Food quality management in cold chains Renzo Akkerman, Aiying Rong, Martin Grunow Department of Management Engineering Technical University of Denmark 3 rd International Workshop on Cold Chain Management, June 2-3, 2008, Bonn, Germany Produktionstorvet 425 2800 Kgs. Lyngby (Copenhagen), Denmark rak@ipl.dtu.dk / ar@ipl.dtu.dk / grunow@ipl.dtu.dk
Presentation outline Introduction Food quality in cold chains Research aims Production and distribution planning problem Modelling quality degradation Problem formulation Model application Conclusions
Food quality in cold chains Increasing awareness for food-specific issues like quality, safety, health, nutrition, Especially food quality affects cold chain operations Related to integrity, safety, and shelf life of products Quality of the end product can be a competitive advantage Huge impact on logistical requirements Despite its importance, product quality is mostly not considered in supply chain management literature What we need here is: quality-controlled logistics (as phrased by Van der Vorst et al., 2007)
Research aims But, how to perform these quality-controlled logistics? From food science, we know that the main factors in quality degradation of food are time and temperature, which are clearly linked to production and distribution! Therefore, our research aims to: Integrate food quality degradation in production and distribution planning This includes: Multi-period modeling approach Heterogeneity in quality of product batches Decision making on storage temperatures Differentiation of product flows, based on batch quality
Production and distribution planning For this paper, we focus on a generic cold chain:
Production and distribution planning Aim: Combine decision-making on temperature control and production/distribution planning: - How much, when, how, and where to produce and ship products? - But also: What storage temperatures to use? Method: Integrating quality degradation functions in a distribution planning model (based on time and temperature for storage)
Modelling quality degradation - Theory Quality degradation is often linear (A) or exponential (B) For example, for fresh meat and fish it mainly depends on microbial growth, which is exponential The rate of quality degradation depends on environmental characteristics, such as temperature Important: logarithms can be used to linearize the relationship
Modelling quality degradation Implementation Introduction of B different quality levels Number of levels is chosen in such a way that quality degrades at least one level for each time period (otherwise quality is not traceable through the network) Quality changes depend on time and temperature: q i (k) q ij Quality degradation in one period in location i at temperature k Quality degradation for products transported on arc (i,j)
Modelling quality degradation Illustration P: Plant D: Distribution center Quality levels R: Retailer s: storage time u: transportation time q: product quality t: time period
Modelling quality degradation Illustration Quality levels Change in storage temp P: Plant D: Distribution center R: Retailer s: storage time u: transportation time q: product quality Quality increase t: time period
Problem formulation MILP model Decision variables: Product flows, production quantity, inventories, and also: Temperature settings for storage facilities Waste in different stages of the cold chain (indirect) Objective function includes: Production and distribution costs, and also: Temperature-dependent storage costs and waste disposal Important modelling aspects: Quality index q to distinguish quality levels throughout the cold chain
Model application - Professionally Prepared Meals* Industrially prepared meal elements for professionally prepared meals Prolonging shelf lives by distributing them super chilled in the conventional cold chain Modelling the dynamics of quality changes during distribution Goals: Production and distribution efficiency Reduction of waste, energy consumption Improved operations in professional kitchens * New research project funded by the Food Research Programme of the Danish Ministry of Food, Agriculture and Fisheries
Conclusions First approach to: Include the important aspect of product quality in production and distribution planning Differentiate product flows based on product quality Chain configuration used is relatively generic, so applicable in a wide variety of food industries Model aim: useful tool in the operation of cold chains Initial test runs have proven to be successful Current work on the distribution of meal elements will facilitate further development and model validation
Contact information Renzo Akkerman Technical University of Denmark Department of Management Engineering Produktionstorvet 425 2800 Kgs. Lyngby (Copenhagen) Denmark rak@ipl.dtu.dk / www.man.dtu.dk