Journal of Applied Research in Technology & Engineering

A Stochastic Goal-Based Economic Order Quantity Model for Dairy Products

2024-07-03T12:25:17+02:00

Resilient efforts are still sought to optimize the inventory of dairy products under demand uncertainty. Several industries operate under uncertainties that severely affect company performance. In this paper, a multi-objective goal programming model is proposed to optimize the economic order quantity of dairy products under stochastic demand. Adopting a Markov chain approach, the model initially defines the demand transition matrix, inventory cost matrix, objective function, priorities, and goal constraints of dairy products. The model seeks to minimize the deviation variables from the targeted economic order quantity and total inventory costs of dairy products over a finite period planning horizon. The sum of deviations is minimized so that the actual economic order quantity and inventory costs meet the targeted levels of dairy products. Using the simplex method, an analytical solution is obtained and a numerical example is presented for illustration; demonstrating the overachievement or underachievement of the targeted economic order quantity and inventory costs of dairy products. Results indicate how priority-based goal programming solution is sensitive to the highest priority to be achieved. The proposed model can be effective where the relevant economic order quantity and inventory costs can be prioritized if necessary.

CFD-based investigation of turbulent flow behavior in 90-deg pipe bends

2024-07-03T12:25:04+02:00

This work investigated the influence of bend curvature on the parameters of turbulent flow through a 90° pipe bend using the numerical CFD method, implemented in ANSYS Fluent. The numerical predictions were validated to be in good agreement with existing experimental measurements. The turbulence of the secondary motion was found to be generally stronger at the outer end of the pipe bend, with the most adverse effect recorded at about 45° along the bend. It was also observed that the RMS velocity is larger near the wall, especially at the outer wall region, and it is highest at 45° due to an increase in the circulation of dean vortices, indicating a turbulence generation. In addition, the RMS velocity increases downstream due to an additional mean strain resulting from the creation of secondary flow as the flow travels through the bend. Furthermore, larger static pressure and turbulent viscosity were observed at the outer wall due to the flow deceleration and swirling. Therefore, it can be established that the bend curvature affects the stability of the flow field inside a pipe bend.

Association rule mining algorithm implementation for e-commerce in the retail sector

2024-07-03T12:24:35+02:00

The growth of online trading platforms and the development of market technology have forced businesses to take part in the analysis of client behavior. Therefore, this research aims to analyze customer behavior in the Kyrgyz Republic to enhance supplier's revenue, service quality, and customer satisfaction. This data was analyzed using the apriori algorithm. Results generated 118 rules which revealed strong connections between items and showed up to 61.06% relationship between the consumption of products, suggesting a connection among the considered items. Thus, the association rule highlights the significance of association rule mining in uncovering valuable insights within sales transaction data. These insights can inform targeted marketing efforts, inventory management, and the enhancement of customer experiences and optimize business strategies to meet customer preferences, ultimately fostering growth and competitiveness in the retail sector.

Impact of Ict on the Performance of Sustainable Logistics

2024-07-03T12:24:50+02:00

The environment of the planet Earth has been the concern of governments, academia, and researchers so the impacts of various factors on it have become the prime focus so that the things that damage it can be investigated and the environmental damage can be minimized accordingly. Logistics and transport are the sectors that are responsible for the greatest percentage of greenhouse gases and carbon emissions. The transport sector has been initiated towards the sustainable side because, in many countries, public transport is operated on electricity, and manufacturers have also introduced electric vehicles for citizens to drive and travel in. Freight transport is still a problem because of its carbon footprint; technological advancement has made it easier to minimize the carbon emissions generated from freight transport and logistics with the advent of information communication technology (ICT) devices. With the help of the Internet of Things (IoT), geographical positioning systems, and sensors, it has become easier to monitor the routes of vehicles, their fuel consumption, and the optimization of routes as well. The various innovations can potentially help the logistics sector increase its overall efficiency. Minimizing the carbon footprint in the logistics sector makes it green logistics. In the present research paper, the authors have conducted a literature review in which they intend to highlight the impacts of ICT on green logistics. It was indicated by the results that ICT positively influences the performance of green logistics, but at the same time, it was concluded that poor quality of logistics’ infrastructure, service quality of logistics, and cargo transportation timeliness consume a greater quantity of fossil fuels and therefore cause increased carbon emissions, which negatively impact human health and the environment of the planet.

Modelling and Optimization of Residential Electricity Load under Stochastic Demand

2024-07-03T12:24:22+02:00

The paper considers a modelling framework for a set of households in residential areas; using electricity as a form of energy for domestic consumption. Considering the demand and availability of units for electricity consumption, optimal decisions for electricity load allocation are paramount to sustain energy management. We formulate this problem as a stochastic decision-making process model where electricity demand is characterized by Markovian demand. The loading and operational framework is governed by the demand and supply phenomena; where shortage costs are realized when demand exceeds supply. Empirical data for electricity consumption was collected from fifty households in two residential areas within the suburbs of Kampala in Uganda. Data collection was made at hourly intervals over a period of four months. The major problem focussed on determining an optimal electricity loading decision in order to minimize consumption costs as demand changes from one state to another. Considering a multi-period planning horizon, an optimal decision was determined for loading or not loading additional electricity units using Markov decision process approach. The model was tested; whose results demonstrated the existence of an optimal state-dependent decision and consumption costs considering the case study used in this study. The proposed model can be cost-effective for managers in the electricity industry. Improved efficiency and utilization of resources for the distribution systems of electricity to residential areas was realised; with subsequent enhanced reliability of service to essential customers of the energy market.