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Platform based approach for economic production of a product family

by Choubey, Anand M

Abstract (Summary)
In present competitive market, there is growing concern for ascertaining and fulfilling the individual customer’s wants and needs. Therefore, the focus of manufacturing has been shifting from mass production to mass customization, which requires the manufacturers to introduce an increasing number of products with shorter life span and at a lower cost. Also, another challenge is to manage the variety of products in an environment where demands are stochastic and the lead times to fulfill those demands are short.

The focus of this thesis is to develop and investigate platform based production strategies, as opposed to producing each product independently, which would ensure the economic production of the broader specialized products with small final assembly time and under demand uncertainty.

The thesis proposes three different platform based production models. The first model considers the economic production of products based on a single platform and with forecasted demands of the products. The model is formulated as a general optimization problem that considers the minimization of total production costs.

The second model is the extension of the first model and considers the production of products based on multiple platforms and considers the minimization of total production costs and the setup costs of having multiple platforms.

The third model is also an extension of the first model and considers the demands of the products to be stochastic in nature. The model considers the minimization of total production costs and shortage costs of lost demands and holding cost of surplus platforms under demand uncertainties. The problem is modeled as a two stage stochastic programming with recourse.

As only the small instances of the models could be solved exactly in a reasonable time, various heuristics are developed by combining the genetic evolutionary search approaches and some operations research techniques to solve the realistic size problems. The various production models are validated and the performances of the various heuristics tailored for the applications are investigated by applying these solution approaches on a case of cordless drills.

Bibliographical Information:

Advisor:

School:Kansas State University

School Location:USA - Kansas

Source Type:Master's Thesis

Keywords:mass customization production planning product platforms stochastic programming genetic algorithm engineering industrial 0546 operations research 0796

ISBN:

Date of Publication:01/01/2007

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