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Research Papers

# Process Optimization and Remanufacturability Analysis of Fuel Cell— Membrane Electrode Assembly With Process Simulation

[+] Author and Article Information
R. Muruganantham

Department of Chemistry,
College of Engineering Guindy,
Anna University,
Chennai 600 025,

S. Annamalaisundaram, S. Rajendra Boopathy

Department of Mechanical Engineering,
College of Engineering Guindy,
Anna University,
Chennai 600 025,

D. Sangeetha

Department of Chemistry,
College of Engineering Guindy,
Anna University,
Chennai 600 025,
e-mail: sangeetha@annauniv.edu

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF FUEL CELL SCIENCE AND TECHNOLOGY. Manuscript received September 30, 2011; final manuscript received June 6, 2012; published online October 17, 2012. Assoc. Editor: Ken Reifsnider.

J. Fuel Cell Sci. Technol 9(6), 061002 (Oct 17, 2012) (9 pages) doi:10.1115/1.4007418 History: Received September 30, 2011; Revised June 06, 2012

## Abstract

One of the most pressing environmental problems faced globally is waste management and landfill space. Remanufacturing is one of the green manufacturing techniques in which the geometrical form of the product is retained and the product is reused for the same purpose as during its original life cycle. This work analyzes the remanufacturability of membrane electrode assembly (MEA) which is the heart of the polymer-exchange membrane fuel cell (PEMFC). MEA was obtained by sandwiching the membrane (proton conducting membrane) between the anode and cathode of the fuel cell by hot pressing the anode and cathode onto the membrane at a desired temperature, pressure for a period of time. It is observed that 10% of MEAs are getting wasted while manufacturing it in the laboratory level. In order to utilize these waste MEAs, remanufacurability analysis is done. Wastages created in manufacturing (hot pressing) of MEA can be reduced by optimizing the manufacturing process parameters, such as temperature of the press, pressure applied, pressing time, and thickness of membrane. Using design of experiment and ANOVA contributing factors which influence the quality of MEA are identified with the help of DESIGN EXPERT software. Optimal values of process parameters are found out using desirability function in the software. The process parameter optimization will lead to reduction of wastage of MEA in hot pressing operation but these wastes cannot be avoided completely due to the presence of uncontrollable factors. So remanufacturability analysis will be useful for investigating the wastes. As a part of remanufacurability analysis design consideration for remanufacturing and recycling, the procedure for recovering the valuable materials from the retired membrane electrode assembly, reusing of electrodes are discussed. Two simulation models (current manufacturing system and manufacturing system with remanufacturing) have been created in WITNESS software in order to find the benefits of remanufacturing. The benefits are increase in MEA production and recovery of scrapped anode and cathode. Increase in MEA production due to remanufacturing has been found as 11.11%. Because of recovery process in remanufacturing, 10% of scrapped anode and cathode are utilized which leads to zero scrap of anode and cathode.

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## References

Freiberger, S., 2005, “Design for Recycling and Remanufacturing of Fuel Cells,” Fourth International Symposium on Environmentally Conscious Design and Inverse Manufacturing, Eco Design 2005, Tokyo, December 12–14, Paper No. IEEE 2C-2-2F.
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Leela Mohana Reddy, A., Shaijumon, M. M., Rajalakshmi, N., and Ramaprabhu, S., 2010, “Performance of Proton Exchange Membrane Fuel Cells Using Pt/MWNT–Pt/C Composites as Electrocatalysts for Oxygen Reduction Reaction in Proton Exchange Membrane Fuel Cells,” J. Fuel Cell Sci. Technol., 7, p. 021001.

## Figures

Fig. 1

3D Model of fuel cell single unit and its exploded view

Fig. 2

Fractional factorial design details

Fig. 3

Locations for measuring thickness of MEA

Fig. 4

Sample prepared MEA

Fig. 5

Factor A effect plot

Fig. 6

Factor C effect plot

Fig. 7

Interaction AC effect plot

Fig. 8

Normal plot of residuals

Fig. 9

Solution of optimization

Fig. 10

Current manufacturing system at laboratory level

Fig. 11

Manufacturing system with remanufacturing

Fig. 12

Comparison of assembled component

Fig. 13

Comparison of scrapped component

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