Optimizing Retrieving Performance of an Automated Warehouse for Unconventional Stock Keeping Units

In recent years, the diffusion of automated warehouses in different industrial sectors has fostered the design of more complex automated storages and handling solutions. These circumstances, from a technological point of view, have led to the development of automated warehouses that are very different from the classic pallet Automated Storage and Retrieval Systems (AS/RS), both in terms of design and operating logic. A context in which these solutions have spread is the steel sector. Warehouses with innovative layouts and operating logics have been designed to move metal bundles of different sizes, weights and quality levels, instead of standard, interchangeable stock keeping units. Moreover, picking is often not allowed in these warehouses, due to the configuration of the loading units. In this work we propose a meta-heuristic algorithm based on the Simulated Annealing (SA) procedure, which aims to optimize performance during the retrieving phase of an automated warehouse for metal bundles. The algorithm translates the customers’ requests, expressed in terms of item code, quality and weight into a list of jobs. The goal is to optimize the retrieving performance, measured in missions per hour, minimizing the deviations in quality and weight between customer request and the material retrieved. For the validation, a simulation model of an existing warehouse has been created and the performance of the algorithm tested on the simulation model has been compared with the current performance of the warehouse

An approach for computing AS/R systems travel times in a class-based storage configuration

This study provides an approach to compute the travel time for AS/R systems in a class-based storage environment. A regression analysis is completed in order to define the importance of the key predictors taken into account and to propose a formulation of travel times. The results show the reliability of the model and allow to evaluate the travel time through the identification of a complete list of predictors. The proposed approach supports managers in theex-ante definition of travel times for a warehouse. A correct evaluation of travel times enables a better monitoring of the performance of warehouse operations and can support practitioners in the choice of the configuration not only in terms of kind of cycle, but also from a policy assignment perspective. From a theoretical point of view, this work can be considered as an attempt to refine the existing methods to compute travel times

An approach for computing AS/R systems travel times in a class-based storage configuration

This study provides an approach to compute the travel time for AS/R systems in a class-based storage environment. A regression analysis is completed in order to define the importance of the key predictors taken into account and to propose a formulation of travel times. The results show the reliability of the model and allow to evaluate the travel time through the identification of a complete list of predictors. The proposed approach supports managers in theex-ante definition of travel times for a warehouse. A correct evaluation of travel times enables a better monitoring of the performance of warehouse operations and can support practitioners in the choice of the configuration not only in terms of kind of cycle, but also from a policy assignment perspective. From a theoretical point of view, this work can be considered as an attempt to refine the existing methods to compute travel times

Design & Modeling of a Single Machine Flow Rack As/rs

In this paper, we aim to introduce a new variation of the flow rack automated storage and retrieval system (AS/RS) using a single machine for storage and retrieval operations instead of two machines. Also, analytical expressions are derived for expected single and dual cycle times of the storage and retrieval machine. For that, randomized storage assignment, and Tchebychev travel are assumed. Two dwell point positions are investigated and compared to determine the best one. Finally an experimental validation using simulation is conducted to verify the quality of the developed

Modelo predictivo-reactivo para el control de un sistema de recolección de productos en bodega (AS / RS)

Los entornos competitivos han obligado a las empresas a mejorar la administración de sus operaciones y evolucionar constantemente. Por esta razón, éstas basan su estrategia de competitividad erunarcadas en la implementación de nuevas tecnologías, el manejo de sus inventarios y la automatización de procesos, con la finalidad de mejorar su flujo logístico. Este trabajo presenta un modelo predictivo-reactivo para el control de un sistema de recolección de productos en bodega. Esta propuesta busca un control óptimo y reactivo de la recolección de los productos en inventario, creando una ventaja operativa capaz de competir con las demás organizaciones. Para construir el sistema de control propuesto, este trabajo de grado utiliza herramientas de optimización como heurísticas y metaheurísticas para buscar la optimización en objetivos globales, y utiliza una modelación de control distribuido para buscar la reactividad en perturbaciones o situaciones de necesidad. La validación de esta propuesta se realiza en un caso de estudio creado por los autores. Jgualmente, se presenta la evaluación del sistema realizado en un software de simulación basado en el paradigma de Multi-agentes.Competitive environments have forced companies to improve their operations management and evolve constantly. Thus, such enterprises base tbeir competitiveness strategies emphasi.zi.ng on the i.mplementation of advanced technologies, i.nventory management and process automatization. This paper presents a predictive- reactive model capable of controlli.ng an automated warehouse's product retrieval system. This work ai.ms to achieve an efficient and reactive control for the retrieval of inventory products, therefore providi.ng an operative advantage. The creation of the control system incorporated optimization tools sucb as beuristics and metaheuristics designed to find efficient solutions. Reactive responses to disturbances and complex situations were solved by a distributed control architecture. Additionally, a study case was created in order to validate the proposal througb a multi-agent-based model.Ingeniero (a) IndustrialPregrad

