Integration of parametric design into modular coordination: A construction waste reduction workflow

The construction industry is under pressure as to reduce the sizable quantities of construction waste generated during construction operations. Modular coordination (MC) and parametric design both have great potentials in reducing waste at the design stage. And anecdotal evidence suggests that great volumes of waste can be reduced through integration of parametric design into MC. The issue of proposing workflows in this context, however, is under-researched, and practical applications, if any, are at the rhetorical stage. To accomplish this, an integration attempt is made in this study to provide the details of a developed-and-experimented workflow for this purpose; a generative algorithm is developed through the Rhinoceros 3D–Grasshopper platform, subject to MC rules. Two sets of horizontal and vertical modules are obtained from a prototype model, while an evolutionary solver function is applied in reducing the generated construction waste volume. According to a pre-defined standard specification, different modular design variants that fully conform to the design constraints in modules array are developed, providing an operational workflow in construction waste reduction at the design stage. Introducing this workflow, and how the proposed workflow reduces the volume of post-optimization paneling waste by 2% at its minimum are the major findings here. The insights derived from this study, would promote the interest of both the construction practitioners and researchers; the practicality of integrating parametric design into MC is proven. •Providing a developed workflow that integrates the parametric design into modular coordination•Developing the algorithms and procedures necessary to implement the workflow•Demonstrating workflow practicality in reducing the amount of post-optimization paneling waste by 2%•Accelerating the rate by which waste reduction moves into the design stage•Justifying the resources needed to enhance the proposed algorithms and workflow