The emergence of cultured meat presents the potential for personalized food additive
manufacturing, offering a solution to address future food resource scarcity. Processing raw …

Root cause analysis (RCA) is a powerful tool utilized to identify the underlying causes of an
event or problem. However, due to the specificity of production requirements in the process …

Modern industry processes are typically composed of multiple operating units with reaction
interaction and energy–mass coupling, which result in a mixed time-varying and spatial …

Abnormal energy consumption mode tracing is used to locate the root cause of the system
deviating from the normal energy consumption mode (ECM), in order to support operators in …

Recently, deep learning-based models such as transformer have achieved significant
performance for industrial remaining useful life (RUL) prediction due to their strong …

Granger causality (GC) analysis is a widely used method in root cause diagnosis; however,
the current GC-based method has deficiencies that need to be improved. Causality exists in …

Existing root cause diagnosis (RCD) methods infer causal relationships among abnormal
variables by decomposing causal graphs into intra-group and inter-group levels, reducing …

Background Plant-wide oscillations are commonly observed in industrial processes and can
have significant impacts on product quality and energy consumption. Accurately diagnosing …

Capturing the root cause is crucial for ensuring the safety and efficiency of industrial
processes. Nevertheless, most of the existing methods are unavailable for resultful causality …