Benjamin Seligmann

New visualizations in the development of function and failure in process design and operations

Visualization can improve insights into choices made in early stages of design, particularly in relation to the impact of system related failures. Improved decision making can lead to higher commitment to inherently safer designs, more fault tolerant systems and increased operational resilience. This paper considers useful ways to visualize the function of a design in terms of the state space defined by multiple capabilities possessed by the individual components that constitute the system. Capability is related to the abilities of the component to affect the states of the system, primarily the properties of mass and energy streams that flow through the system. A representation that is constructed from these capability vectors, defines the potential space in which the system can normally operate. It can also quickly show the impact on that state space when selected capabilities are degraded or lost. It can be used in conjunction with process design tools to show in real-Time the evolution of the design and the impacts of component failures on the operations. An industrial case study drawn from crude oil processing illustrates the visualization insights and benefits of the proposed methodology.

Generating cause-implication graphs for process systems via blended hazard identification methods

Causal knowledge in complex process systems is a powerful representational model that permits a range of important applications related to process risk management. These include the development of operator training systems, diagnosis tools, emergency response planning as well as implications on process and control system retrofit and design. Using a blended hazard identification approach we show how causal knowledge can be generated from design documentation and represented in a structured language, which is then amenable to display cause-implication graphs that explicitly show the links between failures, causes and implications. A case study illustrates the application of the methodology to a safety system in an industrial coke making plant.