Scoring Big on Insight From Effective Data Cleansing and Contextualization
When it comes to time-series data, there is no shortage of options. Cloud-based, data-lake, open source, and historians are all readily available solutions for data storage, along with lower prices for sensors, and wired or wireless offerings for data aggregation.
Five Steps to More Effective Operational Data Collection
In the increasingly high-tech, high-touch realm of manufacturing, actionable data is an ever-growing factor in business and technical decision making. It's tempting to think that data collection can be a fully automated process, especially in the age of IoT and AI.
A Sustainability Process That Drives Business Value
Iota has developed a framework called the Sustainability Process Blueprint that allows businesses to easily monitor, measure, and curate data pertaining to their sustainability performance.
Data Integration is a Key Driver for Industry 4.0 in Polymer Manufacturing
One of Industry 4.0's key drivers is data integration. By expanding the scope of data collection and making information readily retrievable, computers on the production floor have evolved to facilitate a higher level of collaboration and innovation.
Could Predictive Analytics Help Tesla Drop the Cost of the Battery Pack to $100 per kWh?
The battery pack cost of $100/kWh is a primary target for Tesla. To achieve this, the company must solve one of the world's most demanding technology challenges - and it is how to increase the volumetric energy density of battery cells while slashing production costs.
Transforming Manufacturing Takes Good Data Management
By mirroring physical assets as digital systems, manufacturers create products better and cheaper than ever before and, by bridging the physical and digital worlds, solve physical issues faster.
How to Make Sense of Machine Data in Smart Factory 101
The idea of machine to machine communication has raised the initial excitement and high hopes but now owners of mid-size and small factories ask: "What's next? How do I start adopting these technologies in my factory?"
Data Requirements for Artificial Intelligence in Manufacturing
In the manufacturing context, an example of a pattern might be the ways in which a set of parameters contained in that data, which are related to a process in a factory, vary together.
Sensor Data in the Cloud
UrsaLeo is an IoT platform company that aims to make it easy for companies to collect their sensor data in the cloud, store it, visualize it and integrate it with other IT systems. This is done in a highly secure and scalable fashion.
Why Data Empowerment Matters
To successfully empower product and developer teams with data, iteration speed matters. Rather than having a central team determine what data can be used and who can access it, agility is essential.
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Featured Product
T.J. Davies' Retention Knobs
Our retention knobs are manufactured above international standards or to machine builder specifications. Retention knobs are manufactured utilizing AMS-6274/AISI-8620 alloy steel drawn in the United States. Threads are single-pointed on our lathes while manufacturing all other retention knob features to ensure high concentricity. Our process ensures that our threads are balanced (lead in/lead out at 180 degrees.) Each retention knob is carburized (hardened) to 58-62HRC, and case depth is .020-.030. Core hardness 40HRC. Each retention knob is coated utilizing a hot black oxide coating to military specifications. Our retention knobs are 100% covered in black oxide to prevent rust. All retention knob surfaces (not just mating surfaces) have a precision finish of 32 RMA micro or better: ISO grade 6N. Each retention knob is magnetic particle tested and tested at 2.5 times the pulling force of the drawbar. Certifications are maintained for each step in the manufacturing process for traceability.
