Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System

Guerrazzi, Emanuele; Mininno, Valeria; Aloini, Davide; Dulmin, Riccardo; Scarpelli, Claudio; Sabatini, Marco

doi:10.3390/su11143817

Cited by 10 publications

(6 citation statements)

References 30 publications

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“…These observations clearly show that there exists a lack of research investigating integrated warehouses considering both forward and reserve areas, including those with AS/RS and forklifts. [23] Cycle time and waiting time Analytical model [24] Cost and throughput DOE [11] Cycle time and EC - [25] GHG emissions - [26] Cycle time and EC Mathematical model and large neighborhood search [20] GHG emissions - [27] Travel time and cycle time Analytical model [28] Cycle time and throughput DOE [29] Cycle time and throughput DOE [21] Travel time and cost Mathematical model and Dijkstra algorithm [30] EC and energy recovering - [31] Throughput Analytical model [32] Travel time DOE [33] Travel time Analytical model [8] Cycle time, energy regeneration, and EC DOE AS/RS energy efficiency has become crucial in recent years for warehouses in order for them to become sustainable in all design factors in recent years [34]. In other words, a warehouse can be more sustainable by controlling AS/RS from an energy-aware per-spective [15].…”

Section: Literature Reviewmentioning

confidence: 99%

A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems

Jeon,

Ebrahimi,

Lee

2023

Sustainability

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For warehouses to be more sustainable and cost-effective, it is essential to consider energy consumption (EC) and order tardiness (OT) together in evaluating warehouse activities since improving both EC and OT at the same time is very demanding. While existing studies try to improve EC and OT, the current studies consider only either a reserve area or a forward area between the two major warehouse areas. Thus, this study proposes a simulation-based approach to assessing EC and OT when reserve and forward areas are considered together in one framework for different configurations of five important warehousing parameters: (i) number of forklifts, (ii) number of storage/retrieval (S/R) machines, (iii) number of automated storage/retrieval systems (AS/RS) input/output (I/O) points, (iv) order size, and (v) proportions of order flows through a reserve or forward area. In particular, we use real forklift movement and energy data for our simulation models to provide a more realistic analysis. By building the simulation model with the 25 full factorial experimental design, we analyze the results with analysis of variance (ANOVA). The resulting Pareto-optimal solutions show that less traffic flows through a reserve area can help improve both EC and OT while other factors have smaller or limited effects on the two responses. Also, the order flow factor has the largest effect on EC while order size has the largest effect on OT. The results from this study can help warehouse operators make informed decisions in considering and finding a trade-off between sustainability and customer satisfaction.

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Section: Literature Reviewmentioning

confidence: 99%

A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems

Jeon,

Ebrahimi,

Lee

2023

Sustainability

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“…Reference cycles will be also used in the model presented in this paper. Guerrazzi et al [38] considered the configuration of AVS/RS with energy recovery systems and combined travel time modeling with energy usage. Stöhr, Schadler, and Hafner [39] analyzed the energy efficiency of diverse AS/RS, providing a detailed methodology and values for AS/RS energy consumption, which is partially used in this study.…”

Section: Materials Handling Systems and Related Energy Consumptionmentioning

confidence: 99%

Energy Consumption in a Distributional Warehouse: A Practical Case Study for Different Warehouse Technologies

2021

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Energy consumption by distribution warehouses has become an essential component of green warehousing and research on reducing the carbon footprint of supply chains. Energy consumption in warehousing is a complex and multilayered problem, which is generally considered in the literature in relation to its detailed components, not as part of comparative studies. In this article, the authors consider six cross-sectional variants of warehouse technology, from manual to fully automatic, and analyze the energy consumption of a warehouse in various configurations. A methodology for estimating storage space and determining energy consumption is proposed. The energy balance of the warehouse variants includes energy for material handling equipment operation, energy consumption for building maintenance (heating, cooling, lighting, etc.), and energy generated by the photovoltaic system on the roof. Then, the operational costs of the variants are estimated and, on their basis, an automation index is determined. The index allows for a comparative analysis of energy consumption and the mechanization and automation of a warehouse. It is shown that a significant part of the energy is spent on maintaining a warehouse building, especially in the case of facilities with a low degree of automation.

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“…D'Antonio et al proposed an analytical model which is used to calculate the cycle time and evaluate its deviation [27]. Guerrazzi et al developed a simulator able to emulate the operation of the warehouse, considering travel-time and energy model [28]. The number of research articles on AS/SC warehouse systems is limited.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling of Parallel Movement for Deep-Lane Unit Load Autonomous Shuttle and Stacker Crane Warehousing Systems

et al. 2020

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The autonomous shuttle and stacker crane (AC/SC) warehousing system, as a new automated deep-lane unit load storage/retrieval system, has been becoming more popular, especially for batch order fulfilment because of its high flexibility, low operational cost and improved storage capacity. This system consists of a shuttle sub-system that controls motion along the x-axis and a stacker crane sub-system that controls motion along the y-axis and z-axis. The combination of shuttles and a stacker crane performs storage and retrieval tasks. Modelling the parallel motion is an important design tool that can be used to calculate the optimal number of shuttles for a given configuration of the warehousing system. In this study, shuttle movements from one lane to another are inserted into the stock-keeping unit (SKU) task queue, and convert such that they are consistent with the retrieval tasks. The tasks are then grouped according to their starting lane, and converted to an assembly-line parallel job problem by analysing the operating mode with the objectives of minimising the total working time of the stacker crane and the wasted shuttle time. A time sequence mathematical model based on the motion of the shuttles and stacker crane is proposed, and an improved Pareto-optimal elitist non-dominated sorting genetic algorithm is used to solve this multi-objective optimization problem. The model is validated via a simulation study, and via a real-world warehousing case study. We go on to describe guidelines for the layout and configuration of AS/SC warehousing systems, including the optimal number of shuttles and number of x-axis storage cells of lanes, which can improve efficiency and minimise both capital investment and operating costs.

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Energy Evaluation of Deep-Lane Autonomous Vehicle Storage and Retrieval System

Cited by 10 publications

References 30 publications

A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems

A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems

Energy Consumption in a Distributional Warehouse: A Practical Case Study for Different Warehouse Technologies

Modeling of Parallel Movement for Deep-Lane Unit Load Autonomous Shuttle and Stacker Crane Warehousing Systems

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