Tool for the environmental assessment of cranes based on parameterization

Information constitutes one of the main barriers for applying life cycle assessment (LCA) due to complexity and need for great amounts of it. However, most of the parameters that determine the data are defined early in the product development process. Knuckle boom cranes constitute a complex product which poses a particularly pressing need for simplification. This paper models the LCA inventory information out of design parameters. The paper also presents a tool implementing this.

To develop the parametric model, a three-step approach is followed. In the first step, knuckle boom crane designers of an international manufacturer are asked to point out key design parameters. An LCA is then conducted for a representative crane of the same manufacturer. Interdependencies between design parameters and inventories are analyzed. Design parameters influencing the LCA results are defined as primary parameters. Parameters through which it is possible to calculate the LCA inventory are defined as secondary parameters. The relation between primary and secondary parameters is analyzed. Indicators are developed for comparison, and the validity of this parametric model is checked by analyzing six more cranes, different in size and performance.

The parametric model presented in this paper contains 13 primary parameters. Their link to secondary parameters and inventory data is through formulas derived from existing documentation, physical interdependencies, or statistical data. To integrate this model in the design workflow, it is embedded into a software tool. Designers input the primary parameters, and the tool allows visualization and benchmarking of environmental impact results. Three indicators related to weight and environmental performance are defined, as well as the means to benchmark in relative terms. The model diverges in never more than 4% for six additional cranes analyzed.

Through the parametric model, a rigorous estimation of the environmental profile of a crane can already be assessed in an early point of the product development process. Results can be used to define targets for design decisions based on the best-performing products.

The statistics-based estimations carried out by the tool can be further improved, getting a wider range of cranes involved. Differences between these products can increase the understanding of the effect of technology choices in the final environmental impact of the product. This may become particularly useful in early design decisions. The potentials of this parametric approach can also be extended to other types of products.