(SO1): Establishing product-process-production system of systems model Enabling companies to efficiently determine relations between products, processes and production systems, thereby enabling to determine impact of market and supply changes on production systems, and identifying opportunities to utilize existing assets. This is achieved using an ontology-based reference model representing entities and relations in a system of systems perspective in a product-process-production system of systems model (PPPSoS), including human skills and competences. This forms a basis for protocols deriving company-specific data models from which implementations in Enterprise IT systems can be developed. (SO2): Predict reconfiguration needs Enabling companies to predict needs for reconfiguration in response to disrupted supply chains or rapidly changing customer demands based on timely and early identification of internal and external company-specific change triggers and assessment of their impact on products, processes, and production at line level, factory level, and global network level. This is enabled by data in a PPPSoS model analyzed using AI techniques and organizational knowledge, where reconfiguration triggers are first identified, then based on data from various sources monitor whether triggers occur, detect when a change is triggered, and evaluate the impact on production systems. (SO3): Prescribe the best reconfiguration alternative Enabling companies to prescribe reconfigurations by identifying feasible reconfiguration alternatives at line level, factory level, and global network level in response to the detected change in demand and/or disruption in supply chains, using a PPPSoS model representing existing assets internal or external to a company and evaluate time, financial, and organizational aspects of the different reconfiguration alternatives applying machine learning and simulation. Please see PDF for details.
Project leader: Pål Huse
Institution: JOTNE EPM TECHNOLOGY AS