Autonomous nuclear waste management

Redundant and non-operational buildings at nuclear sites are decommissioned over a period of time. The process involves demolition of physical infrastructure resulting in large quantities of residual waste material. The resulting waste materials are packed into import containers to be delivered for post-processing, containing either sealed canisters or assortments of miscellaneous objects. At present post-processing does not happen within the United Kingdom. Sellafield Ltd. and National Nuclear Laboratory are developing a process for future operation so that upon an initial inspection, imported waste materials undergo two stages of post-processing before being packed into export containers, namely sort and segregate or sort and disrupt. The post-processing facility will remotely treat and export a wide range of wastes before downstream encapsulation. Certain wastes require additional treatment, such as disruption, before export to ensure suitability for long-term disposal. This article focuses on the design, development, and demonstration of a reconfigurable rational agent-based robotic system that aims to highly automate these processes removing the need for close human supervision. The proposed system is being demonstrated through a downsized, lab-based setup incorporating a small-scale robotic arm, a time-of-flight camera, and high-level rational agent-based decision making and control framework

Design choices for next-generation IIoT-connected MES/MOM:An empirical study on smart factories

The role of enterprise information systems is becoming increasingly crucial for improving customer responsiveness in the manufacturing industry. However, manufacturers engaged in mass customization are currently facing challenges related to implementing Industrial Internet of Things (IIoT) concepts of Industry 4.0 in order to increase responsiveness. In this article, we apply the findings from a two-year design science study to establish the role of manufacturing execution systems/manufacturing operations management (MES/MOM) in an IIoT-enabled brownfield manufacturing enterprise. We also present design recommendations for developing next-generation MES/MOM as a strong core to make factories smart and responsive. First, we analyze the architectural design challenges of MES/MOM in IIoT through a selective literature review. We then present an exploratory case study in which we implement our homegrown MES/MOM data model design based on ISA 95 in Aalborg University's Smart Production Lab, which is a reconfigurable cyber-physical production system. This was achieved through the use of a custom module for the open-source Odoo ERP platform (mainly version 14). Finally, we enrich our case study with three industrial design demonstrators and combine the findings with a quality function deployment (QFD) method to determine design requirements for next-generation IIoT-connected MES/MOM. The results from our QFD analysis indicate that interoperability is the most important characteristic when designing a responsive smart factory, with the highest relative importance of 31% of the eight characteristics we studied

Reconfigurable middleware architectures for large scale sensor networks

Wireless sensor networks, in an effort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task reconfiguration and high-level object recomposition. Through the layered approach of SENSIX, the software developer creates a domain-specific sensing architecture by defining a customized task specification and utilizing object inheritance. In addition, SENSIX performs better at large scales (on the order of 1000 nodes or more) than other sensor network middleware which do not include such unified facilities for vertical integration

Operator interfaces for the lifecycle support of component based automation systems

Current manufacturing automation systems (specifically the powertrain sector) have been facing challenges with constant pressures of globalisation, environmental concerns and ICT (Information and Communication Technology) innovations. These challenges instigate new demands for shorter product lifecycles and require customised products to be manufactured as efficiently as possible. Manufacturing systems must therefore be agile to remain competitive by supporting frequent reconfigurations involving distributed engineering activities. [Continues.