Mobile technologies are challenging traditional data handling practices as they move into the industrial arena.
Good mobile software promotes efficiency by delivering data on intuitive screens that empower users to integrate information and saves trips back to the control room or to the site.
Momentum around time-series data storage suggests a new chapter for a legacy offering.
Not all data is equal and some require greater attention and priority than others. Industrial companies managing networks need to focus on information-based, mission critical and real-time data.
MIT researchers have developed a method using machine learning to reveal optimal growing conditions to maximize taste and other features.
MIT researchers have developer a flash-storage system designed to cut the energy and physical space required to store and manage data in data centers by half.
Articles about low-power hybrid chips for robots, gaining the edge in automation, connecting quality and process data, manufacturing and process facility trends, and the Engineers' Choice Awards were Control Engineering’s five most clicked articles from March 18-24. Miss something? You can catch up here.
Using advanced analytics can help assure product quality and overall operational efficiencies. See case study example.
Demystify the need for Big Data and five related challenges: data structure, scalability, integration, storage, and upgrades.
Companies need to be open to new technologies to see fundamental paradigm shifts in productivity, beyond incremental improvements. Rapid increases in productivity, visibility, flexibility, and agility are needed.