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Pallets ensure efficient processes in logistics and are exchanged between the different actors, while passing through various supply chains several times. In common practice, the exchange is often not directly carried out on site, e.g. due to a lack of time, so that additional trips and new pallet purchases become necessary. To reduce these negative effects, a digital cross-actor platform is designed, and its potential is investigated.

The authors developed an agent-based simulation model with mathematical optimization. Using experience from practitioners, as well as real-world datasets which were analyzed, the authors ensure a realistic model of the pallet exchange system in Germany.

The authors demonstrated that, with the help of this platform concept, transport routes can be shortened, debts and receivables can partly be equaled out through balancing, and the quantity of pallets in the overall system can be reduced.

The results are not directly transferable to pallet exchange systems in other countries without considering their general settings.

Digital networking increases the efficiency of the existing pallet exchange system. Even small collaborations prove to be reasonable.

The authors developed new mechanisms for a digital pallet exchange platform, which takes on the role of a central planning instance, in addition to recording pallet receivables and debts. It enables the planning of the commodity flow of empty pallets, which are transported by the forwarders on regular routes, and distributed between the platform participants.

This paper presents a comprehensive pallet-picking approach for forklift robots, comprising a pallet identification and localization algorithm (PILA) to detect and locate the pallet and a vehicle alignment algorithm (VAA) to align the vehicle fork arms with the targeted pallet.

Opposing vision-based methods or point cloud data strategies, we utilize a low-cost RGB-D camera, and thus PILA exploits both RGB and depth data to quickly and precisely recognize and localize the pallet. The developed method guarantees a high identification rate from RGB images and more precise 3D localization information than a depth camera. Additionally, a deep neural network (DNN) method is applied to detect and locate the pallet in the RGB images. Specifically, the point cloud data is correlated with the labeled region of interest (RoI) in the RGB images, and the pallet's front-face plane is extracted from the point cloud. Furthermore, PILA introduces a universal geometrical rule to identify the pallet's center as a “T-shape” without depending on specific pallet types. Finally, VAA is proposed to implement the vehicle approaching and pallet picking operations as a “proof-of-concept” to test PILA’s performance.

Experimentally, the orientation angle and centric location of the two kinds of pallets are investigated without any artificial marking. The results show that the pallet could be located with a three-dimensional localization accuracy of 1 cm and an angle resolution of 0.4 degrees at a distance of 3 m with the vehicle control algorithm.

PILA’s performance is limited by the current depth camera’s range (< = 3 m), and this is expected to be improved by using a better depth measurement device in the future.

The results demonstrate that the pallets can be located with an accuracy of 1cm along the x, y, and z directions and affording an angular resolution of 0.4 degrees at a distance of 3m in 700ms.

This paper seeks to frame and model the environmental issues and impacts associated with the management of pallets throughout the entire life cycle, from materials to manufacturing, use, transportation to end‐of‐life disposal.

A linear minimum cost multi‐commodity network flow problem is developed to make pallet‐related decisions based on both environmental and economic considerations.

This paper presents a review of the environmental impacts associated with pallets by life cycle stage. The types of materials used to fabricate pallets, the methods by which they are treated for specific applications, and various pallet management models are described with respect to embodied energies, toxicity and emissions. The need for companies to understand the cost, durability, and environmental impact tradeoffs presented by pallet choices is highlighted. The paper introduces a model to assist in choosing both how pallets are managed and the material they are constructed of that balances these tradeoffs.

There is limited research on the environmental impact of different management approaches of large‐scale pallet operations. The proposed model and approach will provide companies seeking to engage in more sustainable practices in their supply chains and distribution with insights and a decision‐making tool not previously available.

This study aims to present an automated guided logistics robot mainly designed for pallet transportation. Logistics robot is compactly designed. It could pick up the pallet precisely and transport the pallet up to 1,000 kg automatically in the warehouse. It could move freely in all directions without turning the chassis. It could work without any additional infrastructure based on laser navigation system proposed in this work.

Logistics robot should be able to move underneath and lift up the pallet accurately. Logistics robot mainly consists of two sub-robots, like two forks of the forklift. Each sub-robot has front and rear driving units. A new compact driving unit is compactly designed as a key component to ensure access to the narrow free entry of the pallet. Besides synchronous motions in all directions, the two sub-robots should also perform synchronous lifting up and laying down the pallet. Logistics robot uses a front laser to detect obstacles and locate itself using on-board navigation system. A rear laser is used to recognize and guide the sub-robots to pick up the pallet precisely within ± 5mm/1o in x-/yaw direction. Path planning algorithm under different constraints is proposed for logistics robot to obey the traffic rules of pallet logistics.

Compared with the traditional forklift vehicles, logistics robot has the advantages of more compact structure and higher expandability. It can realize the omnidirectional movement flexibly without turning the chassis and take zero-radius turn by controlling compact driving units synchronously. Logistics robot can move collision-free into any pallet that has not been precisely placed. It can plan the paths for returning to charge station and charge automatically. So it can work uninterruptedly for 7 × 24 h. Path planning algorithm proposed can avoid traffic congestion and improve the passability of the narrow roads to improve logistics efficiencies. Logistics robot is quite suitable for the standardized logistics factory with small working space.

This is a new innovation for pallet transportation vehicle to improve logistics automation.

