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General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products

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  • Bex George Thomas

    (General Electric Global Research, Computing and Decision Science, Niskayuna, New York 12309)

  • Srinivas Bollapragada

    (General Electric Global Research, Computing and Decision Science, Niskayuna, New York 12309)

Abstract

General Electric (GE) Energy's nascent solar business has revenues of over $100 million, expects those revenues to grow to over $1 billion in the next three years, and has plans to rapidly grow the business beyond this period. GE Global Research (GEGR), in partnership with GE Energy's solar platform team, is pursuing a number of technological alternatives to bring new low-cost solar products to the market. However, the GE solar business is facing a challenge---making optimal investment decisions to realize its growth objectives in the presence of major uncertainties in technology, costs, demands, and energy policy. We have developed analytical decision support tools with embedded mathematical models to estimate product costs and demands, and to support capacity planning decisions under cost and demand uncertainties. In this paper, we outline our algorithmic approach and system implementation, which help to support strategic decisions at GE.

Suggested Citation

  • Bex George Thomas & Srinivas Bollapragada, 2010. "General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products," Interfaces, INFORMS, vol. 40(5), pages 353-367, October.
    • Handle: RePEc:inm:orinte:v:40:y:2010:i:5:p:353-367
    DOI: 10.1287/inte.1100.0518
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    References listed on IDEAS

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    1. Bian, Yuan & Lemoine, David & Yeung, Thomas G. & Bostel, Nathalie & Hovelaque, Vincent & Viviani, Jean-laurent & Gayraud, Fabrice, 2018. "A dynamic lot-sizing-based profit maximization discounted cash flow model considering working capital requirement financing cost with infinite production capacity," International Journal of Production Economics, Elsevier, vol. 196(C), pages 319-332.
    2. Diana Sánchez-Partida & Rodolfo Rodríguez-Méndez & José Luis Martínez-Flores & Santiago-Omar Caballero-Morales, 2018. "Implementation of Continuous Flow in the Cabinet Process at the Schneider Electric Plant in Tlaxcala, Mexico," Interfaces, INFORMS, vol. 48(6), pages 566-577, November.
    3. Smirnov, Dina & van Jaarsveld, Willem & Atan, Zümbül & de Kok, Ton, 2021. "Long-term resource planning in the high-tech industry: Capacity or inventory?," European Journal of Operational Research, Elsevier, vol. 293(3), pages 926-940.
    4. Martínez-Costa, Carme & Mas-Machuca, Marta & Benedito, Ernest & Corominas, Albert, 2014. "A review of mathematical programming models for strategic capacity planning in manufacturing," International Journal of Production Economics, Elsevier, vol. 153(C), pages 66-85.
    5. Ghadimi, Foad & Aouam, Tarik, 2021. "Planning capacity and safety stocks in a serial production–distribution system with multiple products," European Journal of Operational Research, Elsevier, vol. 289(2), pages 533-552.

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