Warehouse Applications Research Articles

How to Improve Your Warehouse Operating Efficiencies

How to improve your warehouse operating efficiency helps to understand the critical factors that influence the productivity of the warehouse operations. As we know logistics is essential for supply chain in today’s world to reach the products on time and in full (OTIF). To attain better OTIF rate, operating the warehouse to the fullest efficiency is critical. There are various types of warehouses, at different sizes (in Sq. ft), diverse operating models, several applications are available in the market. Warehouses of each industry types have their own uniqueness in operating model, and it comes its own complexity. Operating warehouses to the maximum efficiency is always challenging, constant automation with process and system re-engineering is needed to keep up the pace. Inefficient warehouse operations can bring the business to a standstill unless its upbeat to meet the needs of the customers. Warehouse applications complement to the performance of the deliverables from logistics perspective, fulfilling the customer service level agreements (SLA).

Simultaneous Localization and Mapping (SLAM) for warehouse applications

Simultaneous Localization and Mapping (SLAM) for warehouse applications

Trajectory optimization with hybrid probabilistic roadmap approach to achieve time efficient navigation of unmanned vehicles in unstructured environment

PurposeThis paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.Design/methodology/approachTraditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.FindingsThe proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.Originality/valueThe proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

Zonation Method for Efficient Training of Collaborative Multi-Agent Reinforcement Learning in Double Snake Game

This paper proposes a zonation method for training the two reinforcement learning agents. We demonstrate the method's effectiveness in the double snake game. The game consists of two snakes operating in a fully cooperative setting to maximize the score. The problem in this game can be related to real-world problems, namely, coordination in autonomous driving cars and the operation of collaborative mobile robots in warehouse applications. Here, we use a deep Q-network algorithm to train the two agents to play the double snake game collaboratively through a decentralized approach, where distinct state and reward functions are assigned to each agent. To improve training efficiency, we utilize the snake sensory data of the surrounding objects as the input state to reduce the neural network complexity. The obtained result show that the proposed approaches can be used to train collaborative multi-agent efficiently, especially in the limited computing resources and training time environment

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.

The clinical narrative in electronic health records (EHRs) carries valuable information for predictive analytics; however, its free-text form is difficult to mine and analyze for clinical decision support (CDS). Large-scale clinical natural language processing (NLP) pipelines have focused on data warehouse applications for retrospective research efforts. There remains a paucity of evidence for implementing NLP pipelines at the bedside for health care delivery. We aimed to detail a hospital-wide, operational pipeline to implement a real-time NLP-driven CDS tool and describe a protocol for an implementation framework with a user-centered design of the CDS tool. The pipeline integrated a previously trained open-source convolutional neural network model for screening opioid misuse that leveraged EHR notes mapped to standardized medical vocabularies in the Unified Medical Language System. A sample of 100 adult encounters were reviewed by a physician informaticist for silent testing of the deep learning algorithm before deployment. An end user interview survey was developed to examine the user acceptability of a best practice alert (BPA) to provide the screening results with recommendations. The planned implementation also included a human-centered design with user feedback on the BPA, an implementation framework with cost-effectiveness, and a noninferiority patient outcome analysis plan. The pipeline was a reproducible workflow with a shared pseudocode for a cloud service to ingest, process, and store clinical notes as Health Level 7 messages from a major EHR vendor in an elastic cloud computing environment. Feature engineering of the notes used an open-source NLP engine, and the features were fed into the deep learning algorithm, with the results returned as a BPA in the EHR. On-site silent testing of the deep learning algorithm demonstrated a sensitivity of 93% (95% CI 66%-99%) and specificity of 92% (95% CI 84%-96%), similar to published validation studies. Before deployment, approvals were received across hospital committees for inpatient operations. Five interviews were conducted; they informed the development of an educational flyer and further modified the BPA to exclude certain patients and allow the refusal of recommendations. The longest delay in pipeline development was because of cybersecurity approvals, especially because of the exchange of protected health information between the Microsoft (Microsoft Corp) and Epic (Epic Systems Corp) cloud vendors. In silent testing, the resultant pipeline provided a BPA to the bedside within minutes of a provider entering a note in the EHR. The components of the real-time NLP pipeline were detailed with open-source tools and pseudocode for other health systems to benchmark. The deployment of medical artificial intelligence systems in routine clinical care presents an important yet unfulfilled opportunity, and our protocol aimed to close the gap in the implementation of artificial intelligence-driven CDS. ClinicalTrials.gov NCT05745480; https://www.clinicaltrials.gov/ct2/show/NCT05745480.

