Improving Product Location and Order Picking Activities in a Distribution Center

Size: px
Start display at page:

Download "Improving Product Location and Order Picking Activities in a Distribution Center"

Transcription

1 Improving roduct Location and Order icking Activities in a Distribution Center Jacques Renaud Angel Ruiz Université Laval Centre Interuniversitaire de Recherche sur les Réseaux d Entreprise, la Logistique et le Transport - resentation Outline Introduction Warehouse design and operations Conveyor belt layout Order picking procedure Actual product location strategy New product location strategies Computational results Further results using a Traveling salesman model

2 Introduction Both distribution centers (DC) and warehousing operations are key elements in supply chain efficiency. DC efficiency and throughput are the result of technological and design choices. Although modern supply chain management strategies focus on reducing inventory, product diversification and customization require handling additional stock keeping units (SKU s). For modern DC, the flowthrough is a competitive element.

3 Introduction Warehousing decisions Storage strategies : Assign SKUs to storage location Dedicated storage A A A A A A A A A A D D D D A A C C C C C C B B B B E E Random storage Classed-based storage

4 Introduction Warehousing decisions Order picking strategies : How the SKUs are grouped into picking lists and subsequently retrieved from their storage locations by one or many pickers. Discrete picking Zone picking Batch picking Wave picking

5 Introduction Warehousing decisions Routing strategies : Determine the sequence in which the SKUs on a given picking list are collected, the objective being to minimize the distance covered by the pickers. Objective of this study Optimize both product location and order picking activities (including the routing) of a high throughput DC.

6 Literature Review Order icking The general discrete order picking problem is a traveling salesman problem (Np-Hard). Many researchers studied special warehouse configurations which lead to polynomial solvable cases : Ratliff & Rosenthal (1983) Goetschalckx & Rafliff (1988) De Koster & van der oort (1998) Vaughan, Roodbergen & De Koster (2001) No work related to conveyor like the one studied here.

7 roduct location Considerably less attention Literature Review roduct location is highly dependent on warehouse configuration and order picking strategy and technology. Most of the work deals with specific cases. Heskett (1963), cube-per-order index, Jarvis & McDowell (1983), minimize average order picking time Vickson & Fujimoto (1996), optimal location in a bi-directional carousel Jewkes, Lee & Vickson (2004), product location along a picking line No work related to conveyor like the one studied here.

8 In this study Warehouse design and operations External retailers may order any quantity of any product. roducts for these customers are assigned to storage locations (slots) in a mezzanine shelving system on both sides of a conveyor belt, according to a dedicated storage policy. For a given order, a single picker walks along the shelves, gathers the required quantities of the products from the various locations along the route (broken case picking), and puts them on the conveyor belt which automatically moves them to the right truck in the shipping area.

9 Warehouse design and operations Detailed objective : Improving the storage and order-picking operations by : (1) optimizing the allocation of products to storage locations, and (2) reviewing the picking (routing) strategy.

10 Conveyor belt layout 2 AL 4 AL 5 AL 3 AL 4 AL 5 AL F E D C B A ESCALIER F301 F302 C302 B302 F303 D303 C303 B303 A303 ESCALIER F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306 C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309 panneaux E309 D309 panneaux C309 B309 panneaux A309 F310 E310 D310 C310 B310 A310 F311 panneaux E311 D311 panneaux C311 B311 panneaux A311 F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314 A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316 B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 A318 F319 panneaux E319 D319 C319 B319 panneaux panneaux A319 F320 E320 D320 panneaux panneaux C320 B320 A320 F321 E321 D321 C321 B321 A321 F322 panneaux E322 D322 C322 B322 A322 F323 m ASSAGE ASSAGE ASSAGE A323 F324 E324 D324 C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 B326 A326 F327 E327 D327 C327 B327 panneaux A327 F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331 panneaux E331 D331 panneaux C331 B331 A331 F332 E332 D332 C332 B332 A332 F333 panneaux E333 D333 panneaux C333 B333 A333 F334 E334 D334 C334 B334 panneaux A334 F335 E335 D335 C335 B335 panneaux A335 F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339 panneaux C339 B339 A339 D340 C340 B340 A340 D341 C341 B341 A341 D342 panneaux C342 B342 panneaux A342 Doors for crossing the belt D343 C343 B343 panneaux A343 D344 C344 B344 A344 D345 C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348 panneaux C348 B348 A348 D349 C349 B349 A349 D350 anneaux anneaux A350 D351 D352 D353 D354 D355 D356 D357 D358 D359 roducts to the trucks in the shipping area icking lists printer Empty wooden board The conveyor belt A total of 240 storage locations Heavy products section

11 roduct categories Conveyor belt layout Regular product (80%) : can be ordered by any retailer. Vending product (20%) : Are shipped only to New Brunswick. They are restricted to section F. 2 AL 4 AL 5 AL 3 AL 4 AL 5 AL F E D C B A ESCALIER F301 F302 C302 B302 F303 D303 C303 B303 A303 ESCALIER F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306 C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309 panneaux E309 D309 panneaux C309 B309 panneaux A309 F310 E310 D310 C310 B310 A310 F311 panneaux E311 D311 panneaux C311 B311 panneaux A311 F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314 A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316 B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 A318 F319 panneaux E319 D319 C319 B319 panneaux panneaux A319 F320 E320 D320 panneaux panneaux C320 B320 A320 F321 E321 D321 C321 B321 A321 F322 panneaux E322 D322 C322 B322 A322 F323 m ASSAGE ASSAGE ASSAGE A323 F324 E324 D324 C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 B326 A326 F327 E327 D327 C327 B327 panneaux A327 F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331 panneaux E331 D331 panneaux C331 B331 A331 F332 E332 D332 C332 B332 A332 F333 panneaux E333 D333 panneaux C333 B333 A333 F334 E334 D334 C334 B334 panneaux A334 F335 E335 D335 C335 B335 panneaux A335 F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339 panneaux C339 B339 A339 D340 C340 B340 A340 D341 C341 B341 A341 D342 panneaux C342 B342 panneaux A342 D343 C343 B343 panneaux A343 D344 C344 B344 A344 D345 C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348 panneaux C348 B348 A348 D349 C349 B349 A349 D350 A350 anneaux anneaux D351 D352 D353 D354 D355 D356 D357 D358 D359

12 Conveyor belt layout Conveyor modeling We modelled the belt as an undirected connected graph, in which each storage location corresponds to a node and in which an edge (undirected arc) exists between each pair of adjacent nodes. C321 B321 C322 B322 B333 A333 Footbridge B334 - B D A334 C324 B324 B335 A335 - B C325 B325 C321 B321 B333 B333 5 C B322 B334 6 B C B324 B335 B C325 B325

