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An algorithm for data-driven shifting bottleneck detection

Mukund Subramaniyan (Institutionen för produkt- och produktionsutveckling, Produktionssystem) ; Anders Skoogh (Institutionen för produkt- och produktionsutveckling, Produktionssystem) ; Maheshwaran Gopalakrishnan (Institutionen för produkt- och produktionsutveckling, Produktionssystem) ; Hans Salomonsson (Institutionen för energi och miljö, Fysisk resursteori) ; Atieh Hanna ; Dan Lämkull
Cogent Engineering (2331-1916). Vol. 3 (2016), 1, p. Article no. 1239516.
[Artikel, refereegranskad vetenskaplig]

Manufacturing companies continuously capture shop floor information using sensors technologies, Manufacturing Execution Systems (MES), Enterprise Resource Planning systems. The volumes of data collected by these technologies are growing and the pace of that growth is accelerating. Manufacturing data is constantly changing but immediately relevant. Collecting and analysing them on a real-time basis can lead to increased productivity. Particularly, prioritising improvement activities such as cycle time improvement, setup time reduction and maintenance activities on bottleneck machines is an important part of the operations management process on the shop floor to improve productivity. The first step in that process is the identification of bottlenecks. This paper introduces a purely data-driven shifting bottleneck detection algorithm to identify the bottlenecks from the real-time data of the machines as captured by MES. The developed algorithm detects the current bottleneck at any given time, the average and the non-bottlenecks over a time interval. The algorithm has been tested over real-world MES data sets of two manufacturing companies, identifying the potentials and the prerequisites of the data-driven method. The main prerequisite of the proposed data-driven method is that all the states of the machine should be monitored by MES during the production run.

Nyckelord: data-driven, shifting bottleneck, active duration, bottlenecks, big data, decision support, production

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Denna post skapades 2016-12-05. Senast ändrad 2017-04-27.
CPL Pubid: 245845


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Institutioner (Chalmers)

Institutionen för produkt- och produktionsutveckling, Produktionssystem (2005-2017)
Institutionen för energi och miljö, Fysisk resursteori (2005-2017)


Produktionsteknik, arbetsvetenskap och ergonomi

Chalmers infrastruktur