A Resonator Enhanced UHF RFID Antenna Cable for Inventory and Warehouse Applications

A Resonator Enhanced UHF RFID Antenna Cable for Inventory and Warehouse Applications

Visiting pebbles on rectangular grids: coordinating multiple robots in mobile fulfilment systems

Multi-robot path finding and coordination is one of the key performance-affecting subsystems of the overall robotic order fulfilment process for use in warehouse applications. The purpose of path finding and coordination is to plan and coordinate the motions of multi-robot systems such that all robots reach their assigned goals safely. Much research has focused on solving the multi-robot path finding problem in a general way. As a result, researchers have considered a system-wide goal state where all robots are at their goal destinations in some final time. In this paper, a novel algorithm is designed specifically for order fulfilment used in warehouse applications. The key assumption is that all robots do not necessarily need to be at their destination locations at the same time. The resulting solution is referred to as visiting pebble motion on rectangular grids. More specifically, a starvation-free, semi-decentralized, scalable multi-robot coordination algorithm is presented. The proposed algorithm takes the constraints of real robot dynamics and collision avoidance into account and is capable of operating under asynchronous conditions while providing analytical performance guarantees.

Methodology Proposal for Storage Rationalization by Implementing Principles of Industry 4.0. in a Technology-Driven Warehouse

The main topic of the paper is storage rationalization. Specifically, the proposal of a methodology related to the rationalization of storage systems in warehouses of industrial companies. The methodology emphasizes the new concept of Warehouse 4.0, including Industry 4.0 warehouse applications in general. Firstly, the theoretical basis of the paper is described. This part of the paper starts with a description of logistics, Logistics 4.0, warehouse systems, Warehouse 4.0 and modern approaches linked to Industry 4.0 that can be implemented in logistics. Then the factors influencing the effectiveness of the warehouse are summarized – this is original summary in the paper based on the available literature and other sources. After this, storage rationalization and the costs linked to it are described. The first part of the paper ends with a summary of the theoretical basis of the information. The main subject of the paper is explained in the second part of the paper, which concentrates on the proposal of a methodology related to storage rationalization of warehouses in industrial companies. The individual steps are described. The purpose of the paper is to share our approaches firstly about the summarised factors influencing the effectiveness of a warehouse and secondly about the methodology proposal itself. This information may inspire other research institutions to consider aspects of this topic which could be otherwise overlooked.

Hexacopter design for carrying payload for warehouse applications

Airborne vehicles are gaining traction in research fields and in bringing it for commercial use. Multi-rotors for payload transport is one of the highly researched topics. In this paper, a hexacopter was prototyped based on commercially available components in the market and dynamic analysis was performed with constraints derived from ideal conditions, such as neglecting the effect of air resistance. The experiment shows the flight of the hexacopter to be stable with and without payload attached to it. Also, various computer vision methods were explored to detect and identify waypoints, in the form of gates, for the hexacopter to follow during its flight mission. The detection mechanism employed is HSV mask based filtering on input image and performing moment calculation on the extracted contour to determine the center of the gates. Localization of the drone with respect to the environment is performed with a monocular visual SLAM method known as ORBSLAM2.

A self-adaptive network for multi-robot warehouse communication

With the growing popularity of e-commerce, warehouse communication needs to operate in a dynamic environment with multiple robots in the system. Such multi-robot systems have many practical issues in reality. Among the major issues, end-to-end reliable communication is seen to take up prominence in literature. The current work introduces a novel self-adaptive network structure with two of its essential sub-blocks namely ‘Prioritization’ and ‘Optimal Path Selection’ as part of communication protocol for effective and reliable communication. For the first sub-block, we propose transmission deadline and information content based priority model which significantly improves critical packet transmission success rate and for the second sub-block, an optimal path selection method is proposed as a new path planning method which is capable of reducing the outage probability of the failed transmission. A typical configuration of warehouse has been simulated in Network Simulator-3 (NS-3) and real warehouse data has been used in analyzing the proposed functional blocks. A closed-form expression of outage probability is also analytically derived. Results are promising to apply them for dynamic multi-robot systems in general, and specifically for warehouse applications.

Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications

Designing efficient sensors for soft robotics aiming at human machine interaction remains a challenge. Here, we report a smart soft-robotic gripper system based on triboelectric nanogenerator sensors to capture the continuous motion and tactile information for soft gripper. With the special distributed electrodes, the tactile sensor can perceive the contact position and area of external stimuli. The gear-based length sensor with a stretchable strip allows the continuous detection of elongation via the sequential contact of each tooth. The triboelectric sensory information collected during the operation of soft gripper is further trained by support vector machine algorithm to identify diverse objects with an accuracy of 98.1%. Demonstration of digital twin applications, which show the object identification and duplicate robotic manipulation in virtual environment according to the real-time operation of the soft-robotic gripper system, is successfully created for virtual assembly lines and unmanned warehouse applications.

A sustainable process for conversion of petrol engine vehicle to battery electric vehicle: A case study

A clean environment and sustainable society can be achieved by reducing greenhouse gas emissions, which are measured by the amount of CO2 equivalents in the air. A major part of air pollution is attributed to the exhaust expelled by automobiles which can be reduced by converting existing vehicles to pure battery electric vehicles (BEV). This paper presents the process to convert a petrol-based vehicle (624 cc petrol engine vehicle) to a pure BEV suitable for the Indian automotive sector, aimed at minimizing the cost of conversion and operating cost of the vehicle. The main components used in the conversion of the vehicle are presented and their overall placement is also detailed in the paper. A three-phase brushless DC motor is used with a custom-made Li-ion battery pack along with a motor controller to realize the conversion. While carrying out the conversion process, the coupling of the motor to the gearbox was observed to be a complex task. Additionally, the development of a fool-proof circuit for effective control was observed to be a challenging task too. To tackle the circuitry issue, a novel circuitry was developed to make the connections between the motor, controller, and subsidiary parts for highly efficient vehicle operations. The prototype of the proposed conversion was also developed and tested for regular warehouse applications.

An Improved Framework for Modelling Data Warehouse Systems Using UML Profile

Data Warehouse (DW) applications provide past detail for judgment process for the companies. It is acknowledged that these systems depend on Multidimensional (MD) modelling different from traditional database modelling. MD modelling keeps data in the form of facts and dimensions. Some proposals have been presented to achieve the modelling of these systems, but none of them covers the MD modelling completely. There is no any approach which considers all the major components of MD systems. Some proposals provide their proprietary visual notations, which force the architects to gain knowledge of new precise model. This paper describes a framework which is in the form of an extension to Unified Modelling Language (UML). UML is worldwide known to design a variety of perspectives of software systems. Therefore, any method using the UML reduces the endeavour of designers in understanding the novel notations. Another exceptional characteristic of the UML is that it can be extended to bring in novel elements for different domains. In addition, the proposed UML profile focuses on the accurate representations of the properties of the MD systems based on domain specific information. The proposed framework is validated using a specific case study. Moreover, an evaluation and comparative analysis of the proposed framework is also provided to show the efficiency of the proposed work

A thorough investigation on pushing activities in industry: The impact of the variation in the speed of motion and load conditions on initial and sustained forces

Pushing and pulling wheeled objects represent a significant part of manual material handling activities in industry. Medical investigations and epidemiological studies proved the correlation between such activities and the occurrence of lumbago, low back pain and adverse effects on the shoulders. The ISO 11228–2:2007 provides the recommended limits for pushing and pulling. Such values are the results of psychophysical studies realized under prescribed speed conditions referring to a slow walk. However, observation of real industrial and service sector environments reveals that workers are required to perform pushing activities at higher speed of motion.The aim of this study was to investigate the impact of the variation in the speed of motion and load conditions on push forces. 96 subjects performed a total of 2592 trials consisting of pushing an industrial trolley for warehouse applications, at different speed values and load conditions. Results confirm the presence of correlation between the increasing speed of motion and push forces. The findings have practical value for researchers, occupational physicians and ergonomics practitioners.

PHYSICAL CONDITIONS ASSOCIATED WITH SUICIDE ATTEMPTS: DO RISKS DIFFER AMONG OUR OLDER VETERANS?

Physical illness confers risk for late-life suicide, yet few studies report whether risks differ with older age and among Veterans. We examined age-stratified associations between physical illness and suicide attempt among Veterans 65+ years (n=8452, 97% male) from a larger retrospective case-control study that utilized secondary data from the Veterans Affairs Corporate Data Warehouse and Suicide Prevention Applications Network. Controls were matched by age, sex, and mental health treatment utilization. Risk estimates for 15 conditions and a combined comorbidity score were stratified by young-old (65-74), middle-old (75-84), and oldest-old (85+), adjusting for age and sex within strata. Neurodegenerative disorder (ORs=4.5, 6.0, 6.5) or dementia (ORs=5.0, 5.7, 4.4) diagnosis within 180 days conferred the highest risks across young-, middle-, and oldest-old. Cerebrovascular disorder was associated with higher risk among the oldest-old versus young-old (ORs=6.1 vs 2.2). Findings differ from reported risks for suicide death. Illness may be experienced differently across later-life.

