Abstract
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 reconfiguration of these systems are 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 instantiation using industrial hardware.
Highlights
1.1 MotivationMass customisation, shorter product lifecycles, smaller production batches, and higher product variability all lead to the requirement for manufacturing systems that are rapidly reconfigurable and self-adaptive in response to disruption [3]
We take an approach based on considering how system structure and behaviour relate to the intended system functions, drawing on the Function-Behaviour-Structure (FBS) formalisations by Gero, Rosenman, Umeda, and others [14, 16, 27, 34, 40, 48, 49]
In [15], they give the example of a mobile phone: the user is interested in the structure as given by the screen, the keys, the size, and so on, resulting in a behavioural analysis on the use of the phone; an electrical engineer may find the electronic circuits of the phone to be relevant structural factors, which can be used to account for behaviours relating to the operating system, the ring tone, or the ability of the phone to connect to various different kinds of wireless networks
Summary
The design process links requirements to components that are either to be freshly designed or selected from a set of existing components. There are some approaches for the computer-aided design and modelling of assembly systems [6, 20, 26, 36, 52] but they generally do not address system qualities such as self-adaptation, self-reconfiguration, and self-healing, more generally called the self-x qualities [28, 29] Those approaches that do address self-x qualities in an automated manner [10, 25, 46, 50]—for example through agent-based systems—often focus primarily on one aspect, such as the software and configuration side, rather than a complete product-process-system approach that includes a formal description of the system from its function to the physical hardware. We propose a solution that is capable of addressing a wide range of dynamic requirements, takes advantage of the inherent self-x properties of the system components as a “top-level attribute” of the framework, and allows for a formal description of the whole system in order to enable its application to automated—in our case agent-based—control systems
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