Big data analytics for operations management in engineer-to -order manufacturing

Manufacturing data offers big potential for improving management of manufacturing operations. The paper addresses an approach to data analytics in engineer-to -order (ETO) manufacturing systems where the product quality and due-date reliability play a key role in management decision making. The objective of the research is to investigate manufacturing data which are collected by a manufacturing execution system (MES) during operations in an ETO enterprise and to develop tools for supporting scheduling of operations. The developed tools can be used for simulation of production and forecasting of potential resource overloads. 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.