Automatic Identification and Categorize Zone of RFID Reading in Warehouse Management System

Abstract

Radio Frequency Identification (RFID) technology has improved the operational efficiency and process flow in the distribution of warehouse management system (WMS) around the globe. Nonetheless, a moving or missing tag as well as known and unknown tag's location that may occur in the detection could reduce the efficiency of process flow. This study aims at identifying the location of goods in between two RFID reading zones by means of machine learning, particularly Support Vector Machine (SVM). A total of seven statistical features are extracted from the received signal strength (RSS) value from the raw RFID readings. SVM classifier are evaluated by considering the combination of different statistical features namely COMBINE to produce a more effective classification in comparison to individual statistical feature. The performance of the classifier demonstrated a classification accuracy of approximately 94% by considering all features whereas the performance of the classifier by considering individual features alone is below than 90%. This preliminary study establishes the applicability of the proposed automatic identification is able to provide the management of goods as well as supply chain reasonably well without human intervention.

Warehouse management model based on Lean Warehousing to improve perfect order fulfillment in a pharmaceutical warehouse

“…• Matrix of taking times • ECRS Matrix • Process standardization format Thirdly, the implementation of the Poka Yoke tool is detailed, which focuses on the RFID System to improve the traceability of the products from their arrival to their departure from the warehouse, generating a report of the quantity and exact location of each product at consult at any time, for this reason it is expected that precision errors can be reduced during picking, managing to deliver correct and complete orders [46][47] [48]. This system requires the following artifacts:…”

Supply Chain Digitalization in the Wood Manufacturing Industry: A Bibliometric Literature Review

“…IoT applications has also been examined by many articles and has been linked to several supply chain drivers as well, the most used enablers of IoT application were sensors and RFID devices [11,33,34], the review of the literature has revealed that the implementation of IoT in the wood industry is somehow still limited to the traceability of wood in particular, especially when combined with other technologies such as blockchain and smart contracts [6,29,35,36,37,38,39,40,41], however it is highly anticipated that the wood industry will shortly follow the steps of other industries and overcome its current slow advancement [6,42].…”

“…Blockchain: [26]; [27]; [9]; [28]; IoT: [41]; [40]; [33]. Big Data: [50]; [51]; Cloud: [53] Smart contracts optimized design of business operations less need for intermediary less time and cost prominent level of security and justice hyperconnected logistics Blockchain: [29]; [30]; [31]; [15]; IOT: [39]; [29] As supply chain management core success elements rely on making use of available data and hence big data analytics (BDA) can revolutionise SCM by facilitating concurrent and methodical data collection, analysis and rapid decision making which will provide substantial performance improvements in various processes [43,44,45,46,47,48,49,50,51], Similarly in supply chains, enormous amounts of information can be seamlessly shared and transmitted between different participants using cloud computing [14,43,48,52,53], Although the applications that were proposed in recent research can be applied to various industries, a study of BDA applications in the wood industry has not been found, and a lack of research on further implementation of cloud technology or cloud manufacturing in the wood industry.…”

Enhancing Cloud-Based Inventory Management: A Hybrid Blockchain Approach With Generative Adversarial Network and Elliptic Curve Diffie Helman Techniques

“…Its significance extends across diverse industries, where the dynamic management of inventory proves essential for meeting customer demands, minimizing carrying costs, and ensuring the smooth flow of goods from production to distribution [3]. This encompasses not only the quantitative aspects but also delves into the strategic analysis of ensuring the precise quantity of stock required to meet dynamic customer demands [4]. In its operational continuum, IMS encapsulates the comprehensive journey of inventory, commencing from the point of receipt and extending through various stages until the final sale or utilization [5].…”