PLM and Product Data Insight

by Oleg on February 8, 2013 · 2 comments

Data is a trending topic these days. Big Data is even fascinating. It made me think about the meaning of power. In the past, oil was a meaning for power. These days it applies to data. Social data, corporate data, any data. To have the ability to dig into the data, discover facts, relationships and make decisions spins minds of companies, technologists and investors. All I mentioned above applies to manufacturing companies and the data that these companies holds  on their servers, data centers and desktop computers.

I’ve been reading WIRED article Data-Visualization Firm’s New Software Autonomously Finds Abstract Connections. I wonder… is it a data analysis revolution or another “fancy graphic” of big data? Aysdi – the company behind the article and video is promising you to discover the data and connections you don’t know. Here is a brief description of what system is doing, including some tech ideas

Their new product is called the Iris Insight Discovery platform. It’s a type of machine learning that uses hundreds of algorithms and topological data analysis to mine huge datasets before presenting the results in a visually accessible way. Using algebraic topology, the system automatically hunts down data points close in nature and maps these out to reveal a network of patterns for a researcher to decipher — any closely related nodes of information will be connected and clustered together, like how a social network arranges its data according to relationship connections.

If you don’t have time to read the article, watch the video below. It will give you the idea of what is that about.

It is interesting that Aysdi is coming with some background of manufacturing from DARPA. For the moment, system provide some result in medicine. I wonder if data in manufacturing companies containing product, supply chain and many other aspects can be targeted using this tech.

What is my conclusion? Manufacturing companies are under stress about making an improvement in their decision management process. Decisions are complicated and can be driven by many factors. Product data insight. It can be interesting way to learn what impact product cost, supply chain, manufacturing processes and many other things. It might sounds like a magic. However, many of today’s technologies could potentially considered as a magic 10 years ago. Just my thoughts…

Best, Oleg

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  • BrionC2

    Very useful. I think outside of this capability for life science the results could really be formulated to any domains benefit, given the proper elements to the equation.

    I would think these type of algorithms could be beneficial in seasonal release of retail products to determine pre-season usage based on data from product shop-floor success, demographics, cost and vendor percentage to forecast an already guaranteeing effective product release cycle. Only, if this could have an open source type of collaboration for innovative product design. Then, it would be on the desktop of every designer used in every season throughout the year. Then again, it just might. Thanks for sharing.

  • beyondplm

    Brion, thanks for comments and sharing use-cases. good ideas… best, Oleg

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