Challenges in determining electronics equipment take-back levels

Stuart, J.A.; Low, Ming Kaan; Williams, David J.; Turbini, Laura J.; Ammons, Jane C.

doi:10.1109/3476.720421

Cited by 18 publications

(5 citation statements)

References 4 publications

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“…The fraction of salvaged parts that pass the test is given by pass fraction Quality Quality Quality (5) where the interpretation of test effectiveness is the probability of the test or inspection activity successfully identifying a defect in a part. The assembly cost for the primary build is computed using only (1). Equations (1)-(5) are used to compute the cost of a process step that assembles a component to the system during the secondary build.…”

Section: A Formulationmentioning

confidence: 99%

“…When the primary life of the product is over, the original equipment manufacturer (OEM) of the product is rarely involved with the product again. With the advent of more stringent product take-back laws in Europe and those on the horizon in the United States [1], OEM's of many products are being forced to contend with a significant percentage of the products being returned to the OEM at the end of the product's primary life. OEM's also contend with the return of products when the product is leased to the customer for a finite period of time.…”

Section: Introductionmentioning

confidence: 99%

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A model for optimizing the assembly and disassembly of electronic systems

Sandborn

Murphy²

1999

IEEE Trans. Electron. Packag. Manufact.

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This paper presents a methodology that incorporates simultaneous consideration of economic and environmental merit during the virtual prototyping phase of electronic product design. A model that allows optimization of a product life cycle, which includes primary assembly, disassembly, and secondary assembly using a mix of new and salvaged components, is described. Optimizing this particular life cycle scenario is important for products that are leased to customers or subject to product take-back laws. Monte Carlo simulation is used to account for uncertainty in the data, and demonstrates that high-level design and process decisions may be made with a few basic metrics and without highly specific data sets for every material and component used in a product. A web-based software tool has been developed that implements this methodology. Index Terms-Design-for-environment, design-to-cost, disassembly, electronics product take-back, end of life, recycling, virtual prototyping. NOMENCLATURE Quantities associated with specific process steps and the entire unit assembly: Buy back fraction Fraction of the primary assembly cost paid to reacquire primary assemblies for recovery (per assembly). Cost Cost of performing a single assembly process step (per unit assembly). Cost Allocated buy back cost (per assembly). Cost Cumulative cost of all preceding assembly and test steps (per unit assembly). Cost Cost of manufacturing the primary assembly (per unit assembly). Cost Cost of performing a single test step (per unit assembly). Fraction returned Fraction of the primary unit assemblies returned for recovery that are salvageable.

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Section: A Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A model for optimizing the assembly and disassembly of electronic systems

Sandborn

Murphy²

1999

IEEE Trans. Electron. Packag. Manufact.

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show abstract

“…There are various forecasting method reported in the past (Kelle and Silver, 1989;Marx-Gomez et al, 2000Toktay et al, 2003;Stuart et al, 1998). However, those studies were only based on time series and did not consider the characteristics of the locations.…”

Section: Introductionmentioning

confidence: 99%

“…An effective collection strategy can be designed if the information on the rate of returned products for a period of time in a certain location is available. There are various forecasting method reported in the past (Kelle and Silver, 1989;Marx-Gomez et al, 2000Toktay et al, 2003;Stuart et al, 1998). However, those studies were only based on time series and did not consider the characteristics of the locations.…”

Section: Introductionmentioning

confidence: 99%

Reverse logistics strategies for end‐of‐life products

Hanafi

Kara

Kaebernick

2008

The International Journal of Logistics Management

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -End-of-life (EOL) products have become a major environmental issue among countries and manufacturers. This is due to the growing number of EOL products and their hazardous contents. Many collection strategies and pilot projects have been conducted to manage EOL products, especially Waste Electrical and Electronics equipments (WEEEs). However, as characteristics of a population are different to one another, a customized collection strategy is required. The purpose of this paper is to find an effective collection strategy which considers cost and environmental impact simultaneously. Design/methodology/approach -This paper presents an integrated collection strategy which combines a Fuzzy Colored Petri Net forecasting method and collection network model to collect EOL products. Colored Petri Net is used in modeling the integrated collection strategy. To test the collection strategy, a case study on mobile phone collection in Australia is presented. Findings -The integrated collection strategy developed in this paper finds that by providing demographic data and historical sales of a relevant product in a certain location, the best strategy to collect EOL products in that location can be determined. This paper finds that the best strategy that suits one location might be different to other locations. Originality/value -This paper presents a model which provides a customized collection strategy that follows the characteristics of a population. This strategy allows government organizations or manufacturers to simulate the strategies to collect EOL products in different locations.

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“…Toktay et al modeled predicting return flows for instant cameras (Toktay et al, 2000). Stuart et al developed a new mathematical framework to estimate produt takeback levels by defining various levels of product life and by incorporating those terms into a life estimation framework (Stuart et al, 1998).…”

Section: Reverse Logisticsmentioning

confidence: 99%

Solving Reverse Logistics: Optimizing Multi-Echelon Reverse Network

kim

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SOLVING REVERSE LOGISTICS: OPTIMIZING MULTI-ECHELON REVERSE NETWORK Jun KimAs part of sustainable development initiative, product take-back strategy encourages manufacturers to transform definition of sustainability into business practices that would reduce environmental wastes, while reducing increasingly growing waste management cost from municipal governments. This thesis evaluates the complexity of reverse logistics with regards to product take-back strategy development and presents a programmatic approach of determining appropriate number and location of initial collection points that would reduce variable cost, while promoting more frequent product return. The application of this thesis would grant 'green' opportunities for organizations to strategize and execute cost-efficient reverse logistics to advance sustainability. A single-objective, mixed-integer, binary programming was utilized to optimize the variable cost of handling, transshipping, facilities, and carrying of reverse logistics. Apple Inc.'s current product take-back strategy was carefully evaluated and analyzed to suggest potential improvements to its system. Network optimization design methodology along with case study results would provide useful managerial insights and suggest avenues for further research and applications.v ACKNOWLEDGEMENTS

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Challenges in determining electronics equipment take-back levels

Cited by 18 publications

References 4 publications

A model for optimizing the assembly and disassembly of electronic systems

A model for optimizing the assembly and disassembly of electronic systems

Reverse logistics strategies for end‐of‐life products

Solving Reverse Logistics: Optimizing Multi-Echelon Reverse Network

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