Housing is among the three basic human needs, including shelter and food. However, for a long time, it has been a challenge for many countries to solve. The situation in Africa is worse, where the housing deficit is estimated to be around 52 million housing units. With a growing population currently at 1.3 billion people and estimated to be around 2.4 billion by 2050, the population growth presents an opportunity at the same, it is also a challenge. The rural-urban migration estimated to be around 40,000 people daily, has also contributed to the strain on the city centres across Africa. Prefabrication and modular construction have been suggested and tested in other parts of the world as the solution to the mass housing problem, companies have attempted in the past to solve the housing c...[ Read more ]

Housing is among the three basic human needs, including shelter and food. However, for a long time, it has been a challenge for many countries to solve. The situation in Africa is worse, where the housing deficit is estimated to be around 52 million housing units. With a growing population currently at 1.3 billion people and estimated to be around 2.4 billion by 2050, the population growth presents an opportunity at the same, it is also a challenge. The rural-urban migration estimated to be around 40,000 people daily, has also contributed to the strain on the city centres across Africa. Prefabrication and modular construction have been suggested and tested in other parts of the world as the solution to the mass housing problem, companies have attempted in the past to solve the housing crisis using traditional construction, their attempts have failed to yield tangible results. The goal of this thesis is to explore the various available options for prefabrication and select the best that suits the African market and later to deploy for application. Because existing layouts are not suited for prefabrication, there is an also a need to optimize the traditional layout to fit factory construction, this thesis also setups out to develop an algorithm that will select the best possible panel combination for affordable housing delivery.