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Process for Enhancing the Production System Robustness with Sensor Data – a Food Manufacturer Case Study

Abstract : Global markets for food products are changing towards accommodating larger product variety while experiencing shorter lifespans of products. These market trends impose pressure on the existing manufacturing infrastructure, however the food industry lacks investment in manufacturing technology. This research illustrates how the robustness of the existing production system can be enhanced using sensor data, including a case study of a Danish food company. The paper presents an outline of an iterative process performed in a case company to identify and carry out the potential of utilize sensor data from the existing production setup, and an example of the potential and return of investment is introduced. Several challenges are recognized when implementing sensor data to enhance the production system robustness. The in-house competencies are lacking in order to install the setup of sensors and operating in a database with a big amount of data. In addition, the challenge of continuously maintaining the data and the analyses is present. The research points to the importance of involving operators to better understand the context of the production. In conclusion, the case company has achieved information of the production based on data and not only running adjustments, based intuition of the operators and has thereby enhanced the production system robustness.
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Submitted on : Thursday, January 30, 2020 - 10:16:18 AM
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Sofie Bech, Thomas Ditlev Brunoe, Kjeld Nielsen. Process for Enhancing the Production System Robustness with Sensor Data – a Food Manufacturer Case Study. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2019, Austin, TX, United States. pp.405-412, ⟨10.1007/978-3-030-29996-5_47⟩. ⟨hal-02460505⟩



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