Design and optimization of order picking systems: An integrated procedure and two case studies

Bottani, Eleonora; Volpi, Andrea; Montanari, Roberto

doi:10.1016/j.cie.2019.106035

Cited by 25 publications

(17 citation statements)

References 62 publications

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“…There are many studies on OPS in the scientific literature. However, researchers usually focus on one selected factor influencing the OPS (Bottani et al, 2019;Ho and Lin 2017;Parikh and Meller 2010;Winkelhaus 2022, etc.), e.g. warehouse layout, also in terms of the amount of storage, allocation of storage places, picking or routing system.…”

Section: Introductionmentioning

confidence: 99%

Simulations in planning logistics processes as a tool of decision-making in manufacturing companies

Daroń

2022

Production Engineering Archives

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Appropriate logistics planning is a key factor influencing the quality and efficiency of processes in manufacturing companies. Logistics planning can be defined as the process of making significant decisions (concerning both logistics processes and resources) for the functioning of an organization. It is a process consisting of stages in which important decisions are made regarding the optimization of all activities of the company, including in the field of: production, supply, sales, distribution, transport. The main goal of logistics activities is to minimize the operating costs incurred, as well as to better manage human resources. The main aim of the article is to present the legitimacy of using selected simulation software as an actual tool in making logistic decisions in the field of order picking system (OPS) based on a case study. For research purposes, a model was prepared in FlexSim and there were applied S-shape and Return routing methods. Based on simulation results, an analysis of the selected process was carried out. The obtained results indicate possible directions of changes and allow to make the right decision in the field of planning logistics processes.

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Section: Introductionmentioning

confidence: 99%

Simulations in planning logistics processes as a tool of decision-making in manufacturing companies

Daroń

2022

Production Engineering Archives

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“…The key factors of optimal controlled storage functioning include, in particular (Bottani et al, 2019):…”

Section: Introductionmentioning

confidence: 99%

“…What is typical of zone picking is assignment of a worker to a certain fixed part of the warehouse (zone), where they pick parts of orders. During the sequence zone picking, they then pass a partially picked order to the next zone, while in the case of synchronised zone picking, the individual parts of orders are picked simultaneously in all zones and then usually consolidated via the sorting system (Bottani et al, 2019). Combining orders and picking them at the same time is typical of batch picking.…”

Section: Introductionmentioning

confidence: 99%

“…If we combine the options described above for each factor influencing the picking system efficiency, we will receive a large number of different configuration variants, each of which may theoretically be the most suitable for a particular distribution channel with a specific order composition and service level requirement, while at the same time leading to minimum warehouse operating costs. Bottani et al (2019) refer to dynamic simulation as to a suitable method to determine the effectiveness of a specific picking system layout. Simulation is a process of creating a logical-mathematical model of a real object, a system defined on it or a decision-making process and implementation of a large number of experiments with it, the purpose of which is to describe the system, recognise its function and estimate its future behaviour (Gros & Dyntar, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Effective Designing of Order Picking Systems Using Dynamic Simulation

Kašparová¹,

Dyntar²

2021

AIP

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In this article, we describe the use of dynamic simulation when designing an effective system for order picking within a distribution warehouse. The simulation model was created in the Witness software environment for discrete dynamic simulation and is a modification of a general simulation model of material flows in supplier systems. Using the example of a batch system for picking orders in a drugstore goods warehouse, we discuss the possibilities of using a general simulation model of material flows as an effective framework for the development of system support for warehouse processes using WMS. The simulation model is based on the possibility of dividing any material flow in the supply system into a finite number of movements with the possibility of using one of the sources and fulfilment of certain conditions. In order to achieve the required optimisation of the order picking system, which depends, in particular, on the unknown duration of goods collection at the picking location, and on the duration of goods sorting in consolidation, the "what-if" analysis has been used as a tool to measure the impact of uncertainty of one or more variables entering the model on the uncertainty of output variables. The study showed that minimisation of the number of physical elements in the model leads to a significantly higher speed of its operation. By means of dynamic simulation, it is possible to test a large number of variants of the picking system layout in a relatively short time and minimise the risk of erroneous decisions associated with the implementation of a suitable WMS.

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“…Inventory management has a big impact on logistics performance indices, especially for companies that want to save costs and enhance efficiency in their product preparation and delivery procedures [1]. In affluent countries, warehouses account for approximately 15% of total logistics expenses [2].…”

Section: Introductionmentioning

confidence: 99%

A Data Mining Practical Approach to Inventory Management and Logistics Optimization

Pujiarto

Hanafi

Setyawan

et al. 2021

IJIIS Int. J. Informatics Inf. Syst.

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The latent demand to optimize costs and customer service has been fostered in the current economic situations, characterized by high competitiveness and disruption in supply chains, placing inventories as a vital sector with significant potential to implement improvements in firms. Inventory management that is done correctly has a favorable impact on logistics performance indexes. Warehousing operations account for around 15% of logistics expenditures in terms of dollars. This article employs a method based on the Partitioning Around Medoids algorithm that incorporates, in a novel way, the application of a strategy for locating the optimal picking point based on cluster classification, taking into account the qualitative and quantitative factors that have the greatest impact or priority on inventory management in the company. The results obtained with this model improve the routes of distributed materials based on the identification of their characteristics such as the frequency of collection and handling of materials, allowing for the reorganization and expansion of storage capacity of the various SKUs, moving from a classification by families to a cluster classification. This article shows a suggestion for a warehouse distribution design using data mining techniques, which uses indicators and key qualities for operational success for a case study in a corporation, as well as an approach to improve inventory management decision-making.

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Design and optimization of order picking systems: An integrated procedure and two case studies

Cited by 25 publications

References 62 publications

Simulations in planning logistics processes as a tool of decision-making in manufacturing companies

Simulations in planning logistics processes as a tool of decision-making in manufacturing companies

Effective Designing of Order Picking Systems Using Dynamic Simulation

A Data Mining Practical Approach to Inventory Management and Logistics Optimization

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