Importance of an Efficient Warehouse Management System

: In the preview of efficient supply chain management, the warehouse operations play a vital role. The warehouse operation is crucial since it act as the hub were the nodes are connected to the respective spokes. In the current environment it is very much essential to become competitive in a sustainable way. The warehousing operation is the key in order to meet the customers demand and hence it has to be continuously improved. The continuous improvement can be in a way obtained by being flexible in meeting the customers demand based upon their unique requirements. In this article the efficiency of the overall performance of warehouse operation is studied using questionnaire as the tool.

Case study: the simulation modelling of selected activity in a warehouse operation

The paper deals with the simulation of selected activities in the warehouse. Routine logistics activities are the receipt of the goods, the control of the goods, and the goods’ storage in the warehousing system on the side of the entry into the warehouse. On the output side, these are activities such as picking, packing and shipping. The economy of warehouse operations depends on the efficiency of the logistics activities performed and on deployed the technical means. The paper’s main goal is to present a created simulation model for a selected warehouse activity—receipt of goods into the warehouse. This operation involves unloading the goods from the trucks, moving them to the physical receipt, where the quantitative and qualitative control of the goods is performed (acceptance of goods). An analysis of this activity preceded the creation of the simulation model under operating conditions. The research was performed by observing and measuring the forklift’s work cycle, which unloaded pallets from the trucks. The obtained data from the analysis were the input to the simulation model. The EXTENDSIM8 simulation system was used to create a simulation model. The several experiments were performed on the model after its creating and verifying the functionality. The paper evaluates 3 experiments and analyzes their results. The main benefit, novelty, of the article is the simulation of a selected activity for a specific company’s conditions. The experiments results are a reasonable basis for the creation of an operational tool for the company.

SFlex-WMS: a novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0

Production lines form the backbone of a manufacturing plant while the warehouse is the heart that pumps the supplies through logistics veins. However, logistics issues among manufacturing industries are well known for causing downstream production problems. Non-transparent warehouse operation and inevitable human error in logistics activities seriously jeopardise the entire downstream manufacturing processes. Existing warehouse management solutions require many sensors spanning the warehouse for tracking logistics activities which are cost-ineffective and inflexible. One aspect of intelligent WMS that has not been explored is the integration of computer vision modeling with Artificial Intelligence (AI) to create a more flexible, transparent, and autonomous warehouse management system (WMS). This study aims to devise a Smart and Flexible WMS (SFlex-WMS) to improve logistics operations in terms of operation costs, process time, and space utilisation. The highlight of the proposed framework is the two major work packages (WP) which focus on flexible, autonomous sensing mechanisms for inventory, logistics tracking, and space mapping, as well as reconstructing the warehouse environment model that reflects all physical changes in the warehouse. SFlex-WMS intends to realize real-time transparent monitoring of warehouse operations. By exploiting the outputs from both WPs, SFlex-WMS is expected to achieve more effective and flexible warehouse operations.

The Rise of “Big Data” in the Field of Cloud Analytics

The huge amount of data burst which occurred with the arrival of economic access to the internet led to the rise of market of cloud computing which stores this data. And obtaining results from these data led to the growth of the “big data” industry which analyses this humongous amount of data and retrieve conclusion using various algorithms. Hadoop as a big data platform certainly uses map-reduce framework to give an analysis report of big data. The term “big data” can be defined as modern technique to store, capture, and manage data which are in the scale of petabytes or larger sized dataset with high-velocity and various structures. To address this massive growth of data or big data requires a huge computing space to ensure fruitful results through processing of data, and cloud computing is that technology that can perform huge-scale and computation which are very complex in nature. Cloud analytics does enable organizations to perform better business intelligence, data warehouse operation, and online analytical processing (OLAP).

Revising the warehouse productivity measurement indicators: ratio-based benchmark

Purpose The literature on warehouse performance assessments is mainly focussed on the efficiency and effectiveness of an action or activity due to customer demand and tailored fulfilment, with less attention being given to the performance measurement of each function of the warehouse and its overall productivity. Therefore, this study was aimed at revising the key warehouse performance metrics to a set of productivity measurement indicators that can be adopted internationally for benchmarking productivity performance. Design/methodology/approach A literature review and semi-structured survey questionnaire were used for this study. The importance of warehouse productivity performance was reviewed to revamp the measurement indicators. Through the use of a directed content analysis and descriptive analysis, an extensive study was carried out to analyze existing warehouse productivity indicators. Findings The findings of this study provide comprehensive references for practitioners and academicians for improving the classification of productivity measurements from existing key performance metrics for warehousing. Also, this paper highlights the warehouse resources related to the respective warehouse operation activities. Research limitations/implications The study was limited to productivity performance indicators adapted from Staudt et al. (2015). Furthermore, the samples for this study comprised Malaysian academicians and practitioners in the related field. The findings can be adapted on a global scale as this study implemented general warehouse operation processes. Originality/value Consequently, the contributions of this study are that it provides relevant benchmarks for key productivity performance indicators in the warehousing sector that has worldwide applicability and the developed model provides a conceptual platform from which further theoretical and empirical developments can be carried out.

The Effect of Integrated Warehouse Operation Efficiency on Organizations Performance

Worldwide several firms have suffered a lot of problems in inventory management which concerns their operational achievement. Good inventory management is a means to improve customer service and reduce stock. The objective of inventory management is to handle it in a most reasonable cost and remove the constant accumulations for continuous developments. This paper brings out how to assess the effect of integrated inventory management practices on organizations representation of some selected universities in Amhara region, Ethiopia. To remain competitive, inventory accounts needs a huge capital of an organization and must have a good management in the overall flow of resource from the initial purchase to final usage. Generally, the goal of every business is to hold little inventory and keep their business running. So, those universities in this region have hold a little inventory and make their organizations run well, even determine how much they do have in their store and determine for how long it will serve them.

Improved Anti-Collision Algorithm for the Application on Intelligent Warehouse

As an important part of economic development, warehousing logistics also needs to be transformed and upgraded in order to adapt to the development of the new situation. The RFID reader records the related information of the goods to improve the efficiency of warehouse operation by identifying the RFID tags attached to the goods in batches. This paper also proposes an improved group-based anti-collision algorithm (GMQT) to solve the problem of tag collision in the process of Radio Frequency Identification (RFID) identification. The simulation results show that the GMQT algorithm improves the recognition efficiency of the system. The algorithm has the advantages of small data transmission and stable performance; in particular, the recognition efficiency is not affected by the number of tags.