Robotized Warehouse Systems: Developments and Research Opportunities

Robotized handling systems are increasingly applied in distribution centers. They require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. This makes them particularly fit for e-commerce operations. This paper reviews new categories of robotized handling systems, such as the shuttle-based storage and retrieval systems, shuttle-based compact storage systems, and robotic mobile fulfillment systems. For each system, we categorize the literature in three groups: system analysis, design optimization, and operations planning and control. Our focus is to identify the research issue and OR modeling methodology adopted to analyze the problem. We find that many new robotic systems and applications have hardly been studied in academic literature, despite their increasing use in practice. Due to unique system features (such as autonomous control, networked and dynamic operation), new models and methods are needed to address the design and operational control challenges for such systems, in particular, for the integration of subsystems. Integrated robotized warehouse systems will form the next category of warehouses. All vital warehouse design, planning and control logic such as methods to design layout, storage and order picking system selection, storage slotting, order batching, picker routing, and picker to order assignment will have to be revisited for new robotized warehouses

Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

Introduction to Production: Philosophies, Flow, and Analysis

Production is a fundamental societal and economic activity. Production has to do with the transformation of raw materials into useful objects and includes the knowledge to complete the transformation effectively. Thus, production is a board topic ranging from philosophies about how to approach production such as lean and quick response manufacturing, how to organize production facilities, how to analyze production operations, how to control the flow of materials during production, the devices used to move materials within a facility, and strategies for coordinating multiple production facilities. An integrated introduction to production is presented in a set of learning modules. In significant part, these learning modules are based on over 20 years of interactions with the professional production community in the West Michigan region where Grand Rapids and Holland are the principal cities. This community consists almost exclusively of small and medium size companies engaged primarily in high mix, low volume manufacturing. Students in the Bachelor of Science in Engineering and Master of Science in Engineering programs at Grand Valley State University often work in production for these companies. Thus, interactions are facilitated particularly though master’s degree capstone projects, several of which are referenced in the learning modules. The learning modules are well-grounded in established production concepts. Emphasis is placed on proven procedures such as systematic layout planning, factory physics, various production flow control techniques such as kanban and POLCA, and discrete event simulation. Professional practice is a focus of the learning modules. Material from processional groups such as the Lean Enterprise Institute and the Material Handling Institute (MHI) is integrated. The opportunity to read and discuss professional publications presenting production improvement projects is provided. Students are referred to professional videos and web sites throughout the learning modules. All materials provided are referenced are open access and free of charge. When downloading the main file, it is important to also download and use the Main File Support as it contains supplemental materials.https://scholarworks.gvsu.edu/books/1022/thumbnail.jp

Collaborative Systems, Operation and Task of the Manufacturing Execution Systems in the 21st Century Industry

Until the first two decades of the 21st century, as part of the Enterprise Resourse Planning (ERP), the Manufacturing Execution System (MES) and related systems have undergone development in both complexity and efficiency. In the field of production technology, there are many sources of work nowadays to get a detailed picture of the solutions offered by MES. The purpose of this article is to give a comprehensive overview of the MES solutions that currently used in industry. In addition to the general structure of the systems and Holonic MES are briefly described. Special attencion is paid to various collaborative systems that complement the MES. The additional manufacturing tools for MES is also described shematically in this article

Modeling and Design of Container Terminal Operations

Design of container terminal operations is complex because multiple factors affect the operational perfor- mance. These factors include: topological constraints, a large number of design parameters and settings, and stochastic interactions that interplay among the quayside, vehicle transport, and stackside processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with Automated Lift Vehicles (ALVs) and Automated Guided Vehicles (AGVs). These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of alternate vehicle dwell point policy is analyzed using state-dependent queues, whereas the efficient terminal layout is determined using variation in the service time expressions at the stations. Further, using embedded Markov chain analysis, we develop an approximate procedure for analyzing bulk container arrivals. These models form the building block for design and analysis of large-scale terminal operations. We test the model efficacy using detailed in-house simulation experiments and real-terminal validation by partnering with an external party

Evaluating a Data Distribution Service System for Dynamic Manufacturing Environments: A Case Study

AbstractSmall and Medium sized Enterprises (SMEs) in Europe struggle to incorporate industrial robots in their production environments, while large enterprises use these robots for large batch production only. The paradigm shift from mass production to mass personalization decreases batch sizes and changes the approach to implementation of industrial robots in manufacturing environments. It also opens doors for SMEs to further incorporate robots in their production environments. The goal of this research is to evaluate the suitability of a data-centric, distributed, decentralized manufacturing system for cooperation between robots and humans. A case is presented featuring cooperation between robots and humans. A control system is proposed based on distributed intelligence and decentralized control, to handle the rapidly expanding complexity in dynamic manufacturing environments. The communication in such a distributed environment is provided by a Data Distribution Service system; an extendible, flexible approach to communication. Key issues that are encountered in implementing the cooperation into the current industrial environments are identified. The proposed control system is projected on the case and evaluated for application suitability and expected performance