This paper presents an investigation on the development of different pattern placement strategies in robotic palletisation of box packages in the packaging industry with practical implementations for one, two, four and five block patterns with the aim of improving the operational efficiency in robotic palletisation.

The work involves considering the gripper design and maximum number of picks and various process parameters that affect the robotic implementation of pallet patterns and develops a methodology to form different patterns for a given pallet size.

The proposed methodology represents an efficient approach for pallet pattern implementation and results in reduced number of placements required for a given number of boxes per layer and reduced time for palletisation.

The paper introduces a novel technique for pallet loading problem (PLP) considering the physical aspects and restrictions encountered when using the robot and the gripper size to generate the pattern on the pallet. Traditional solutions of PLP do not consider these aspects in pattern placements.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

The success of the pallet began with the development of the fork‐lift truck and with increased mechanisation of piece‐good transport since the Second World War. This brought with it a world‐wide revolution in distribution which has still today not yet run its full course. Specialised educational faculties, technical magazines and industrial management positions have been established for the “TOTAL DISTRIBUTION CONCEPT” discipline since the latter part of the Sixties and there is talk of enormous unexploited rationalisation reserves in this field which commences at the end of the extraction or manufacturing process and terminates either with the subsequent processor or the final consumer.

The purpose of this paper is to quantitatively assess wood pallet suppliers' reaction to online reverse auctions and its impact on their business policies and practices.

Survey method was used to determine how pallet suppliers react to online reverse auctions.

Determines that pallet suppliers do not realize the benefits claimed by online reverse auction service providers. Identifies new sources of costs which accrue to buyers and are not accounted for in so‐called “total cost” request for quotes including: retaliatory pricing practices, less cooperative relationships, and sourcing work back to the original supplier. The qualitative benefits identified for suppliers by third‐party online reverse auction service providers are overstated or false.

The present work can be extended to other commodity categories to identify similarities and differences in how suppliers react to online reverse auctions, understand the domain of successful and unsuccessful application of the online reverse auction tool, and provide further insight into the evolution of buyer‐seller relationships, including embedded organizational routines such as power‐based bargaining.

Findings mirror the results found in a previous study that examined aerospace parts suppliers' reaction to online reverse auctions, and indicates that market makers have consistently overstated the benefits of online reverse auctions to both sellers and buyers, and the use of this tool will typically result in unfavorable outcomes for both buyers and sellers.

This paper will be of interest to buyers, sellers, and market makers, as it identifies important problems with online reverse auctions, and suggests questions that buyers should ask market makers to ensure better sourcing decisions.

The contemporary e-tailing marketplace insists that distribution centers are playing the roles of both wholesalers and retailers which require different storage-handling load sizes due to different product variants. To fulfill piecewise retail orders, a separate small size-fast pick area is design called “forward buffer” wherein pallets are allocated from reserve area. Due to non-uniform pallets, the static allocation policy diminishes forward space utilization and also, more than practically required buffer size has been identified as wastage. Thus, dynamic storage allocation policy is required to design for reducing storage wastage and improving throughput considering non-uniform unit load sizes. The purpose of this paper is to model such policy and develop an e-decision support system assisting enterprise practitioners with real-time decision making.

The research method is developed as a dynamic storage allocation policy and mathematical modeled as knapsack-based heuristics. The execution procedure of policy is explained as an example and tested with case-specific data. The developed model is implemented as a web-based support system and tested with rational data instances, as well as overcoming prejudices against single case findings.

The provided model considers variable size storage-handling unit loads and recommends number of pallets allocations in forward area reducing storage wastes. The algorithm searches and suggests the “just-right” amount of allocations for each product balancing existing forward capacity. It also helps to determine “lean buffer” size for forward area ensuring desired throughput. Sensitivity and buffer performance analysis is carried out for Poisson distributed data sets followed by research synthesis.

Warehouse practitioners can use this model ensuring a desired throughput level with least forward storage wastages. The model driven e-decision support system (DSS) helps for effective real-time decision making under complicated business scenarios wherein products are having different physical dimensions. It assists the researchers who would like to explore the emerging field of “lean” adoption in enterprise information and retail-distribution management.

The paper provides an inventive approach endorsing lean thinking in storage allocation policy design for a forward-reserve model. Also, the developed methodology incorporating features of e-DSS along with quantitative modeling is an inimitable research contribution justifying rational data support.

The study aims to compare and analyze the impact of the commonly used pallets (wooden pallet and plastic pallets), using life cycle assessment (LCA), then provide certain suggestions for the development of green packaging.

In this study, software Simapro was used to calculate and analyze the whole life cycle of pallets from the stage of raw materials and production to processing and waste disposal.

A total of 12 environmental categories were used to quantitatively analyze the environmental impact of the four different pallets. The results showed that, regardless of raw material, processing, or waste stage, the environmental impact of wooden pallet was lower than that of plastic pallet. Wooden pallet was better than plastic pallets.

This study compared and analyzed the pallet of 1 × 1.2m with different materials.

Green packaging is the development trend of the future packaging, which follows the principle of 3R1D. According to the calculation results, corresponding suggestions can be put forward from production, processing, using, wasting and other aspects, and make corresponding contributions to the development of green packaging.

The contribution and impact of each stage of the product on the environment can be studied. The environmental impact, such as global warming potential, water scarcity, can be reduced through different solutions such as the use of green materials, good processing techniques and higher recycling rates.