Cyclical industrial networks are becoming highly desirable for their efficient use of resources and capital. Progress toward this ideal can be enhanced by mimicking the structure of naturally sustainable ecological food webs (FWs). The structures of cyclic industrial networks, sometimes known as eco-industrial parks (EIPs), are compared to FWs using a variety of important structural ecological parameters. This comparison uses a comprehensive data set of 144 FWs that provides a more ecologically correct understanding of how FWs are organized than previous efforts. In conjunction, an expanded data set of 48 EIPs gives new insights into similarities and differences between the two network types. The new information shows that, at best, current EIPs are most similar to those FWs that lack the components that create a biologically desirable cyclical structure. We propose that FWs collected from 1993 onward should be used in comparisons with EIPs, given that these networks are much more likely to include important network functions that directly affect the structure. We also propose that the metrics used in an ecological analysis of EIPs be calculated from an FW matrix, as opposed to a community matrix, which, to this point, has been widely used. These new insights into the design of ecologically inspired industrial networks clarify the path toward superior material and energy cycling for environmental and financial success.

A key element for achieving sustainable manufacturing systems is efficient and effective resource use. This potentially can be achieved by encouraging symbiotic thinking among multiple manufacturers and industrial actors and establish resource flow structures that are analogous to material flows in natural ecosystems. In this paper, ecological principles used by ecologists for understanding food web (FW) structures are discussed which can provide new insight for improving closed-loop manufacturing networks. Quantitative ecological metrics for measuring the performance of natural ecosystems are employed. Specifically, cyclicity, which is used by ecologists to measure the presence and strength of the internal cycling of materials and energy in a system, is discussed. To test applicability, groupings of symbiotic eco-industrial parks (EIP) were made in terms of the level of internal cycling in the network structure (high, medium, basic, and none) based on the metric cyclicity. None of the industrial systems analyzed matched the average values and amounts of cycling seen in biological ecosystems. Having detritus actors, i.e., active recyclers, is a key element for achieving more complex cycling behavior. Higher cyclicity values also correspond to higher amounts of indirect cycling and pathway proliferation rate, i.e., the rate that the number of paths increases as path length increases. In FWs, when significant cycling is present, indirect flows dominate direct flows. The application of these principles has the potential for novel insights in the context of closed-loop manufacturing systems and sustainable manufacturing.

A sustainable global community requires the successful integration of environment and engineering. In the public and private sectors, designing cyclical (“closed loop”) resource networks increasingly appears as a strategy employed to improve resource efficiency and reduce environmental impacts. Patterning industrial networks on ecological ones has been shown to provide significant improvements at multiple levels. Here, we apply the biological metric cyclicity to 28 familiar thermodynamic power cycles of increasing complexity. These cycles, composed of turbines and the like, are scientifically very different from natural ecosystems. Despite this difference, the application results in a positive correlation between the maximum thermal efficiency and the cyclic structure of the cycles. The immediate impact of these findings results in a simple method for comparing cycles to one another, higher cyclicity values pointing to those cycles which have the potential for a higher maximum thermal efficiency. Such a strong correlation has the promise of impacting both natural ecology and engineering thermodynamics and provides a clear motivation to look for more fundamental scientific connections between natural and engineered systems.

Biologically Inspired Design (biomimicry) and Industrial Ecology both look to natural systems to enhance the sustainability and performance of engineered products, systems and industries. Bioinspired design (BID) traditionally has focused on a unit operation and single product level. In contrast, this paper describes how principles of network organization derived from analysis of ecosystem properties can be applied to industrial system networks. Specifically, this paper examines the applicability of particular food web matrix properties as design rules for economically and biologically sustainable industrial networks, using an optimization model developed for a carpet recycling network. Carpet recycling network designs based on traditional cost and emissions based optimization are compared to designs obtained using optimizations based solely on ecological food web metrics. The analysis suggests that networks optimized using food web metrics also were superior from a traditional cost and emissions perspective; correlations between optimization using ecological metrics and traditional optimization ranged generally from 0.70 to 0.96, with flow-based metrics being superior to structural parameters. Four structural food parameters provided correlations nearly the same as that obtained using all structural parameters, but individual structural parameters provided much less satisfactory correlations. The analysis indicates that bioinspired design principles from ecosystems can lead to both environmentally and economically sustainable industrial resource networks, and represent guidelines for designing sustainable industry networks.

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