Progress in Material Handling Research: 2012

Table of Content

Serial laser lithography for efficient manufacture of universal microstructures

The technique of microstructuring revolutionises all classical fields of engineering like electronics, optics and mechanics. In order to manufacture a microstructure in large quantities and at a reasonable price, master elements or masks will be formed that can be duplicated in a highly efficient process. Further development in technology leads, on the one hand, to further reduction of possible dimensions of structures down to the range of sub-nano technology and, on the other hand, to the development of more flexible systems in using more reasonably priced technologies for the structuring in the classical micrometre range, which in turn opens a much larger field of use. This study examines the use of serial laser lithography for efficient manufacture of universal microstructures. To facilitate this, a laser beam writer or so-called Laser Pattern Generator (LPG) was developed and described here as well as in a previous work[Samu96a]. The laser beam writer uses a precise positioning system for the movement of a substrate for material processing using a focussed laser beam. This system permits the production of structures with dimensions down to 0.5 μm which can be used in several application fields. This was systematically analysed for optimisation of the production process. Based on the achieved results, a computer-aided simulation system for process parameter determination and optimisation was developed that may be used in order to minimise the experimental effort in LPG manufacturing. The total production process and the individual optimising steps are illustrated by the manufacture of different microstructures. Because of the high reproducibility in manufacturing different structure types and, compared with other manufacturing methods, the low equipment and manufacturing effort, serial laser lithography is an efficient process for the microstructuring of universal microstructures down to the dimensions in the micrometre range

Adaptive Multi-Priority Rule Approach To Control Agile Disassembly Systems In Remanufacturing

End-of-Life (EOL) products in remanufacturing are prone to a high degree of uncertainty in terms of product quantity and quality. Therefore, the industrial shift towards a circular economy emphasizes the need for agile and hybrid disassembly systems. These systems feature a dynamic material flow. Besides that, they combine the endurance of robots with the dexterity of human operators for an effective and economically reasonable EOL-product treatment. Moreover, being reconfigurable, agile disassembly systems allow an alignment of their functional and quantitative capacity to volatile production programs. However, changes in both the system configuration and the production program to be processed call for adaptive approaches to production control. This paper proposes a multi-priority rule heuristic combined with an optimization tool for adaptive re-parameterization. First, domain-specific priority rules are introduced and incorporated into a weighted priority function for disassembly task allocation. Besides that, a novel metaheuristic parameter optimizer is devised to facilitate the adaption of weights in response to evolving requirements in a reasonable timeframe. Different metaheuristics such as simulated annealing or particle swarm optimization are incorporated as black-box optimizers. Subsequently, the performance of these metaheuristics is meticulously evaluated across six distinct test cases, employing discrete event simulation for evaluation, with a primary focus on measuring both speed and solution quality. To gauge the efficacy of the approach, a robust set of weights is employed as a benchmark. Encouragingly, the results of the experimentation reveal that the metaheuristics exhibit a notable proficiency in rapidly identifying high-quality solutions. The results are promising in that the metaheuristics can quickly find reasonable solutions, thus illustrating the compelling potential in enhancing the efficiency of agile disassembly systems

Adaptive Multi-Priority Rule Approach To Control Agile Disassembly Systems In Remanufacturing

End-of-Life (EOL) products in remanufacturing are prone to a high degree of uncertainty in terms of product quantity and quality. Therefore, the industrial shift towards a circular economy emphasizes the need for agile and hybrid disassembly systems. These systems feature a dynamic material flow. Besides that, they combine the endurance of robots with the dexterity of human operators for an effective and economically reasonable EOL-product treatment. Moreover, being reconfigurable, agile disassembly systems allow an alignment of their functional and quantitative capacity to volatile production programs. However, changes in both the system configuration and the production program to be processed call for adaptive approaches to production control. This paper proposes a multi-priority rule heuristic combined with an optimization tool for adaptive re-parameterization. First, domain-specific priority rules are introduced and incorporated into a weighted priority function for disassembly task allocation. Besides that, a novel metaheuristic parameter optimizer is devised to facilitate the adaption of weights in response to evolving requirements in a reasonable timeframe. Different metaheuristics such as simulated annealing or particle swarm optimization are incorporated as black-box optimizers. Subsequently, the performance of these metaheuristics is meticulously evaluated across six distinct test cases, employing discrete event simulation for evaluation, with a primary focus on measuring both speed and solution quality. To gauge the efficacy of the approach, a robust set of weights is employed as a benchmark. Encouragingly, the results of the experimentation reveal that the metaheuristics exhibit a notable proficiency in rapidly identifying high-quality solutions. The results are promising in that the metaheuristics can quickly find reasonable solutions, thus illustrating the compelling potential in enhancing the efficiency of agile disassembly systems