Agriculture Reference
In-Depth Information
Table 14.1
Generic logistics decisions versus specific QCL decisions. (Van der Vorst et al.
2011
)
Generic logistics decisions
Specific QCL decisions
Determine generic customer service standards
Customer needs (e.g. quantity, quality)
Customer service levels (e.g. lead time,
reliability)
Determine requirements on supply of products
in each stage of the chain
Determine customer acceptance levels and
periods for specific market segments using
accepted and measurable quality standards.
Translate this into specific product quality
requirements for each stage in the supply
chain (next to of course volume and timing
requirements)
Determine facility network design
Number, location of stocking points
Equipment selection, capacity planning
Use customer requirements data, informa-
tion on supply qualities and volumes and
transport scenarios with quality predictions
to determine the required network design
and equipment
Determine inventory management
Position Customer Order Decoupling Point
(CODP); push-pull strategies
Warehousing policies
Use supply chain data to determine the optimal
position of inventory points in the network
taking predicted quality changes (and thus
environmental conditions) into account
Determine information flows and order
processing
Ordering rules
Order inventory interface procedure
Order picking procedures
Determine Critical Quality Points (CQPs) to
monitor quality changes. Use quality predic-
tion models and product quality information
to apply optimal picking policies (e.g. first-
expired-first-out policy). Re-sort batches if
needed. Aim for homogenous batches for
specific market segments
Plan order fulfilment
Allocate harvested produce to customer orders
and deliver the products without dealing with
quality changes and differences that occur in
the supply process. A batch is not re-sorted or
re-allocated unless serious issues arise.
Determine transport management (mode,
scheduling)
Dynamic logistics planning in the complete
chain based upon real time product-quality
information (using critical quality points
and predictive models). If needed, batches
are re-sorted into homogeneous batches,
re-allocated to different market segments,
transported with different modes or envi-
ronmental conditions are adapted to meet
customer requirements. Technologies such
as data loggers, RFID and GPS are used to
capture all relevant information, translated
into meaningful information through models
b. Critical Quality Points
A critical quality point (CQP) refers to a point in the process where variation in
product properties and or processes results in unacceptable and or irreversible de-
viations in required quality attributes of the final product (Luning and Marcelis
2009
). By studying chain conditions and relating the findings to the dynamic be-
havior of quality attributes, it becomes possible to determine the effects of different
chain configurations (and thus logistics decisions in different stages in the chain)
on the product quality and product availability. This supports the determination of
locations in the chain where certain measurements should be done and logistics and
