Operation Opportunities
Receiving { Better accuracy of received products when products are checked-in"
{ Faster scanning of big pallets especially when wireless technologies
are being used (e.g. RFID)
{ Improved visibility of inventory in warehouse facilities even though
products are not yet stored in shelves
Storing { Easier identication of empty shelves that meet product's physical
dimensions
{ Determination of proper storage zones based on real historical data
{ Faster identication of a product's predened storage location in a
warehouse according to the storing policy
{ Richer information availability |such as product's turnover rate, demand,
picking frequency| for storage location assignment algorithms
Picking { Identication of products' locations in the warehouse for the determination
of the fastest route
{ Consideration of multiple feasible locations for each product type if
several product instances are available
{ Scheduling subject to trolley's capacity
Shipping { Identication of proper packaging option for each order
{ Determination of best delivery service available
{ Automatic generation of shipping documents
Due to the rapidly changing preferences of customers, orders received by warehouse companies (espe-
cially third-party-logistics ones) increasingly exhibit special characteristics, such as smaller order size, higher
product variety, request of shorter response time, and request for changes after the order has been initially
created and placed [6]. This means that although the traditional performance targets for warehouse services
(e.g. warehouse utilisation, tighter inventory control) still remain, in today's environment, they are subject to
the specic, special needs of dierent customers. This is particularly true in third-party-logistics warehouses
that manage a high variety of products and a big number of individual customers. Here, the operations are
required to become more customer-oriented and more responsive to requests with dierent characteristics
and needs in an ecient manner.
In this paper we aim to demonstrate the way the product intelligence paradigm can respond to the above
challenges by studying its future application in a third-party-logistics warehouse company. After reviewing
the current situation in warehouse management systems in Section 2, we discuss the opportunities for the
adoption of intelligent products in warehouse operations and their potential applications in Section 3. We
present our scoping case study along with two specific application examples in Section 4 before concluding
with our findings.