Batch processing is used extensively in the production of high value products, and there are strong economic incentives for developing methodologies for ensuring the successful completion of batches via process monitoring and fault detection. Building on our previous work using time-explicit Kiviat diagrams for continuous processes, this paper introduces data visualization, data-driven process monitoring and fault detection for batch systems. Handling batch data, including unfolding and alignment are addressed as well. The proposed methodology is demonstrated on data obtained from a benchmark bioreactor simulator and a semiconductor etching process. (C) 2017 Elsevier Ltd. All rights reserved.