Ford estimates that a single engine production line costing £30 million could be built and commissioned 50% faster, with over 30% cost savings, if the system could reconfigure itself automatically. This research aims to create manufacturing systems that behave like intelligent Lego sets—modular machines that can rearrange themselves as products change. Currently, even flexible factories are designed by intuition, not systematic methods. When a car model changes, production lines must be torn down and rebuilt from scratch, a slow and expensive process. The project tackles this gap by building highly accurate virtual models that simulate the entire lifetime of a production system, allowing engineers to predict exactly how a reconfigurable line will perform before a single physical component is moved. If successful, this work could transform high-value engineering in the UK. The automotive and aerospace sectors, which rely on modular assembly lines for powertrains and airframes, would gain the ability to switch between products rapidly without massive capital expenditure. This would help retain manufacturing activity in the UK by making its factories more competitive. The research builds on an existing method from Loughborough University already being adopted in automotive supply chains, extending it from intuitive practice into a rigorous, model-driven science.
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The proposed research programme will attempt to create self-reconfiguring manufacturing systems that are based on intelligent and highly accurate models of manufacturing processes and the products being manufactured. The goal of the research is to enable a radical change in manufacturing effectiveness and sustainability. The target type of manufacturing is component-based modular reconfigurable systems, i.e. systems that are built up of various elements and assembled together, in a similar fashion to building with 'lego'. This is a class of manufacturing system that is typically used in assembly and handling applications, where you tend to find families of modular machine components that can be reused and reconfigured as the product, and hence production processes change. Major applications for this are in the automotive and aerospace sectors. One example is in powertrain assembly, as seen in the UK at Ford. If the re-configurability of such production systems can be enhanced, Ford estimate that potential savings of over 30% in costs are achievable with a target of a 50% reduction in the time to build and commission such a system that typically costs £30 million per engine line. The realisation of this research has the potential to help enable the retention of high value engineering activity in the UK by improving the competiveness in the engineering of reconfigurable manufacturing systems. The capability to achieve this aim is to be built on the foundation of current, internationally leading research at Loughborough University, which has created a method for building reconfigurable systems from reusable components that is currently being adopted in automotive supply chains. The concepts of flexible and reconfigurable manufacturing systems are well established; however problems still exist in the effective, efficient, rapid, configuration of such flexible systems, particularly as lifecycle product changes occur, whether such changes are minor or more fundamental. Many flexible and reconfigurable system examples exist. However, most are designed intuitively and a systematic methodology is still lacking. Additionally, engineering this integration of product and processes is essential in a lifecycle context across the supply-chain, yet this remains largely unaddressed. Virtual engineering also has a major role to play in that we can simulate production systems and products. However the effectiveness of such simulation design tools for reconfigurable systems remains poor. Such tools need to be able to encompass the full system lifetime and be able to replicate the functions of the production system exactly in the models. These models are key enablers for understanding what might happen throughout a production system's lifecycle and can drive better configuration of the modular manufacturing systems we aspire to create.
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