State estimators, including observers and Bayesian filters, are a class of model-based algorithms for estimating variables in a dynamical system given the sensor measurements of related system states. They can be used to derive fast and accurate estimates of system variables that cannot be measured directly (‘soft sensing’) or for which only noisy, intermittent, delayed, indirect, or unreliable measurements are available, perhaps from multiple sources (‘sensor fusion’). In this paper, we introduce the concepts and main methods of state estimation and review recent applications in improving the sustainability of manufacturing processes across sectors including industrial robotics, material synthesis and processing, semiconductor, and additive manufacturing. It is shown that state estimation algorithms can play a key role in manufacturing systems for accurately monitoring and controlling processes to improve efficiencies, lower environmental impact, enhance product quality, improve the feasibility of processing more sustainable raw materials, and ensure safer working environments for humans. We discuss current and emerging trends in using state estimation as a framework for combining physical knowledge with other sources of data for monitoring and controlling distributed manufacturing systems.
Injection moulding is an extremely important industrial process, being one of the most commonly-used plastic formation techniques. However, the industry faces many current challenges associated with demands for greater product customisation, higher precision and, most urgently, a shift towards more sustainable materials and processing. Accurate real-time sensing of the material and part properties during processing is key to achieving rapid process optimisation and set-up, reducing down-times, and reducing waste material and energy in the production of defective products. While most commercial processes rely on point measurements of pressure and temperature, ultrasound transducers represent a non-invasive and non-destructive source of rich information on the mould, the cavity and the polymer melt, and its morphology, which affect critical quality parameters such as shrinkage and warpage. In this paper the relationship between polymer properties and the propagation of ultrasonic waves is described and the application of ultrasound measurements in injection moulding is evaluated. The principles and operation of both conventional and high temperature ultrasound transducers (HTUTs) are reviewed together with their impact on improving the efficiency of the injection moulding process. The benefits and challenges associated with the recent development of sol-gel methods for HTUT fabrication are described together with a synopsis of further research and development needed to ensure a greater industrial uptake of ultrasonic sensing in injection moulding.
Here we describe a proof-of-concept case study focusing on the design and development of a novel computer interface that uses facial muscles to control interactivity within a virtual environment. We have developed a system comprised of skin-mounted electrodes that detect underlying muscle activity through electromyography. The signals from the electrodes are filtered and smoothed, then used as input data to an application that displays a virtual environment with a 3D animated avatar. The user’s expressions control the facial movements of the avatar, thus conveying user emotions through real-time animation of a representative face in a virtual scenario. To achieve this, we collaborated with our Public and Patient Involvement focus group to discuss concepts and design appropriate interactions, while simultaneously developing a prototype system. Programmers and 3D artists worked together to create a system whereby individual user facial muscles are connected to 3D animated models of the same muscle features represented in an avatar, providing the user with an option to receive visual and numerical feedback on the extent of their muscle control. Using the prototype system, people can communicate facial expressions virtually with each other, without the need for a camera. This research is part of an on-going project to develop a facial muscle rehabilitation system that can be optimized to help patients with conditions such as hypomimia.