AUTHOR=A. Udugama Isuru , Öner Merve , Lopez Pau C. , Beenfeldt Christan , Bayer Christoph , Huusom Jakob K. , Gernaey Krist V. , Sin Gürkan 

TITLE=Towards Digitalization in Bio-Manufacturing Operations: A Survey on Application of Big Data and Digital Twin Concepts in Denmark

JOURNAL=Frontiers in Chemical Engineering

VOLUME=Volume 3 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/chemical-engineering/articles/10.3389/fceng.2021.727152

DOI=10.3389/fceng.2021.727152

ISSN=2673-2718

ABSTRACT=Digitalization in the form of Big Data and Digital Twin inspired applications are hot topics in today’s bio-manufacturing organizations. As a result, many organizations are diverting resources  to these applications. In this manuscript, a targeted survey was conducted amongst individuals from the Danish biotech industry to understand both the current state and perceived future obstacles in implementing digitalization concepts in bio-tech production processes. The survey consisted of questions on current level of (a) Big Data analytics and (b) Digital Twins  applications and obstacles to expanding these applications. Overall, 33 individuals responded the survey, a group spanning from bio-chemical to bio-pharmaceutical production. With over 73% of the respondents indicating their organization had an enterprise-wide level plan for digitalization, it can be concluded that the digitalization drive in the Danish bio-tech industry is well under way. However, only 30% of the respondents reported that there was a well-established business case for the digitalization applications in their organization. This is a strong indication that the value proposition for digitalization applications is somewhat ambiguous in view of the significant implementation costs. Further, digital applications (58%) were more widely used in industry than Big Data analytic tools (37%). On top of the lack of a business case, organizational readiness was identified as a key hurdle that needs to be overcome for both Digital Twin and Big Data applications. Infrastructure was another key hurdle for implementation with only 6% of the respondents stating that their production processes were 100% covered by advanced process analytical technologies.