I focus on multi-purpose batch chemical plants in industry, complex batch processes in edible oil processing, and pesticide production. Batch chemical processes are characterized by discontinuous operations and the critical role of time. My contributions include development of a graphical water optimization method in batch plants and the state-sequence-network (SSN) approach for scheduling, thereby reducing the complexity of mathematical models used in batch process optimization. The developed method extends to heat integration, leading to a new operational philosophy in batch chemical plants – process intermediate storage. A pivotal moment came when my PhD student, E. R. Seid, discovered a flaw in my mathematical formulation premised on a SSN, which resulted in a more robust framework, and a method to predict the optimal number of time points in scheduling problems. I emphasize the recognition of knowledge gaps, industry collaboration, and an interdisciplinary approach to drive innovation and highlight how conscious awareness of the unknown, the ‘black cat in the dark room’, is crucial for advancing scientific knowledge. Ignorance is at the heart of breakthroughs in science engineering.