threat of a product glitch. Depending on the size and scope of a problem and the number of products or consumers affected, product recalls can mean billions of dollars in recall costs for manufacturers, not to mention legal and medical expenses (when applicable), government fines as well as millions of dollars in lost sales due to damage to brand reputation.
Fortunately, manufacturers can protect themselves by detecting the first signs that problems may be on the horizon before they inflict damage on their businesses. Once they detect potential problems, they can take immediate action to develop fixes, limiting the costs of recalls and manufacturing or product repairs that may be required.
A warranty early warning system that’s powered by data and predictive analytics can help manufacturers establish baseline criteria for manufacturing operations and failure rates that can be used as guidelines for product development.
For instance, a laptop maker is able to gather and analyze data used in component manufacturing. This data can help the manufacturer determine acceptable levels of heat, vibration, and other factors used in the manufacturing processes for different components, including cooling fans, CPU, memory, batteries, etc.
Laptop cooling fans need to work properly to prevent devices from overheating, system shutdowns and, in worst-case scenarios, fire, irreparable device damage and user injury.
The use of predictive analytics and data generated from manufacturing systems can alert organizational leaders when assembly systems used to make cooling fans aren’t operating within acceptable ranges. If not caught quickly, an aberration can cause a high number of cooling fans to crack or be malformed, which can result in cooling problems after assembly.
By identifying potential issues with manufacturing equipment quickly, company leaders are able to stem widespread problems and prevent costly recalls, lawsuits, and other losses.
- We invite you to watch our complimentary, on-demand webcast, “Big Data Science and Intelligent Manufacturing Part 1 of 3: “Guided Self-Service and In-line Analytics for Manufacturing.” In this webcast, you will learn how Spotfire is being used to create guided, self-service analytics for engineers and/or operators who readily access, analyze and visually explore manufacturing big data.
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