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Food quality management in cold chains
Renzo Akkerman, Aiying Rong, Martin Grunow
Department of Management Engineering
Technical University of Denmark
3rd International Workshop on Cold Chain Management,
June 2-3, 2008, Bonn, Germany
Produktionstorvet 425
2800 Kgs. Lyngby (Copenhagen), Denmark
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Presentation outline
• Introduction
� Food quality in cold chains
� Research aims
• Production and distribution planning problem
• Modelling quality degradation
• Problem formulation
• Model application
• Conclusions
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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)
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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
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Production and distribution planning
For this paper, we focus on a generic cold chain:
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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)
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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 de-
gradation depends on environmental char-
acteristics, such as
temperature
• Important: logarithmscan be used to linearize
the relationship
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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:
Quality degradation for products transported on arc (i,j)∆qij
Quality degradation in one period in location i at temperature k
∆qi(k)
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Modelling quality degradation – Illustration
Quality levels
P: Plant
D: Distribution center
R: Retailer
s: storage time
u: transportation time
q: product quality
t: time period
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Modelling quality degradation – Illustration
Quality levels
P: Plant
D: Distribution center
R: Retailer
s: storage time
u: transportation time
q: product quality
t: time period
Change in
storage temp
Quality
increase
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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
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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
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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
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Contact information
Renzo Akkerman
Technical University of Denmark
Department of Management Engineering
Produktionstorvet 425
2800 Kgs. Lyngby (Copenhagen)
Denmark
[email protected] / www.man.dtu.dk