Issue link: https://resources.pcb.cadence.com/i/1180526
PSpice User Guide Digital worst-case timing analysis October 2019 656 Product Version 17.4-2019 © 1999-2019 All Rights Reserved. typical one might expect for any of these particular component delay values. Realizing that any two (or more) instances of a particular type of component may have propagation delay values anywhere within the published range, designers are faced with the problem of ensuring that their products are fully functional when they are built with combinations of components having delay specifications that fall (perhaps randomly) anywhere within this range. Historically, this has been done by making simulation runs using minimum (MIN), typical (TYP), and maximum (MAX) delays, and verifying that the product design is functional at these extremes. But, while this is useful to some extent, it does not uncover circuit design problems that occur only with certain combinations of slow and fast parts. True digital worst-case simulation, as provided by PSpice A/D, does just that. Other tools called timing verifiers are sometimes used in the design process to identify problems that are indigenous to circuit definition. They yield analyses that are inherently pattern-independent and often pessimistic in that they tend to find more problems than will truly exist. In fact, they do not consider the actual usage of the circuit under an applied stimulus. PSpice A/D does not provide this type of static timing verification. Digital worst-case timing simulation, as provided by PSpice A/D, is a pattern-dependent mechanism that allows a designer to locate timing problems subject to the constraints of a specific applied stimulus. Digital worst-case analysis compared to analog worst-case analysis Digital worst-case timing simulation is different from analog worst-case analysis in several ways. Analog worst-case analysis is implemented as a sensitivity analysis for each parameter which has a tolerance, followed by a projected worst-case simulation with each parameter set to its minimum or maximum value. This type of analysis is general since any type of variation caused by any type of parameter tolerance can be studied. But it is time consuming since a separate simulation is required for each parameter. This does not always produce true worst-case results, since the algorithm assumes that the sensitivity is monotonic over the tolerance range.