Conceptual framework for ubiquitous cyber-physical assembly systems in airframe assembly

Current sectoral drivers for the manufacturing of complex products - such as airframe assembly -require new manufacturing system paradigms to meet them. In this paper, we propose a conceptual framework for cyber-physical systems driven by ubiquitous context-awareness by drawing together a unique and coherent vision that merges several extant concepts. This framework leverages recent progress in agent-based systems, exible manufacturing, ubiquitous computing, and metrology-driven robotic assembly in the Evolvable Assembly Systems project. As such, although it is adapted for and grounded in manufacturing facilities for airframe assembly, it is not specifically tailored to that application and is a much more general framework. As well as outlining our conceptual framework, we also provide a vision for assembly grounded in a review of existing research in the area

A Function-Behaviour-Structure design methodology for adaptive production systems

Adaptive production systems are a key trend in modern advanced manufacturing. This stems from the requirement for the system to respond to disruption , either in the form of product changes or changes to other operational parameters. The design and reconfig-uration of these systems is therefore a unique challenge for the community. One approach to systems design is based on functional and behavioural modelling, drawn from the field of design theory. Existing approaches suffer from lack of focus on the adaptive properties of the system. While traditional production systems design focusses on the physical system structure and associated processes, new approaches based on functional and behavioural models are particularly suited to addressing the challenges of disruptive production environments resulting from Industry 4.0 and similar trends. We therefore present a Function-Behaviour-Structure (FBS) methodology for Evolvable Assembly Systems (EAS), a class of self-adaptive reconfigurable production systems, comprising an ontology model and design process. The ontology model provides definitions for Function, Structure, and Behaviour of an adaptive production system. This model is used as the input to a functional modelling design process for EAS-like systems , where the design process must be integrated into the system control behaviour. The framework is illustrated with an example taken from a real EAS instan-tiation using industrial hardware

Affordable data integration approach for production enterprises

© 2020 The Authors. The manufacturing industries in a number of high-labour-cost economies are undergoing a shift towards increased automation and intelligence typified by the ‘Industry 4.0' paradigm. Advances from computer science research including digital informatics enables the addition of intelligence and autonomy to the flexible and reconfigurable manufacturing systems developed by manufacturing systems research. One such advance is the development of Data Distribution Services (DDSs) that enable the robust and timely distribution of high-quality data in a scalable manner. This paper describes how a DDS can be used to integrate systems across a production enterprise, including directly on a shop floor rather than using additional specialised shop floor integration components often required by other communications protocols

Realisability of production recipes

There is a rising demand for customised products with a high degree of complexity. To meet these demands, manufacturing lines are increasingly becoming autonomous, networked, and intelligent, with production lines being virtualised into a manufacturing cloud, and advertised either internally to a company, or externally in a public cloud. In this paper, we present a novel approach to two key problems in such future manufacturing systems: the realisability problem (whether a product can be manufactured by a set of manufacturing resources) and the control problem (how a particular product should be manufactured). We show how both production recipes specifying the steps necessary to manufacture a particular product, and manufacturing resources and their topology can be formalised as labelled transition systems, and define a novel simulation relation which captures what it means for a recipe to be realisable on a production topology. We show how a controller that can orchestrate the resources in order to manufacture the product on the topology can be extracted from the simulation relation, and give an algorithm to compute a simulation relation and a controller

Realisability of production recipes

There is a rising demand for customised products with a high degree of complexity. To meet these demands, manufacturing lines are increasingly becoming autonomous, networked, and intelligent, with production lines being virtualised into a manufacturing cloud, and advertised either internally to a company, or externally in a public cloud. In this paper, we present a novel approach to two key problems in such future manufacturing systems: the realisability problem (whether a product can be manufactured by a set of manufacturing resources) and the control problem (how a particular product should be manufactured). We show how both production recipes specifying the steps necessary to manufacture a particular product, and manufacturing resources and their topology can be formalised as labelled transition systems, and define a novel simulation relation which captures what it means for a recipe to be realisable on a production topology. We show how a controller that can orchestrate the resources in order to manufacture the product on the topology can be extracted from the simulation relation, and give an algorithm to compute a simulation relation and a controller