13 Order icking rocedure A picker starts the tour at location A303, where a computer prints the picking list. S/he visit sections B, C, F, E, D and A in that order before returning to location A303. In this strategy, the picker uses a predetermined route (but he can skip useless part of the belt). 2 AL 4 AL 5 AL 3 AL 4 AL 5 AL F E D C B A ESCALIER F301 F302 C302 B302 F303 D303 C303 B303 A303 ESCALIER F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306 C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309 panneaux E309 D309 panneaux C309 B309 panneaux A309 F310 E310 D310 C310 B310 A310 F311 panneaux E311 D311 panneaux C311 B311 panneaux A311 F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314 A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316 B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 A318 F319 panneaux E319 D319 C319 B319 panneaux panneaux A319 F320 E320 D320 panneaux panneaux C320 B320 A320 F321 E321 D321 C321 B321 A321 F322 panneaux E322 D322 C322 B322 A322 F323 m ASSAGE ASSAGE ASSAGE A323 F324 E324 D324 C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 B326 A326 F327 E327 D327 C327 B327 panneaux A327 F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331 panneaux E331 D331 panneaux C331 B331 A331 F332 E332 D332 C332 B332 A332 F333 panneaux E333 D333 panneaux C333 B333 A333 F334 E334 D334 C334 B334 panneaux A334 F335 E335 D335 C335 B335 panneaux A335 F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339 panneaux C339 B339 A339 D340 C340 B340 A340 D341 C341 B341 A341 D342 panneaux C342 B342 panneaux A342 D343 C343 B343 panneaux A343 D344 C344 B344 A344 D345 C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348 panneaux C348 B348 A348 D349 C349 B349 A349 D350 A350 anneaux anneaux D351 D352 D353 D354 D355 D356 D357 D358 D359

14 Order icking rocedure A 5 products example. The storage locations are sorted automatically on the picking list following the sequence BCFEDA. F E D C B A F301 Starting F302 C302 B302 D point F303 D303 D C303 B303 A303 F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306- C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309-B E309 D309 C309-B B309-B A309 F310 E310 D310 C310 B310 A310 F311 E311-B D311-B C311 B311 A311-B F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314- A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316- B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 D A318 F319-B E319 D319 C319 B319-B A319-B F320 E320 D320-B C320-B B320 A320 F321 E321 D321 C321 B321 A321 F322 D E322-B D322 C322 B322 A322 F323 Footbridge Footbridge A323 F324 E324 D324 D C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 DISC B326 A326 F327 E327 D327 C327 B327 A327-B F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331-B E331 D331 C331-B B331 A331 F332 E332 D332 C332 B332 A332 F333 E333-B D333-B C333 B333 A333- F334 E334 D334 C334 B334-B D A334 F335 E335 D335 C335 B335 A335-B F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339-B C339 B339 A339 D340 C340 DISC B340 A340 D341 C341 B341 A341 D342 C342-B B342-B A342 D343 C343 B343 A343-B D344 C344 B344 A344 D345- C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348-B C348 B348 A348 D349 D C349 B349 A349 D350 A350 D Congrès conjoint SCRO/Journées D351-B D352 D353 D354de D355 l Optimisation D356 D357 D358 D359-B 2006, Montréal

15 Actual roduct Location Strategy At present, products are assigned to locations based solely on the experience and knowledge of the logistics manager. The rule-of-thumb used by the logistics manager is that products with the highest sales forecast are placed as near as possible to the starting point, filling sections A and B first followed by C, D and E (the allocation is revised 4 times a year).

16 Actual roduct Location Strategy 2 AL 4 AL 5 AL 3 AL 4 AL 5 AL F E D C B A ESCALIER F301 F302 C302 B302 F303 D303 C303 B303 A303 ESCALIER F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306 C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309 E309 D309 C309 B309 A309 F310 E310 D310 C310 B310 A310 F311 E311 D311 C311 B311 A311 F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314 A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316 B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 A318 F319 E319 D319 C319 B319 A319 F320 E320 D320 C320 B320 A320 F321 E321 D321 C321 B321 A321 F322 E322 D322 C322 B322 A322 F323 ASSAGE ASSAGE A323 F324 E324 D324 C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 B326 A326 F327 E327 D327 C327 B327 A327 F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331 E331 D331 C331 B331 A331 F332 E332 D332 C332 B332 A332 F333 E333 D333 C333 B333 A333 F334 E334 D334 C334 B334 A334 F335 E335 D335 C335 B335 A335 F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339 C339 B339 A339 D340 C340 B340 A340 D341 C341 B341 A341 D342 C342 B342 A342 D343 C343 B343 A343 D344 C344 B344 A344 D345 C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348 C348 B348 A348 D349 C349 B349 A349 D350 A350 roducts having the highest sales forecasts D351 D352 D353 D354 D355 D356 D357 D358 D359

17 New roduct Location Strategies To obtain a product allocation, two decisions are needed: -in whichorderproduct should be considered, -in whichorderstorage locations should be assigned. Solution rocedure To determine the location allocation, the first non-assigned product in the list was selected and assigned to the first available position in the location list. This procedure was repeated until all the products have been assigned. We used 2 product sorting rules and 3 locations sorting rules.

18 New roduct Location Strategies 1) roduct sorting rule : Quantity Sorts the products in decreasing order accordingly to their forecast demand 2) roduct sorting rule : Frequency Sorts the products in decreasing order of their ordering frequency (the number of times that a product is ordered by customers, independent of the requested quantity) If vending products are taken into consideration, they are automatically allocated to section F.

19 New roduct Location Strategies 1) Location sorting rule : Shortest distance Sort the locations according to their distance from the starting point. 2) Location sorting rule : ABCDEF The second rule, ABCDEF, first sorts the locations by section, following the order A-B-C-D-E-F; then sort the locations within a section according to their distance from the starting point, with those closest to the starting point coming first. 3) Location sorting rule : BCFEDA As the second rule but sections are sorted in the order BCFEDA which is the order followed by the picker. 2 AL 4 AL 5 AL 3 AL 4 AL 5 AL F E D C B A ESCALIER F301 F302 C302 B302 F303 D303 C303 B303 A303 ESCALIER F304 D304 C304 B304 A304 F305 E305 D305 C305 B305 A305 F306 E306 D306 C306 B306 A306 F307 E307 D307 C307 B307 A307 F308 E308 D308 C308 B308 A308 F309 E309 D309 C309 B309 A309 F310 E310 D310 C310 B310 A310 F311 E311 D311 C311 B311 A311 F312 E312 D312 C312 B312 A312 F313 E313 D313 C313 B313 A313 F314 E314 D314 C314 B314 A314 F315 E315 D315 C315 B315 A315 F316 E316 D316 C316 B316 A316 F317 E317 D317 C317 B317 A317 F318 E318 D318 C318 B318 A318 F319 E319 D319 C319 B319 A319 F320 E320 D320 C320 B320 A320 F321 E321 D321 C321 B321 A321 F322 E322 D322 C322 B322 A322 F323 ASSAGE ASSAGE A323 F324 E324 D324 C324 B324 A324 F325 E325 D325 C325 B325 A325 F326 E326 D326 C326 B326 A326 F327 E327 D327 C327 B327 A327 F328 E328 D328 C328 B328 A328 F329 E329 D329 C329 B329 A329 F330 E330 D330 C330 B330 A330 F331 E331 D331 C331 B331 A331 F332 E332 D332 C332 B332 A332 F333 E333 D333 C333 B333 A333 F334 E334 D334 C334 B334 A334 F335 E335 D335 C335 B335 A335 F336 E336 D336 C336 B336 A336 F337 E337 D337 C337 B337 A337 D338 C338 B338 A338 D339 C339 B339 A339 D340 C340 B340 A340 D341 C341 B341 A341 D342 C342 B342 A342 D343 C343 B343 A343 D344 C344 B344 A344 D345 C345 B345 A345 D346 C346 B346 A346 D347 C347 B347 A347 D348 C348 B348 A348 D349 C349 B349 A349 D350 D351 D352 D353 D354 D355 D356 D357 D358 D359 A350

