Cloud Kanban Framework for Service Operations Management

Abstract

As continuous improvement tools evolve, so does the complexity and the size of data. With the ubiquity of data and the scale of machine automation, abilities for rapid decision making and handling of ever increasing complexity of system become necessary. Kanban is on the robust tool to visualize any process. In this paper, we propose a cloud Kanban framework that enables deployment of process excellence. The study addresses two research questions: (1) how can a robust cloud-based Kanban decision support framework work for a service industry, particularly in operations? (2) how can an evolutionary algorithm, specifically Ant Colony Optimization (ACO), augment a cloud-based Kanban decision support framework?

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