PhD Defence Maaike Slot | Digital Twinning for Decision-Making | A structured approach for manufacturing SMEs

Digital Twinning for Decision-Making | A structured approach for manufacturing SMEs

Maaike Slot is a PhD student in the department Design, Production and Management. (Co)Promotors are prof.dr.ir. D. Lutters & dr.ir. R.G.J. Damgrave from the faculty Engineering Technology (ET), University of Twente.

Small and medium-sized enterprises (SMEs) that develop and manufacture customised discrete products operate in a volatile, uncertain, complex, and ambiguous manufacturing environment. Navigating it involves myriad decisions across organisational levels, for which decision-makers require reliable information to underpin decisions and anticipate outcomes. This dissertation addresses how manufacturing SMEs can be enabled to achieve more informed, multi-level decision-making, while capitalising on the applicability, reliability, predictability, and dependencies of information.

Companies often have vast quantities of data, but digital solutions are typically implemented ad hoc, leaving a fragmented digital infrastructure that limits their ability to provide information in a perspective-dependent, timely manner for decision-making. To overcome this, companies need support to select, develop, and implement solutions rooted in their own vision and strategy.

A structured digital twinning approach was developed, applied, and validated across four case studies: an engine shop, a bicycle manufacturer, the advanced manufacturing centre, and a consortium of companies. The approach comprises a vision-based, pull-oriented modus operandi and a development guide that translates the modus operandi into practical guidance for the purposeful development of information provisioning solutions.

The developed digital twinning approach has proved to enable companies to facilitate well-informed decision-making. The approach enables companies to develop their information provisioning solution in a structured, vision-based manner, thereby fostering an information-driven mindset. This enables decisions to be grounded in applicable, reliable, and predictable information, while also fostering a deeper understanding of interdependencies in the manufacturing environment, thereby enhancing the quality of decision-making processes across the organisation.