20 New roduct Location Strategies Improvement procedure Given an initial solution and a number of picking lists, the heuristic evaluates, for each possible pair of products, the decrease in the distance walked if their storage locations were exchanged. After all the possible exchanges have been evaluated, the one that offers the most improvement is selected and implemented. This procedure continues until no improvement can be obtained.

21 Computational Results Test Data Real data provided by our industrial partner. Orders from 372 customers between March 21st and May 15th forecast sets of 20 orders each Used in the place of the manager s sales forecast to assign products to specific locations. 4 test sets of 20 orders each Used to evaluate the company s product allocation and the product allocations produced by our algorithms.

22 Computational Results Total picking distances obtained with the Quantity product sorting rule Data set Without any product category With vending/regular products handled separately Shortest ABCDEF BCFEDA Shortest ABCDEF BCFEDA Current location Global % These results demonstrates that vending products should be assigned to section F

23 Computational Results Total picking distances obtained with the Frequency product sorting rule Data set Without any product category With vending/regular products handled separately Shortest ABCDEF BCFEDA Shortest ABCDEF BCFEDA Current location Global % These results demonstrates that vending products should be assigned to section F

24 Computational Results Data set Total picking distances after the improvement procedure [Quantity; * ; Vending] [Frequency; * ; Vending] Shortest ABCDEF BCFEDA Shortest ABCDEF BCFEDA Company s improved location Global % %% % ercentage of reduction of the picking distances produced by the improvement procedure %% Reduction of the picking distances compared to the current company s location

25 Further Results using the TS Actually, the order picker follows a predetermined route through all the sections (skipping useless sections). Clearly this problem is a symmetrical traveling salesman problem which we solved by using the classical 3-Opt (Lin 1965).

26 Further Results using the TS D C B A D C B A D D D D redetermined route 908 feet D Footbridge D D Footbridge D TS route 798 feet D D A saving of 110 feet on this small example D D D D

27 Further Results using the TS Data set Improvement obtained by scheduling order-picking operations by solving a traveling salesman problem [Quantity; * ; Vending] [Frequency; * ; Vending] Shortest ABCDEF BCFEDA Shortest ABCDEF BCFEDA Company s improved location Global % %% % ercentage of reduction in term of distance obtained by solving a TS %% Total reduction of the picking distances compared with the current company s location

28 Conclusion Improvements of up to 11.25% can be achieved if product location is done using a shortest distance rule Using a post-optimization procedure, reduction up to 19% can be achieved Using a TS to schedule order pickers provide an additional 5 to 13% distance reduction Overall, these procedures reduce the total picking distance from 21 to 28% which significantly increase warehouse productivity

A SIMULATION MODEL TO IMPROVE WAREHOUSE OPERATIONS. Jean Philippe Gagliardi Jacques Renaud Angel Ruiz

A SIMULATION MODEL TO IMPROVE WAREHOUSE OPERATIONS. Jean Philippe Gagliardi Jacques Renaud Angel Ruiz Proceedings of the 2007 Winter Simulation Conference S. G. Henderson, B. Biller, M.-H. Hsieh, J. Shortle, J. D. Tew, and R. R. Barton, eds. A SIMULATION MODEL TO IMPROVE WAREHOUSE OPERATIONS Jean Philippe

More information

MTTN L11 Order-picking MTTN25 Warehousing and Materials Handling. Warehousing and Materials Handling 1. Content. Learning objectives

MTTN L11 Order-picking MTTN25 Warehousing and Materials Handling. Warehousing and Materials Handling 1. Content. Learning objectives L11 Order-picking MTTN25 Warehousing and Materials Handling Warehousing and Materials Handling Tools & Techniques Optimization models Pick-paths Inclusion of SKU in FPA Lane depth & slotting L11 Layout

More information

A Solution Approach for the Joint Order Batching and Picker Routing Problem in Manual Order Picking Systems

A Solution Approach for the Joint Order Batching and Picker Routing Problem in Manual Order Picking Systems A Solution Approach for the Joint Order Batching and Picker Routing Problem in Manual Order Picking Systems André Scholz Gerhard Wäscher Otto-von-Guericke University Magdeburg, Germany Faculty of Economics

More information

Routing order pickers in a warehouse with a middle aisle

Routing order pickers in a warehouse with a middle aisle Routing order pickers in a warehouse with a middle aisle Kees Jan Roodbergen and René de Koster Rotterdam School of Management, Erasmus University Rotterdam, P.O. box 1738, 3000 DR Rotterdam, The Netherlands

More information

Improving Order Picking Efficiency with the Use of Cross Aisles and Storage Policies

Improving Order Picking Efficiency with the Use of Cross Aisles and Storage Policies Open Journal of Business and Management, 2017, 5, 95-104 http://www.scirp.org/journal/ojbm ISSN Online: 2329-3292 ISSN Print: 2329-3284 Improving Order Picking Efficiency with the Use of Cross Aisles and

More information

AN EVALUATIVE FRAMEWORK FOR PICK AND PASS ZONE PICKING SYSTEMS

AN EVALUATIVE FRAMEWORK FOR PICK AND PASS ZONE PICKING SYSTEMS Rotterdam School of Management Erasmus University AN EVALUATIVE FRAMEWORK FOR PICK AND PASS ZONE PICKING SYSTEMS Master Thesis AUTHOR Alina Stroie 332925 MSc Supply Chain Management Date: 13.03.2014 COACH

More information

XXVI. OPTIMIZATION OF SKUS' LOCATIONS IN WAREHOUSE

XXVI. OPTIMIZATION OF SKUS' LOCATIONS IN WAREHOUSE XXVI. OPTIMIZATION OF SKUS' LOCATIONS IN WAREHOUSE David Sourek University of Pardubice, Jan Perner Transport Faculty Vaclav Cempirek University of Pardubice, Jan Perner Transport Faculty Abstract Many

More information

DECISION SCIENCES INSTITUTE. Cross aisle placement in order picking operations. Charles Petersen Northern Illinois University