Photochromic molecular implementations of universal computation

Unconventional computing is an area of research in which novel materials and paradigms are utilised to implement computation. Previously we have demonstrated how registers, logic gates and logic circuits can be implemented, unconventionally, with a biocompatible molecular switch, NitroBIPS, embedded in a polymer matrix. NitroBIPS and related molecules have been shown elsewhere to be capable of modifying many biological processes in a manner that is dependent on its molecular form. Thus, one possible application of this type of unconventional computing is to embed computational processes into biological systems. Here we expand on our earlier proof-of-principle work and demonstrate that universal computation can be implemented using NitroBIPS. We have previously shown that spatially localised computational elements, including registers and logic gates, can be produced. We explain how parallel registers can be implemented, then demonstrate an application of parallel registers in the form of Turing machine tapes, and demonstrate both parallel registers and logic circuits in the form of elementary cellular automata. The Turing machines and elementary cellular automata utilise the same samples and same hardware to implement their registers, logic gates and logic circuits; and both represent examples of universal computing paradigms. This shows that homogenous photochromic computational devices can be dynamically repurposed without invasive reconfiguration. The result represents an important, necessary step towards demonstrating the general feasibility of interfacial computation embedded in biological systems or other unconventional materials and environments

Towards Flexible, Fault Tolerant Hardware Service Wrappers for the Digital Manufacturing on a Shoestring Project

The adoption of digital manufacturing in small to medium enterprises (SMEs) in the manufacturing sector in the UK is low, yet these technologies offer significant promise to boost productivity. Two major causes of this lack of uptake is the high upfront cost of digital technologies, and the skill gap preventing understanding and implementation. This paper describes the development of software wrappers to facilitate the simple and robust use of a range of sensors and data sources. These form part of a common architecture for data acquisition in the Digital Manufacturing on a Shoestring project. We explain the existing Shoestring demonstrator architecture, and discuss how a'crash-only' microservices architecture would improve fault tolerance and adaptability of the system

Implementing large-scale Aerospace Assembly 4.0 demonstration systems?

The Future Automated Aerospace Assembly phase 1 technology Demonstrator (FA3D) was commissioned at the University of Nottingham and used to demonstrate concepts from the EPSRC Evolvable Assembly Systems project in specific industrial use cases. A number of lessons were learned from the specification, procurement, commissioning, and use of the cell. These lessons have been applied to the specification of Phase 2 of the Future Automated Aerospace Assembly Demonstrator (FA3D2) - currently in development - that will translate the Evolvable Assembly Systems research to a higher technology readiness level and address the challenges of scalable and transformable manufacturing systems. The FA3D2 will act as a showcase national experimental testbed and technology demonstrator in digital- and informatics-enabled aerospace manufacturing technologies, and the project itself will generate knowledge, skills, and experience in the delivery of such systems for academia and industry. After summarising the Evolvable Assembly Systems project, this paper presents details of the technologies demonstrated through the FA3D, and how this experience has been used to develop a novel approach to specifying the FA3D2

Semantic models and knowledge graphs as manufacturing system reconfiguration enablers

Reconfigurable Manufacturing System (RMS) provides a cost-effective approach for manufacturers to adapt to fluctuating market demands by reconfiguring assets through automated analysis of asset utilization and resource allocation. Achieving this automation necessitates a clear understanding, formalization, and documentation of asset capabilities and capacity utilization. This paper introduces a unified model employing semantic modeling to delineate the manufacturing sector's capabilities, capacity, and reconfiguration potential. The model illustrates the integration of these three components to facilitate efficient system reconfiguration. Additionally, semantic modeling allows for the capture of historical experiences, thus enhancing long-term system reconfiguration through a knowledge graph. Two use cases are presented: capability matching and reconfiguration solution recommendation based on the proposed model. A thorough explication of the methodology and outcomes is provided, underscoring the advantages of this approach in terms of heightened efficiency, diminished costs, and augmented productivity