Digital Twin has become an important technology for advanced manufacturing. However, to ensure that
digital twins provide valuable decision support, the results generated by the digital twins must be trustworthy
for real manufacturing systems. Model credibility assessment including Verification, Validation,
and Uncertainty Quantification (VVUQ) techniques need to be applied throughout the life cycle of digital
twins. Verification and Validation (V&V) activities are necessary to ensure that a digital twin meets its
intended purpose and design goals used to establish its credibility. Uncertainty Quantification (UQ) produces
a measure of performance that users can apply as part of a credibility assessment for a given digital
twin. Credibility assessment of digital twins also includes factors beyond VVUQ. This paper discusses
requirements of the digital twin credibility assessment, identifies potential uncertainty areas of digital
twins, introduces a new digital-twin framework standard, proposes potential extension of the standard
with credibility consideration, and discusses other ongoing relevant standards.