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Logistical Model for Closed Loop Recycling of Textile Materials

In the United States alone, people consume and discard over 500 billion pounds of wastes annually. Wastes discarded in landfills create threats to land, air, and water, but also represent lost resources. Recycling has the ability to divert wastes from landfills and recover precious raw materials. However, recycling activities are only as efficient as the reverse logistics and supply chains that support them. These areas are relatively new, but successful implementations have real benefits for companies in terms of profits and environmental goodwill. Many companies are creating closed loop supply chains where forward and reverse activities are interlinked in cyclical processes. Ideally, a virgin input enters the system only once and is recycled forever. The problem with most current closed loop supply chains is that they are product-specific. When a closed-loop supply chain is designed, the product must be designed so that it can easily be recycled back into the supply chain. The problem is that the product must contain a minimum number of dissimilar components. For textile products, this presents a real challenge because of fiber blends and finishes that make component separation difficult. These problems create the need to design textile recycling systems. This research focuses on the logistical systems necessary to recycle textile materials. Methodologies for estimating post-consumer carpet (PCC) returns and trailer loading capacities are first discussed, followed by location allocation models that determine the geographical placement of recycling sites of an existing carpet collection network. The location allocation model utilizes zip code populations to allocate percentages of the PCC returns to the collection sites. The population for each site is determined by summing the five-digit zip code populations within a specified collection radius. The collection site weight is then calculated as the percentage of the total population for the collection network. A proposed national network model, based on three-digit zip codes, has also been developed. This model includes economies of scale for recycling processing costs. Increasing annual returns have been modeled to study the effects of changing network morphologies on the location and allocation of recycling sites. A PCC reverse supply chain cost model is also presented to study the cost relationships of the activities that comprise the recycling network. Transportation costs from the location allocation models were utilized in the model, as well as cost data from industry. It was found that processing costs are the main drivers in a nylon 6 recycling network, while a nylon 6,6 network is sensitive to cost changes in any reverse activity. Quantified results show that either recycling technologies must become more efficient or virgin nylon prices must increase for recycled nylon to be competitive with virgin polymers.

Identiferoai:union.ndltd.org:NCSU/oai:NCSU:etd-03262009-143230
Date27 April 2009
CreatorsWoolard, Ryan
PublisherNCSU
Source SetsNorth Carolina State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.lib.ncsu.edu/theses/available/etd-03262009-143230/
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