Order picking optimisation on a unidirectional cyclical picking line

Thesis (PhD)--Stellenbosch University, 2020.ENGLISH SUMMARY : The order picking system in a company's distribution centre is the biggest contributor to the operational cost within the DC. Optimisation should thus aim at running this activity as effciently as possible. The order picking process consists of three main activities, namely walking to the stock, picking stock in fullment of a customer order and handling the picked stock for further processing. While the total amount of work for the picking and handling activities remain constant, the minimisation of walking distance becomes the main objective when minimising the total picking effort. The minimisation of walking distance can be translated into a reduced overall picking time which can lead to a decrease in the total cost of operating the picking system. The main objective of this dissertation is to optimise the order picking system on a unidirectional cyclical picking line. Order batching is introduced to the picking system, since it is an effective methodology that minimises walking distance in operations research literature. Order batching has been introduced to the standard single block parallel-aisle warehouse layout, but not to the specic layout of a unidirectional cyclical picking line. Additionally, the unidirectional cyclical picking line can offer two conguration options that change the physical set up and thereby inffuence the way in which pickers walk during the order picking process. Order batching is introduced to the unidirectional cyclical picking line through picking location based order-to-route closeness metrics. These metrics are further extended by taking the characteristics of the layout into account. The distribution centre of a prominent South African retailer provides real life test instances. Introducing the layout specic stops non-identical spans metric in combination with the greedy smallest entry heuristic results in a reduction of 48:3% in walking distance. Order batching increases the pick density which may lead to higher levels in picker congestion. In a discrete event simulation, the reduction of the overall picking time through a decrease in walking distance is thus conrmed. On tested sample picking waves, the overall picking time can be reduced by up to 21% per wave. A good number of pickers in the picking system is dependent on the pick density. The pick density, amongst other explanatory variables, can also be used to predict the reduction in picking time. The effects of different structural options of the unidirectional cyclical picking line, namely the U- and Z-conguration, are investigated. This results in four decision tiers that have to be addressed while optimising the order picking system. The rst decision tier assigns stock to picking lines, the second arranges stock around a picking line, the third chooses the conguration and the last sequences the orders to be picked. Order batching is added as an additional layer. An increase in pick density benets the reduction of walking distance throughout the decision tiers and supports the choice of the U-conguration after evaluating different test instances. The total completion time of a picking wave can thus be reduced by up to 28% when compared to benchmark instances. The dissertation is concluded by suggesting further research directions.AFRIKAANSE OPSOMMING : Die opmaak van bestellings op 'n uitsoeklyn in 'n onderneming se distribusiesentrum is die grootste bydraer tot die bedryfskoste van 'n distribusiesentrum. Dit is dus belangrik om hierdie aktiwiteit so doeltreffend moontlik te maak. Die proses om bestellings op te maak bestaan uit drie hoofaktiwiteite, naamlik stap na die voorraad, uitsoek (kies en bymekaarsit) van die voorraad vir 'n bestelling en die pak van die gekose voorraad in kartonne vir verdere verwerking en verspreiding. Omdat die totale hoeveelheid werk vir die uitsoek- en hanteringsaktiwiteite konstant bly, word die vermindering van loopafstand die hoofdoelwit om die totale koste van hierdie proses te minimeer. Die minimering van loopafstand lei tot 'n vermindering in totale tyd om bestellings op te maak, wat op sy beurt weer lei tot 'n afname in die totale koste van die stelsel om bestellings op te maak. Die hoofdoel van hierdie proefskrif is om die stelsel vir die uitsoek van bestellings op 'n eenrigting sikliese uitsoeklyn te optimeer. Metodes vir die samevoeging of groepering (Eng.: batching) van bestellings (om gelyktydig opgemaak te word) word ontwikkel vir hierdie uitsoekstelsel aangesien operasionelenavorsingsliteratuur aantoon dat groepering van bestellings 'n effektiewe metode is om loopafstand te verminder. Groepering van bestellings is reeds gedoen vir die standaard blokuitleg van distribusiesentra, maar nie vir hierdie spesieke uitleg van 'n eenrigting sikliese uitsoeklyn nie. Daarbenewens het die eenrigting sikliese uitsoeklyn twee kongurasie-opsies wat die siese opstelling verander en sodoende die manier beinvloed waarop werkers tydens die uitsoekproses loop. Die groepering van bestellings word ontwikkel vir 'n eenrigting sikliese uitsoeklyn deur middel van 'n plek-gebaseerde maatstaf wat die nabyheid van bestellings se roetes meet. Hierdie maatstaf word verder uitgebrei deur die eienskappe van die uitleg in ag te neem. Regte voorbeelde van die probleem uit 'n distribusiesentrum van 'n prominente Suid-Afrikaanse kleinhandelaar word gebruik vir toetsing. Die ontwikkeling en implementering van 'n uitlegspesieke stop-nie identiese-strek-maatstaf in kombinasie met die gulsige kleinste-invoegingsheuristiek lei tot 'n vermindering van 48:3% in stapafstand. Die groepering van bestellings verhoog die digtheid van plekke waar werkers stop vir voorraad, wat kan lei tot ho er vlakke van kongestie vir werkers. 'n Diskrete-gebeurtenis-simulasie bevestig dat 'n afname in loopafstand ook 'n vermindering van die totale voltooiingstyd tot gevolg het. Met behulp van werklike historiese data kon die totale tyd vir die uitsoek van bestellings met tot 21% per golf verminder word. 'n Goeie aantal werkers in die uitsoekstelsel is afhanklik van die uitsoekdigtheid. Die uitsoekdigtheid en andere verklarende veranderlikes, kan ook gebruik word om die vermindering in totale tyd om bestellings op te maak, te voorspel. Die invloed van verskillende strukturele opsies van die eenrigting sikliese uitsoeklyn, naamlik die U- en Z-kongurasie, word ook ondersoek. Dit het tot gevolg dat vier besluitnemingsvlakke aangespreek moet word om die uitsoekstelsel te optimeer. Die eerste besluitnemingsvlak ken voorraad aan die uitsoeklyne toe, die tweede rangskik voorraad binne die uitsoeklyn, die derde kies die kongurasie van die lyn en die laaste kies die volgorde waarin die bestellings uitgesoek word. Groepering van bestellings word bygevoeg as 'n addisionele vlak. 'n Toename in werksdigtheid bevoordeel die vermindering van loopafstand deur die besluitvlakke en bevoordeel die U-kongurasie na evaluering van verskillende toetsdata. Die totale voltooiingstyd van 'n uitsoekgolf kan dus verminder word met tot 28% in vergelyking met eweknie voorbeelde. Die studie word afgesluit deur verdere navorsingsmoontlikhede voor te stel.Doctora

