Using Linear Programming to Improve Productivity and Profitability with Six-sigma in the Fast-moving Consumer Goods Industry

This paper investigates the suitability of linear programming techniques to optimize profitability and productivity in the fast-moving consumer goods (FMCG) industry. The impact of six-sigma implementation on the dual objective function problem is also explored. A mixed integer linear programming (MILP) model suitable for the FMCG industry is selected with reference to the classification of lot sizing models found in literature, the classification is based on the type of problem that the model intends to solve. Two literature derived case studies that are representative of the FMCG industry are used to answer the research question in this work through a simulation research approach in the General Algebraic Modelling System (GAMS) software. The study found that linear programming can be used as an optimization technique in the FMCG industry with the lot-sizing concept. The implementation of six-sigma has a big impact on profitability and productivity as it reduces number of defects and failures, thus improving quality of products and maximizing the output with minimal re-work. This research in engineering management can be used to build a business case for resources to be directed at implementing six-sigma as it provides an alternative way to show the benefits of six sigma implementation.