Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

A bimetallic catalyst on a dual component support for low temperature total methane oxidation

Palladium, platinum bimetallic catalysts supported on η-Al₂O₃, ZSM-5(23) and ZSM-5(80), with and without the addition of TiO₂, were prepared and used for low temperature total methane oxidation (TMO). The catalysts were tested under reaction temperatures of 200-500 °C with a GHSV of 100,000 mL g^-1 h^-1. It was found that all four components, palladium, platinum, an acidic support and oxygen carrier were needed to achieve a highly active and stable catalyst. The optimum support being 17.5% TiO₂ on ZSM-5(80) where the T_10% was observed at only 200 °C. On addition of platinum, longer time on stream experiments showed no decrease in the catalyst activity over 50 h at 250 °C.