DECISION SCIENCES INSTITUTE. Cross aisle placement in order picking operations. Charles Petersen Northern Illinois University DECISION SCIENCES INSTITUTE Charles Petersen Northern Illinois University Email: cpetersen@niu.edu Gerald Aase Northern Illinois University Email: gaase@niu.edu ABSTRACT Order picking operations need to

More information

DOCUMENT DE TRAVAIL

DOCUMENT DE TRAVAIL Publié par : Published by: Publicación de la: Édition électronique : Electronic publishing: Edición electrónica: Disponible sur Internet : Available on Internet Disponible por Internet : Faculté des sciences

More information

DOCUMENT DE TRAVAIL

DOCUMENT DE TRAVAIL Publié par : Published by: Publicación de la: Édition électronique : Electronic publishing: Edición electrónica: Disponible sur Internet : Available on Internet Disponible por Internet : Faculté des sciences

More information

A thesis presented to. the faculty of. the Russ College of Engineering and Technology of Ohio University. In partial fulfillment

A thesis presented to. the faculty of. the Russ College of Engineering and Technology of Ohio University. In partial fulfillment Methodology for Data Mining Customer Order History for Storage Assignment A thesis presented to the faculty of the Russ College of Engineering and Technology of Ohio University In partial fulfillment of

More information

Travel Time in a Warehouse: Process. Improvement at The Toro Company. John Cinealis

Travel Time in a Warehouse: Process. Improvement at The Toro Company. John Cinealis 1 Travel Time in a Warehouse: Process Improvement at The Toro Company by John Cinealis A Research Paper Submitted in Partial Fulfillment of the Requirements for the Master of Science Degree In Technology

More information

Order Fulfillment Strategies for Low Velocity Inventory

Order Fulfillment Strategies for Low Velocity Inventory Order Fulfillment Strategies for Low Velocity Inventory Presented by: Ken Ruehrdanz 2018 MHI Copyright claimed for audiovisual works and sound recordings of seminar sessions. All rights reserved. Order

More information

An algorithm for dynamic order-picking in warehouse operations

An algorithm for dynamic order-picking in warehouse operations An algorithm for dynamic order-picking in warehouse operations Wenrong Lu a,, Duncan McFarlane a, Vaggelis Giannikas a, Quan Zhang b, a Institute for Manufacturing, University of Cambridge, 17 Charles

More information

Dynamic Slotting and Cartonization Problem in Zone-based Carton Picking Systems. Byung Soo Kim

Dynamic Slotting and Cartonization Problem in Zone-based Carton Picking Systems. Byung Soo Kim Dynamic Slotting and Cartonization Problem in Zone-based Carton Picking Systems by Byung Soo Kim A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements

More information

Warehouse layout alternatives for varying demand situations

Warehouse layout alternatives for varying demand situations Warehouse layout alternatives for varying demand situations Iris F.A. Vis Faculty of Economics and Business Administration, Vrije Universiteit Amsterdam, Room 3A-31, De Boelelaan 1105, 1081 HV Amsterdam,

More information

OPTIMIZING THE SUPPLY CHAIN OPERATIONS OF E-SHOP WAREHOUSES

OPTIMIZING THE SUPPLY CHAIN OPERATIONS OF E-SHOP WAREHOUSES OPTIMIZING THE SUPPLY CHAIN OPERATIONS OF E-SHOP WAREHOUSES Submitted by Vassilis Pergamalis A thesis Presented to the Faculty of Tilburg School of Economics and Management In Partial Fulfillment of Requirements

More information

Picker routing and storage-assignment strategies for precedence-constrained order picking

Picker routing and storage-assignment strategies for precedence-constrained order picking Picker routing and storage-assignment strategies for precedence-constrained order picking Working Paper DPO-2017-04 (version 1, 28.07.2017) Ivan Zulj zulj@uni-hohenheim.de Department of Procurement and

More information

Impressum ( 5 TMG) Herausgeber: Fakultät für Wirtschaftswissenschaft Der Dekan. Verantwortlich für diese Ausgabe:

Impressum ( 5 TMG) Herausgeber: Fakultät für Wirtschaftswissenschaft Der Dekan. Verantwortlich für diese Ausgabe: WORKING PAPER SERIES Impressum ( 5 TMG) Herausgeber: Otto-von-Guericke-Universität Magdeburg Fakultät für Wirtschaftswissenschaft Der Dekan Verantwortlich für diese Ausgabe: Otto-von-Guericke-Universität

More information

The Picking Playbook Batch Picking, Zone Picking or Cluster Picking Which is Right for Your Distribution Center?

The Picking Playbook Batch Picking, Zone Picking or Cluster Picking Which is Right for Your Distribution Center? The Picking Playbook Batch Picking, Zone Picking or Cluster Picking Which is Right for Your Distribution Center? Publication Date: September, 2016 Author: Ian Hobkirk The Picking Playbook Batch Picking,

More information

A Thesis presented to the Faculty of the Graduate School. University of Missouri. In Partial Fulfillment. Of the Requirements for the Degree

A Thesis presented to the Faculty of the Graduate School. University of Missouri. In Partial Fulfillment. Of the Requirements for the Degree DETERMINING A HEURISTIC FOR PICK LOCATION DESIGN IN AN END USER WAREHOUSE A Thesis presented to the Faculty of the Graduate School University of Missouri In Partial Fulfillment Of the Requirements for

More information

RELATION-BASED ITEM SLOTTING

RELATION-BASED ITEM SLOTTING RELATION-BASED ITEM SLOTTING A Thesis presented to the Faculty of the Graduate School University of Missouri In Partial Fulfillment Of the Requirements for the Degree Master of Science by Phichet Wutthisirisart

More information

Design of warehousing and distribution systems: an object model of facilities, functions and information

Design of warehousing and distribution systems: an object model of facilities, functions and information Design of warehousing and distribution systems: an object model of facilities, functions and information T. Govindaraj, Edgar E. Blanco, Douglas A. Bodner, Marc Goetschalckx, Leon F. McGinnis, and Gunter

More information

OPTIMIZING THE REARRANGEMENT PROCESS IN A DEDICATED WAREHOUSE

OPTIMIZING THE REARRANGEMENT PROCESS IN A DEDICATED WAREHOUSE OPTIMIZING THE REARRANGEMENT PROCESS IN A DEDICATED WAREHOUSE Hector J. Carlo German E. Giraldo Industrial Engineering Department, University of Puerto Rico Mayagüez, Call Box 9000, Mayagüez, PR 00681

More information

AN INTEGRATED MODEL OF STORAGE AND ORDER-PICKING AREA LAYOUT DESIGN

AN INTEGRATED MODEL OF STORAGE AND ORDER-PICKING AREA LAYOUT DESIGN AN INTEGRATED MODEL OF STORAGE AND ORDER-PICKING AREA LAYOUT DESIGN Goran DUKIC 1, Tihomir OPETUK 1, Tone LERHER 2 1 University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture Ivana

More information

The order picking problem in fishbone aisle warehouses

The order picking problem in fishbone aisle warehouses The order picking problem in fishbone aisle warehouses Melih Çelik H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 30332 Atlanta, USA Haldun Süral Industrial

