text: Challenges of modeling and analysis in cybermanufacturing a review from a machine learning and computation perspective In Industry 4 0 smart manufacturing is facing its next stage cybermanufacturing founded upon advanced communication computation and control infrastructure Cybermanufacturing will unleash the potential of multi modal manufacturing data and provide a new perspective called computation service as a part of service oriented architecture SOA where on demand computation requests throughout manufacturing operations are seamlessly satisfied by data analytics and machine learning However the complexity of information technology infrastructure leads to fundamental challenges in modeling and analysis under cybermanufacturing ranging from information poor datasets to a lack of reproducibility of analytical studies Nevertheless existing reviews have focused on the overall architecture of cybermanufacturing SOA or its technical components e g communication protocol rather than the potential bottleneck of computation service with respect to modeling and analysis In this paper we review the fundamental challenges with respect to modeling and analysis in cybermanufacturing Then we introduce the existing efforts in computation pipeline recommendation which aims at identifying an optimal sequence of method options for data analytics machine learning without time consuming trial and error We envision computation pipeline recommendation as a promising research field to address the fundamental challenges in cybermanufacturing We also expect that computation pipeline recommendation can be a driving force to flexible and resilient manufacturing operations in the post COVID 19 industry 