Digital Twins & IIoT support monitoring, diagnostics, scheduling and controlled execution by connecting actual process data with virtual representations and associated execution contexts. This important integrated literature review identifies those connections' role in supporting these operations and synthesizes 35 relevant peer-reviewed journal articles written since 2020. Articles included are a variety of types, including conceptual analyses, computational studies, laboratory experiments and industrial trials. The synthesis differentiates evidence of capability from evidence of operation and identifies three applications that were common among all the articles surveyed: monitoring, diagnosing bottlenecks in production processes, coordinating production and logistics processes, and scheduling production based upon product-condition. There was no evidence from the surveys that would indicate the current level of development regarding implementing fully autonomous control at a manufacturing facility. Successful integration of DTs and IIoT will require a reliable collection of plant floor data, common understanding of events, sufficient model accuracy for decision making, and clear definition of the authority to execute. The authors propose an execution-oriented architecture where MES or a designated orchestration service verifies production plans and local controllers continue to have real-time control over machines and remain responsible for independent safety functions. The proposed control cycle includes maintaining a fresh view of system states, assessing uncertainty related to states, evaluating constraints on planned activities, and defining appropriate fallback behaviors. The primary areas requiring additional research include assessments of synchronization across systems, issues with model maintenance and reuse within multiple DTs, coordination of multiple DTs operating in a distributed environment, and long-term evaluations in industrial settings.