Design and optimization of an explosive storage policy in internet fulfillment warehouses

This research investigates the warehousing operations of internet retailers. The primary physical process in internet retail is fulfillment, which typically involves a large internet fulfillment warehouse (IFW) that has been built and designed exclusively for online sales and an accompanying parcel delivery network. Based on observational studies of IFW operations at a leading internet retailer, the investigations find that traditional warehousing methods are being replaced by new methods which better leverage information technology and efficiently serve the new internet retail driven supply chain economy. Traditional methods assume a warehouse moves bulk volumes to retail points where the bulks get broken down into individual items and sold. But in internet retail all the middle elements of a supply chain are combined into the IFW. Specifically, six key structural differentiations between traditional and IFW operations are identified: (i) explosive storage policy (ii) very large number of beehive storage locations (iii) bins with commingled SKUs (iv) immediate order fulfillment (v) short picking routes with single unit picks and (vi) high transaction volumes with total digital control. In combination, these have the effect of organizing the entire IFW warehouse like a forward picking area. Several models to describe and control IFW operations are developed and optimized. For IFWs the primary performance metric is order fulfillment time, the interval between order receipt and shipment, with a target of less than four hours to allow for same day shipment. Central to achieving this objective is an explosive storage policy which is defined as: An incoming bulk SKU is exploded into E storage lots such that no lot contains more than 10% of the received quantity, the lots are then stored in E locations anywhere in the warehouse without preset restrictions. The explosion ratio Ψo is introduced that measures the dispersion density, and show that in a randomized storage warehouse Ψoo\u3e0.40. Specific research objectives that are accomplished: (i) Develope a descriptive and prescriptive model for the control of IFW product flows identifying control variables and parameters and their relationship to the fulfillment time performance objective, (ii) Use a simulation analysis and baseline or greedy storage and picking algorithms to confirm that fulfillment time is a convex function of E and sensitive to Ǩ, the pick list size. For an experimental problem the fulfillment time decrease by 7% and 16% for explosion ratios ranging between Ψo=0.1 and 0.8, confirming the benefits of an explosive strategy, (iii) Develope the Bin Weighted Order Fillability (BWOF) heuristic, a fast order picking algorithm which estimates the number of pending orders than can be filled from a specific bin location. For small problems (120 orders) the BWOF performes well against an optimal assignment. For 45 test problems the BWOF matches the optimal in 28 cases and within 10% in five cases. For the large simulation experimental problems the BWOF heuristic further reduces fulfillment time by 18% for Ǩ =13, 27% for Ǩ =15 and 39% for Ǩ =17. The best fulfillment times are achieved at Ψo=0.5, allowing for additional benefits from faster storage times and reduced storage costs

