Multi-objective optimization of OEE (Overall Equipment Effectiveness) regarding production speed and energy consumption

Adriaan Van Horenbeek, Liliane Pintelon, Abdellatif Bey-Temsamani, and Andrei Bartic
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Full Paper
phmce_14_053.pdf588.97 KBJune 12, 2014 - 8:08am

Using condition monitoring to track machine health and trigger maintenance actions is a proven best practice. By monitoring machinery health, costly failures are avoided and downtime due to outages is reduced. This results in an improved OEE (Overall Equipment Effectiveness) by increasing operational efficiency and productivity of the equipment and decreasing equipment downtime. Many papers discuss the implementation of condition monitoring to prevent failures and optimize maintenance actions. However, much less attention is paid to the use of condition monitoring information in order to optimize production capacity of a machine or a plant. This optimization is often translated in production plants by maximizing the production capacity (speed) and minimizing machine’s downtime. As energy consumption is becoming more and more an important decision criterion in modern manufacturing plants, the former optimization needs to take this parameter into account. As such a trade-off has to be made between the gain in capacity and the cost of the additional energy consumed. Therefore, in this paper we will develop a multi-objective optimization of OEE to allow multiple-criteria decision making. More precisely, the goal of this paper is to establish the link between condition monitoring information and production capacity optimization by continuously adjusting production parameters (i.e. production speed) according to the measured condition monitoring information. The effect on the energy consumption is taken into account. This is important as a higher machines speed results in an increase of production capacity, however at the same time the energy consumption will rise. The proposed optimization approach is validated in a case study of steel production machines using cost-effective temperature sensors to monitor possible overheating of the machine. If overheating of the machine occurs the machine has to be stopped and valuable production time or capacity is lost. In a previous work [1], the condition monitoring information is used as an input to the machine’s controller in order to optimize the production speed through a developed model-based approach which relates speed to temperature of the machine. Optimization of the production speed results in maximal production capacity and minimal machine downtime by preventing overheating. In this paper we extend this optimization by taking the energy consumption parameter as one of the optimization objectives. This clearly illustrates how temperature condition monitoring information can be used to maximize industrial production capacity regarding speed and energy consumption.

[1] A. Bey-Temsamani, A. Van Horenbeek, et al. (2013). “Prognostics for optimal maintenance: industrial production capacity optimization using temperature condition monitoring”. In: Proceedings of the 26th International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM)

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Submission Keywords: 
production optimization; overall equipment effectiveness (OEE); condition monitoring; maintenance; energy consumption; multi-objective
Submission Topic Areas: 
CBM and informed logistics
Economics and cost-benefit analysis
Industrial applications
Modeling and simulation
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