  Industrial processes rely on sensory data for decision-making processes, risk
assessment, and performance evaluation. Extracting actionable insights from the
collected data calls for an infrastructure that can ensure the dissemination of
trustworthy data. For the physical data to be trustworthy, it needs to be
cross-validated through multiple sensor sources with overlapping fields of
view. Cross-validated data can then be stored on blockchain, to maintain its
integrity and trustworthiness. Once trustworthy data is recorded on the
blockchain, product lifecycle events can be fed into data-driven systems for
process monitoring, diagnostics, and optimized control. In this regard, Digital
Twins (DTs) can be leveraged in industry to draw intelligent conclusions from
data by identifying the faults and recommending precautionary measures ahead of
critical events. Empowering DTs with blockchain in industrial use-cases targets
key challenges of disparate data repositories, untrustworthy data
dissemination, and the need for predictive maintenance. In this survey, while
highlighting the key benefits of using blockchain-based DTs, we present a
comprehensive review of the state-of-the-art research results for
blockchain-based DTs. Based on the current research trends, we discuss in
detail a framework for trustworthy blockchain-based DTs. Furthermore, we also
discuss current and future research and deployment challenges along with
essential measures that must be taken by the blockchain-based DTs.
