Intralogistics systems, while complex, are crucial for a range of industries. One of their challenges is deadlock situations that can disrupt operations and decrease efficiency. This paper presents a four-stage framework for applying reinforcement learning algorithms to manage deadlocks in such systems. The stages include Problem Formulation, Model Selection, Algorithm Selection, and System Deployment. We carefully identify the problem, select an appropriate model to represent the system, choose a suitable reinforcement learning algorithm, and finally deploy the solution. Our approach provides a structured method to tackle deadlocks, improving system resilience and responsiveness. This comprehensive guide can serve researchers and practitioners alike, offering a new avenue for enhancing intralogistics performance. Future research can explore the framework’s effectiveness and applicability across different systems.

The digital transformation is increasingly affecting the field of intralogistics. In order to develop corresponding concepts in logistics planning in a short time, software tools should profitably transfer the theoretical knowledge into practice and support the user in the best possible way. This article gives insight in particular into the typical tasks involved in the planning and optimization of internal transport processes and how LOGSOL as a consultany company addresses these with the help of the RoutMan planning tool.:1. Introduction 2. Planning of internal transport processes 3. LOGSOL's approach to planning and optimizing internal transport processes 4. Conclusion

Intralogistics, or material handling, traditionally use roller or chain conveyors to moveo bjects and goods in factories and warehouses. One negative aspect of the traditional types of conveyors is that they are expensive, as they are comprised of many moving parts. This thesis proposes a novel type of conveyor solution in which a transportation fixture with an integrated open thread slides on L­-shaped profiles and is propelled forward by a screw. A potential obstacle to the usefulness of such a conveyor is that a screw has innately low efficiency due to the mechanics of screws compared to the principle of rolling that is employed in a roller or chain conveyor. This thesis investigates the functionality and efficiency of the proposed conveyor, or more particularly the core functionality, which is the screw and thread mechanism. A test rig was designed and built, in which experiments were carried out. In the experiments, the material, manufacturing technology, and helix angle of the screw and thread, and the speed were varied. The influence on torque, power demand, and efficiency among other parameters were measured and evaluated. Additionally, a method for automatic thread meshing is presented and testing of it was carried out, which showed reliability with and without positional feedback, which gives the conveyor more use cases. It was found that the efficiency of the screw and thread mechanism was higher for screws with a higher lead, steel screws with a diameter of 50 mm exhibited an efficiency of 31% ± 4.5 % with a lead of 32 mm but only 8.7% ± 1.6 % with a lead of 8 mm. 3D printed plastic screws had slightly lower but similar early life efficiency as steel screws, but seized or wore down when tested in an accelerated lifetime experiment. Because a high screw lead is favorable, and because of the size and geometry constraints of such a conveyor (discussed in the conclusion of the report), a direct drive motoris not suitable, and instead a motor and gearbox combination is recommended. The conveyor shows promise as an alternative solution to traditional conveyors in low load applications. / Intralogistik, eller materialhantering, använder traditionellt rull-­ eller kedjetransportörer för att flytta gods i fabriker och lager. En negativ aspekt med dessa traditionella transportörer är att de är dyra, då de består av ett stort antal rörliga delar. Detta examensarbete föreslår en ny typ av transportör i vilken en transportfixtur med en inbyggd kuggstång glider på L­-formade profiler and drivs framåt av en skruv. Ett potentiellt hinder för denna typ av transportörs användbarhet är att en skruv naturligt har låg verkningsgrad på grund av skruvens mekanik i jämförelse med principen av rullning som används av rull- och kedjetransportörer. Detta examensarbete undersöker funktionaliteten och verkningsgraden av den föreslagna transportören, mer specifikt kärnfunktionaliten som är en skruv-­ och gängmekanism. En testrigg designades och byggdes, i vilken experiment utfördes. I experimenten varierades materialet och spiralvinkeln av skruven och gängan, samt hastigheten. Vridmomentet, effekten, verkningsgraden och andra parametrar mättes och utvärderades. Dessutom presenteras en metod för automatiskt gängingrepp som även testades, som visade sig vara tillförlitligt både med och utan positionsåterkoppling, vilket ger skruvtransportören fler användningsområden. Resultaten visade att verkningsgraden av skruv­ och gängmekanismen var högre för skruvar med högre spiralvinkel. Stålskruvar med en diameter på 50 mm visade på en verkningsgrad om 31% ± 4.5 % med en stigning på 32 mm men endast 8.7% ± 1.6 % med en stigning på 8 mm. 3D­-Printade plastskruvar hade något lägre men liknande verkningsgrad som stålskruvar i början av sin livslängd, men skar fast eller nöttes ned när de testades i ett långtidsexperiment. Eftersom hög stigning på skruven är fördelaktigt och på grund av de geometriska begränsningar av en sådan transportör (diskuteras i slutsatsen av rapporten), är det inte lämpligt att driva skruven direkt från en elmotor, utan istället rekommenderas en motorväxellådekombination. Transportören verkar lovande som ett alternativ till traditionella transportörer i applikationer med låg last.

<p dir="ltr">The emergence of Autonomous Mobile Robots (AMR) signifies a pivotal shift in vehicle-based material handling systems, demonstrating their effectiveness across a broad spectrum of applications. Advancing beyond the traditional Automated Guided Vehicles (AGV), AMRs offer unprecedented flexibility in movement, liberated from electromagnetic guidance constraints. Their decentralized control architecture not only enables remarkable scalability but also fortifies system resilience through advanced conflict resolution mechanisms. Nevertheless, transitioning from AGV to AMR presents intricate challenges, chiefly due to the expanded complexity in path planning and task selection, compounded by the heightened potential for conflicts from their dynamic interaction capabilities. This dissertation confronts these challenges by fully leveraging the technological advancements of AMRs. A kinematic-enabled agent-based simulator was developed to replicate AMR system behavior, enabling detailed analysis of fleet dynamics and interactions within AMR intralogistics systems and their environments. Additionally, a comprehensive fleet management protocol was formulated to enhance the throughput of AMR-based intralogistics systems from an integrated perspective. A pivotal discovery of this research is the inadequacy of existing path planning protocols to provide reliable plans throughout their execution, leading to task allocation decisions based on inaccurate plan information and resulting in false optimality. In response, a novel machine learning enhanced probabilistic Multi-Robot Path Planning (MRPP) protocol was introduced to ensure the generation of dependable path plans, laying a solid foundation for task allocation decisions. The contributions of this dissertation, including the kinematic-enabled simulator, the fleet management protocol, and the MRPP protocol, are intended to pave the way for practical enhancements in autonomous vehicle-based material handling systems, fostering the development of solutions that are both innovative and applicable in industrial practices.<br></p>