The human element is the limiting factor in order picking; gathering items from warehouse storage systems and collecting them for despatch to customers. There have been lots of attempts to increase the productivity of order pickers; each attempt has its own benefits and drawbacks. Alina studied pick-and-pass systems, which are relatively easy to implement and which are commonly used to collect orders in e.g. e-commerce distribution centres, where short response time are crucial.
Alina was able to build a 3D simulation model of different pick-and-pass system configurations and analytically compare multi-objective performance. She investigated the optimum number of pick stations, layouts for storing products around the collection system, and the way these affect cost and throughput.
Clear design rules
The jury of logistics professors from universities in the Netherlands was particularly impressed with the way Alina’s study focused on clear design rules, such as dividing the system into segments with shortcuts, and creating the right number and type of pick stations. She found that optimised pick-and-pass systems perform significantly better than the ones currently used, achieving short lead times and high throughput with lower operating costs.
The five professors on the jury were Dirk Pieter van Donk, University of Groningen; Wout Dullaert from the VU University Amsterdam; Goos Kant , Tilburg University and Ortec; Lori Tavasszy from TNO and TU Delft; and Jack van der Veen from Nyenrode Business University.
Alina’s coaches were René de Koster, RSM’s Professor of Logistics and Operations Management and Jelmer van der Gaast (PhD candidate).
Most efficient order picking
The outcome of Alina’s analysis suggests that the most efficient order picking systems have a small number of zones and segments, use a U-shape layout so people can use shortcuts between parts of the warehouse, and store items according to type rather than randomly.
Another RSM finalist for the VLM prize was Timo Polman, another cum laude graduate of the MSc in Supply Chain Management at RSM in 2013. Polman developed and tested a method that allows calculation of the punctuality of train travellers based on smart card data. This data now contributes to the assessment of the performance of the Dutch national railway system NS, and is used in government statistics.
