Posts Tagged ‘manufacturing’

Machine Learning’s Future: Fortune 500 Buys In, Manufacturing Sees The Light

STServerMartin Hack, CEO and co-founder of machine learning company Skytree, has a prediction to make: “In the next three to five years we will see a machine learning system in every Fortune 500 company.” In fact, he says, it’s already happening, and not just among the high-tech companies in that ranking but also among the “bread and butter” enterprises.

“They know they need advanced analytics to get ahead in the game or stay competitive,” Hack says. For that, he says, they need machine learning algorithms for analyzing their Big Data sets, and they need to be able to deploy them quickly and easily — even if those who will be doing the deployments are coming from at best a background of basic analytics and business intelligence.

“There just aren’t enough data scientists to go around,” he says. It’s very tough to fill those roles in most companies, he says, “so like it or not, we have to make it much, much easier for people to digest and use this.”

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MESA Announces New White Paper: The Role of Semantic Models in Smarter Industrial Operations

CHANDLER, ARIZ. — The paper investigates the application of semantic model design and technology in industrial operations integration and the evolving role of Semantic Computing in operations management.  Semantic (data) modeling as a core component of application architecture is compared to more familiar architectural integration patterns. As operations functions are described, the value of semantic models is illustrated through a series of examples that should be familiar to the reader. Read more

Inforbix acquired by Autodesk

inforbix LogoAutodesk (NASDAQ: ADSK), “a world leader in 3D design, engineering and entertainment software” announced today that it has acquired assets of Inforbix. Inforbix is a Semantic Technology-based product lifecycle management (PLM) company. Terms of the transaction were not disclosed.

Inforbix was co-founded  in 2010 by CEO Oleg Shilovitsky and CIO Anatoly Savin to answer the problem of how to retrieve product data located in different places in manufacturing companies that affects development, supply chains and manufacturing systems. Our own Jennifer Zaino interviewed Shilovitsky last year about this.

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Inforbix Announces Cloud-Based Product Data Apps

Inforbix has announced a new cloud product data solution for manufacturing, Product Data Apps: “The revolutionary cloud-centric service helps engineers, project managers and other team members quickly and easily find, re-use, and share product data from disparate sources and file types.” Inforbix CEO Oleg Shilovitsky stated, “Money and time are wasted because most product data management professionals cannot locate the specific information needed without a manual search. Our system makes it easy for an engineer to pinpoint designs, specifications, and even quality control data with a mouse click. After extensive validation, we learned that as much as 40 percent of productive engineering time is wasted in data management activities. Inforbix reduces much of that wasted time.” Read more

Linking Disparate Data in Manufacturing

A recent article from Inforbix discusses the difficulties of linking data in manufacturing businesses. The article notes, “Product data in all its forms is located and sourced in different places in manufacturing companies.  Accessing product data is, moreover, confounded by how different systems deploy different methodologies (or languages) for how they keep track of it.  For example, an item known in engineering as a ‘Part’ may be called a ‘Component’ in production… What I’m trying to say here is that the mixture of different vocabularies or vernacular used in a typical manufacturing company makes it difficult for different systems to have a macro understanding of how product data located in different places is connected together.” Read more

What Inforbix is Doing for Engineers

A recent article from Inforbix comments on a quote from Lynda Moulton, writer of Semantic Software Technologies. Moulton said, “Besides baked-in intelligence for answering human questions using natural language processing (NLP) to search, an answer-platform like Watson requires tons of data. Also, data must be assembled in conceptually and contextually relevant databases for good answers to occur. When documents and other forms of electronic content are fed to a knowledgebase for semantic retrieval, finely crafted metadata (data describing the content) and excellent vocabulary control add enormous value. These two content enhancers, metadata and controlled vocabularies, can transform good search into excellent search.” Read more

Make Manufacturing Easier — At Least the Dealing With Data Part of It

When you think of manufacturing companies, you probably picture conveyor belts, milling machines, spot welders, and a whole slew of stamping, polishing, extracting and reformulating processes going on at the factory. But what you also should think about is all the darn data around the products these companies produce that resides in different files and across multiple applications and databases, and how navigating and presenting it in a way to get some meaning out of it can seem as complicated a process as operating a gear cutting machine or taking on a precision grinder.

That’s where startup Inforbix thinks product data semantics will make a  difference. The company was co-founded last year by CEO Oleg Shilovitsky and CIO Anatoly Savin to answer the problem of how to retrieve product data located in different places in manufacturing companies that affects development, supply chains and manufacturing systems, and it’s expected to bring a beta solution to light in the next couple of months.

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Semantics For The Connected World: Thingworx Goes Live

Manufacturers, utilities, health care and other industrial and services organizations have an opportunity to develop applications that model and draw upon the capabilities of the increasingly connected physical world around them. Seems, after all, as if almost everything already is or soon will be connected to a sensor of some sort, reeling in data to private intranets and, phase by phase, to the Internet, and creating opportunities to create smart grids, smart parking, and smart cities.

Thingworx may be able to help them take advantage of that opportunity. The start-up today plans to formally launch its application platform in Downingtown, Pa. (hopefully bringing a bit of cheer to state residents still getting over last night’s Pittsburgh Steelers Super Bowl loss). It leverages its semantic definitions for this “Internet of things” world to help those organizations – and not just the techies within them – to search, query, and analyze data, and then build mash-ups using the results.

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Bringing together Systems Engineering and the Semantic Web

Systems Engineering (SE) is a vast discipline that includes many sub-disciplines. The International Council on Systems Engineering (INCOSE) defines Systems Engineering as:

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Bringing together Systems Engineering and the Semantic Web

Systems Engineering (SE) is a vast discipline that includes many sub-disciplines. The International Council on Systems Engineering (INCOSE) defines Systems Engineering as:

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