Automated Warehouse Systems: A Guideline for Future Research

This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios. We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from literature. Numerical experiments illustrate that when a company tends to have multiple short planning horizons with small task batches (i.e., aims to increase the responsiveness level), adding more shuttles is helpful. However, if a company has a long planning horizon with a large task batch size, having faster cranes is more efficient to reduce the makespan. We then focus on the impacts of the number of shuttles, operational mode, storage policies, and shuttle dispatching rules on the expected cycle time of a tier-to-tier shuttle-based storage and retrieval system. The system is modeled as a discrete-time Markov Chain to derive the shuttle distribution under each scenario create the expected travel time models. Numerical experiments indicate that class-based storage is always better than the random storage policy. The best shuttle dispatching rule under each combination of the number of shuttles, operational mode, and storage policy can be quickly identified through the expected cycle time models which are simple and computation friendly. At last, we study the warehouse design problem considering the choice, design, and operation of 2D AS/RS and 3D AS/RS in a systematic way. The warehouse design problem under consideration aims to reduce the investment while satisfying different business needs measured by the desired throughput capacity. We propose a branch-and-bound algorithm to conquer the computational challenges. With the developed algorithm, an optimal warehouse design can be obtained under different application environments, characterized by the desired throughput capacity, inventory level, and demand rate of each SKU

Problemas de conformación de lotes con ruteo en el acomodo y la preparación de pedidos considerando K equipos heterogéneos

Esta tesis doctoral tiene como objetivo modelar problemas de conformación de lotes con ruteo en el acomodo y la preparación de pedidos. En la preparación de pedidos, se modeló un problema que considera K equipos de materiales (EMMateriales) heterogéneos, n productos, m posiciones de almacenamiento y la condición de disponibilidad del inventario, lo cual permite superar las limitaciones detectadas en la literatura científica. De otra parte, al revisar el estado del arte del acomodo no se identificaron problemas que abordan la formación de lotes con ruteo, sino que únicamente solucionan el problema de asignación de posiciones de almacenamiento (Slotting). Para solucionar la conformación de lotes en cada uno de los problemas modelados, se desarrollaron reglas de prioridad y metaheurísticos basados en búsqueda local inteligente. En tanto, para resolver el ruteo se modelaron metaheurísticos de búsqueda tabú híbridos con estrategias de intensificación y diversificación. Las reglas y metaheurísticos para cada problema, se integraron a un WMS (Warehouse Management System) y fueron modelados considerando las características y restricciones particulares de estas operaciones del Centro de Distribución (CEDI). Diseños de experimentos (Designs of Experiment_DoE) de parcelas divididas no sólo fueron implementados para validar los problemas modelados sino también para realizar un análisis numérico exhaustivo que permitió identificar las combinaciones de niveles de los factores significativos que generan los menores tiempos promedios totales y la mayor eficiencia en el acomodo y la preparación de pedidos. El uso de diseños de parcelas divididas puede considerarse un aporte metodológico al estado del arte, ya que este enfoque no fue detectado en la literatura para resolver este tipo de problemas. A partir del análisis experimental se identificó que los metaheurísticos para la formación de lotes, INS (Intelligent Neighboorhood Search) y PNS (Picking Neighboorhood Search), generaron las mejores soluciones para el acomodo y la preparación de pedidos. De otra parte, los metaheurísticos híbridos RABTIN (Ruteo acomodo búsqueda tabú intensificación) y RUPBTDI (Ruteo preparación de pedidos búsqueda tabú diversificación) 3-Opt Inserción produjeron las mejores soluciones para el ruteo de estas operaciones.Abstract: The aim of doctoral thesis is to model and valid the order batching and routing problem in the putaway and picking operation. In the picking operation was modelled a problem, took in account K Material Handling Equipment, n products, m storage locations and a condition of available inventory. This approach contributed to overcome the gaps detected in the scientific literature. On the other hand, a significant contribution to the knowledge was achieved in the putaway operation since the batching and routing problems had not been detected in the systematic literature review (SLR) results. This is raised because the slotting problem was only approach identified for the putaway operation in the scientific literature. Priority rules and metaheuristics based on intelligent local search were developed to solve the order batching component in each modelled problem. Meanwhile, hybrid tabu search metaheuristics with intensification and diversification strategies were implemented to sort out routing component in the putaway and picking problem. In addition, the priority rules and metaheuristics developed not only were integrated a WMS (Warehouse Management System) but these were modelled considering the specific characteristics and constrains of the putaway and picking operation. A DOE (Design of Experiment) named Split Plot not only was implemented to valid the modelled problems but also performed an exhaustive numeric analysis, enabled to identify the combination of significant factors levels that generated the shortest average times and the higher efficiency in the putaway and picking operation. Split plot design could be considered a methodological contribution to the state of the art since this approach was not identified in the scientific literature for solving is kind of problems. Based on results of experiments it was detected that INS (Intelligent Neighboorhood Search) and PNS (Picking Neighboorhood Search) metaheuristics generated the best solutions for solving the order batching component in the putaway and picking operation. Meanwhile, the hybrid metaheuristics called RABTIN (Putaway routing using intensification strategy with tabu serach) and RUPBTDI (Picking routing using diversification strategy with tabu search) 3-Opt produced the best solution for sorting out the routing component of these operations.Doctorad