More information

New tool for aiding warehouse design process. Presented by: Claudia Chackelson, Ander Errasti y Javier Santos

New tool for aiding warehouse design process. Presented by: Claudia Chackelson, Ander Errasti y Javier Santos New tool for aiding warehouse design process Presented by: Claudia Chackelson, Ander Errasti y Javier Santos Outline Introduction validation validation Introduction Warehouses play a key role in supply

More information

Association Rule Based Approach for Improving Operation Efficiency in a Randomized Warehouse

Association Rule Based Approach for Improving Operation Efficiency in a Randomized Warehouse Proceedings of the 2011 International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia, January 22 24, 2011 Association Rule Based Approach for Improving Operation

More information

DYNAMIC ABC STORAGE POLICY IN ERRATIC DEMAND ENVIRONMENTS

DYNAMIC ABC STORAGE POLICY IN ERRATIC DEMAND ENVIRONMENTS DYNAMIC ABC STORAGE POLICY IN ERRATIC DEMAND ENVIRONMENTS (Benjamin Pierre, et al.) DYNAMIC ABC STORAGE POLICY IN ERRATIC DEMAND ENVIRONMENTS Benjamin Pierre, Bart Vannieuwenhuyse, Denis Dominanta Centrum

More information

White Paper. Dynamic Slotting (Capabilities of Exacta Profile)

White Paper. Dynamic Slotting (Capabilities of Exacta Profile) White Paper On Dynamic Slotting (Capabilities of Exacta Profile) Software and Automation Technology for Supply Chain Logistics Louisville, Kentucky This paper contains information considered proprietary

More information

SIX MONTHS TO A STRONGER OPERATION

SIX MONTHS TO A STRONGER OPERATION SIX MONTHS TO A STRONGER OPERATION OVERALL OPERATIONAL EFFICIENCY YOUR SYSTEM, ONLY BETTER. www.dlneu.com (616) 538-0638 WELCOME The January edition of D.L. Neu s series, Six Months to a Stronger Operation,

More information

Oracle Warehouse Management (WMS) and RFID

Oracle Warehouse Management (WMS) and RFID Oracle Warehouse Management (WMS) and RFID Integrations, Enhancements and an Overview Aditya Agarkar Director, Product Strategy Safe Harbor Statement The following is intended to

More information

white paper Top 10 Trends Driving Order Fulfillment

white paper Top 10 Trends Driving Order Fulfillment white paper Top 10 Trends Driving Order Fulfillment Introduction What is driving the design of order fulfillment systems today? What is driving the design of order fulfillment systems today? While an analysis

More information

Optimizing the Storage Assignment in a Warehouse Served by Milkrun Logistics

Optimizing the Storage Assignment in a Warehouse Served by Milkrun Logistics Optimizing the Storage Assignment in a Warehouse Served by Milkrun Logistics András Kovács Computer and Automation Research Institute, Budapest, Hungary E-mail address: akovacs@sztaki.hu June 23, 2009

More information

PICK PATH OPTIMIZATION. An enhanced algorithmic approach

PICK PATH OPTIMIZATION. An enhanced algorithmic approach PICK PATH OPTIMIZATION An enhanced algorithmic approach Abstract Simulated annealing, enhanced with certain heuristic modifications, provides an optimized algorithm for picking parts from a warehouse or

More information

DRAFT ANALYSIS AND OPTIMAL DESIGN OF DISCRETE ORDER PICKING TECHNOLOGIES ALONG A LINE. Donald D. Eisenstein

DRAFT ANALYSIS AND OPTIMAL DESIGN OF DISCRETE ORDER PICKING TECHNOLOGIES ALONG A LINE. Donald D. Eisenstein ANALYSIS AND OPTIMAL DESIGN OF DISCRETE ORDER PICKING TECHNOLOGIES ALONG A LINE Donald D. Eisenstein Graduate School of Business, The University of Chicago, Chicago, Illinois 60637 USA. don.eisenstein@chicagogsb.edu

More information

Small Item Sortation: Solving the BIG Problem of Sorting Small Things

Small Item Sortation: Solving the BIG Problem of Sorting Small Things Welcome to Session 206 Small Item Sortation: Solving the BIG Problem of Sorting Small Things Presented by: Sponsored by: John Park: Doug Jones: Product Manager Director, Business Development 2012 Material

More information

Supply Chain Best Practices Consortium

Supply Chain Best Practices Consortium Supply Chain Best Practices Consortium Order Picking Executive Seminar Supply Chain Leadership Forum Track B, Session 3 September, 2007 1 Session Scope This session covers best practices for what is generally

More information

Lecture 08 Order Picking & Bucket Brigades

Lecture 08 Order Picking & Bucket Brigades .. Lecture 08 Order Picking & Bucket Brigades Oran Kittithreerapronchai 1 1 Department of Industrial Engineering, Chulalongkorn University Bangkok 10330 THAILAND last updated: December 29, 2014 Warehouse

More information

SEQUENCING APPROACHES FOR MULTIPLE-AISLE AUTOMATED STORAGE AND RETRIEVAL SYSTEMS

SEQUENCING APPROACHES FOR MULTIPLE-AISLE AUTOMATED STORAGE AND RETRIEVAL SYSTEMS SEQUENCING APPROACHES FOR MULTIPLE-AISLE AUTOMATED STORAGE AND RETRIEVAL SYSTEMS Jean-Philippe Gagliardi 1,2, Jacques Renaud 1,2,* & Angel Ruiz 1,2 1 Faculté des Sciences de l administration, Université

More information

LOAD SHUFFLING AND TRAVEL TIME ANALYSIS OF A MINILOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEM WITH AN OPEN-RACK STRUCTURE

LOAD SHUFFLING AND TRAVEL TIME ANALYSIS OF A MINILOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEM WITH AN OPEN-RACK STRUCTURE LOAD SHUFFLING AND TRAVEL TIME ANALYSIS OF A MINILOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEM WITH AN OPEN-RACK STRUCTURE Mohammadreza Vasili *, Seyed Mahdi Homayouni * * Department of Industrial Engineering,

More information

The Put Wall: Versatile Facilitator of Omnichannel Distribution Effective Means of Diverse Product Consolidation Across Multiple Channels

The Put Wall: Versatile Facilitator of Omnichannel Distribution Effective Means of Diverse Product Consolidation Across Multiple Channels The Put Wall: Versatile Facilitator of Omnichannel Distribution Effective Means of Diverse Product Consolidation Across Multiple Channels The Put Wall: Versatile Facilitator of Omnichannel Distribution

More information

Waiting Strategies for Regular and Emergency Patient Transportation

Waiting Strategies for Regular and Emergency Patient Transportation Waiting Strategies for Regular and Emergency Patient Transportation Guenter Kiechle 1, Karl F. Doerner 2, Michel Gendreau 3, and Richard F. Hartl 2 1 Vienna Technical University, Karlsplatz 13, 1040 Vienna,

