
AbstractThis paper presents a framework for monitoring, analysing and decision making for a smart manufacturing environment. We maintain that this approach could play a vital role in developing an architecture and implementation of Industry 4.0. The proposed model has features like experience based knowledge representation and semantic analysis of engineering objects and manufacturing process. It is also capable of continuous real time visualization of key performance indicators (KPI's) and supports M2M communications over novel protocols like OPC-UA. Our model covers the industrial manufacturing cycle right from capturing raw data at machine level, converting it into useful information, doing semantics analysis and performs real time KPI visualization.
Decisional DNA, OPC-UA., Virtual Engineering Process (VEP), Virtual Engineering Object (VEO), Set of knowledge Experience Structure (SOEKS)
Decisional DNA, OPC-UA., Virtual Engineering Process (VEP), Virtual Engineering Object (VEO), Set of knowledge Experience Structure (SOEKS)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
