Intelligent Inventory Research Articles

Storage Optimization (r, Q) Strategy under Condition-Based Maintenance of Key Equipment of Coal-Fired Power Units in Carbon Neutrality Era

For the safe, stable, and economic operation of thermal power units in new power systems, the condition-based maintenance mode and storage strategy of key equipment and materials for power generation enterprises were selected. According to the storage linkage demand of condition-based maintenance, a Weibull probability density function was used to calculate spare parts demand, and an intelligent storage optimization model with an availability constraint was established. The application cases of spare parts cost and availability of high-value key equipment and low-value key equipment of coal-fired thermal power units were analyzed, respectively, and the influence of different life spans and the number of covered units on the model were expounded. The results show that the cost of spare parts borne by a single unit is greatly reduced via the optimization of an intelligent inventory (r, Q) strategy on the premise that the availability of units is not less than 99.5%.

A Closed Stockyard UAV Intelligent Inventory System

Strategic resources affect national development and security at all times. Actual utilization of strategic resources is crucial. In recent years, strategic resources such as coal and mineral powder usually need to be stored in closed stockyards after mining due to environmental protection, concealment, and other reasons. The existing stockpiling inventory system cannot autonomously complete the stockpiling inventory in the closed stockyard with low risk, low cost, and high precision. Therefore, this paper proposes a closed stockyard UAV intelligent inventory system. Our inventory system comprises a UAV system, a visual mapping system, and a classification and volume calculation system. In this paper, we focus on the navigation system belonging to the UAV system and propose a GNSS-denied environment navigation system based on lidar and ArUco markers. We conduct experiments in the dry coal shed of thermal power plants, one of the application scenarios. After analysis and comparison, it can be concluded that our intelligent UAV stockpiling inventory system can complete the task with high robustness and high precision with the assistance of our navigation system.

Research on Process Control Strategy of Asphalt Tank Inventory Based on Dynamic Programming Algorithm in Post Epidemic Era

Abstract Based on the background of post epidemic era, starting with the traditional industrial inventory process control, this paper discusses the dynamic inventory process control strategy under the asphalt tank inventory mode, and analyzes the intelligent inventory mode under the trend of intelligent logistics through the dynamic programming method, so as to provide reference for the development direction of intelligent inventory of unconventional storage materials such as chemical industry and energy. At the same time, with the recurrence of short-term epidemic and the dilemma of low return to work and production rate, through the integration and interconnection of mobile communication, intelligent analysis, digital management and other technologies with all links, the strategies of inventory dynamic control, inventory risk control, improving inventory efficiency and optimizing inventory cost are put forward.

Intelligent Inventory Management for Cryptocurrency Brokers

Intelligent Inventory Management for Cryptocurrency Brokers

Research on Stereo Library Based on Homogeneous Markov Chain

The intelligent inventory has not yet been implemented in the automated three-dimensional library. The warehouse basically relies on the accounts of the warehouse. It is really necessary to check the pallets manually with the help of a stacker, or venture into the aisle to check on the spot, or install radio frequency identification (RFID) on the pallet. The radio frequency recognition device on the stacker’s loading platform obtains the information of a specific pallet to achieve a physical inventory. After investigation, the results that can pass the three-dimensional library system automatic library are still blank. For the three-dimensional library, the intelligent inventory is of great significance to the actual production. It can automatically identify whether the goods in the designated cargo space are consistent with the storage according to the needs of the warehouse manager, so the demand for the intelligent inventory is very urgent.

A Framework for Intelligent Inventory Prediction in Small and Medium- Scale Enterprise

The aim of this research is to apply an intelligent technique to predict optimal inventory quantity in small and medium-scale enterprise. This is in view of the fact that the conventional models such as the EOQ model use only deterministic while some decision variables are non- deterministic in nature. Forecasted average demand of items for ten months in a small-scale retail outlet was collected and trained using an Artificial Neural Networks (ANN) of 5 neurons in the input layer with eight neurons in the first hidden layer and four neurons in the second hidden layer. Two feed-forward training algorithms of quasi-newton and quick propagation were employed in the training with the results of fuzzy logic technology found in the literature as the target output. Results obtained show that the quasi-newton algorithm covaries stronger with the fuzzy logic results than the quick propagation results. The objective and subjective feelings of the inventory manager were also captured to optimise the results of the training. The study is at a framework stage and will proceed to implementation level when more datasets are collected. Data collection in a small-scale outlet is a daunting task as record keeping is hardly done. The inclusion of non-deterministic circumstances such as emotional and objective feelings of the inventory manager to predict inventory is novel considering the fact that studies in the available intelligent inventory prediction have not employed such variables in their predictions. Keywords : Artificial Neural networks, Fuzzy logic, Quasi newton, Quick propagation, EOQ, Inventory, Forecast. DOI: 10.7176/EJBM/13-2-03 Publication date: January 31 st 2021

A Stereoscopic Warehouse Stocktaking Method Based on Machine Vision

In order to solve the problem of high security risk, low efficiency and low accuracy of the manual stocktaking during stocktaking of stereoscopic warehouse, the image processing method of python+OpenCV visual library software was adopted. Firstly, the sampling camera is controlled by the stacker PLC to traverse all cargo positions and obtain physical images of the goods. Then, OpenCV platform is used to provide operators for image preprocessing, image segmentation and one-dimensional barcode recognition, so as to identify the barcode information and determine the material type. Finally, the inventory report is generated by comparing with WMS system. The research shows that the OpenCV-based method can quickly and accurately identify the one-dimensional barcode, and realize the automatic unmanned intelligent inventory, effectively reduce the workload of staff, improve the production efficiency, avoid the potential risk of manual inventory, and achieve the expected goal.

