Product planning of manufactured construction products

Abstract

The construction industry is experiencing further industrialisation to achieve greater efficiency and flexibility in the development of manufactured construction products. The development of these products poses challenges because of new complex design requirements and manufacturing processes. There is therefore a need to develop product planning methods that can effectively address these challenges. This research aims to develop product planning methods for complexity management of manufactured construction products. A framework for product planning for manufactured construction products is proposed, which involves application of methods for requirements management and modularisation. Using a reverse engineering approach, the Quality Function Deployment (QFD) method was applied to a modular plantroom to model and analyse its requirements. The plantroom QFD model facilitated a deeper understanding of requirements analysis than existing practice at the collaborating company. The QFD method was subsequently applied to a whole modular apartment building to analyse its requirements and investigate how requirements flow down across hierarchical levels. The application showed that a series of connected QFD models support requirements analysis by allowing to investigate systems structure, traceability and data analytic solutions of complex building systems. The QFD models were evaluated and validated by engineers at the collaborating company and were found to be effective at capturing and analysing requirements. QFD is a powerful requirements analysis method for manufactured construction products because it offers a more systematic, holistic and structured approach to requirements analysis than those currently adopted in the industry. The research also investigated the development and application of a multi-driver modularisation approach for manufactured construction products. The approach uses and integrates three modular tools, namely Dependency Structure Matrix, Modular Identification Matrix and Generational Variance Indexes, which support the design of flexible product systems. The approach is able to address multiple modularisation drivers and provide valuable design information.