Modelos de Picking, Routing, Layout y Slotting en la Gestión de Almacenes - una Revisión Sistemática de la Literatura

Cuatro Bases de Datos fueron exploradas, EBSCO, SCHOLAR, IEEE Explorer y SCOPUS, con el objetivo de identificar a lo largo de la literatura modelos de Picking, Routing, Layout y Slotting que han sido propuestos como aportes a la gestión de almacenes en publicaciones de Revistas Científicas. Se describen los modelos propuestos segmentados por cada una de estas temáticas así como un breve análisis cienciométrico

Modelos de Picking, Routing, Layout y Slotting en la Gestión de Almacenes - una Revisión Sistemática de la Literatura

Cuatro Bases de Datos fueron exploradas, EBSCO, SCHOLAR, IEEE Explorer y SCOPUS, con el objetivo de identificar a lo largo de la literatura modelos de Picking, Routing, Layout y Slotting que han sido propuestos como aportes a la gestión de almacenes en publicaciones de Revistas Científicas. Se describen los modelos propuestos segmentados por cada una de estas temáticas así como un breve análisis cienciométrico

Development of a warehouse slotting model to improve picking performance

Congestion during picking operations in warehouse with mixed aisles (narrow aisles and wide aisles) has rarely been studied in current literature in the context of warehouse slotting (i.e. arrangement of inventory in warehouse). This study aims at improving the picking efficiency of the Asmodee Canada Inc. warehouse. Using a combination of clustering slotting heuristics and popularity-based slotting heuristics, a re-slotting policy was developed. Furthermore, to provide a robust re-slotting with limited number of items moves, a healing technique based on urgency score was developed. Use of a process control chart to monitor the picking performance of Asmodee’s warehouse and hence to signal healing was suggested. Using picking simulation, we find that when the re-slotting heuristics is used, there is substantial reduction in distance travelled of up to 29% and waiting times due to congestion can be reduced by as much as 85%. The healing technique also decreased distance travelled and waiting times. However, as the number of items moved in healing constitute on average less than 5% of the items, such improvements are limited. The distance traveled was reduced by as high as 9.4% in some aggregated orders and waiting time reduction was as high as 29.1%. The techniques developed in this paper will help Asmodee Canada Inc. in improving their picking operations. It will also help to build better strategies for warehouses having mixed aisles, where in aisle congestion is an issue to consider while re-slotting

