Why the Future of Manufacturing Depends on Statistical Data Analysis
The emergence of Industry 4.0, the Internet of Things and other ‘Big Data’ initiatives serve as a timely reminder that data collected by companies throughout the product lifecycle remain an under-utilised asset. This data can be used to build a model that abstracts important features of a real-world situation in an actionable way, but only if you have the skill, knowledge and tools to do this quickly. Unfortunately, this has always been difficult, and these initiatives, with their emphasis on collecting more data from more things, more often, just make this worse.
In this presentation, we will address some of the primary obstacles associated with data analysis, and how you can get started with data sampling, preparation and analysis, both visual and statistical. You will see how to combine and analyze quality, production, engineering and in-usage data, using examples from a variety of manufacturing sectors. We will also show you how to present your findings in a compelling way to stakeholders that may not be statically minded, so that your work has maximum impact and the benefits of being data-driven become real.