Kimberly-Clark Latin America Builds an Optimization-Based System for Machine Scheduling

Nazrul Shaikh (), Vittal Prabhu (), Danilo Abril (), David Sánchez (), Jorge Arias (), Esteban Rodríguez () and Germán Riaño ()
Additional contact information
Nazrul Shaikh: Department of Industrial Engineering, College of Engineering, University of Miami, Coral Gables, Florida 33146
Vittal Prabhu: Marcus Department of Industrial and Manufacturing Engineering, Pennsylvania State University, University Park, Pennsylvania 16802
Danilo Abril: Kimberly-Clark, Latin American Operations, Bogotá, Colombia
David Sánchez: Kimberly-Clark, Latin American Operations, Bogotá, Colombia
Jorge Arias: Kimberly-Clark, Latin American Operations, C1001ABR Buenos Aires, Argentina
Esteban Rodríguez: Kimberly-Clark, Latin American Operations, Heredia, Costa Rica
Germán Riaño: Kimberly-Clark, Latin American Operations, Bogotá, Colombia

Interfaces, 2011, vol. 41, issue 5, 455-465

Abstract: During a single planning period, Kimberly-Clark Latin America manufactures dozens of stock-keeping units (SKUs) in varying quantities using a few machines. The same SKU can be manufactured on multiple machines, some of which are more efficient than others. In addition, the setup time for an SKU is sequence dependent, and its demand is stochastic between planning periods. The stochastic demand necessitates changing production plans each planning period; given the large number of SKUs and small number of machines, this leads to inefficiencies. This paper describes the formulation and corresponding solution approach of an integrated inventory, production-planning, and detailed scheduling model to address the inefficiencies in lot sizing, production scheduling, and inventory management. The paper's key contribution is the solution approach, which solves the resultant industry-size NP-hard problem in minutes. The solution quality and its implementation have been tested extensively, and the model has been successfully deployed in five countries. A reduction in finished product inventories of up to 45 percent, an increase in yield and uptime of 2 percent, and improvements in service levels of 2.4 percent are directly attributable to the model and the solution approach highlighted in the paper.

Keywords: production scheduling; sequencing; programming; integer; applications; production scheduling; lot sizing (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (2)

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