Hybrid order picking: A simulation model of a joint manual and autonomous order picking system

Winkelhaus, Sven; Zhang, Minqi; Grosse, E. H.; Glock, C. H.

doi:10.1016/j.cie.2022.107981

Cited by 37 publications

(13 citation statements)

References 46 publications

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“…The number of sheets received is the same according to the production batch and color type. By consulting the literature, it can be seen that Winkelhaus et al (2022) reached basically the same conclusion by studying the different characteristics and parameters of hybrid order picking systems. The results showed that the throughput and total costs can be improved generally compared with the picking method of traditional pure manual (Winkelhaus et al 2022).…”

Section: Comparative Analysis Of Panel Picking Quantitymentioning

confidence: 67%

Investigation on panel material picking technology for furniture in automated raw material warehouses

Niu

Xiong

2022

BioRes

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The integrated development of the global economy has prompted the manufacturing industry of China to enter the era of intelligence, and manufacturing in the furniture manufacturing industry has gradually realized the transformation and upgrading from manual or semi-automation to automation and informatization. The traditional storage mode of receiving materials has been unable to coordinate and match the efficiency of its upstream supply and downstream processing. In order to coordinate production, reduce management costs, and achieve zero inventory, this paper integrates the common needs of the market, enterprises, actual production, and storage conditions. In addition, it designs a technical solution for the collection of sheet materials in furniture enterprises based on the environment foundation of automated three-dimensional warehouses. The research results show that the collation algorithm proposed in this study can reduce the amount of sheet material collated by 152 sheets, improve the pallet utilization rate by up to 21.6%, and increase the storage space utilization rate by up to 22.7%.

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Section: Comparative Analysis Of Panel Picking Quantitymentioning

confidence: 67%

Investigation on panel material picking technology for furniture in automated raw material warehouses

Niu

Xiong

2022

BioRes

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“…GTP represents an automated system that integrates an AMR and an Automated Storage and Retrieval System (AS/RS) to increase the efficiency of MH activities in logistics centers. In some ways, this technology is an upgrade to AS/RS, which, in addition to automatic storage and retrieval, also performs order-picking activities [102,103]. By applying CWMS, goods are stored in predefined locations, from which they are picked up and automatically transported directly to the picker, eliminating unnecessary movement time and providing accurate stock data [84,102].…”

Section: Defining Alternative Smart Solutionsmentioning

confidence: 99%

“…The pick-up-delivery station, as one of the most responsible entities in MH, can have a classic configuration with only a monitor and scanner, but it can also be supported by Pick by Vision technology and scales, and can be equipped with packaging material and other equipment for finalizing warehouse assignment. The mentioned and other demanding tasks can be effectively performed by engaging AI and AR technologies, thus providing employees with timely information about the goods they handle [99,[102][103][104]. In this way, repetitive and frequent activities are minimized to the point of elimination, and the abilities and skills of the employees are directed toward the improvement of the MH process, thus contributing to more efficient customer service [103,104].…”

Section: Defining Alternative Smart Solutionsmentioning

confidence: 99%

Smart Material Handling Solutions for City Logistics Systems

et al. 2023

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Globalization, the growth of the world population, urbanization and the growth of the volume of the flow of goods have generated numerous problems in city logistics (CL). The opportunity to solve them is found in various fields by defining and implementing initiatives, concepts, measures, modern technologies and scenarios. The efficiency of the solution largely depends on the efficiency of logistics centers, which is one of the key subsystems of CL. The requirements for the reliable delivery of goods to customers in urban areas are conditioned by the efficiency their order fulfillment in logistics centers. Therefore, optimizing material handling (MH) time and costs aimed at reducing delivery errors, minimizing damage to goods and increasing customer service efficiency is directly conditioned by the automation of MH in logistics centers. Accordingly, this paper aims to rank and select smart MH solutions in logistics centers where deliveries are prepared for the supply of the city area. This paper proposes four smart solutions for a real company, and fourteen criteria are selected for the evaluation. A new hybrid Multi-Criteria Decision-Making model that combines the Fuzzy Analytic Hierarchy Process method, used to determine the criteria weights, and the Fuzzy COmprehensive distance-Based RAnking (FCOBRA) method, used to rank the alternatives, is proposed. The application of the model shows that the best alternative is the implementation of an autonomous forklift, which can greatly automate logistics activities and reduce the rate of delivery errors. The main contributions of this research are the definition of smart solutions, a framework for their evaluation and a new model for their ranking.

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“…In sog. hybriden Kommissioniersystemen hingegen teilen sich autonome mobile Lagerroboter und menschliche Kommissionierende die Arbeitsaufgaben kollaborativ, was zu Kosten-und Flexibilitätsvorteilen gegenüber rein manuellen oder automatisierten Systemen führen kann (Winkelhaus et al 2022b). Wie in der Transportlogistik gibt es auch in der Intralogistik Untersuchungen zum Einsatz von intelligenten Ladungsträgern (wie bspw.…”

Section: Forschungsschwerpunkte In Der Transportlogistik 40unclassified

Logistik 4.0: Stand der Forschung und Praxis

Grosse

2022

HMD

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ZusammenfassungViele Unternehmen stehen aktuell vor großen Herausforderungen aufgrund hoher Kundenansprüche für individualisierte Produkte, aber auch aufgrund des Fachkräftemangels, des demographischen Wandels, volatiler Lieferantenmärkte, der Auswirkungen auf die Versorgungssicherheit ausgelöst durch Krisen wie die Corona-Pandemie sowie hohe Energiepreise und Rohstoffknappheit. Die Transformation zur Logistik 4.0 wird hierbei oftmals als Möglichkeit genannt, die Herausforderungen in den Griff zu bekommen und verspricht einen entscheidenden Wettbewerbsvorteil. Der Forschungsstrang ist jedoch noch relativ jung und für viele Entscheider in der Praxis ist noch unklar, was sich hinter dem Begriff Logistik 4.0 konkret verbirgt und welche Chancen daraus für Unternehmen entstehen können. Daneben gibt es viele Barrieren, die Transformationsprozesse scheitern lassen. Dieser Artikel gibt einen Überblick über den Stand der Forschung zur Logistik 4.0 und diskutiert Implikationen für die Praxis für einen nachhaltig erfolgreichen Transformationsprozess.

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Hybrid order picking: A simulation model of a joint manual and autonomous order picking system

Cited by 37 publications

References 46 publications

Investigation on panel material picking technology for furniture in automated raw material warehouses

Investigation on panel material picking technology for furniture in automated raw material warehouses

Smart Material Handling Solutions for City Logistics Systems

Logistik 4.0: Stand der Forschung und Praxis

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