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Using Prescriptive Analytics to Support the Continuous Improvement Process

Abstract : The continuous improvement process (CIP) enables companies to increase productivity constantly by sourcing ideas from their employees on the shop floor. However, shorter production cycles require manufacturing companies to also adapt their production processes in a faster manner and reduce resources for CIP activities. Traditional CIP approaches fall short in such a fast-paced environment characterized by uncertainty. This study proposes a novel approach for increasing the efficiency and speed of the CIP by using data of previous improvements and predict current potentials. This results in a prescriptive model supporting the employees how to improve their processes.
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https://hal.inria.fr/hal-02419264
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Submitted on : Thursday, December 19, 2019 - 1:17:47 PM
Last modification on : Thursday, December 19, 2019 - 1:47:57 PM
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Günther Schuh, Jan-Philipp Prote, Thomas Busam, Rafael Lorenz, Torbjörn Netland. Using Prescriptive Analytics to Support the Continuous Improvement Process. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2019, Austin, TX, United States. pp.46-53, ⟨10.1007/978-3-030-30000-5_6⟩. ⟨hal-02419264⟩

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