Manufacturing IT, MES
Model developed by MIT researchers could help predictive virtual models become standard practice in engineering, which integrates data and decision making.
When coupled with diagnostic software, smart positioners can be used to reduce maintenance costs and outages.
Industrial manufacturers are using edge controllers and industrial PCs (IPCs) to implement practical analytics initiatives from the edge up, instead of from the enterprise down.
Advances in Industrial Internet of Things (IIoT) technologies and software analytics are empowering plant managers with valuable insights into the health and performance of critical assets. Analytics software and wireless communications are helping reduce costs, emissions and wasted production time.
Traditional distributed control system (DCS) and supervisory control and data acquisition (SCADA) systems designs can be improved with industrial digital transformation. Seek industrial interoperability, modularity, conformity to standards, including security standards, scalability and portability.
Industrial Internet of Things serves as backbone for other Industry 4.0 and smart manufacturing technologies, including artificial intelligence (AI), machine learning, augmented reality (AR), virtual reality (VR), digital twins, the digital thread, big data, analytics, and cloud and edge computing.
Process engineers enabled with advanced analytics can have better operational control.
Mature engineering information management can save millions in operational costs.
A well-planned virtual buy-off process for factory acceptance tests (FATs) can benefit all involved parties.
Original equipment effectiveness (OEE) can be used as a gauge to determine how effective and productive a manufacturing plant is.