Sistem Pendeteksi Mundur Dan Manuver Pada Forklift Menggunakan Sensor Ultrasonik Berbasis Arduino

Abstrak— Dewasa ini setiap perusahaan bergerak dalam lingkungan dunia bisnisnya masing-masing, banyak perusahaan yang memanfaatkan kendaraan alat berat dengan harapan agar tak ingin mengecewakan costumer atau pembelinya dan juga bermaksud dapat mempertahankan pelanggannya. FORKLIFT adalah perangkat alat berat yang digunakan untuk hal angkat – mengangkat atau memindahkan berkapasitas besar sekaligus juga mampu mengangkat dalam proses penataan di atas rak – rak tinggi dan FORKLIFT memiliki kapasitas hinggga 3 ton dengan tinggi mengangkat hingga 4 meter. Sistem pendeteksi Jarak menggunakan ultrasonic sangat efisien digunakan pada bagian belakang kendaraan alat berat tersebut, menggunakan modul Arduino sebagai kontrol. Sistem pendeteksi jarak ini terintegrasi dengan seven segment sebagai display jarak dan led serta buzzer sebagai indikator. Sensor ultrasonic akan mengirimkan sonar untuk mengetahui pengahalang didepannya serta akan dikirimkan sinyal melalui pin output echo ke Arduino yang akan di eksekusi dengan tampilan indikator, sehingga operator FORKLIFT yang mengoperasikan akan lebih mudah melihat jarak belakang jika ada penghalang saat bermanuver dan mundur.Kata kunci: Sensor Ultrasonic, Arduino, Forklift, Sistem Pendeteksi JarakAbstract— Today every company engaged in the world of their respective businesses, many companies that use heavy equipment in the hope that does not want to disappoint the customer or buyer and also intends to maintain the customers. FORKLIFT is a device used heavy equipment to lift it - to lift or move a large capacity as well as capable of lifting the setup process on the shelves - a high shelf and FORKLIFT has finite capacity of 3 tons with a lifting height of up to 4 meters. The distance using ultrasonic detection system very efficiently used at the rear of the vehicle the heavy equipment, using Arduino as a control module. Distance detection system is integrated with a seven segment display and LED and buzzer distance as an indicator. The sensor sends ultrasonic sonar to determine to obstacle in front of him and will be sent a signal through output pin to Arduino echo that will be executed by the display indicator, so that the forklift operator that operate will be easier to see if there is a barrier rear distance when maneuvering and backwards. Keywords: Ultrasonic sensors, Arduino, Forklift, Distance Detection Syste

Augmenting the distribution of goods from warehouses in dynamic demand environments using intelligent agents

Warehouses are being impacted by increasing e-commerce and omni-channel commerce. Future innovation may predominantly involve automation but many warehouses remain manually operated. The golden rule of material handling is smooth product flow, but there are day-to-day operational issues that occur in the warehouse that can impact this and order fulfilment. Standard operational process is paramount to warehouse operational control but inflexible processes don’t allow for a dynamic response to real-time operational constraints. The growth of IoT sensor and data analytics technology provide new opportunities for designing warehouse management systems that detect and reorganise around real-time constraints to mitigate the impact of day-to-day warehouse operational issues. This paper presents an intelligent agent framework for basic warehouse management systems that is distributed, is structured around operational constraints and includes the human operator at operational and decision support levels. An agent based simulation was built to demonstrate the viability of the framework

RIDESOURCING IN MANUFACTURING SITES: A FRAMEWORK AND CASE STUDY

With the recent innovations in transportation, ridesourcing services have been proliferating in many countries. There are increasing attempts to apply ridesourcing in the corporate context. Manufacturing companies now install the Industrial Internet of Things (IIOT) sensors to vehicles to obtain real-time data on the movement of goods and materials. Despite the massive amount of data accumulated, little attention has been paid to exploiting the data for vehicle fleet management (FM). This paper proposes an analytical framework to solve two FM problems: how to group organizational units for vehicle sharing and where to deploy the groups. The framework is then validated with a case study of a Korean shipbuilder. The results indicate that grouping departments with similar spatial patterns can reduce the current fleet

Design and Simulation Analysis of Deep Learning Based Approaches and Multi-Attribute Algorithms for Warehouse Task Selection

With the growth and adoption of global supply chains and internet technologies, warehouse operations have become more demanding. Particularly, the number of orders being processed over a given time frame is drastically increasing, leading to more work content. This makes operational tasks, such as material retrieval and storage, done manually more inefficient. To improve system-level warehouse efficiency, collaborating Autonomous Vehicles (AVs) are needed. Several design challenges encompass an AV, some critical aspects are navigation, path planning, obstacle avoidance, task selection decisions, communication, and control systems. The current study addresses the warehouse task selection problem given a dynamic pending task list and considering multiple attributes: distance, traffic, collaboration, and due date, using situational decision-making approaches. The study includes the design and analysis of two situational decision-making approaches for multi-attribute dynamic warehouse task selection: Deep Learning Approach for Multi-Attribute Task Selection (DLT) and Situation based Greedy (SGY) algorithm that uses a traditional algorithmic approach. The two approaches are designed and analyzed in the current work. Further, they are evaluated using a simulation-based experiment. The results show that both the DLT and SGY have potential and are effective in comparison to the earliest due date first and shortest travel distance-based rules in addressing the multi-attribute task selection needs of a warehouse operation under the given experimental conditions and trade-offs