Understand the uncertainties and their effects in future human-machine engineering systems

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"Uncertainty occurs in every step of product design, manufacturing, operation and recycling. Uncertainties can bring significant impacts to the success of new products, quality and productivity of production systems, and service / product performance. This is very evident during the recent pandemic, in which formidable uncertainties such as disruptions of supply chain, changing demand and lack of workforce occurred all at once, leading to dramatic reduction of productivity or even collapse of engineering systems. A recent Industrial strategy workshop revealed that UK manufacturing industry has no models or tools yet to deal with uncertainties, although many enterprises have taken uncertainties as an increasing threat to their profitability. Intelligent human-machine systems are a new paradigm for realising integrated product design and process systems utilising newly developed computing power and AI. However, uncertainties in such systems need be understood and their effects should be pre-evaluated qualitatively or quantitively at early design/planning stage, so that a risk mitigation strategy can be established and embedded in the engineering system, in order to avoid the pitfalls resulted from the 'untransparent' system.This project aims to understand the uncertainties (e.g. price variations of materials, and designer's preference) and their effects in future human-machine engineering systems. This will be part of an ongoing large project which aims to Re-Imagine Design Engineering so that new ideas and concepts are generated rapidly, and where both the product and its associated manufacturing system (including its supply chain and people) are designed concurrently and fully tailored to each other. More details of the RIED project are available at: https://riedesign.org/The following work packages will be developed in this project.1. Identify and classify uncertainties in our newly developed human-machine engineering system2. Investigate and create uncertainty propagation models and evaluate the effect on performance metrics in product/production/supply chain 3. Develop a risk mitigation strategy and integrate the strategy into existing systems"