Fast Ellipse Detection via Gradient Information for Robotic Manipulation of Cylindrical Objects

Robotic manipulation of objects requires a fast recognition from image stream. For many cylindrical object (e.g., cans, cups, pipes, bottles, etc.) this is possible through detection of ellipse depicting the circular top of the cylinder. Growing industrial and warehouse applications of robots drive the demand for fast and reliable detection of ellipses, while state-of-the-art methods are lacking in either speed or accuracy strength. We present a novel algorithm to perform fast and robust ellipse detection. First, the method utilizes the information of edge curvature to split curves into arcs. Next, the arc convexity–concavity is used to classify arcs into different quadrants of ellipses. Then, based on multiple geometric constraints the arcs can be grouped at low computational cost. Our method is compared with six state-of-the-art methods using three public image datasets. The comparison results show that the proposed algorithm outperforms other methods with high detection accuracy and fast detection speed. Lastly, the algorithm is applied to identifying cylindrical objects in real-time for arranging and tracking purposes.

Application of Data Warehouse in Real Life: State-of-the-art Survey from User Preferences’ Perspective

In recent years, due to increase in data complexity and manageability issues, data warehousing has attracted a great deal of interest in real life applications especially in business, finance, healthcare and industries. As the importance of retrieving the information from knowledge-base cannot be denied, data warehousing is all about making the information available for decision making. Data warehouse is accepted as the heart of the latest decision support systems. Due to the eagerness of data warehouse in real life, the need for the design and implementation of data warehouse in different applications is becoming crucial. Information from operational data sources are integrated by data warehousing into a central repository to start the process of analysis and mining of integrated information and primarily used in strategic decision making by means of online analytical processing techniques (OLAP). Despite the applications of data warehousing techniques in number of areas, there is no comprehensive literature review for it. This survey paper is an effort to present the applications of data warehouse in real life. It focuses to help the scholars knowing the analysis of data warehouse applications in number of domains. This survey provides applications, case studies and analysis of data warehouse used in various domains based on user preferences.

Data Mining Architecture System Expansion

How to build a data warehouse and data mining is constantly worth exploring and optimization, not only technically, in commercial applications as well. This article discusses the introduction of new technologies and concepts, the traditional method of data warehouse technology has changed dramatically, based on data warehouse applications are a new development. Each enterprise data warehouse based on the characteristics of different companies, you can use a very flexible method of selection and design selection, implementation. According to some relatively new technical features, talk about data warehousing and data mining architecture.

Effect of beacon orientation on beacon placement strategies in the ultrasonic positioning system

Ultrasonic positioning system (UPS) is useful in warehouse and underwater applications to track automated objects. One of the key factors determining the performance of the UPS is the beacon placement. Existing literatures are restricted to placing beacons perpendicularly downward to the target moving plane. In this study, considering three common placement patterns: triangle, square and hexagon, by relaxing beacon orientation, our analysis shows that hexagon placement is the best option, and the improvement in terms of qualified coverage per beacon has a negative relationship with the beacon height. Even conditioning on a height of 20% of the sensing range, a factor of 8 and 7 can be achieved in the non-regular placement and regular placement, respectively. Furthermore, critical heights which differentiate the non-perpendicular placement (NPP) and perpendicular placement (PP) for all patterns are identified. In general, regular NPP with the hexagon pattern is advised. In addition, our analysis investigates the advantage of increasing the cone angle by clustering which groups transducers by relaxing transducer orientation, and result shows that continuous clustering of seven transducers has the largest marginal contribution of 24% and 41% to improve the qualified coverage in the non-regular NPP with hexagon placement and regular PP, respectively. Finally, considering the beacon clustering cost and the beacon station cost, the economic beacon placement strategies are identified for applications with different clustering cost and beacon height.

EVALUATION OF BITMAP INDEX USING PROTOTYPE DATA WAREHOUSE

Bitmap indices have become popular access methods for data warehouse applications and decision support systems with large amounts of read-mostly data. This paper could arrive a number of results such as ; Bitmap Index highly improves the performance of Query Answering in Data Warehouses, It highly increases the efficiency of Complex Query processing through using bitwise operations (AND, OR). A prototype of Data Warehouse “STUDENTS DW” has been built according to the conditions of W. Inomn of Data Warehouses. This prototype is built for student's information.