RESEARCH ARTICLE A Fuzzy Logic Model of Deionised and Water for Injection Systems for Sizing and Capacity Assessment Under Uncertainty Frank Riedewald & Edmond Byrne & Kevin Cronin Published online: 29 July 2011 # Springer Science+Business Media, LLC 2011 Abstract The operating performance of deionized and water for injection (DI/WFI) distribution systems can be difficult to analyse due to the highly variable demand that is drawn from these systems, a situation compounded by schedule uncertainties. This paper presents a fuzzy logic (FL) model of a typical DI/WFI system simulating schedule uncertainties in the opening and closing events of the offtake valves based on operator behaviour, e.g. tiredness of the operators. The model utilises discrete-event simulation to calculate the demand profile of the distribution system and a continuous simulation to compute the variation of the level in the storage tank. It is shown that the FL model may be useful in the design of new DI/WFI systems if little historical data are available. Keywords WFI . DI . Capacity extension . Fuzzy logic . Uncertainty . High-purity water Nomenclature act i,k Opening/closing event of valve i, k act Wait i;k Opening/closing event of valve i, k waiting to be served f Div Diversity factor i Integer parameter k Integer parameter n Integer parameter n op Number of operators n op,min Minimum number of operators Pr i,k Priority rules for each act i,k t Time (h:m:s) tap i Valve of offtake point (tap) i along the distribution system t B 2;j Beginning of core break (h:m:s) t B 3;j End of core break (h:m:s) t close i;k Scheduled closing time for each act i,k (h:m:s) t close i;k;new New closing time for each act i,k (h:m:s) t D i;k Time delay for each act i,k (h:m:s) t D;De i;k Defuzzified time delay for each act i,k (%) t Delay;1 i;k Time delay caused by operator for each act i,k (h:m:s) t Delay;2 i;k Time delay caused by operator for each act i,k (h:m:s) t Delay;NoOp: i;k Delay caused by no operator being available for act i,k (h:m:s) t min;D i;k Minimum duration of each act i,k (h:m:s) t open i;k Scheduled opening time for each act i,k (h:m:s) t open i;k;new New closing time for each act i,k (h:m:s) t open;R1 i;k;new New opening time due to influence of rule 1 (h:m:s) t open;R4 i;k;new New opening time due to influence of rule 4 (h:m:s) t open;R5 i;k;new New opening time due to influence of rule 5 (h:m:s) t sim Simulated time (s) F. Riedewald (*) : E. Byrne : K. Cronin Department of Process and Chemical Engineering, University College Cork, Cork, Ireland e-mail: frankriedewald@gmail.com J Pharm Innov (2011) 6:125–141 DOI 10.1007/s12247-011-9108-4