Neha B. Raikar

Optimizing the tactical planning in the Fast Moving Consumer Goods industry considering shelf-life restrictions

Abstract This paper addresses the optimization of the tactical planning for the Fast Moving Consumer Goods industry using an MILP model. To prevent unnecessary waste and missed sales, shelf-life restrictions are introduced using three methods. The direct method tracks the age of products directly. While it provides optimal solutions, it is computationally inefficient. The indirect method forces products to leave inventory before the end of their shelf-life. It obtains solutions within a few percent of optimality. Moreover, compared to the direct method, the computational time was on average reduced by a factor 32. The hybrid method models the shelf-life directly in the first and indirectly in the second storage stage. It obtains near optimal solutions and, on average, reduces the required computational time by a factor 5 compared to the direct method. Cases containing up to 25, 100, and 1000 SKUs were optimized using the direct, hybrid and indirect method respectively.

Tactical Planning with Shelf-Life Constraints in the FMCG Industry

Shelf-life restrictions play an important role in the tactical planning for the Fast Moving Consumer Goods (FMCG) industry. Ignoring shelf-life limitations could lead to unnecessary waste of products and missed sales. We present 3 methods of implementing shelf-life limitations in an LP planning model. A direct method, where the number of weeks since a product was produced is tracked, an indirect method, which ensures that the total shelf-life of a product is not exceeded, and a hybrid method that models the shelf-life on the first storage stage directly and on the second stage indirectly. With the direct method solutions with the lowest costs were obtained. However, with the hybrid method solutions with a cost increase of only 0.01–0.03% could be obtained in about 1/5th of the computational time. With the indirect method solutions could be obtained in 1/50th of the time of the direct method. However, the costs increased by up to 13.3%.

An optimization of the food quality products throughout the supply chain

Abstract Quantitative supply chain modelling has contributed substantially in fields such as automotive, logistic, hardware, etc. However, these methods and optimization have not been employed widely in the food industry despite all the potential benefits they may bring to this sector. The reason is integration of quantitative supply chain models into food industry brings difficulties into the optimisation approaches. The objective of this work is to develop a supply chain model for the food industry based on the relationships between raw material quality, processing conditions and final product quality and customer satisfaction. Moreover, based on the developed model, we have determined key factors in the whole chain that are most likely to affect customer satisfaction and consequently overall demand. Optimum conditions to minimize overall cost and energy consumption have been determined. New methodology has been developed that simplifies and enables the model to find the optimum processing conditions to obtain maximum quality across all quality indicators with minimum cost and energy usage by developing the interrelationships between quality and processing conditions.

Food supply chain planning and quality optimization approach.

Abstract Controlling shelf-life and material quality is an essential factor in the food industry to overcome seasonality problems. The objective of this work is to address the seasonality problem of the raw materials by adding a preparation process to increase their shelf-life. Every process in the supply chain model will affect the quality of the product, as a result a quality model has been integrated which is based on the interrelationship between the raw materials and the processing conditions. Thus, this model enables comparing alternative manufacturing systems based on the optimum processing conditions and obtaining maximum quality with minimum cost and energy usage. In this paper a food supply chain model has been designed for planning to satisfy the given demand, and simultaneously optimising the quality and energy usage of the product at every stage of processing.

Applications of population balance equation modeling to pharmaceutical emulsions

Emulsions are usually generated in high-pressure homogenization chambers. The flow field is these units are typically highly turbulent and chaotic, and mechanisms for drop formation under these conditions are not well understood. In this paper, we have applied the PBE modeling approach to droplet break-up in a high pressure homogenizer using mechanistic functions for breakage rate. We have compared our modeling results to experimental data that we have obtained on a model oil-in-water emulsion. In principle, once these functions are known, the PBE approach can be used in a predictive manner to aid in the selection of process and product variables that will lead to the desired drop size distribution. This was verified for a number of test cases by changing product properties and homogenizing conditions. We observed that the population balance model did a reasonably good job of predicting the drop size distribution and therefore look promising. For cases where the model fails, we discuss strategies for improving predictions for these types of systems.