More information

MOBILE-RACKS AND ROBOTS: A PARADIGM SHIFT IN ORDER PICKING. Dr. Debjit Roy 24 April 2014 Material Handling Forum Seminar, VU Amsterdam

MOBILE-RACKS AND ROBOTS: A PARADIGM SHIFT IN ORDER PICKING. Dr. Debjit Roy 24 April 2014 Material Handling Forum Seminar, VU Amsterdam MOBILE-RACKS AND ROBOTS: A PARADIGM SHIFT IN ORDER PICKING Dr. Debjit Roy 24 April 2014 Material Handling Forum Seminar, VU Amsterdam Email: debjit@iimahd.ernet.in Material Handling Forum, Erasmus University

More information

Case study: Van Heck Interpieces Speedy order picking at the large-sized Van Heck Interpieces installation

Case study: Van Heck Interpieces Speedy order picking at the large-sized Van Heck Interpieces installation Case study: Van Heck Interpieces Speedy order picking at the large-sized Van Heck Interpieces installation Location: France Van Heck Interpieces, an automotive spare parts distribution business, owns a

More information

Warehouse Design Process

Warehouse Design Process Warehousing Warehousing are the activities involved in the design and operation of warehouses A warehouse is the point in the supply chain where raw materials, work in process (WIP), or finished goods

More information

Dynamic Vehicle Routing and Dispatching

Dynamic Vehicle Routing and Dispatching Dynamic Vehicle Routing and Dispatching Jean-Yves Potvin Département d informatique et recherche opérationnelle and Centre interuniversitaire de recherche sur les réseaux d entreprise, la logistique et

More information

New Tool for Aiding Warehouse Design Process

New Tool for Aiding Warehouse Design Process New Tool for Aiding Warehouse Design Process Chackelson C 1, Errasti A, Santos J Abstract Warehouse design is a highly complex task, due to both the large number of alternative designs and the strong interaction

More information

AN EXPERIMENTAL STUDY OF THE IMPACT OF WAREHOUSE PARAMETERS ON THE DESIGN OF A CASE-PICKING WAREHOUSE

AN EXPERIMENTAL STUDY OF THE IMPACT OF WAREHOUSE PARAMETERS ON THE DESIGN OF A CASE-PICKING WAREHOUSE AN EXPERIMENTAL STUDY OF THE IMPACT OF WAREHOUSE PARAMETERS ON THE DESIGN OF A CASE-PICKING WAREHOUSE Russell D. Meller University of Arkansas and Fortna Inc. Lisa M. Thomas University of Arkansas and

More information

DOCUMENT DE TRAVAIL

DOCUMENT DE TRAVAIL Publié par : Published by: Publicación de la: Édition électronique : Electronic publishing: Edición electrónica: Disponible sur Internet : Available on Internet Disponible por Internet : Faculté des sciences

More information

Automated Materials Handling and Picking Solutions

Automated Materials Handling and Picking Solutions Automated Materials Handling and Picking Solutions Company profile Who is Diamond Phoenix Automation? With over 50 years of experience Diamond Phoenix Automation is one of the leaders in the design, integration

More information

Minimizing order picking distance through the storage allocation policy. Vadim Smyk

Minimizing order picking distance through the storage allocation policy. Vadim Smyk Minimizing order picking distance through the storage allocation policy Vadim Smyk Master s Thesis International Business Management 2018 DEGREE THESIS Arcada Degree Programme: International Business Management

More information

Case study: Corep Corep s warehouse solution shines bright

Case study: Corep Corep s warehouse solution shines bright Case study: Corep Corep s warehouse solution shines bright Location: France Corep, a principal light fixture manufacturer, has a warehouse that is sectored and equipped with pallet racking in its production

More information

Achieving Better Warehouse Management:

Achieving Better Warehouse Management: Achieving Better Warehouse Management: icepts Technology Group, Inc. Warehouse Management Systems are becoming more popular as supply chain logistics become ever more complication along with increasing

More information

OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS. Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez

OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS. Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez OPERATIONAL-LEVEL OPTIMIZATION OF INBOUND INTRALOGISTICS Yeiram Martínez Industrial Engineering, University of Puerto Rico Mayagüez Héctor J. Carlo, Ph.D. Industrial Engineering, University of Puerto Rico

More information

Picker routing and storage-assignment strategies for precedence-constrained order picking

Picker routing and storage-assignment strategies for precedence-constrained order picking Picker routing and storage-assignment strategies for precedence-constrained order picking Ivan šulj Christoph H. Glock Eric H. Grosse Michael Schneider Ÿ June 21, 2017 Abstract Order picking describes

More information

Modeling and Analysis of Automated Storage and Retrievals System with Multiple in-the-aisle Pick Positions

Modeling and Analysis of Automated Storage and Retrievals System with Multiple in-the-aisle Pick Positions University of Central Florida Electronic Theses and Dissertations Doctoral Dissertation (Open Access) Modeling and Analysis of Automated Storage and Retrievals System with Multiple in-the-aisle Pick Positions

More information

Building a Omni- Channel Distribution Center A Case Study

Building a Omni- Channel Distribution Center A Case Study Building a Omni- Channel Distribution Center A Case Study Sponsored by: Presented by: Chris Castaldi Allen Sisk Marc Teychene 2015 MHI Copyright claimed for audiovisual works and sound recordings of seminar

More information

Storage and Retrieval Cycle

Storage and Retrieval Cycle Storage and Retrieval Cycle A storage and retrieval (S/R) cycle is one complete roundtrip from an port to slot(s) and back to the Type of cycle depends on load carrying ability: Carrying one load at a

More information

Aisle Configurations for Unit-Load Warehouses

Aisle Configurations for Unit-Load Warehouses Aisle Configurations for Unit-Load Warehouses Kevin R. Gue Department of Industrial & Systems Engineering Auburn University Auburn, Alabama 36849 kevin.gue@auburn.edu Russell D. Meller Department of Industrial

More information

On Storage Assignment Policies for Unit-Load Automated Storage and Retrieval Systems

On Storage Assignment Policies for Unit-Load Automated Storage and Retrieval Systems On Storage Assignment Policies for Unit-Load Automated Storage and Retrieval Systems Jean-Philippe Gagliardi Jacques Renaud Angel Ruiz June 2010 CIRRELT-2010-25 Bureaux de Montréal : Bureaux de Québec

More information

Profitable Distribution System Design Part I

Profitable Distribution System Design Part I White Paper Profitable Distribution System Design Part I By John T. Giangrande Senior Account Executive www.fortna.com This report is provided to you courtesy of Fortna Inc., a leader in designing, implementing

More information

Flexibility in storage assignment in an e-commerce fulfilment environment

Flexibility in storage assignment in an e-commerce fulfilment environment Eindhoven, August 2013 Flexibility in storage assignment in an e-commerce fulfilment environment by Tessa Brand BSc Industrial Engineering TU/e 2011 Student identity number 0640072 in partial fulfilment