Emotional Intelligence and Academic Achievement Among Management and Science University’s (MSU) School of Education and Social Sciences (SESS) students

This study aims to look at the existing level of emotional intelligence among Management and Science University’s (MSU) School of Education and Social Sciences (SESS) students. It will also look at the relationship between intrapersonal and interpersonal level among SESS students. The sample is 100 students that divide by 50 males and 50 females. In this research, it used a survey tool which Emotional Competencies Inventories (ECI). In this research it used inventory with 40 items in it. It is divided to two parts, intrapersonal and interpersonal abilities. First is to recognize emotions categories of self. Second is emotional self-management and lastly personal motivation. Interpersonal part is consists of two categories, which is the ability to recognize others feelings and the ability to handle relationships effectively. This researcher analyzes the data using the Statistical Package for the Social Science (SPSS) version 17.0. The reliability for this instrument (Emotional Intelligent Inventory) is .791. The data was process by using the descriptive statistics of the mean score and the standard deviation. Pearson correlation coefficient is used to measure the relationship between the construct of intrapersonal and interpersonal relationships among the students. The results showed that each of the questions and objectives of the study have been answered. The results of the study also illustrate the level of emotional intelligence among SESS students are at moderate level. This study also discusses the results of the study, future research recommendations and limitations of the study

RFID + Wi-Fi system to control the location of biomedical equipment within hospital areas and linked to an intelligent inventory

One of the most common problems in a hospital is the loss of medical equipment due to the change of areas to cover emergency needs. As a consequence, some preventive maintenance is omitted for months, causing a reduction in the useful life of the medical equipment, an additional investment of resources by the hospital and, mainly, a greater risk to the patient or medical staff. In this work we propose the development of an RFID + Wi-Fi access control system for medical equipment in the different areas of a hospital linked to an intelligent inventory. The system consists of 10 antennas mounted on each equipment with an RFID reader RC522 using a frequency of 13.56 MHz, a Wi-Fi NodeMCU card allows the transmission of equipment data to the inventory to keep it updated. The developed interface allows the interaction of the area of biomedical engineering with the records in the inventory, but also performs the deployment of important information such as: equipment documentation, an intelligent maintenance manager and an access meter based on the mobility of the equipment and the areas involved to detect needs in future purchases for the institution.

Emotional Intelligence: Does Emotional Intelligence Scores Differ in Variant Nursing Leadership Levels?

In the recent past Emotional intelligence has evoked a lot of attention in leadership. While intelligence quotient and technical skills contribute considerably to leadership, emotional intelligence is the gold standard for leadership. This study explores the differences in emotional intelligence scores between the mid-level managers and of the team leaders. Therefore, a quantitative approach was adopted. Correlational study design was employed to explore the emotional intelligence scores between the two levels of leadership in a private city hospital. An adopted seven- Likert scale emotional intelligent inventory; self-administered tool was used in data collection from the two groups of leaders. Data was analysed using Statistical Package for the Social Sciences (SPSS). The results of the two groups was generated and correlated, and the standard deviation was identified. The findings of the study demonstrated that the mid-level managers demonstrated higher levels of emotional intelligence score in some facets like flexibility with a standard deviation of 38.1, and optimism with a standard deviation of 17.7. On the contrary, the team leaders demonstrated higher emotional intelligence score on emotional self-control with a standard deviation of 2.1 and an initiative with a standard deviation of 3.5. The conclusion was drawn that, in deed, emotional intelligence is a valuable construct in leadership. The senior leaders had higher emotional intelligence scores than the junior leaders. There is need for further study using variant triangulated tools to measure emotional intelligence comprehensively.

Vision‐based position computation from in‐vehicle video log images for road sign inventory

Computing the positions of road signs from in-vehicle video log images is one of the most fundamental tasks for intelligent sign inventory. This study analysed vision-based positioning methods from video log images and proposed an analytic model of road sign positioning (AM-RSP) based on error propagation and first-order approximation. Both image noises and camera calibration errors were modelled as two error sources. The AM-RSP model can evaluate and quantify the positioning uncertainties for both single view and stereo vision-based methods. Moreover, it can quantitatively establish the relationship between the positioning uncertainties and the various parameters of the vehicle and the camera,such as camera focal length, view angle, baseline width, height, image acquisition interval, vehicle distance to the road edge etc. Hence, the proposed AM-RSP model can be applied to configure the parameters of the camera and the vehicle to meet some specific computation requirement such as RSP accuracy. The proposed AM-RSP model has been validated with real video log image data collected in the field. These results show that the AM-RSP model is accurate and reliable to compute sign positioning uncertainties.

Ruminative Reinforcement Learning: Improve Intelligent Inventory Control by Ruminating on the Past

Reinforcement Learning (RL) can solve practical sequential decision problems, even when structures of the problems are less understood. However, some sequential decision problems intrinsically have structural parts that are easily to formulate and distinguish from less understood parts. Exploiting this knowledge may help improve performance of RL. This study proposed and investigated an approach to exploit the knowledge of structural parts of inventory management problems in the context of RL. The proposed method is motivated by human behavior of ruminating on what has happened and what would happen if alternative choices would have been taken. Our investigation provides an insight into RL mechanism and our experimental results show viability of the approach.