Order-picking workstations for automated warehouses

The FALCON (Flexible Automated Logistic CONcept) project aims at the development of a new generation of warehouses and distribution centers with a maximum degree of automation. As part of the FALCON project, this dissertation addresses the design and analysis of (automated) workstations in warehouses with an end-of-aisle order-picking system (OPS). Methods are proposed for architecting, quantifying performance, and controlling such a system. Four main topics are discussed in this dissertation. First, a modular architecture for an end-of-aisle OPS with remotely located workstations is presented. This architecture is structured into areas and operational layers. A hierarchical decentralized control structure is applied. A case of an industrial-scale distribution center is presented to demonstrate the applicability of the proposed architecture for performance analysis using the process algebra-based simulation language $\chi$ (Chi). Additionally, it is demonstrated how the architecture allows straightforward modification of the systems configurations, design parameters, and control heuristics. Second, a method to quantify the operational performance of order-picking workstations has been developed. The method is based on an aggregate modeling representation of the workstation using the EPT (Effective Process Time) concept. A workstation is considered in which a human picker is present to process one customer order at a time while products for multiple orders arrive simultaneously at the workstation. The EPT parameters are calculated from arrival and departure times of products using a sample path equation. Two model variants have been developed, namely for workstations with FCFS (First-Come-First-Serve) and for workstations with non-FCFS processing of products and orders. Both models have been validated using data from a real, operating workstation. The results show that the proposed aggregate modeling methodology gives good accuracy in predicting product and order flow time distributions. Third, the dissertation studies the design and control of an automated, remotely located order-picking workstation that is capable of processing multiple orders simultaneously. Products for multiple orders typically arrive out-of-sequence at the workstation as they are retrieved from dispersed locations in the storage area. The design problem concerns the structuring of product/order buffer lanes and the development of a mechanism that overcomes out-of-sequence arrivals of products. The control problem concerns the picking sequence at the workstation, as throughput deteriorates when a poor picking sequence is applied. An efficient control policy has been developed. Its performance is compared to a number of other picking policies including nearest-to-the-head, nearest neighbor, and dynamic programming. Subsequently, the resulting throughput and queue length distribution are evaluated under different settings. Insights for design considerations of such a system are summarized. Finally, the dissertation reflects on the findings from the proposed methods and uses them to come up with comprehensive design principles of end-of-aisle OPS with remotely located workstations. The various issues influencing the performance of such a system are highlighted. Moreover, the contribution of each proposed method with regards to these issues is delineated

A framework for personalized dynamic cross-selling in e-commerce retailing

Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and rating differences across users. The retail setting differs in that there are only records of transactions (in period X, customer Y purchased product Z). Instead of a range of explicit rating scores, transactions form binary datasets; 1-purchased and 0-not-purchased. This makes it a one-class collaborative filtering (OCCF) problem. Notwithstanding the existence of wider application domains of such an OCCF problem, very little work has been done in the retail setting. This research addresses this gap by developing an effective framework for dynamic cross-selling for online retailing. In the first part of the research, we propose an effective yet intuitive approach to integrate temporal information regarding a product\u27s lifecycle (i.e., the non-stationary nature of the sales history) in the form of a weight component into latent-factor-based OCCF models, improving the quality of personalized product recommendations. To improve the scalability of large product catalogs with transaction sparsity typical in online retailing, the approach relies on product catalog hierarchy and segments (rather than individual SKUs) for collaborative filtering. In the second part of the work, we propose effective bundle discount policies, which estimate a specific customer\u27s interest in potential cross-selling products (identified using the proposed OCCF methods) and calibrate the discount to strike an effective balance between the probability of the offer acceptance and the size of the discount. We also developed a highly effective simulation platform for generation of e-retailer transactions under various settings and test and validate the proposed methods. To the best of our knowledge, this is the first study to address the topic of real-time personalized dynamic cross-selling with discounting. The proposed techniques are applicable to cross-selling, up-selling, and personalized and targeted selling within the e-retail business domain. Through extensive analysis of various market scenario setups, we also provide a number of managerial insights on the performance of cross-selling strategies

Design of an MAV for the 2019 SAE Aero Design Competition

The goal of this project was to design a Fixed-Wing Micro Aerial Vehicle in compliance with the rules of the Society of Automotive Engineers 2019 Aero Design Competition. These rules included carrying a payload of 2 inch inner diameter PVC pipe, fitting the unassembled aircraft within a box of dimensions 12.125” x 3.625”x 13.875”, and assembling the aircraft in under 3 minutes. The project team conducted analysis and testing in the areas of aircraft structures, stability and controls, aerodynamics, and propulsion. The final aircraft was constructed with laser-cut plywood and balsa, monokote, carbon fiber, and 3D printed components, weighed 2 pounds unloaded and 3.85 pounds loaded, while still meeting all competition requirements