More information

Time Based Modeling of Storage Facility Operations

Time Based Modeling of Storage Facility Operations Clemson University TigerPrints All Dissertations Dissertations 8-2016 Time Based Modeling of Storage Facility Operations Nadeepa Devapriya Wickramage Clemson University Follow this and additional works

More information

Proven Strategies to Increase Productivity and Deal with Slow Movers

Proven Strategies to Increase Productivity and Deal with Slow Movers Proven Strategies to Increase Productivity and Deal with Slow Movers Sponsored by: Presented by: Allan Kohl, President 2013 MHI Copyright claimed as to audiovisual works of seminar sessions and sound recordings

More information

The Pennsylvania State University. The Graduate School. College of Engineering MODIFICATION OF THE ORDER PICKING AND REPLENISHMENT POLICY IN A

The Pennsylvania State University. The Graduate School. College of Engineering MODIFICATION OF THE ORDER PICKING AND REPLENISHMENT POLICY IN A The Pennsylvania State University The Graduate School College of Engineering MODIFICATION OF THE ORDER PICKING AND REPLENISHMENT POLICY IN A DISTRIBUTION CENTER A Thesis in Industrial Engineering and Operations

More information

ON STORAGE ASSIGNMENT POLICIES FOR UNIT-LOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEMS

ON STORAGE ASSIGNMENT POLICIES FOR UNIT-LOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEMS ON STORAGE ASSIGNMENT POLICIES FOR UNIT-LOAD AUTOMATED STORAGE AND RETRIEVAL SYSTEMS Jean-Philippe Gagliardi 1,2, Jacques Renaud 1,2,* & Angel Ruiz 1,2 1 Interuniversity Research Center on Enterprise Networks,

More information

AGI - WMS Overview. AGI Worldwide Warehouse Solutions

AGI - WMS Overview. AGI Worldwide Warehouse Solutions AGI - WMS Overview In today s rapidly changing business environment, successful supply chain management relies on accurate and instantaneous information. The ability to deliver the right product to the

More information

A Genetic Algorithm for Order Picking in Automated Storage and Retrieval Systems with Multiple Stock Locations

A Genetic Algorithm for Order Picking in Automated Storage and Retrieval Systems with Multiple Stock Locations IEMS Vol. 4, No. 2, pp. 36-44, December 25. A Genetic Algorithm for Order Picing in Automated Storage and Retrieval Systems with Multiple Stoc Locations Yaghoub Khojasteh Ghamari Graduate School of Systems

More information

Picker routing and storage-assignment strategies for precedence-constrained order picking

Picker routing and storage-assignment strategies for precedence-constrained order picking Picker routing and storage-assignment strategies for precedence-constrained order picking Ivan šulj Christoph H. Glock Eric H. Grosse Michael Schneider Ÿ May 15, 2018 Abstract Order picking describes the

More information

Case study: 3LP S.A. Mecalux equips one of the largest logistics centers in Poland

Case study: 3LP S.A. Mecalux equips one of the largest logistics centers in Poland Case study: 3LP S.A. Mecalux equips one of the largest logistics centers in Poland Location: Poland 3LP S.A., the logistics operator of the TIM company, has a huge logistics center in the Polish city of

More information

Twice the work, half the time

Twice the work, half the time Twice the work, half the time Industrial manufacturer Gardner Denver enjoyed a 100% increase in picking productivity and a 50% reduction in labor hours by combining new and aftermarket business in a horizontal

More information

AUTOMATIC ORDERPICKING

AUTOMATIC ORDERPICKING AUTOMATIC ORDERPICKING TREND OR ONLY A NICHE APPLICATION Jan van der Velden Logimat 02-02-2005 Slide 1, draft logimat 10-01-2005 Jan van der Velden l CONTENT l Introduction Man-to-goods systems Goods-to-man

More information

Order Fulfillment Systems

Order Fulfillment Systems Order Fulfillment Systems Honeywell Intelligrated Order Fulfillment Systems Software Intelligence That Delivers Honeywell Intelligrated draws on decades of experience and hundreds of installations to provide

More information

Travel Models for Warehouses with Task Interleaving

Travel Models for Warehouses with Task Interleaving Proceedings of the 2008 Industrial Engineering Research Conference J. Fowler and S. Mason, eds. Travel Models for Warehouses with Task Interleaving Letitia M. Pohl and Russell D. Meller Department of Industrial

More information

Dispen-SI-matic and Mobile-matic Easton, Pennsylvania

Dispen-SI-matic and Mobile-matic Easton, Pennsylvania Dispensing Technologies Dispen-SI-matic and Mobile-matic e x t e n s i v e e x p e r i e n c e i n s o lv i n g m at e r i a l f l o w c h a l l e n g e s 800-523-9464 www.sihs.com Easton, Pennsylvania

More information

Layout design analysis for the storage area in a distribution center.

Layout design analysis for the storage area in a distribution center. University of Louisville ThinkIR: The University of Louisville's Institutional Repository Electronic Theses and Dissertations 5-2009 Layout design analysis for the storage area in a distribution center.

More information

Blackwood Greystanes DC Lifting Order Picking Productivity, Accuracy, & Safety with GTP. Darren Rawlinson, Solutions Manager, Dematic

Blackwood Greystanes DC Lifting Order Picking Productivity, Accuracy, & Safety with GTP. Darren Rawlinson, Solutions Manager, Dematic Productivity & Collaboration Blackwood Greystanes DC Lifting Order Picking Productivity, Accuracy, & Safety with GTP Darren Rawlinson, Solutions Manager, Dematic Blackwoods Greystanes D.C. Lifting order

More information

WMS Best Practices Top Ten List

WMS Best Practices Top Ten List WMS Best Practices Top Ten List David Letterman Top Ten List Top 10 reasons to adopt WMS best practices Reason 10 Your receiving backlog is so bad you haven t seen the dock floor since 1974 Advanced shipping

More information

Warehousing Systems Design

Warehousing Systems Design Warehousing Systems Design Marc Goetschalckx, Doug Bodner, T. Govindaraj, Leon McGinnis, Gunter Sharp, Lei Tian Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332-0205

More information

1 D Multiple Region Expected Distance

1 D Multiple Region Expected Distance 1 D Multiple Region Expected Distance A A A B B B B I/O I/Oʹ 0 3 7 X A, X B X B A SC A A d d X 3 d di/o to I/ O XB In 1 D, easy to determine the offset In 2 D, no single offset value for each region d

More information

How to Model your Goods-to-Person System for Higher Picking Performance

How to Model your Goods-to-Person System for Higher Picking Performance How to Model your Goods-to-Person System for Higher Picking Performance Sponsored by: Presented by: Dave Simpson Director of Applications Engineering 2013 MHI Copyright claimed as to audiovisual works

More information

Improvement order picking in mobile storage systems with a middle cross aisle

Improvement order picking in mobile storage systems with a middle cross aisle International Journal of Production Research, Vol. 47, No. 4, 15 February 2009, 1089 1104 Improvement order picking in mobile storage systems with a middle cross aisle KUAN-YU HUy, TIEN-HSIANG CHANGz,

