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.

Cooling channels are critical in injection mould tooling as cooling performance influences component quality, cycle time, and overall process efficiency. Additively Manufactured moulds allow the incorporation of cooling channels conforming to the shape of the cavity and core to improve heat removal. These conformal channels can reduce the cycle time, reduce mould temperature, and enhance the temperature uniformity on the mould's surface, leading to improved quality of the moulded components and reduced wastage in the production. The design of such channels is more challenging than conventional channels; thus, Computer-Aided Engineering (CAE) has a significant role within the design process. In this paper, a novel design for conformal cooling channels for the production of a commercial component from an industrial partner is investigated. This component had issues of high cycle time and a high defect rate due to residual stresses, resulting in component shrinkage. First, the existing conventional drilled cooling channels in the mould were simulated in Autodesk Moldflow Insight to evaluate temperature distribution and cycle time. Based on the temperature distribution, conformal cooling channels were designed in Solidworks, addressing the problem areas. Next, a simulation of fluid flow in the conformal channels was conducted in ANSYS-Fluent to ensure equal flow distribution in the entire circuit, iteratively arriving at an optimal configuration. Finally, the results of the new conformal channels, including mould temperature and cycle time, were compared with conventional cooling channels in simulation. The results showed a significant reduction in cycle time and improvement in the temperature distribution, thereby minimising residual stresses and shrinkage.

Injection moulding is an important industry, providing a significant percentage of the demand for plastic products throughout the world. The process consists of many variables which directly or indirectly influence the part quality and cycle time. The first step in optimizing the process parameters is identifying the most significant variables affecting the desired output. For this purpose, various Design of Experiments methods (DOE) have been developed to investigate the effect of the experimental variables on the output and predict the required settings to achieve the optimal value of the output. In this study we investigate the application of DOE for a commercial injection moulded component which suffers from a long cycle time and high shrinkage. The Taguchi method has been used to analyze the effect of four input variables on the two output variables: cycle time and shrinkage. The component has been simulated in the Moldflow software to validate the predicted output and optimized settings of the variables from the DOE. A comparison of the simulation result and the predicted value from the DOE illustrated good accordance. The calculated optimal setting with the Taguchi method reduced the cycle time from the 40s to about 23s and met the shrinkage criteria for this commercial part.