Browsing by Author "Samuels, Jason"

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    Carton and volume forecasting from picking lines
    (Stellenbosch : Stellenbosch University, 2017-03) Samuels, Jason; Visagie, Stephan E.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics. Logistics.
    ENGLISH SUMMARY : Supply chains consist of many stages and all these stages need to be managed. Being able to predict stock flow at any stage can be cost effective for the whole supply chain. In this thesis data from the Pepstores Ltd (PEP) distribution centre in Kuilsrivier, Cape Town are used to predict number of cartons and volume of stock that a hub in their supply chain owned by Pepkor logistics (PKL) will receive. These forecasts will help PKL to schedule delivery trucks and routes to stores with more accurate data and thus lower transportation costs. Simple linear regression (SLR) and multiple linear regression (MLR) are used to predict cartons and volume, but heteroscedasticity is obtained in the residuals. Different types of transformations on the SLR model are introduced and used on dependent and independent variables. A logarithmic weighted transformation could overcome these problems and is thus used along with polynomial regression to predict the number of cartons and volume of stock. The carton prediction model uses a polynomial regression model with order 2 and the volume prediction model uses a SLR model on the logarithmic weighted variables. Accuracy tests show that the models predict the number of cartons and volumes of stock well. A case study on actual data to forecast volume and cartons is presented. These predictions were then compared to the actual values and the forecast that was sent to the hub from the DC over a two week period. It is concluded that PEP can use these models within their systems, but coecients need to be reviewed periodically in order to take into account the different types of products.
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    Electrical-energy in schools with a focus on behavioural and efficiency interventions
    (Stellenbosch : Stellenbosch University, 2021-12) Samuels, Jason; Booysen, Thinus; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.
    ENGLISH ABSTRACT: Schools are a substantial contributor in South Africa’s constricted energy landscape. Schools also face infrastructure and resource limitations and budgetary pressures. This tension thus creates a need for schools to reduce their effective usage of electricity to save money and reduce their environmental impacts. To help schools reduce these impacts, this study embarked on the understanding of their energy usage. This was done with smart-energy meter data analysis of schools within Stellen- bosch in the Western Cape province of South Africa. The investigation compared the energy intensity of schools in South African with schools worldwide, and then compared South African schools across affluence levels. Usage was predominantly analysed as hourly load profiles for certain times of the year and as aggregate energy usages per day. After investigating the energy usage of the schools and upon the completion of energy audits, interventions were introduced to reduce the energy usage of the schools. The first method of reduction was to implement efficiency interventions with regards to energy-intensive items in the schools. The schools in the sample set were found to have many high-power fluorescent lights that were used in c lassrooms. These lights were then replaced w ith the LED lights with lower power consumption, high power factor and better light quality. A model was created and validated for schools’ usage based on the lighting utilisation in the schools. The second method of reduction included the implementation of behavioural interventions in schools. Periodic reporting based on the energy usage data was presented to schools with the cost and environmental impacts. The energy usage could be reduced through awareness with ongoing and digestible energy reports. As the study took place during the COVID-19 pandemic, the energy usage of schools were assessed with the influence of the pandemic’s r estrictions. The change in energy and occupancy changes were evaluated as the pandemic presented the opportunity to measure the differential demand of occupants and buildings’ base loads. With the understanding of schools’ energy usage and the implementation of possible ways of reductions, schools would be in a better position to transition to alternative energy sources. Therefore, this study included the evaluation of a solar PV system at a single school and its impacts on the schools carbon emissions and costs was evaluated. Altogether, the understanding of energy usage; reductions through efficiency and behavioural interventions; and evaluation of solar PV in schools present the foundations to help schools. This could improve their energy efficiency, help schools save electricity costs and reduce their carbon emissions