Abstract:
Rapid responsiveness to diversifying customer needs is considered a competitive advantage in manufacturing business. To shrink the inquiry-to-order process, manufacturing firms could benefit a lot from operating a configure-to-order (CTO) strategy which necessitates implementing of a product configuration system (PCS), the enabler of mass customisation. A PCS, also known as product configurator, can enable an agile and efficient product customisation process by assembling a set of predefined customisable modules to satisfy both customer requirements (CRs) and technical constraints. Since PCS technologies have been matured for decades, the advancement of AI and Internet has facilitated PCSs evolved to carry features including cloud-based multi-device access, compatibility with CAD systems, 3D visualisation, etcetera. However, due to insufficient connectivity to enterprise systems, even state-of-the-art PCS solutions cannot respond quickly to changes in manufacturing systems and supply chains. This results in the incapability of performing configuration activities for highly customised product which entails the integrated configuration of product, process and supply chains. In addition, since increasingly more dispersed companies collaboratively carry out product configuration in the global manufacturing environments, the connectivity issues of PCS have become more prominent. Similar to the concept of design for manufacturing, the foundation of product configuration is the manufacturing paradigm. Most current research and industrial practices on PCS technologies revolve around mass customisation. Therefore, the disruptive innovation of manufacturing models will drive the evolvement of PCS. As a nascent mode of networked manufacturing, cloud manufacturing (CMfg) is capable of enabling agile configuration of distributed manufacturing resources to fabricate products customised with high customisation freedom. In CMfg, a global service-oriented manufacturing environment (i.e., manufacturing cloud) is constructed by virtualising and encapsulating manufacturing resources and capabilities from service providers (i.e., manufacturers in CMfg). To develop the next generation PCS, CMfg is regarded as fundamental to the product configuration process in this research. The CMfg-enabled configuration application is abbreviated as CM-PCS. To extend the configuration process from product domain to service domain, a framework for realising CM-PCS is proposed in consideration of the configuration of product, process and manufacturing service providers. Aiming to realise accurate discovery and composition of manufacturing services for configuration fulfilment, advanced semantic web technologies are adopted to build a product configuration knowledge base comprised of product knowledge, process knowledge, and cloud-sourced knowledge, among which STEP-NC is utilised as a complementary measure for documenting detailed process information. To cope with scalable configuration space (i.e., the solution space of configuration problem) in CMfg, the author presents an optimisation approach based on augmented Lagrangian coordination (ALC) to achieve scalability management. Apart from coping with general product, the personalisation process of smart product, in terms of IoT-based smart environment, service ecosystem and manufacturing cloud, is presented. The methodology of this research has been validated through case studies and a human ethics experiment. The main scientific contributions of this research include: (1) product configuration knowledge modelling for a service-oriented manufacturing environment, (2) a novel configuration approach for integrated and distributed configuration, (3) a STEP-NC enriched product configuration process, (4) the optimisation of scalable configuration space in CMfg, and (5) personalisation of smart product in CMfg, smart environment and service ecosystem.