Industrial Product-Service Systems (IPSS) denote a service-oriented (SO) way
of providing access to CPS capabilities. The design of such systems bears high
risk due to uncertainty in requirements related to service function and
behavior, operation environments, and evolving customer needs. Such risks and
uncertainties are well known in the IT sector, where DevOps principles ensure
continuous system improvement through reliable and frequent delivery processes.
A modular and SO system architecture complements these processes to facilitate
IT system adaptation and evolution. This work proposes a method to use and
extend the Digital Twins (DTs) of IPSS assets for enabling the continuous
optimization of CPS service delivery and the latter's adaptation to changing
needs and environments. This reduces uncertainty during design and operations
by assuring IPSS integrity and availability, especially for design and service
adaptations at CPS runtime. The method builds on transferring IT DevOps
principles to DT-enabled CPS IPSS. The chosen design approach integrates,
reuses, and aligns the DT processing and communication resources with DevOps
requirements derived from literature. We use these requirements to propose a
DT-enabled self-adaptive CPS model, which guides the realization of DT-enabled
DevOps in CPS IPSS. We further propose detailed design models for
operation-critical DTs that integrate CPS closed-loop control and
architecture-based CPS adaptation. This integrated approach enables the
implementation of A/B testing as a use case and central concept to enable CPS
IPSS service adaptation and reconfiguration. The self-adaptive CPS model and DT
design concept have been validated in an evaluation environment for
operation-critical CPS IPSS. The demonstrator achieved sub-millisecond cycle
times during service A/B testing at runtime without causing CPS operation
interferences and downtime.Comment: Final published version appearing in 17th Symposium on Software
Engineering for Adaptive and Self-Managing Systems (SEAMS 2022