More information

Aisle Configurations for Unit-Load Warehouses

Aisle Configurations for Unit-Load Warehouses Aisle Configurations for Unit-Load Warehouses Kevin R. Gue Department of Industrial & Systems Engineering Auburn University Auburn, Alabama 36849 kevin.gue@auburn.edu Russell D. Meller Department of Industrial

More information

Order batching and picking optimization in terms of supply chain management (SCM)

Order batching and picking optimization in terms of supply chain management (SCM) Retrospective Theses and Dissertations 2004 Order batching and picking optimization in terms of supply chain management (SCM) Jaeyeon Won Iowa State University Follow this and additional works at: http://lib.dr.iastate.edu/rtd

More information

Impressum ( 5 TMG) Herausgeber: Fakultät für Wirtschaftswissenschaft Der Dekan. Verantwortlich für diese Ausgabe:

Impressum ( 5 TMG) Herausgeber: Fakultät für Wirtschaftswissenschaft Der Dekan. Verantwortlich für diese Ausgabe: WORKING PAPER SERIES Impressum ( 5 TMG) Herausgeber: Otto-von-Guericke-Universität Magdeburg Fakultät für Wirtschaftswissenschaft Der Dekan Verantwortlich für diese Ausgabe: Otto-von-Guericke-Universität

More information

GAINING EFFICIENCIES WITHIN THE WAREHOUSE. Setting Up Your Warehouse for Optimal Distribution

GAINING EFFICIENCIES WITHIN THE WAREHOUSE. Setting Up Your Warehouse for Optimal Distribution GAINING EFFICIENCIES WITHIN THE WAREHOUSE Setting Up Your Warehouse for Optimal Distribution TABLE OF CONTENTS INTRODUCTION 3 SPACE UTILIZATION BIN CHARACTERISTICS LAYOUT CONSIDERATIONS CROSS DOCK IF POSSIBLE

More information

Simulation based Performance Analysis of an End-of-Aisle Automated Storage and Retrieval System

Simulation based Performance Analysis of an End-of-Aisle Automated Storage and Retrieval System Simulation based Performance Analysis of an End-of-Aisle Automated Storage and Retrieval System Behnam Bahrami, El-Houssaine Aghezzaf and Veronique Limère Department of Industrial Management, Ghent University,

More information

Lean Distribution. Mark Kushner, COO Lloyed Lobo, Director Business Development

Lean Distribution. Mark Kushner, COO Lloyed Lobo, Director Business Development Lean Distribution Mark Kushner, COO Lloyed Lobo, Director Business Development Agenda Brief Company Overview What is Lean? Lean in the Extended Supply Chain Benefits of Lean Distribution Can Lean Help

More information

CHAPTER 3 FLOW, SPACE, AND ACTIVITY RELATIONSHIPS. In determining the requirement of a facility, three important consideration are: Flow

CHAPTER 3 FLOW, SPACE, AND ACTIVITY RELATIONSHIPS. In determining the requirement of a facility, three important consideration are: Flow 1 CHAPTER 3 FLOW, SPACE, AND ACTIVITY RELATIONSHIPS Asst.Prof.Dr.BusabaPhruksaphanrat IE333 Industrial Plant Design Introduction 2 In determining the requirement of a facility, three important consideration

More information

Warehouse Operations. Putaway

Warehouse Operations. Putaway Warehouse Operations 195 ing Putaway Putaway Warehouse Management System WMS interfaces with a corporation s enterprise resource planning (ERP) and the control software of each MHS Inventory Master File

More information

E-Commerce is entering a new dimension. Are your conveyors and sorters ready for the challenge?

E-Commerce is entering a new dimension. Are your conveyors and sorters ready for the challenge? E-Commerce is entering a new dimension. Are your conveyors and sorters ready for the challenge? Sponsored by: Presented by: Stephen Cwiak, Interroll Tim Kraus, Intelligrated 2015 MHI Copyright claimed

More information

Analysis of AS/RS travel times in class-based storage environment through a simulation approach

Analysis of AS/RS travel times in class-based storage environment through a simulation approach Analysis of AS/RS travel times in class-based storage environment through a simulation approach MAURIZIO SCHENONE, GIULIO MANGANO, SABRINA GRIMALDI Department of Management and Production Engineering Politecnico

More information

Increase Productivity, Improve Picking Accuracy And Reduce Costs With Warehouse Navigation

Increase Productivity, Improve Picking Accuracy And Reduce Costs With Warehouse Navigation Increase Productivity, Improve Picking Accuracy And Reduce Costs With Warehouse Navigation Sponsored by: Presented by: Perry Ardito Greg Mason 2013 MHI Copyright claimed as to audiovisual works of seminar

More information

modern system report Canada s largest retailer has built the country s largest distribution center, handling enough product to fill more

modern system report Canada s largest retailer has built the country s largest distribution center, handling enough product to fill more Canada s largest retailer has built the country s largest distribution center, handling enough product to fill more than,000 trailers a year. By Bob Trebilcock, Executive Editor Despite its name, no tires

More information

DATASCOPE WMS FOR SYSPRO MODEL BASED IMPLEMENTATIONS

DATASCOPE WMS FOR SYSPRO MODEL BASED IMPLEMENTATIONS MODEL BASED IMPLEMENTATIONS MODEL BASED IMPLEMENTATIONS These standard DATASCOPE implementation models have been created over time to offer a range of standard implementation approaches that are proven

More information

May The Force Be With You

May The Force Be With You May The Force Be With You White Paper As the human workforce ages and shrinks, automated storage and retrieval systems can help to maximize warehouse associates productivity levels while reducing overall

More information

modern system report Deon Wagner, director of warehouse operations, Oriental Trading Company.

modern system report Deon Wagner, director of warehouse operations, Oriental Trading Company. Oriental Trading PHOTOGRAPHY BY BLAINE FISHER/GETTY IMAGES Deon Wagner, director of warehouse operations, Oriental Trading Company. 16 S e p t e m b e r 2 0 1 1 / Modern Materials Handling mmh.com Company

More information

MTTN L3 Activity profiling MTTN25 Warehousing and Materials Handling. Warehousing and Materials Handling 1. Content. Learning objectives

MTTN L3 Activity profiling MTTN25 Warehousing and Materials Handling. Warehousing and Materials Handling 1. Content. Learning objectives L3 Activity profiling MTTN25 Warehousing and Materials Handling Warehousing and Materials Handling Tools & Techniques Optimization models Pick-paths Inclusion of SKU in FPA Lane depth & slotting Layout

More information

accuracy. operations: This white storage and Possible How much paper, then marking the order fulfillment

accuracy. operations: This white storage and Possible How much paper, then marking the order fulfillment 5 Ways To Increase Profit With Simple Picking Automation White Paper Increase your operation s profitability through improvements in inventory accessibility, floor space, time, improved ergonomics and

More information